technology it integration strategy & goals

STUDY

Technology

Strategy & Goals

IT Integration

INDUSTRY 4.0 BAROMETER 2019

Contacts

The Study Industry 4.0 Barometer 2019 and its summary have been published by:

MHP Management- und IT-Beratung GmbH in cooperation withLudwig Maximilian University, Munich.

All rights reserved! Reproduction, microfilming, storage and processing on electronic media are only permitted with the consent of the publishers. The content of this publication is intended to provide information to our cus-tomers and business partners. It reflects the authors’ state of knowledge at the time of publication. To resolve the relevant issues, please use the sources specified in the publication or contact the persons detailed above. Any views expressed here merely reflect those of the relevant authors. Charts may contain rounding differences.

SponsorTom Huber

MHPAssociated PartnerHead of Operations

Performance & [email protected]

+49 151 40667630

Project ManagerAndreas Henkel

MHPSenior Manager

Operations Performance & Strategy

[email protected]+49 151 40 66 75 26

SponsorProf. Dr. Johann Kranz

LMUHead of the Chair of Internet Business and Internet Services

[email protected]+49 89 21 80 18 75

Thank you. On behalf of MHP Management- und

IT-Beratung: To all respondents for sup-porting the study with their views and assessments.

To the Ludwig Maximilian University, Munich for the successful and continu-ously productive collaboration. Our special thanks go to Prof. Dr. Johann Kranz and Ms. Esther Nagel, Chair for Internet Busi-ness and Internet Services.

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00Table of Contents and List of Abbreviations

2019 Summary 6

The MHP Industry 4.0 Barometer 121.1 A Look Back: Industry 4.0 Barometer 2018 121.2 2019 Focus Topic: Drivers & Obstacles 13

Methodology and Respondents 142.1 Methods of Evaluation 152.2 Study Respondents 152.3 Interviews and Case Studies 15

Results of the Study 203.1 Technology 20Case Study RFID-Implementierung 22Expert Interview 263.2 IT Integration 30Case Study Production Performance Manager 323.3 Strategy & Goals 35Case Study Industry 4.0 Strategy 36Industry 4.0 Strategy @ VW ATJ 36Expert Interview 42

Recommended Actions 484.1 Technology 484.2 IT Integration 494.3 Strategy & Goals 494.4 Drivers & Obstacles 50

Conclusion 52

Abbreviations

Fraunhofer IPT Fraunhofer-Institut für Produktion-stechnologie (Frauenhofer Institute of Production Technology)

OEM Original Equipment ManufacturerSOA Service-Orientied Architecture RFID Radio-Frequency Identification NFC Near Field CommunicationAPI Application Programming InterfaceESB Enterprise Service Bus

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0 10 20 30 40 50 60 70 80 90 100

2018 Barometer value 2019 Barometer value

2018 Barometer value 2019 Barometer value Disagree Neutral Agree

Cost reduction and increase in process quality and efficiency

Development of new market and customer segments

Provision of new services for one’s own products

Development of new business models

Supply chain transparency

Digital Twin

Automation & autonomous systems

Digital production technologies

Big data & data analytics

Key Findings

2 %

9 %

8 %

9 %

23%

51%

31%

43%

75 %

40 %

61 %

48 %

Use is planned

Practical testing

Partial use

Full use

2019 Barometer value Disagree Neutral Agree

... because established, historically grown IT systemsimpede the integration.

... because function-related and historically grown data silos complicate the implementation of cross-departmental solutions.

... because there is no continuous data exchange within the value chain.

… because due to the daily business not enough capacities are available.

... because it is difficult to define the profitability of the invest-ments.

... because of difficulties for Industry 4.0 to hire qualified staff („War of Talents“).

9 % 43% 48%

44%

48%

53%

42%

38 %

50%

46%

40%

50 %

54%

6 %

6%

7%

7%

9%

0 10 20 30 40 50 60 70 80 90 100

Obstacles for the introduction of Industry 4.0 technologies

The introduction of Industry 4.0 technologies in our company is being delayed, …

Rigid legacy systems as well as historically grown data repositories with the resulting data disruptions complicate the implementation of the Industry 4.0 solutions.

Across all industries, Industry 4.0 focuses more on cost reduction and efficiency increase rather than new business models.

The use of industry 4.0 technologies is increasing and is outgrowing the experimental phase.

Strategic Focus of Industry 4.0

Aggregated presentation of technology dissemination in German industry

2019Summary

Industry 4.0 Barometer

The development of new business models and services by Industry 4.0 is considered less of a priority than last year.

The awareness for Industry 4.0 has increased across all sectors.

The use of Industry 4.0 technologies is increasingly shifting from the experimental phase to the test and pilot phase.

There is an even stronger focus on cost reduction and efficiency improvement through Industry 4.0.

77

The Digital Twin of plants and systems is

still only in the experimental phase.

The use of additive manufacturing technologies such as 3D printing has increased by 20% compared to the previous year.

Products and components are increasingly being equipped with sensors to improve transparency in the Supply Chain.

The IT system landscape does not show Industry 4.0 maturity yet.

IT security is a high priority in important decisions regarding Industry 4.0.

Almost every second compa-ny sees the lack of qualified employees as an obstacle to the implementation of Industry 4.0.

Technology pioneers see cyber security and unsuccessful pilot projects in particular as primary obstacles to the implementation of I4.0 - technology latecomers, on the other hand, see the problems for the industry 4.0 rollout in organizational issues, such as the burden of day-to-day business and lack of responsibilities.

Almost every second respondent

sees the lack of cooperation

between the areas involved as

an obstacle to the introduction of

Industry 4.0 technologies.

For technology pioneers, the CIO is three times more likely to be part of the manage-ment than for technology latecomers.

More than 50% of the companies lack the capacity to implement Industry 4.0 due to the daily business.

High investment costs as well as an indefina-ble profitability are for 40% of the respondents an obstacle for the implementation of Industry 4.0 solutions.

According to 50% of the respondents, legacy systems and data silos prevent the rollout of Indus-try 4.0 – especially in large companies.

The Industry 4.0 focus on cost reduction and ef-ficiency improvement has increased by 27%.

Key FindingsOverview

The complete use of Condition Monitor-ing has increased three times compared to the previous year.

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Technology Strategy & Goals Drivers & Obstacles IT Integration

Conclusion The technological maturity of Industry 4.0 and the awareness of Industry 4.0 have widely increased. The use of technology shows a clear trend from the experimental stage towards practical application across all sectors.

Conclusion There is a huge backlog in IT requirements for Industry 4.0. Rigid and inflexible, low performance legacy sys-tems are the biggest challenge for implementing Industry 4.0. solutions.

Conclusion The focus on reducing costs and increasing efficiency was strengthened, while the development of new business models and services plays a subordinate role. This shows that evolutionary rather than revolutionary changes are being sought. One reason for this may be the current uncer-tain geopolitical and economic situation.

Conclusion The challenges of IT integration, such as historically grown IT system landscapes and data silos, are also the most serious obstacle to the implementation of Indus-try 4.0 solutions. These conditions promise high investment costs, while at the same time the ROI of these investments is often not clearly foreseeable. In addition, organizational conditions such as lack of capacity due to day-to-day business or lack of qualified employees impede successful implementation of Industry 4.0 projects.

Recommended Actions Improve supply chain transparency and traceability of products and components through even greater use of sensors

Digitally upgrade equipment and systems to enable 5G connectivity and create the basis for high performance networking

Intensify data analysis along the value chain to validate the benefits of Industry 4.0 solutions and justify their rollout

Develop innovative Industry 4.0 solutions through cooperation with specialized technology partners to integrate their core competencies

Recommended Actions Increase modularity of IT systems to improve the performance of the infrastructure and thus create the basis for the rollout of Industry 4.0

Keep increasing the scalability of IT architectures by using cloud solu-tions and APIs

Dissolve system boundaries and data silos to facilitate and accelerate the integration of new applications and partners

ntensify exchange and cooperation with partners along the value chain to develop common standards and data formats

Recommended Actions Intensify cross-departmental cooperation and knowledge exchange between business and IT

Promote cross-company and cross-sector know-how transfer with tech-nology leaders in order to exploit synergy potentials

Test innovative Industry 4.0 solutions together with technology partners in test environments in order to avoid risks for the operational business

Management must play a key role as a driver and motivator in a dynamic environment and move forward on the path to Industry 4.0

Recommended Actions Creating an organisational framework through management and establishing a defined project organisation for innovative Industry 4.0 projects

Intensification of approaches to data centricity to dissolve silo thinking and focus on the opportunities offered by openness and transparency of data

Implementation of innovative data management solutions (e.g. Enterprise Knowledge Graph) to enable Industry 4.0 solutions despite historically grown IT system landscapes and data silos

Rapid implementation of pilot projects to quantify and validate the potential benefits of data and predict the return on investment in Industry 4.0

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Industry 4.0 Maturity

01The MHPIndustry 4.0Barometer

ularisation would allow different IT technologies to be adapted and integrated into the company more quickly.

Furthermore, the results of the study showed that the the-oretical potential of Industry 4.0 is still insufficiently used by German industry. The widespread silo thinking complicates the utilization of this potential. In order to break down these silos, the study respondents found it essential that the IT department and the specialist department exchange information regularly, as this enables cross-departmental know-how transfer and strengthens cooperation. The same applies to the exchange between partners along the entire value chain - i.e. also beyond the boundaries of the company. In conclusion, the Industry 4.0 Barometer 2018 showed that the relevance of Industry 4.0 has been under-stood in a competitive context, but that the company-wide implementation of Industry 4.0 often fails due to a lack of strategy, silo thinking and non-modular IT landscapes. It also became clear that many Industry 4.0 initiatives are not pursued beyond the status of a pilot project.

1.2 2019 Focus Topic: Drivers & Obstacles

Based on the findings and recommended actions from last year’s study, the MHP Industry 4.0 Barometer is entering its second round this year. The focus of the 2019 Barometer is on the drivers and obstacles to the cross-divisional and cross-company implementation of Industry 4.0 solutions. The study’s questions focus on the possible reasons and causes:

Are the investment costs for Industry 4.0 too high? Does the management not see and pursue the opportu-nities offered by Industry 4.0?

Are the necessary technological and organisational changes too complex?

Is there a concern that competitors and suppliers may gain access to important internal company data?

These and other questions regarding the implementation and benefits of Industry 4.0 solutions will be statistically analyzed and interpreted in order to ease the company-wide introduction of Industry 4.0.

The choice of topics is based on the drivers and obstacles we observe most frequently in customer projects as well as on current scientific work. They cover the most diverse aspects and areas of a company and range from strategic (e.g. top management roles, cyber security), tactical (e.g. Change Management, investment decisions) to operational (e.g. resource allocation) topics.

In summary, when introducing Industry 4.0 projects, com-panies are confronted with numerous influencing factors which can have a decisive influence on success as accelerat-ing or inhibiting elements. In order to reduce blocking fac-tors and to be able to push positive influences further, this year’s MHP Industry 4.0 Barometer is intensively dedicated to investigating these drivers and obstacles of Industry 4.0.

The MHP Industry 4.0 Barometer was set up and carried out for the first time last year by MHP Management- und IT-Beratung in cooperation with Prof. Dr. Johann Kranz, Head of the Chair for Internet Business and Internet Ser-vices at Ludwig Maximilian University in Munich. The aim of the survey is the long-term establishment of an industry-wide benchmark to determine the maturity level of existing and future digitization activities within German industry. In the past year, more than 220 respondents, in particular managers and senior staff from IT and specialist depart-ments in various industries, were surveyed on the following key topics: technology, IT integration and strategy & goals.

1.1 A Look Back: Industry 4.0 Barometer 2018

The results of last year‘s study showed that all companies surveyed were aware of the relevance of Industry 4.0 and see the introduction of new Industry 4.0 technologies as a decisive factor for success. On the other hand, the implementation is partly detached from a strategic basis. The study clearly showed that there is often a lack of a coordinated approach within the company when planning, initiating and managing Industry 4.0 projects and that the company-wide implementation of Industry 4.0 solutions therefore often fails due to unstructured methods.

With regard to IT integration, the study respondents confirmed the increasing complexity of IT architectures and inconsistent roadmaps, software platforms and IT strategies.

As a possible explanation, the strong dependency between individual IT systems was mentioned, which continues to impede a modular IT architecture. A high degree of mod-

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02Methodology and Respond-ents

As in last year’s Industry 4.0 Barometer, the methodological and technical starting point is the MHP Industry 4.0 Frame-work. This enables companies to structure the complex field of Industry 4.0 and efficiently exploit their potentials. The framework forms a matrix, whose horizontal perspec-tive with the steps Develop, Source, Make, Deliver and Pro-vide contains all central processes along the classic value chain. The vertical perspective consists of the three main clusters Technology, Strategy and IT Integration, which have been identified through the step-by-step analysis of business requirements for Industry 4.0 solutions.

The survey of the Industry 4.0 Barometer is divided into the Technology, IT Integration and Strategy and Goals clusters, similar to the MHP Industry 4.0 Framework presented here. The focus topic of this year’s Barometer is examined in the fourth cluster, Drivers & Obstacles.

2.1 Methods of Evaluation

The survey response patterns followed a five- or seven-level Likert scale. For a clearer evaluation, the possible answers of the different multi-level Likert scales were clustered.

In addition to the distribution of the answers, the weight-ed arithmetic average was formed as a percentage value, which is referred to as the barometer value in the study. For the calculation, the five- or seven-level Likert scale was converted into a metric scale with the values 0-4 or 0-6. After multiplying the metric scale values by the respective relative frequencies from the answers, the weighted arith-metic average was divided by 4 or 6 to obtain a barometer value between 0% and 100%. Given that the Industry 4.0 Barometer is to be developed

into a periodic survey, the barometer value serves as a benchmark.

The evaluation of the answers was anonymous.

2.2 Study RespondentsThe results of the Industry 4.0 Barometer 2019 are based on the responses of 195 respondents from various indus-tries, company sizes, hierarchical levels and functional are-as in the German-speaking countries (DACH). (See graph on the left and next double page). 87% of the respondents are male and 13% female. At the time of the survey, 55% of the respondents were 18 to 39 years old, 43% of all respondents were aged between 40 and 59 years. 3% of the respondents were in the age group between 60 and 70 years.

Very poor Average Very good

Poor Average Good

Not in use Use is planned Practical tests Partial use Full use

Not in useUse is planned or

practical testsPartial use Full use

Totally disagree Neutral Totally agree

Disagree Neutral Agree

2.3 Interviews and CaseStudies

In addition to the analysis of the survey results, the Industry 4.0 Barometer 2019 contains case studies and interviews from the Industry 4.0 environment. In this way, the Barom-eter is supplemented by expert contributions from indus-trial practice in addition to the empirical survey values.

The case studies contain concrete successful use cases of Industry 4.0 solutions and technologies. They describe the initial situation at the client’s site, the procedure during the project and finally the most important results.

The interviews were conducted with Industry 4.0 experts from industry and research. The interviewees were asked about their assessment of the current state of develop-ment of Industry 4.0 in German industry and about Indus-try 4.0 application examples and initiatives within their organizations.

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Hierarchy levels between the respond-ents and management / executive board

No levels

1 level

2 levels

3 levels or more

IT

Production andLogistics

Research andDevelopment

Marketing andDistribution

Management

Purchasing Department

Other

26 %

22 %12 %

11 %

6 %

4 %

19 %

N = 195

Functional Areas

N = 195

Company Size

Small companies(<1,000 employees)

Medium-sized companies(1,000 to 9,999 employees)

Automotive OEM

AutomotiveSuppliers

Medicine andHealth

Machinery and Equipment

Energy andWater Industry

Paper andPrinting

Other

Industry Sectors

Large companies(>10,000 employees)

N = 195N = 195

31 %

25 %

44 % 19 % 22 %

24 %

17 %

7 %

7 %

4 %

33 %

50 %

7 %

10 %

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Our products are equipped with a “digital product memory” (RFID, NFC, embedded system) that automatically transmits relevant data.

We have a digital map of our production facilities, which contains process and status data and enables simulations.

We have a digital image of our products, which contains detailed data about process and condition data, which are related to the product.

We have a digital map of our entire value chain, which contains process and status data and enables simulations.

24%

20% 33% 36% 11%

41% 21% 9%29%

29% 39% 8%

15%

10%

6%

8%

40%

27%

20%

44%

27%

38%

42%

28%

18%

26%

32%

20%

23%

23%

39%

19%

25% 40% 30% 5%

38% 39% 4%

47%

47%

44%

39% 34%

26%

26% 6%

6%

4%

13% 1%

21%

03Results of the Study

3.1 Technology

The Technology Cluster focuses on the use of Industry 4.0 technologies. An overview is given of the extent to which processes, systems, plants and products have already been digitized.

Supply Chain Transparency

The mapping of product or plant states in real time and the creation of meaningful parameters enable a high level of transparency along the value chain. A prerequisite for this is that plants and products have the appropriate techno-logical equipment to be able to map the processes carried out with data.

In 2019, the location of individual parts and products along the entire value chain continues to show the great-est potential for improvement in supply chain transpar-ency. The traceability of parts to the respective products is indispensable in order to be able to react promptly and flexibly to changes in the status of production. Just under a third of the respondents - in 2018 it was still 45% - state that traceability is not possible.

Within the factory gates, components and products in the automotive industry can be tracked much better than in the other reference industries. More than 80 % of the respondents stated that an application is being planned or that a tracking system is already in use. RFID technology, for example, which is being used more and more in the automotive industry, could also help. RFID is a transmitter-receiver system for the automatic and contactless identifi-cation and localization of objects and is thus a major ena-bler in improving transparency in the logistics chain (see the Case Study).

Digital Twin

Digital Twins represent the digital map of all relevant infor-mation of a physical product, the production facilities as well as the processes that can be mapped and are regarded as a fundamental element of Industry 4.0. Only 4% of the respondents stated that their companies use RFID, NFC and embedded systems completely within the company to automatically send the relevant data for the Digital Twin.

A partial use of these technologies is 34%, while most respondents stated that the use of digital product memo-ries is being planned or that practical tests are being con-ducted. Only every fourth company has so far made partial use of digital maps to obtain process and status data and to enable simulations in production.

A similar picture emerges for the digital product twin. The holistic networking of the digital twins of products and processes along the value chain is only known or imple-mented in a few exceptions.

In comparison to the Industry 4.0 Barometer 2018, the results show an increasing use of digital twins in the own company. According to this study, significantly more digital images will be used in production than in 2018. Overall, the barometer value in this theme cluster will rise from 36% to 40%.

Supply Chain Transparency

Digital Twin

All our products are equipped with sensors or could be easily retrofitted to record and transmit environmental parameters and status data.

Information about components can be traced back to the manufacturer and limited in time.

We can locate all parts of our products as well as end products within our plants.

We can locate all individual parts of our products as well as end products along the entire value chain.

Automotive industry

Automotive industry

Reference industries


Our plants and systems in production, warehouse and logistics are equipped with sensors to record and transmit environmental parameters and status data

Automotive industry vs. reference industries We can locate all individual parts of our products as well as end products within our plants.

Automotive industry vs. reference industries Our products are equipped with a “digital product memory” (RFID, NFC, embedded system) that automatically transmits relevant data.

No use Use is planned or practical tests Partial use Full use


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Analysis Phase

Implementation PhaseMaturity level and industrial application of RFID technology

In times of digitalisation, the focus is on reducing media disruptions, i.e. closing the gap between the real and digi-tal world. Even in the highly complex system of the auto-motive industry consisting of manufacturers (OEMs), sup-pliers and logistics providers, this is a constant challenge. In this area of conflict, the potential for optimizing value-adding and supporting processes based on RFID is enor-mous. For several years now, countless tests and projects have been running in the automotive industry and the Ger-man Association of the Automotive Industry (VDA) has also compiled a comprehensive library of recommendations for the use of RFID technology over many years. Nevertheless, the widespread use of RFID in production and logistics between suppliers and OEMs has not yet been realized. Only now, in 2019, German OEMs are bringing the topic of RFID to the big stage with extensive rollouts. RFID tech-nology is on the verge of exploiting the prepared potential through targeted implementation on a wide scale. From the point of view of technology, standards, interfaces and integration, it is clear that the use of RFID on a large scale generates numerous benefits. A positive example of a first successful initiative is a German manufacturer of premium vehicles that integrates more than 1,000 suppliers into an RFID-based cycle. One obstacle to the rollout is that some

Implementation Phase

4. Recording and Definition of Processes and Informa-tion FlowIn the next step, concepts were developed for the selected use cases to integrate them into existing structures and pro-cesses. Within the framework of process and IT workshops, the new concepts were developed and documented along the processes of the reference work.

5. Hardware Selection and Operating Concept Subsequently, use case specific requirements were devel-oped. On this basis, pilots were developed and tested in a testing and real environment. Afterwards, potential suppli-ers were contacted to submit offers and a selection of sup-pliers was made. Furthermore, a rollout, operation, mainte-nance and training concept was developed and elaborated.

companies do not take sufficient account of functional-ity requirements. It is therefore necessary to analyze the technical and economic benefits of process optimization in advance and to define and calculate the corresponding use cases.

l. Initial Situation & Challenge

MHP has taken up these challenges and manages projects on the part of both suppliers and OEMs in order to optimally exploit the potential of the technology. Among other things, the opening of a new engine plant for a premium automo-tive OEM in Eastern Europe is to serve as a flagship and test environment for new technologies. Within the scope of the project supported by MHP, the use of RFID in inbound, intra- and outbound logistics of production materials and load carriers will be highlighted and should contribute to an increase in process reliability and reaction speed as well as to greater transparency of operating resources of the entire logistics chain.

ll. Procedure & Results

The project procedure was divided into the analysis phase and the implementation phase. Both phases were divided into three further work packages:

6. Implementation and StabilizationFinally, the first proofs of concepts were introduced at the new plant along the rollout concept, ensuring the start-up and implementing initial improvements in the live setting. The project is currently in the phase of stabilisation and con-tinuous improvement.

lll. Results & Forecast

The project shows that the structured derivation of use cases along customer-specific processes paves the way for a prom-ising establishment of RFID. The operational and economic process optimizations can be scaled by the findings and the know-how gained within the framework of a global rollout. While the barcode has reached the end of its development

Analysis Phase

1. Process AnalysisFuture relevant processes were identified holistically on the basis of a reference work in order to obtain valid compara-tive values for the subsequent use case conception. The material and information flows were recorded and also visualized in a big picture in order to sustainably record the transparency gained.

2. Use Case ConceptionBased on the Big Picture, 24 RFID use cases were developed along the entire value chain (end-to-end). These were evalu-ated on the basis of a defined catalogue of criteria and prior-itised in terms of maturity level and implementation speed.

3. Business Case CalculationWith the help of a business case calculation, the RFID project of the new engine plant was analysed and evaluated quan-titatively. The economic evaluation of the implementation was carried out under consideration of process optimiza-tions, IT, hardware, installation & operating costs. In addi-tion to a holistic analysis, use case specific calculations were also carried out. The analysis phase was concluded with the final selection of use cases for implementation.

potential, RFID is being further developed and optimized as the second most mature AutoIdent technology. A con-tinuous transparency along the logistics processes leads to a higher reaction speed, which in turn leads to a reduction of working capital, e.g. through inventory reduction. Fur-ther benefits are the tracking of errors in order to increase product quality and the flexibility gained through faster and better information processing. From the project described and the potentials shown, it becomes clear what is already possible with today’s technology standard. The application possibilities shown suggest that the use of RFID is not just a vision of the future, but that it can be used in real Industry 4.0 scenarios

End-to-End RFID Implementation inYour New Plant

CASE STUDY RFID IMPLEMENTATION

Process Analysis- Process Analysis of a reference plant- Process documentation and visu-

alization

Detailed Process Inform. Flow- Process Analysis of Use Case Process- Process documentation and IT

workshop

Use Case Development- Development of 24 RFID Use Cases- Use Cases prioritization & implemen-

tation plan

Hardware Select Operation Concept- Specification of hardware requirements- Development of operating, mainte-

nance training concept

Business Case Calculation- Analysis of quality structure- Overall and Use Case specifica

Business Case Calculation

Implementation & Stabilization- Testing & Implementation of RFID- Implementation of RFID Use cases

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Automation & Autonomous Systems Digital Production Technologies

33%

38%

35%

45%

39%

19% 4%

1%18%

32%

42%

31% 33% 7%

3%

3%

2%

24%

19%

11%

40%

41%

51%

14% 40% 41%

31% 37% 27% 5%

5%

14% 27% 45% 14%

36% 37% 11%

35% 11%

8%

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41% 27%

16%

14%

24%

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18% 23% 45% 14%

34% 45% 13%

Automation & Autonomous Systems

In industrial production, complex and interlinked systems already form the basis for highly flexible automation along the entire value chain. The path to a finished product is cost-intensive, requires a high degree of coordination and often represents critical points.

This is reflected in the Automation & Autonomous Systems category. Although this category still has the lowest level of implementation at 3.8%, there is a clear trend towards ongoing practical tests.

The currently most frequently implemented method among the respondents is the central communication of plants, devices and systems by means of an Enterprise Service Bus (ESB). This central communication solution is in operational use more than twice as often as decentralized machine-to-machine communication.

Decentralized machine-to-machine communication can also form the basis for autonomous systems and processes. Although the degree of implementation of this solution

has been rated lower than that of the Enterprise Service Bus, the survey shows that the decentralized communica-tion solution will continue to be the focus of attention in the future. Last year, almost two thirds of the respondents had not yet deployed decentralised communication solu-tions. In this year’s study, on the other hand, only about one third of the respondents are still using decentralized communication solutions. Delays caused by the transmis-sion of large amounts of data can be reduced and thus complex production processes can be executed decentrally, taking local data into account.

Independently reacting processes in conjunction with autonomously organizing machines and robots form the basis for modular production in Industry 4.0. It is there-fore not surprising that the proportion of participants who stated that they did not use autonomously organizing machines and robots has decreased by more than one fifth.

Digital Production Technologies

The highest degree of implementation can be found in the remote control of plants and machines. In comparison to the previous year, the majority of the study respondents are partially or fully using remote control of plant and machin-ery, whereas last year the focus was on planning and test-ing. The systemic integration of machines and equipment for greater process automation has also increased signifi-cantly compared to the previous year.

The use of additive manufacturing technologies continues to make inroads into the industry due to rapid technologi-cal developments and positive business cases. The major-ity of the companies surveyed stated that they are already using these manufacturing methods in part or are currently running practical tests. What is striking here is that many companies did not yet use the production methods last year or were still planning to do so. The use of modular

production technologies to increase agility and flexibility has already partially entered the industry. The transforma-tion to SAP S/4HANA that is currently being initiated in many companies is only one of the many driving forces that are currently affecting companies. This is also shown by the barometer value, as companies in 2018 used fewer modular production technologies than in 2019.

Data Analytics

Data Analytics comprise various methods for the analysis of information, which are used for decision making and process optimization. The use of predictive maintenance solutions has increased significantly compared to the previ-ous year. More than half of the respondents stated that machine data is used partially or completely to indepen-dently identify maintenance needs.

It is also noticeable that the collection and analysis of data along the value chain is being increasingly initiated. 40% of those surveyed stated that planning or practical tests are being carried out in this topic. This represents an increase of 10% compared to 2018.

In summary, it is clear that the subject area of data analyt-ics is becoming increasingly important for companies and that the use of the technologies required for this purpose is constantly increasing. Compared to the previous year, the respondents indicated that the four topics surveyed are in the planning phase or already in use.

Our equipment, devices and systems communicate with each other via an Enterprise Service Bus.

Our plants and machines can be remote controlled via software.

Our equipment, devices and systems communicate autonomously with each other via the Internet (machine-2-machine).

Plants and machines can be integrated into and work together with other plants and systems.

We use autonomously organizing machines and robots. We integrate additive manufacturing methods into our production(e.g. 3D printing of spare parts).

There are company processes in production, warehouse and logistics that can react independently to changes, be controlled or improved.

We use modular production technologies to increase our production agility and flexibility.

Our systems and machines send their operating and machine data to signal the need for maintenance and trigger this independently (Condition Monitor-ing).

All operating and machine data of our plants and machines are recorded centrally and are available for analysis at any time.

Central data along the value chain are continuously collected and analyzed.

We operate a central data platform whose data is made available to selected respondents within the value chain.

Automotive industry vs. reference industriesWe integrate additive manufacturing methods into our production (e.g. 3D printing of spare parts).

Automotive industry vs. reference industriesOur systems and machines send their operating and machine data to signal the need for maintenance and trigger this independently (Condition Monitoring).

29% 13% 17% 45% 25%

8%

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8%

41%

32%

31%

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38%

38%

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Data Analytics

continued on page 30

Automotive industry

Automotive industry

Automotive industry




Automotive industry vs. reference industries We use autonomously organizing machines and robots.

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Short CVThomas Bergs (Source: Fraunhofer IPT Homepage)

Professor Dr.-Ing. Thomas Bergs, as a member of the board of directors of the Fraunhofer Institute of Production Tech-nology IPT, heads the Process Technology Department and is head of the Chair of Manufacturing Technology at the Machine Tool Laboratory WZL of RWTH Aachen University. From 1995 to 2000, he was a research associate in the Pro-cess Technology Department at the Fraunhofer Institute of Production Technology IPT in Aachen. In 2000, he became head of the Laser Technology Group and the “Aachener Werkzeug- und Formenbau” business field. Since 2001 he has also held the position of managing senior engineer at the Fraunhofer IPT. From 2005 to 2019, Thomas Bergs was also the managing partner of Aixtooling GmbH in Aachen, which is active in the field of toolmaking for precision moulding. On June 1, 2018, he was appointed university professor at the Chair of Manufacturing Process Technolo-gy at the WZL of the RWTH Aachen University and head of the Process Technology Department at the Fraunhofer IPT. As successor to Professor Fritz Klocke, he is also a member of the board of directors of both production technology institutes.

Company ProfileFraunhofer Institute of Production Technology IPT

The Fraunhofer IPT develops system solutions for net-worked, adaptive production. The clients and coopera-tion partners come from the entire manufacturing indus-try - from aerospace technology, automotive engineering and its suppliers, especially from tool and mould making, precision mechanics and optics, but also from the life sci-ences and many other sectors. The Fraunhofer IPT com-bines knowledge and experience in all fields of production technology.

In the areas of process technology, production machines, production quality and measuring technology as well as technology management, project partners and clients are offered customised solutions and directly implementable results for the manufacture of sophisticated components and high-tech products

MHP: The Fraunhofer IPT operates at the interface between research and industry. With this positioning, how do you support your industrial customers and cooperation part-ners in the topic area of Industry 4.0?

Prof. Thomas Bergs: From a global perspective, Germany has a great deal of expertise in the excellence of technolo-gies in the field of production engineering. This contrasts with the USA, which is very strong in IT development and data processing, and China, which is particularly fast in implementing new technologies. In order to advance the positioning of German companies in the Industry 4.0 sec-tor, technological capabilities must be combined with dig-itisation so that solutions can be developed quickly. To this end, platforms must be created where concrete manufac-turing tasks can be tested and data can be analysed and validated. The Fraunhofer IPT connects industry through collaborations in which solutions can be tested that are related to digitization and manufacturing technologies. To this end, the Fraunhofer IPT provides the cooperation part-ners with technology knowledge, test environments and digital solutions to help them implement the Industry 4.0. solutions.

MHP: The Fraunhofer IPT has already implemented numer-ous aspects of Industry 4.0 in its research and development projects with partners from various industries. Could you name some successful examples?

Prof. Thomas Bergs: For ourselves, we have created so-called pilot lines as well as incubators in which we investi-

gate certain types of manufacturing issues and make use of the possibilities of digitization. A concrete example is from the field of turbomachinery. Here, we are concerned with the manufacture or series production of a safety-crit-ical component in a compressor of an engine, a so-called blisk. Here, data from a 5-axis milling machine are collected and analyzed, which are then synchronized with data from the simulator. The synchronization of the data from the simulation models and the production provides informa-tion and prognosis possibilities for the quality of the pro-duced component and helps to detect causes for defects faster. Another pilot line in toolmaking reads out technol-ogy chains for the production of an injection mould. Here-by, individual technologies can be evaluated and predicted with regard to effect, quality, runtime and productivity and offer planners the possibility to select the optimal process chain according to the requirements. This is comparable to a Google Maps approach, which usually shows alternative routes depending on whether you want to go through a production process particularly quickly, with high quality or under different conditions.

MHP: They coordinate the “Networked Adaptive Produc-tion” performance centre, where, among other things, an open research platform and test environment for industry is being designed. How do your industrial customers ben-efit from this?

Prof. Thomas Bergs: The performance center is a project funded by the Fraunhofer Gesellschaft and the state of North Rhine-Westphalia, which has made it possible to set up such pilot lines or test environments for representative manufacturing examples. Real manufacturing cases are now being developed and tested here together with the project partners. This is followed by the ICNAP (Interna-tional Center for Networked, Adaptive Production), a com-munity for companies from the IT and manufacturing sec-tors who, through membership, have access to the results

ExpertInterview

Prof. Dr.-Ing. Thomas BergsHead of the Process Technology Department at the Fraunhofer IPT

of the tested pilot lines and can participate and contribute to future joint work.

MHP: Which technological and organizational prerequi-sites do companies have to create in order to successfully integrate new solutions from information technology into production? How important is the cooperation with part-ners in the value network?

Prof. Thomas Bergs: The cooperation of the partners is very important. For the first time, the Fraunhofer IPT has developed a 5G platform that allows working with real 5G applications. This was not a strategic in-house devel-opment, but was the result of innovation platforms and collaborations, for example with the Ericsson company, where different disciplines developed ideas together. In these platforms, the communities can think up new, inno-vative solutions, test them in test environments and discuss the results. Hackathons are also used to establish contact with up-and-coming talents who, together with the com-munity, conduct workshops and studies on the topic of 5G and digital twins.

MHP: Which obstacles or challenges for the operation-alization of Industry 4.0 are do your industry customers encounter most frequently?

Prof. Thomas Bergs: In the field of data engineering, there are still few standards that enable and simplify the linking and synchronization of data formats and sources in order to achieve usable results. Especially if the data is more complex and time sensitive. The task of the Fraun-hofer IPT is to implement exemplary projects, develop solu-tions and demonstrate the advantages, so that in the end standards or integrated software solutions are developed that are transferable to other formats and can automati-cally synchronize data. In addition, a major challenge lies in the value-added networks. If data is collected from process

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with high precision. With 5G, these functions can be implemented wirelessly and are available as standard. In addition, the use of the 5G network can be focused and prioritized. If, for example, critical processes require a large part of the per-formance, the allocation of the performance components in the 5G network will be auto-mated and ensures that latency relevant tasks are not interrupted due to tracking tasks.

MHP: In which areas do you see a backlog demand for German industry on the way to Industry 4.0? What do the manufactur-ing companies have to concentrate on in order to remain competitive in the long term?

Prof. Thomas Bergs: An important element is to get to implementation quickly. The German industry tends to take precautions in all directions before decisions are made. To be more efficient, ideas must be tried out and tested more quickly. And with its communities and platforms, the Fraunhofer IPT provides German companies with the framework for testing ideas, checking them for added value and implementing them in their companies.

chains involving different players in the value chain, they must jointly develop a homogeneous solution along the supply chain.

MHP: In your opinion, what are the critical success fac-tors for a cross-departmental or cross-company rollout of Industry 4.0 solutions?

Prof. Thomas Bergs: The question of added value is cru-cial when it comes to implementing Industry 4.0: “Turning data into value”. (This is also a central theme of this year’s AWK - Aachen Machine Tool Colloquium, where experts from industry, science and politics discuss this question of the added value of Industry 4.0). This value can vary depending on the objective and the company. On the one hand, it can be economic dimensions, such as productivity gains, cost savings or quality improvements, and on the other hand, it can also be the optimization of sub-areas of production. In this respect, Industry 4.0 offers compa-nies the opportunity to try out new technologies and check their added value. To do this, however, the data must first be collected, evaluated and processed in order to be able to identify added value. Industry 4.0 is also not a technical solution, but rather a view or assumption that a potential can be exploited by using data. For this, real cases must be implemented and validated with regard to their added value.

MHP: Do you think that the background with the Fraun-hofer Institute and the orientation towards research is a positive factor regarding the trust of the individual partners?

Prof. Thomas Bergs: For companies, the neutral environ-ment is particularly relevant when dealing with customer-specific data. For example, a machine tool manufacturer can analyze and evaluate data with a customer outside the critical area of its own production using representative

components. This process creates a basis of trust, where on the one hand the added value of the technological change is shown and on the other hand the return on investment is presented transparently.

MHP: The Digital Twin represents a central element of Industry 4.0 in terms of the evaluation and analysis of product and process data. How can companies effectively use the Digital Twin to reduce costs or generate additional revenues?

Prof. Thomas Bergs: Several aspects have to be taken into account for this. Firstly, the definition of the concept of the Digital Twin is still very heterogeneous. From a production technology point of view, it is the maximum information view that can be attached to a component in development or refinement. This information view allows to identify and exploit potential uses. If, for example, a safety-critical com-ponent is being processed, the condition of the component is relevant. And this information can be carried along to the machine with the help of the Digital Twin in order to be able to design and determine the process step differently according to the status and to check whether this change has an influence on the functionality of the component. On the other hand, the history of the Digital Twin can be used to carry out retrospective analyses to find out why certain batches are better or worse in terms of use.

MHP: The topic of 5G is very present in the media as well as in the industry. From a research perspective, where do you currently see the greatest potential for the use of 5G technology in production?

Prof. Thomas Bergs: The benefit of 5G lies in the sim-plification and standardization of connectivity in produc-tion. In manufacturing, 5G is relevant due to its low latency and high deterministics. However, it is also possible to link several machines in a network and localize components

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Platform & Connectivity

New applications and features can be quickly integrated into critical applica-tions according to end-user needs.

We use a software platform to integrate our supply chain partners into our systems (IT, production).

Our IT architecture becomes more complex through Industry 4.0, e.g. through point-to-point application connections.

In our company there is a clearly defined roadmap, how our IT architecture with Industry 4.0 should look like in the future.

Our company has a plan on how to integrate or replace legacy systems in the future to meet Industry 4.0 requirements.

26% 56% 18%

25% 51% 24%

10% 49% 41%

23% 52% 25%

24% 56% 20%

Disagree Neutral Agree 2018 Barometer value 2019 Barometer value

3.2 IT Integration

The IT integration cluster refers to the performance of the companies’ own IT systems and areas of the companies surveyed.

IT-Standards

Overall, there is a positive trend towards the use of uniform communication standards and data formats. Almost half of the respondents agree with the statement that their own IT and that of their partners follows industry standards, 7% have the opposite opinion. 31% of the respondents con-firm that they agree on uniform communication standards and data formats with their partners along the value chain. 53% have a neutral opinion on this statement, while 16% state that they do not coordinate standards and data for-mats with their partners. 28% of the respondents agree with the statement that they use open and non-proprietary standards to the greatest extent possible for the commu-nication of equipment, devices, systems and products to ensure interoperability.

In comparison to the Industry 4.0 Barometer 2018, this year it becomes clear that coordination with partners along the value chain on standards and data formats has increased significantly and that work is being done on open stand-ards to ensure interoperability.

IT Architecture

The results of the survey on the performance of the com-munication architecture in and between the plants as as with the customers show that one in seven respondents perceives their own architecture as inefficient.

On the other hand, 30% attribute high performance to

their communication architecture. When asked about the use of an end-to-end service-oriented IT architecture (SOA), two-thirds of respondents voted “neutral”. Only 15% of the participants confirm the use of an SOA in their compa-ny. The respondents’ assessment of a modular IT architec-ture is also in the neutral range. 18% of the respondents estimate that their company has an architecture in which modules can be quickly integrated via defined interfaces. With regard to the dependencies between the systems and the architecture, 6% feel that these are reduced to a mini-mum in their company. One third feel that there are major dependencies between the system and the architecture.

In comparison to the “Industry 4.0 Barometer 2018”, a negative trend could be observed in the IT architecture in the area of dependencies between systems and architec-ture: The average barometer value fell from 44% in 2018 to 38% in 2019.

Platform & Connectivity

17% of respondents agree with the statement that they can quickly integrate new functions into critical applica-tions, while 26% see difficulties with integration in their company. A quarter of respondents say that their com-panies use software platforms to integrate supply chain partners with IT and production systems. Similarly, 25% also agree that they do not use platforms for this purpose. 51% are not sure whether the integration of the partners is done via software platforms. 41% of the respondents agree that Industry 4.0 makes IT architecture more com-plex, while 10% do not see any increase in complexity as a result of Industry 4.0. Every second respondent (49 %) is neutral regarding this statement. 25% of the respondents agree with the statement that there is a clearly defined roadmap for architecture in the Industry 4.0 context, while 23% disagree. More than half

of the respondents (52%) are “neutral”. A similar picture can be seen for the statement of the legacy systems. One in five respondents say that there is a plan in their company for integrating or replacing legacy systems in the future. 24% state that there is no plan for this and 56% are neu-tral towards this statement.

Compared to the Industry 4.0 Barometer 2018, a continu-ous increase in the values can be observed. Accordingly, the average barometer value for Platform & Connectivity will rise from 48% (2018) to 52% (2019). Especially in the use of software platforms the barometer value has risen by 8 percentage points.

Big Data

The Big Data section deals with the assessment of dif-ferent techniques and capabilities for the availability and

processing of data. Almost half of the respondents (48%) consider the preparation and management of data to be good with regard to availability, consistency and topicality. 36% of the respondents rate their company as mediocre in the management of data and 16% give their company a poor rating. The automated generation of reports, anal-yses and notifications based on current company data is rated as good by almost every second (46%) respondent in their company. The majority of those surveyed rated their company as poor when using partially or fully automated decisions through artificial intelligence or machine learn-ing. In this point only 14 % of the interviewees consider their company well positioned In the area of advanced data analysis, 39% of the respondents don’t have the personnel skills for data mining and machine learning in their com-pany. Similarly, 35% of respondents say that the technical infrastructure for advanced data analysis, such as in-mem-ory databases, is poor.

IT Standards

IT Architecture

We coordinate with our partners along the value chain on the use of uniform communication standards and data formats for Industry 4.0 projects.

We have a powerful communication architecture in and between our plants and with our customers

We use, wherever possible, open and non-proprietary standards for the communication of our equipment, devices, systems and products to ensure the interoperability of our systems.

We use an end-to-end service-oriented IT architecture (SOA).

Our IT infrastructure and that of our partners follow the industry standards.

Our IT architecture is modular according to the building block principle, i.e. modules can be quickly integrated and combined via defined interfaces.

The dependencies between the systems of our IT architecture are reduced to a minimum.

16% 53% 31%

29%

47%

58%

46%

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7%

14%

18%

21%

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The expectations for Industry 4.0 are clear: Manufacturing companies are striving for lower maintenance and repair costs with higher machine availability, as well as increased efficiency through transparency and traceability. Employees want the best possible support in a modern, digital work-ing environment. Intelligent software solutions and services ensure consistent transparency and efficiency in manufac-turing and logistics processes. Bosch Connected Industry bundles these in a comprehensive portfolio called Nexeed.

With Nexeed, we are pursuing one main goal: to provide our customers with the best possible support in networking their value stream. That’s why we are at their side from the initial consultation, through the corresponding implementation, to further networking. Together, our solutions simplify the daily work of our employees and optimise production and logis-tics processes in terms of transparency, agility, costs, quality and time.

Nexeed software solutions ensure that product, process and logistics data from all machines and systems are used for continuous improvement - from procurement to production and delivery to the end customer. Nexeed enables a simple and targeted entry into the networked factory: customers receive both cost-effective starter kits and simple retrofit solutions as well as comprehensive packages with tailored services.

the punching machine. This information can be used to determine possible signs of mechanical wear - for example, if the cycle time increases or the load becomes greater. Sup-ported by an intelligent trend analysis, employees can bet-ter plan maintenance and reduce downtimes to a minimum. Pre-definable rules that automatically issue warnings when limit values are exceeded also enable potential faults to be detected and rectified at an early stage.

lll. Summary & Outlook

As the Nexeed Production Performance Manager has meanwhile proven itself successfully at various stations, the BMW Group decided to implement further projects: In cockpit production, the software is currently being rolled

Accordingly, Nexeed solutions can be combined to network individual lines, entire plants and plant groups as well as their intralogistics and external goods traffic.

Nexeed Production Performance Manager – Soft-ware for the Systematic and Sustainable Production Optimization

The Nexeed Production Performance Manager (PPM) records and coordinates production and machine data from various sources in the shop floor in real time. The data is visualized and forwarded to the employees as defined events. The simple rule configuration enables maintenance personnel to carry out predictive maintenance with the least possible downtime. The product quality can be optimized by continu-ous monitoring and documentation of process data.

Possible applications of the PPM:

Condition Monitoring: Permanent status recording for maximum transparency

Real-time process data analysis: Reduce production errors and process deviations to a minimum

Predictive maintenance through configurable rules, auto-matic notifications and order assignment

Flexible industrial 4.0 all-purpose tool for customer-specific applications in the factory

out to identical processes. Other production steps, such as glue application, are also being integrated. In the long term, the Nexeed Production Performance Manager is to be used not only in the interior area, but throughout the plant. Through the simple customisation of the software, it will also be permanently improved in existing areas of application.

The high flexibility and the functionality of the system pro-vided by us makes a use case-oriented application possible without any problems.

Ole Schulczewski – Automation EngineeringBMW Group

Use of the PPM at the BMW Group Plant Landshut

l. Initial Situation & Challenge

The BMW Group plant in Landshut is the BMW Group’s competence centre for electric mobility and lightweight con-struction. This is where innovative components for all vehi-cles are produced, for example the BMWi models. Custom-ers have high expectations of their cars: safety and quality are just as important as comfort, functions and individuality. These demands are met at the Landshut plant with a high level of manufacturing expertise.

Greater transparency in the production processes should result in better equipment availability and a faster response to process fluctuations. Cockpit production marked the starting point for the implementation of the Nexeed Produc-tion Performance Manager at Bosch Connected Industry.

ll. Procedures & Results

The punching machine of the cockpit production was select-ed as a pilot plant. It was connected to the software via the Bosch Rexroth IoT Gateway. This collects relevant machine data and messages and displays them in a user-friendly form. The responsible employees see the time required between the retraction and extension of each individual actuator of

Maximum Process Transparency in AutomotiveComponent ProductionBosch Connected Industry – Industry 4.0 Software from one provider

Bosch Connected Industry Contacts

Dr. Nils-H. Schmidt Chief Product & Service Owner PPM Bosch Connected Industry [email protected]

Hr. Daniel Prinzing Senior Sales Manager Industry Solutions Bosch Connected Industry [email protected]

Full transparency of machine and process data

Increased efficiency through optimised digital processes

Lower costs thanks to systematic improvements

CASE STUDY PRODUCTION PERFORMANCE MANAGER

The advantages of the Nexeed Production Performance Manager:

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Access to operating and machine data is clearly regulated by a uniform identity and access management.

Our company has defined guidelines regarding the security and use of machine data.

Those responsible for IT security have a special say in important decisions.

The use of our own or third-party Industry 4.0 applications is carried out in accordance with recognised security guidelines (e.g. end-to-end encryption, ISO 27001).

IT Security

In comparison to the Industry 4.0 Barometer 2018, a posi-tive change can be noted especially in the areas of artificial intelligence, machine learning and automated decisions. Here the average barometer value has risen from 24% (2018) to 33% (2019).

IT Security

The IT Security section deals with the guidelines for the use of encryption technologies and for secure communication of machine data. Every second respondent (54%) states that access to operating and machine data in their com-pany is regulated by a uniform identity and access man-agement system. 11% do not have a uniform identity and access management. A similar picture can be seen with the guidelines for the security and use of machine data.

Here 60% of the respondents agree with the statement that they have guidelines for security and use of machine data. For 5% of the respondents, security guidelines are taken into account when using their own or third-party Industry 4.0 applications. 42% have a neutral opinion on this, while in 6% of cases guidelines such as ISO 27001 are not taken into account. The statement that those respon-sible for IT security have a special say in important deci-sions meets with the approval of every second respond-ent (50%). Only 7% of the respondents disagree with this statement.

Compared to the Industry 4.0 Barometer 2018, the barom-eter value has risen sharply. Access management and the introduction of guidelines for the security and use of machine data has achieved a 10% increase.

Scalability

In the last set of questions in the IT integration category, the focus is on the scalability of the IT architecture used in

each case through the use of cloud solutions and applica-tion programming interfaces (APIs). The scalability of the IT infrastructure is perceived by 17% of the respondents as particularly insufficient, whereas 23% have the opposite opinion. Regarding the possibility to connect business part-ners via APIs, 23% agree, while more than half of the par-ticipants are neutral towards the question. Compared to the Industry 4.0 Barometer 2018 an improvement in scal-ability and connectivity can be observed. The barometer value rises to 54 % in 2019 (previous year: 45 %).

3.3 Strategy & GoalsWithin the Strategy and Goals cluster, the strategic orienta-tion of the implementation of Industry 4.0 was addressed. For this purpose, fundamental prerequisites, organisational structures and internal and external communication chan-nels were examined.

Strategic Industry 4.0 Focus

The first section of this set of questions aimed to deter-mine the strategic focus of the current and future planned Industry 4.0 projects and initiatives of the participating companies. The survey results showed an increasing focus on cost reduction and efficiency improvement. As a result, three quarters of all respondents agree that their compa-nies are trying to reduce costs and increase the efficiency of their business processes. This results in an increase in the barometer value of approx. 27% compared to the previous year. Participants from IT departments see a stronger focus on developing new business models compared to partici-pants from other departments. Nevertheless, this aspect only plays a subordinate role in the overall picture. Par-ticipants from the automotive industry in particular place less emphasis on solving customer-specific problems with Industry 4.0 solutions than in the previous year.

Big Data

Preparation and management of data (availability, topicality, consistency).

Automated creation of reports, analyses and messages based on current company data.

Personnel skills for advanced data analysis methods (e.g. artificial intelligence, Data Mining, Machine Learning).

Technical infrastructure for advanced data analysis (e.g. In-MemoryData Base, Distributed File System, GPU Server, Hadoop, Spark).

Partially and fully automated decisions through artificial intelligence or machine learning.

With Industry 4.0 our company primarily aims to, ...

Poor Average Good 2018 Barometer value 2019 Barometer value

17% 35% 48%

20% 34% 46%

39% 28% 33%

36% 32% 32%

56% 30% 14%

21%

11% 35% 54%

9% 31% 60%

7% 43% 50%

6% 42% 52%

19% 26% 55%

44% 35%


Scalability

We can quickly scale our IT infrastructure up or down(e.g. through the use of cloud solutions).

We can contact business partners via Application Programming Interfaces(APIs, programming interface for software integration).

16%

2% 23% 75%

26% 71%3%

9% 51% 40%

9% 44% 47%

8% 31% 61%

9% 43%

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... reduce costs and at the same time improve quality, speed andto increase the efficiency of our business processes.

… increase the effectiveness of business processes.

… develop new market and customer segments.

… solve our customers’ problems.

… offer new services for our products (e.g. Predictive Maintenance).

… develop new business models.

Strategic Industry 4.0 Focus



Automotive industry

Automotive industry



Automotive industry vs. reference industries Automated creation of reports, analyses and messages based on current company data.

Automotive industry vs. reference industries Reduce costs and at the same time improve quality, speed and to increase the efficiency of our business processes.

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Industry 4.0 StrategyFramework

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Industry 4.0 Strategy& Vision

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North StarRoadmap

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Use-Case-Implementierung

The Volkswagen Group, based in Wolfsburg, is one of the world’s largest automobile manufacturers. The subsidiary Volkswagen Automatic Transmission (VW ATJ) operates two plants in the Chinese city of Tianjin. Since In 2014, VW ATJ will manufacture various transmissions in the plants. During the project period, the focus was on the start of production of electric drives on a new e-mobility produc-tion line. VW ATJ wants to set the worldwide standard for modern and innovative automatic transmissions. In particular for the Asian automotive market, the growth and success of the Chinese VW group subsidiaries SAIC Volkswagen and FAW-Volkswagen should be ensured. In addition, VW ATJ, as part of the Volkswagen Group, is committed to the highest production standards in order to guarantee a sustainable and effective use of resources. For this reason, the company focuses on various digitisation topics. The core of the digitisation initiative is Industry 4.0, and in order to address this issue in the most effective and targeted manner possible, VW ATJ would like to define a specific Industry 4.0 strategy.

The e-mobility production line, which was being planned at the time of the project, served as a pilot environment for the Industry 4.0 activities. After successful implementation, the new strategy will be transferred to the existing trans-mission production.

lll. Outlook

The workshops held were used to develop various fields of action for the VW ATJ Industry 4.0 Strategy and to identify related use cases. The implementation will be carried out within flagship projects in the examined areas of produc-tion (Shopfloor 4.0 Management, Smart Production Steer-ing, Smart Material Supply) and data management (BDE and QDE Data Correlation Analysis). This will be followed by the rollout

l. Initial Situation / Challenge

The existing transmission production in Tianjin has a low degree of digitalization. The manufacturing machines, pro-duction processes and products are currently only slightly networked with each other, if at all. Apart from this, cur-rent Industry 4.0 initiatives are not based on any common basis and are insufficiently coordinated with each other.

In order to meet the goals of efficient, sustainable and innovative production of VW ATJ as well as the high stand-ards of the Chinese automotive industry, a superordinate and coordinated digitisation strategy for the smart factory of the future is therefore required. Based on selected Indus-try 4.0 initiatives, the existing plans for powertrain produc-tion must be re-evaluated, changes defined and pursued in further implementation.

ll. Procedures & Results

First, we analyse the current corporate strategy and the industry-specific process landscape of the planned produc-tion line in order to determine the Industry 4.0 maturity level of VW ATJ. For this purpose, current use cases and capabilities are analysed with the help of the MHP Industry 4.0 Framework and combined into a vision and

of further fields of action such as a data storage concept or a knowledge database based on artificial intelligence. Thus, a use case-based implementation is to take place and the developed Industry 4.0 strategy is to be operationalised in order to realize the mission of VW ATJ as one of the most modern and innovative automatic transmission manufac-turers worldwide

mission in several strategy workshops. From this, both a cross-departmental and department-specific Industry 4.0 target picture is derived. In addition, strategic fields of action are identified, evaluated and prioritised with regard to their specific benefits for VW ATJ. In doing so, various framework conditions such as the existing IT landscape or the integration of the existing machinery are taken into account. Use cases are derived from the fields of action, such as “Shopfloor 4.0 Management” or “Smart Mate-rial Supply”, which are then implemented within the framework of flagship projects. Locating the use cases in the North Star Roadmap visualizes the time and content dependencies between the use cases and flagship projects. To ensure the sustainability and profitability of the initia-tives, a business case is created for each flagship project. Associated implementation and control strategies ensure successful implementation.

For the customer, the project results in a clearly defined Industry 4.0 strategy with a corresponding vision and mis-sion, as well as strategic fields of action for the entire fac-tory and all departments involved. This allows VW ATJ in Tianjin to initiate the most promising use cases in a target-oriented manner in order to achieve a high standard of implemented Industry 4.0 measures in the future.

Industry 4.0 Strategy @ VW ATJ

VW ATJ Contact

Jan-Philipp ThoeneLocal Digitalization Manager VW [email protected]

CASE STUDY INDUSTRY 4.0 STRATEGY

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Knowledge from other Disciplines

A mutual understanding of each other’s processes by the business and IT departments is a decisive success factor for target-oriented cooperation. The following section shows the extent to which the various company divisions have knowledge from other disciplines.

The survey results with regard to knowledge from outside

the field of study are for the most part in a neutral area. In particular, the assessment of whether operational depart-ments have a good understanding of the IT systems used is rated neutral by three quarters of the respondents. The assessment of the IT department’s operative process knowl-edge is also predominantly neutral. In contrast, more than one third of the respondents from the IT department state

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that they have knowledge from outside the department. However, less than a quarter of the participants from the business departments hold this opinion. Overall, only 26% of all respondents agree that the IT department has expertise in other functional areas. This barometer value shows a ris-ing trend of just under 10% compared to the 2018 survey.

Technology Intelligence

In order to be familiar with the latest technologies, it is necessary to look beyond one’s own company boundaries for know-how and innovations.

The survey shows that about one third of the companies already practice this innovative idea, with the approval of the surveyed employees from IT departments in particular being 10 percentage points higher. Significant trends com-pared to the 2018 survey can also be observed in the evalu-ation of the specialist departments on the following topics:

Lack of jobs with new digital technologies in the Industry 4.0 environment (barometer values 2018: 33%, 2019: 54%). Respondents from IT departments show the greatest drop in agreement.

Exchange with external partners about new and old technologies (barometer values 2018: 40%, 2019: 53%).

This year, the question of further training opportunities in the context of technical competence in the Industry 4.0 environment has been newly included. About one fifth of the study respondents agreed that such offers exist in their companies.

3.4 Drivers & ObstaclesIn the Drivers & Obstracles, the companies were asked to what extent different factors and framework conditions

Although the other aspects of entrepreneurial orientation also show increasing survey results, they still leave room for a possible need for action.

The integration and further training of employees from dif-ferent hierarchical levels is a decisive factor in the success of digitisation. The management is regarded as a driver of cultural change within the company.

Interdepartmental Collaboration

For the successful implementation of innovative technolo-gies in the context of Industry 4.0, it is necessary to dis-solve silo thinking and transfer technological know-how to the individual company departments. The basis for this is a regular exchange between the IT department and the specialist departments.

A third of the respondents stated that there are regular meetings between departments to exchange knowledge about the business environment, which in comparison to the barometer value corresponds to an increase of 26% compared to the 2018 study. A comparative increase can also be noted in the willingness to exchange information when making decisions. Compared to the previous year, this barometer value has increased by 22%.

The question of a common agenda also shows a similar increase, but is evaluated specifically by study respondents from IT departments with less agreement than last year.

Taking a holistic view of interdepartmental collaboration, a large proportion of the data (60%) lies within a neutral range.



Company Orientation Knowledge from other Disciplines

Technology Intelligence

Interdepartmental Collaboration

The management of our company is an essential driver for a very dynamic and entrepreneurial culture in our company. Employees of our IT department have a good understanding of the operative

processes of the business departments.

Our business units are on the lookout for innovative technologies and com-panies in the Industry 4.0 environment; also beyond our industry boundaries (e.g. acquisition/participation, technology partnerships).

Our specialist departments are too little concerned with the use of new digital technologies in the Industry 4.0 environment.

Our specialist departments quickly understand how we can use IT to improve processes and products.

Our specialist departments often exchange information with external partners (e.g. suppliers, customers, consultants, universities) about new and alternative technologies in the Industry 4.0 environment.

Our specialist departments offer employees the opportunity to expand their technical skills with regard to Industry 4.0 through (external) training and further education measures.

Employees in our departments have a good understanding of the IT systems used in the company.

There are regular meetings in which the IT department and other departments share their knowledge of the business environment

In our company, all persons involved in decision-making are willing to exchange information.

The IT department and other departments of our company have a common agenda.

The IT department and other departments have a common understanding of the role of IT in our company.

The management of our company has a good sense for new business ideas (e.g. product innovations, new business models, profitable market niches).

The management of our company promotes innovation and accepts risks.

Our company does not place great value on research and development, innovation and technological leadership.

11% 38% 51%13% 61% 26%

12%

13% 56% 31%

17% 55% 28%

16% 74% 10%

12% 74% 14%

18% 60% 22%

76% 12%54% 38%

57% 34%

8%

9%

14% 54% 32%

12% 61% 27%

18% 60% 22%

60% 21%19%

54% 32% 14%

The empirically collected results regarding cost and effi-ciency focus can be confirmed by the case study of VW ATJ. The study shows exemplarily how companies can explicitly use novel technologies to achieve efficiency and sustainability.

Company Orientation

The entrepreneurial orientation refers to various activities of the management and the resulting corporate culture in

relation to Industry 4.0 The survey results show that more than half of the companies place considerable emphasis on research and development, innovation and technologi-cal leadership. The corresponding barometer value shows a slight decline in terms of entrepreneurial orientation compared to the 2018 study. In contrast, the perception of management as a key driver of a dynamic and entrepre-neurial culture shows an upward trend. The survey results represent an increase in the barometer value of 24% com-pared to the 2018 survey.

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Disagree Neutral Agree 2019 Barometer value



Priorisation Employees & Resources

Change Management

Requirements

The introduction of Industry 4.0 technologies is delayed in our company because the daily business does not leave enough capacities.

... because we don’t want to replace employees with machines.

... because processes and responsibilities for implementation are not clearly defined.

... because existing employees are against it.

... because no pressure to change is perceived.

... because the necessary adjustments are perceived by employees as too new and complex.

... because not all divisions involved are pulling in the same direction.

... because of difficulties to employ Industry 4.0 qualified staff („War of Talents“).

... because established, historically grown IT systems complicate the integration.

The introduction of Industry 4.0 technologies in our company is delayed...


... because function-related and historically grown data silos make it difficult to implement cross-divisional solutions.

... because there is no continuous data exchange along the value chain.

The introduction of Industry 4.0 technologies in our company has so far been mainly for marketing reasons

The introduction of Industry 4.0 technologies in our company is delayed…

Employees & Resources

In addition to the lack of time capacity of the employees involved to successfully carry out Industry 4.0 technology projects, companies face the challenge of qualifying their own employees and retaining them in the long term. Fur-thermore, the recruitment of Industry 4.0-qualified employ-ees to strengthen their own Industry 4.0 skills is seen as dif-ficult (38%).

Change Management

As soon as the introduction of Industry 4.0 technologies in the company is discussed, aspects of the company’s willing-ness to change come up as well as aspects of profitability. Industry 4.0 initiatives fail, for example, due to the refusal of existing employees to change, which can result from the lack of pressure to change from inside and outside, or because the necessary adjustments are perceived as too new and complex. The evaluation of the survey shows a general approval of the reasons given. In addition, the lack of clearly defined processes and responsibilities (29%) and the lack of cross-departmental cooperation (43%) received just as strong an approval as an aspect for delays in the introduc-tion of Industry 4.0 technologies.

Cyber Security

The topic of cyber security is becoming increasingly impor-tant in the political, social and industrial environment. Cor-respondingly, about 30% of the respondents do not agree that cyber security would not be prioritized sufficiently.

The fear of cyber security risks as an obstacle to Industry 4.0 is also assessed rather neutrally. However, a quarter of the respondents state that they do not have sufficient equipment and expertise in cyber security.

influence the implementation and rollout of Industry 4.0 technologies.

Prioritisation

Prioritisation describes the internal support and perception of the initiative by a company. Here, the general percep-tion that the company introduces Industry 4.0 technology primarily for marketing reasons is only confirmed by about 10% of respondents. On the other hand, about half of the respondents confirm that the introduction is delayed because the daily business does not leave enough capacity to support the digital transformation.

Requirements

In order to successfully implement the future technology, technological and IT-related obstacles must be identified. The requirements for Industry 4.0 focus on historically grown IT system landscapes, function-related data silos and the lack of continuous data exchange along the val-ue chain. It is striking that two thirds of the participants confirmed that these IT-related prerequisites are obstacles to the introduction of Industry 4.0 technologies in their companies.

Profitability

In the context of economic efficiency as a possible obsta-cle to the introduction of Industry 4.0 technologies, it has been shown that the level of investment costs (36%) and the difficult-to-define profitability of investments in Indus-try 4.0 technologies (42%) complicate the decision. In con-trast, only 10% of the respondents agreed that the lack of economic success was the reason for the delaying of Industry 4.0.

6%

9% 43% 48%

48%

44%50%

46%6%

6%

41% 53%

35% 55% 10%

Profitability

... because the investment costs are too high.

... because it is difficult to define the profitability of the investments.

... because pilot projects have not achieved the expected economic success.

... because the decisive factor for the introduction of Industry 4.0 technol-ogies is not the profitability analysis but rather getting financial support.

9% 55% 36%

8% 50% 42%

20% 69% 11%

39% 55% 6%

30%

10% 61% 29%

60% 24%

53% 29%

16%

18%

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8% 54% 38%

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ExpertInterview

Hans-Christian Brockmann,Founder and managing director of eccenca GmbH and brox IT-Solutions GmbH

Short CVHans-Christian Brockmann

Hans-Christian Brockmann is founder and managing direc-tor of eccenca GmbH and brox IT-Solutions GmbH. He is also an advisor to the President of the APICS Supply Chain Council and head of the APICS Digital Readiness Task Force. With eccenca, he supports companies in effective and scal-able digitalisation. Hans-Christian Brockmann is convinced that in order to realize Data-as-a-Service, Artificial Intelli-gence, Smart Supply Chain and Data Privacy, companies must shift their focus from applications to data. Only in this way is it possible to benefit from data-centered work with-out the limitations of data silos. A central component of eccenca’s strategy is the creation of Business Digital Twins, which semantically link the data of a company’s products, processes, partners, customers and employees.

Company Profile

eccenca is a leading German company in the field of Enter-prise Knowledge Graphs. The company offers solutions for automated integration and management of heterogene-ous big data. This allows innovative industry concepts such as Smart Supply Chain, IoT automation, AI applications and Data-as-a-Service as well as compliance solutions for regulations such as GDPR or BCBS 239 to be implemented quickly and efficiently. eccenca uses the concept of the Business Digital Twins to achieve a continuous integra-tion of physical, logical and process-related information in companies. These companies benefit from the system-independent and cross-system use of their data, previ-ously managed in silos, via arbitrarily scalable corporate networks. eccenca is listed by CIOApplications as a Top 10 GDPR Solution Provider 2019 and is named by Gartner Inc. in the report “Cool Vendor in Intelligent Supply Chain Execution Technologies”. Source: www.eccenca.com

MHP: eccenca is a young company and yet already a lead-er in data management solutions. What distinguishes the company and its products in particular?

Hans-Christian Brockmann: Data Centricity is the cen-tral philosophy of eccenca. Existing IT system landscapes are characterised by relational databases, which are based on a closed-world-assumption. These databases are high-performance and strongly oriented towards individual processes, people or customer needs and are therefore highly specialised. However, it is not possible to map dif-ferent, sometimes competing views of one and the same subject matter with them. Consequently, new systems (applications) have been developed for each view, e.g. sales, development or production, and this is the starting point of our highly complex IT landscape today. Digital transformation requires us to overcome application cen-tricity, as today’s requirements demand highly networked work. The data centricity approach and the core idea of an enterprise knowledge graph, on the other hand, ena-bles us to break open these application silos. The goal is not to reproduce existing processes, but to create a gen-eral integrative understanding of enterprise data. We see with our customers that with knowledge-based network-ing, complexity can be reduced by orders of magnitude. This ensures more agile solutions while reducing costs significantly.

MHP: Which obstacles or challenges for the company-wide implementation of Industry 4.0 do you particularly encounter with your customers?

Hans-Christian Brockmann: We see the Application Centricity as a central obstacle. We have the head of the data warehouse, the business warehouse or the CRM tool, but there is insufficient communication between them. The different systems all have their own support, technology or database. The problem is that these differ-

ent data can no longer be properly superimposed. Within a project, this can perhaps be compensated for, but at the company level there is a lack of data consistency. If non-standardized and semantically ambiguous data already pose a challenge within the company, cross-company networks with customers and suppliers cannot develop in the context of Industry 4.0.

MHP: How does eccenca position itself with its portfolio in the Industry 4.0 field and how do you enable your cus-tomers to implement the digital transformation?

Hans-Christian Brockmann: We use enterprise knowl-edge graphs to define a common language level in com-panies, which enables cooperation with customers and suppliers on a common data level. Enterprise Knowledge Graphs standardize knowledge based on open, globally recognized standards rather than applications. For exam-ple, we are working with a Supply Chain Council on a Supply Chain Ontology, a vocabulary that standardizes the description of the content of data shared between business partners in such a way that the data content can be interpreted clearly and immediately at any time, across the entire planet of man and machine. Knowledge graphs create links between product and process data along the entire supply chain. However, this does not work if there is no data that can be clearly interpreted by the machine. In this case, information would have to be entered manu-ally on a permanent basis and digitalisation does not work that way. With data networking, we help companies, for example, with predictive maintenance or batch tracking when faulty machines or products need to be identified quickly.

MHP: Can you explain the technology of semantic linking in a few words?

Hans-Christian Brockmann: At the moment the mean-

ing of data is divided. On the one hand there is the data schema for the database and there is the software code for the application. Only through the combination of code and scheme the application can understand that a series of numbers like “4711” stands for a product code. If this series of numbers is passed on to any other posi-tion, only a context-free string of four digits arrives, with-out any information. The goal of Industry 4.0, however, is to ensure that the number “4711” is understood as a product code on the production line, on the loading ramp and also at the customer’s premises, and that it also passes on additional information. The new data language requires a uniform grammar, globally unique identifiers that can be called up as URLs, for example, and vocabu-laries that can be interpreted by machines. The Seman-tic Web already has this grammar, which consists of the simple elements subject, predicate, and object, always in this order. It is based on the HTTP principle and uses, for example, the vocabulary that we are developing with the Supply Chain Council. Thus, the product “4711” becomes a link to which stocks, storage locations, prices, etc. are traceably assigned. If further information such as a paint finish or a specific batch number is added, this informa-tion is added as an additional hyperlink and can then be retrieved. The Semantic Web is based on the HTTP model and enables information to be shared publicly or securely across the entire internal or external Web via proprietary partner networks. In the end, the Semantic Web is what we have always been missing. The understanding of what data means within applications has been largely lacking until now.

MHP: What problems do your customers face when pro-cessing internal data? Are data silos and a lack of data consistency an obstacle for the customers of eccenca?

Hans-Christian Brockmann: This is an obstacle for abso-lutely every customer and this can also be shown measur-

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explain the digital transformation based on the KPIs they use to measure their processes and themselves. Unfor-tunately, a flawed value system has become established, even among managers. In the Industry 4.0, IT will prob-ably account for half of the value added to the product, but today - to put it simply - the person who promises the CEO to reduce IT costs by 2% is still promoted. A change in thinking is needed here.

MHP: The Digital Twin represents a central element of Industry 4.0 with regard to the evaluation and analysis of product and process data. Where are your customers currently positioned on the way to the digital twin of the entire company (Business Digital Twin)?

Hans-Christian Brockmann: The Business Digital Twin is built from the customer perspective. Here‘s an example of a success story of a manufacturer of microwave cables. This manufacturer produced microwave cables according to different standards in different markets and built its data models according to the respective standards. As a result, according to the metadata, the cables were very dif-ferent even though all products were ultimately identical. Our approach was therefore based on the differentiating product features from the customer’s perspective, which is why we first communicated with the sales department. This customer centricity enabled us to identify relevant product features. In a second step, we then considered which processes and plants have an influence on these relevant features. If, for example, painting is the central product feature for the customer, the painting plant, the paint suppliers, the lighting systems, etc. must therefore be the focus of the measurement and reflected in the data of the Digital Twin. The model can also be mapped over several locations. In this way, processes, suppliers, etc. could be compared and all influencing factors identi-fied in order to maximize the quality of the final prod-uct. This backward-looking view along the supply chain

ably. For example, if you ask a customer what proportion of the total effort in a data-related project is spent on data search, provision and alignment, and harmonization, you will receive dishonest answers with 65% and too honest ones with 90%. However, the real share averages about 80%. The lack of experts, so-called data scientists, is often cited as a reason. However, this is understandable if 8 out of 10 employees are involved in searching and maintaining the data. If harmonised data were already available, the capacities could also be used more sensibly.

MHP: In addition to the development of in-house data management solutions, another competence of eccenca is the cross-company linking of partners along the supply chain. Which obstacles regularly arise in this context?

Hans-Christian Brockmann: There are two dimen-sions here: technology and Change Management. New projects are built up as independent data silos. The silos aim to secure and locally stabilize data instead of shar-ing it transparently and openly with internal or external partners. Therefore, existing governance models are also designed to retain data instead of sharing it. The main problem for companies is that sharing data with other stakeholders is completely against the nature of the exist-ing IT system landscape. There is a fear of losing con-trol over data and knowledge and this is also a change management issue. The focus is on the risks of opening up rather than the opportunities, which is why only very innovative and, as it turns out, particularly successful companies dare to take the first step. We are therefore very pleased that IATA, the airfreight industry association, is now joining this network with its OneRecord initiative, thus providing us with standardized access to airfreight information from all airlines.

MHP: The loss or sharing of data and related know-how is a critical issue in the industry. How do you proceed in

projects in such situations?

Hans-Christian Brockmann: We confront the compa-nies with relevant success stories, of which there are really hundreds in the meantime. Small companies in particu-lar realize that they can only survive in competition with partners, because not everyone can have every core com-petence. It takes far too long if the competence of the competitor has to be copied first. Medium-sized compa-nies quickly realize that powerful networks are indispen-sable for innovation, and so our radius of action expands. The management of our customers talks to their suppliers and these in turn approach us. However, one must always start at the highest level and convince the CEO or Head of Supply Chain Management of the concept of Data Cen-tricity. Once the key drivers in the company have under-stood that it is the fitness of the company to compete, changes can be successfully driven forward.

MHP: In your opinion, is there a sufficiently intensive exchange between IT and the business departments of your customers when implementing Industry 4.0 projects?

Hans-Christian Brockmann: We have also recognized this as our own weakness. I think IT is making an effort to talk to the business department. The business depart-ment, on the other hand, hopes that IT will provide a flex-ibility that it cannot provide because of the way it works. At the same time, IT speaks in codes, applications and data models, while the business department communi-cates in processes and customer benefits. We also have this problem with our product. We tried for a long time to sell the topic of data centricity to IT, but in the end, IT does not buy the system because it sees itself as a service center rather than a value driver or innovator. We need to talk to the specialist department about our data man-agement solutions. We also need to discuss lead times or perfect order fulfillment for the business perspective and

enables the Business Digital Twin to capture only the relevant data that has an effect on customer benefit. The added value of the model increases with each further integration step. The oppo-site of the model described above would be an Engineering Digital Twin, which measures all the data generated in the course of value creation. However, about 90% of this data usually has no influence on the customer benefit. Business Digital Twins therefore offer a unique opportunity to get a grip on the complexity that has grown out of silos, also with regard to data, and thus to create added value in an agile manner without having to convert the entire IT landscape.

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Cyber Security

Strategic Control

... because there is a fear of losing control over production processes.

... due to concerns that competitors and suppliers could gain access to important internal company data.


Strategic Control

Due to the increasing complexity of the IT infrastructure and the growing number of internal and external company interfaces, the question of the controllability of operative processes with increasing digitalization arises. The question of existing fears of losing control over production processes is rated rather neutrally by the participants. The concern that competitors and suppliers could gain access to impor-tant, internal company data also shows no clear tendency in one direction - one in four participants even has no con-cerns about this.

25%

29% 59% 12%

28% 50% 22%

53% 22%

29% 51% 20%

31% 45% 24%

... due to fear of cyber security risks.

... because cyber security is not being adequately prioritised.

... as we do not have sufficient equipment and competence in cyber security.



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04Recommended Actions

In conclusion, we will evaluate the results of the study and present recommended actions for the Cluster technology, IT integration, strategy and goals as well as drivers and obstacles.

4.1 TechnologyThe Industry 4.0 Barometer 2019 shows that the techno-logical Industry 4.0 maturity level in German industry has developed further compared to the previous year. In par-ticular, an increase was recorded in the use of sensor tech-nologies. However, automated and autonomous processes and systems are the area with the greatest development potential.

One way to increase transparency both inside and outside the factory is illustrated by the increasing number of roll-outs by German car manufacturers using RFID. In a case study carried out by MHP at a German premium OEM, RFID was used across the board in the areas of inbound, intra- and outbound logistics for production materials and load carriers in order to increase process reliability and transpar-ency of the entire logistics chain. These “enablers” provide a basis for using the information gained profitably in future for data-driven process orientation.

In the area of Digital Twins, the study shows that the use of the technology within companies is continuing to increase. If, however, the use of digital twins is considered along the entire value chain, it becomes clear that there is a major deficit there. In order to optimise the problems of network-ing along the supply chain, Prof. Dr.-Ing. Thomas Bergs of the Fraunhofer Institute recommends to join cooperations to test technologies and thus jointly develop the industry standard: “Cooperations lead to the fact that we produce new innovative ideas on certain topics and can also test them directly. And that, I believe, is the key”.

At present, the market mainly relies on central solutions for the communication of plants, devices and systems. How-ever, a trend towards decentralization can be seen. This trend suggests that the share of decentralized solutions in the market will increase significantly in the future. Decen-tralized solutions offer the advantage that network traffic is reduced and data can be processed decentrally in almost real time, taking local data into account.

In order to make better use of digital production tech-nologies, it is recommended that companies start thinking about how to equip their machines for 5G. The first step should therefore be to adapt interfaces to the control sys-tem to enable machine tools to communicate with a 5G network in the future.

The study clearly shows that data analytics is becoming increasingly important for companies and that the use of the respective technologies is growing steadily. For an effi-cient and process-related use of the data analysis meth-od, it is important to know exactly which data is required for the respective application. A distinction is made here between data that is already available and data that would first have to be determined. The former must be evaluated with a focus on results, the latter should be generated at an effective level.

4.2 IT IntegrationIt is becoming clear that companies are dealing more inten-sively with the topic of standardization. Standards and common data formats are increasingly being sought with partners along the value chain, and the integration of open standards is also being pursued more intensively.

There is a clear recommendation to continue along the current path and to continue to develop open standards

to ensure interoperability. The multifaceted and constantly changing technological landscape demands flexibility, which is made possible by open, adaptable standards.

The further development of modular IT architectures and the continuously increasing use of digital platforms shows a positive trend. However, the results continue to confirm that there is still a great need to catch up in terms of the IT capabilities needed to make extensive use of the Industry 4.0 potential. Here, as well, it is advisable to strive for flex-ibility, which is ensured by high modularity and the associ-ated rapid integration of IT systems.

Particular attention must continue to be devoted to fur-ther developments in data management and IT security. The results of this year’s study show that companies are aware of the relevance and that in many areas the neces-sary steps towards secure data management have already been taken. Here is the recommendation to further sensi-tize employees with regard to data security and to establish corresponding governance functions.

4.3 Strategy & GoalsThe results of the study clearly show that companies are increasingly focusing on cost reduction and efficient busi-ness processes, whereas the development of new business models is showing a slightly declining trend. This trend can be explained by a possible recession and the result-ing savings. Although the striving for an efficient and cost-reduced overall process already forms an initial basis for the implementation of Industry 4.0 technologies, the development of new business models is still in its early stages. However, the full potential of Industry 4.0 can only be achieved if new business models are also brought into focus and unique selling points and competitive advantag-es are created.

When it comes to initializing and promoting the sustain-able industry, the management assumes particular respon-sibility. As the driver and motivator of a dynamic culture, management can and should assume a key position. Espe-cially study respondents from smaller companies evaluate the activities of management positively and essential in the context of Industry 4.0. In addition, the survey results show that suitable further training measures for the respective employees form a meaningful and important basis for the implementation of pioneering technologies. Here, too, leadership is recommended by senior management or the executive board.

As in the previous year, cooperation between departments has also been assessed as capable of development. In par-ticular, the exchange between IT and other departments is not yet fully practiced here. The benefits of close coopera-tion are demonstrated in particular by the fact that current leaders in technology topics also have a high query value in the area of interdepartmental cooperation. In general, it is recommended to promote an exchange of knowledge within the company, to strengthen the mutual understand-ing of the respective processes and to create an interdisci-plinary team structure. In the past, IT was often only a tool for production and logistics, but it is increasingly becoming part of the actual product and thus a central component of business success.

In addition to the interdisciplinary transfer of knowledge within the company, an exchange beyond the company’s boundaries should also be aimed for. Especially with new, fast-moving and future-oriented topics such as Industry 4.0, a holistic understanding and up-to-date knowledge form the basis for successful implementation. The survey results show that such an exchange already exists, espe-cially in larger companies. Such an exchange can be fur-ther strengthened by working groups and participation in Industry 4.0 forums, for example. Furthermore, coop-

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eration in the form of co-opetition is recommended. This intensive and close type of cooperation with actual com-petitors makes it possible to jointly develop knowledge bases and learn from each other. Another possibility is to participate in communities and platform concepts in order to expand your own Industry 4.0 competencies.

4.4 Drivers & ObstaclesThe evaluation of the survey clearly showed that a sig-nificant proportion of German automotive and industrial companies still fall short of the technological possibilities when it comes to implementing Industry 4.0 solutions. In addition to the complex requirements in terms of technol-ogy and IT infrastructure, the organisational framework conditions also play a decisive role in the implementation of Industry 4.0.

The low capacities due to day-to-day business and a lack of cooperation towards a common goal are the biggest challenges in the implementation of Industry 4.0 projects.

Management must create appropriate framework condi-tions so that experts from all involved areas can exchange and complement each other both internally in the project team and with external partners. For innovative Industry 4.0 projects, it is advisable to establish a separate project organization with defined roles and responsibilities. The respective teams must jointly develop clear goals for the Industry 4.0 projects and be enabled by the management to pursue these goals consistently.

A new way of thinking about data centricity must also be initiated within the project teams. The opportunities that lie in the openness and transparency of data must be the focus of every pilot project. Thinking and working in silos will not result in any economic or technological added val-

ue in the long run. The lack of data consistency and avail-ability results in an immense effort in data-driven Industry 4.0 projects, so that the output cannot be economically related to the input. In addition to the organisational framework conditions, there are technological data management solutions available on the market that enable significant increases in efficiency as defined in Industry 4.0. An Enterprise Knowledge Graph offers promising possibilities to minimize the implications of historically grown IT landscapes and data silos. This is based on a graph database, in which not only the data itself, but also its contexts and relations are rep-resented by a multidimensional linking of the data. With the knowledge graph, hundreds of systems can be intelligently networked with each other, even in larger companies. Among other things, this reduces the effort for data acquisition and analysis, accelerates data integration and ulti-mately leads to better business decisions. Tech-nological innovations of this kind also dissolve the way of thinking in rigid silos and promote a general integrative data understanding.

Pilot projects can be implemented quickly and effectively only through a combination of organisational and technological solutions, that can prove that revenues can be gener-ated or costs saved. As a result, the ben-efits are quantifiable and a profitability of Industry 4.0 projects is predictable despite high investment costs.

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The Industry 4.0 Barometer clearly shows that awareness of Industry 4.0 and technological maturity have increased across industries. The use of Industry 4.0 technologies is increasingly shifting from the experimental to the test phase. The performance of IT infrastructure and IT services has also been further developed, but not at the same pace as technological maturity due to legacy issues and com-plexity. As a result, there is a lack of basic IT prerequisites for successful networking of plants, systems, products and business processes within the meaning of Industry 4.0.

The companies themselves are increasingly placing their strategic focus on reducing costs and increasing their process efficiency, while the development of new busi-ness models or services is of secondary importance. This evolutionary rather than revolutionary orientation can be explained by the declining economic growth and the resulting growing uncertainty. Global geopolitical tensions can also be a decisive factor for the described prioritisation of strategic business objectives. In many places, Industry 4.0 solutions fail to make the transition from the pilot phase to a factory or company-wide rollout. The main reasons for this are high investment

costs and the often difficult to define profitability of the individual initiatives. In addition, IT also represents a weak point here. Rigid legacy systems and historically grown data silos with the resulting data disruptions complicate the implementation of Industry 4.0 solutions and the integration of partners along the supply chain.

Finally, companies also face personnel and organi-ational challenges when implementing Industry 4.0. The prioritisation of day-to-day business operations leads to a lack of capacity in the implementation of innovative projects. In addition, there is a lack of sufficiently qualified personnel for the success-ful implementation of Industry 4.0 projects both within the organizations and on the labor market.

05Conclusion

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AuthorEsther Nagel

LMU Research Assistant and

Doctoral Candidate, Chair forInternet Business and Internet Services

AuthorTim Dröscher

MHP Senior Management Consultant


06About Us

AuthorRené Schneider

MHPManagement Consultant


AuthorThomas Klüe

MHPSenior Management Consultant


AuthorJan Schäfer

MHPManager


SponsorTom Huber

MHPAssociated Partner

Head of Operations Performance & Strategy

Project ManagerAndreas Henkel

MHP Senior Manager


AuthorChristopher Dechent



SponsorProf. Dr. Johann Kranz

LMUHead of the Chair for Internet Business and Internet Services

AuthorMatthias Grawe



AuthorManuel Schulze-Ganzlin

MHPSenior Management Consultant


AuthorThomas Stošić

MHP Management Consultant


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About MHP

Welcome to the future. MHP is a globally active and lead-ing management and IT consulting company. We develop groundbreaking mobility and manufacturing solutions for international corporations, established medium-sized companies and disruptive start-ups. As a premium busi-ness and technology partner, we are already shaping tomorrow’s digital future today.

Our consulting approach is unique: We combine holistic IT and technology expertise with profound management know-how. This makes MHP the ideal partner for a successful digital turn. As digitalisation experts, we deliver innovative strategies based on sound analyses, in order to transform change pro-cesses into sustainable success.

With more than 3,000 employees at 16 locations worldwide, we drive digital progress - together with over 300 customers. And all this with excel-lence at all levels.

ENABLING YOUTO SHAPE A BETTERTOMORROW

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Atlanta (USA) Birmingham (United Kingdom) Cluj-Napoca (Romania) Timișoara (Romania) Shanghai (China)Tel Aviv (Israel)

Ludwigsburg (Headquarters)BerlinEssen Frankfurt a. M.Ingolstadt MunichNurembergWolfsburg

InternationalGermany

MHP : DRIVEN BY EXCELLENCE

www.mhp.com

16 MHPOffices in Germany, United Kingdom, USA, China and Romania.

https://www.mhp.com/en/company/studies/

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