1. INTRODUCTION

1.1. What is Industry 4.0?Smart industry or “INDUSTRY 4.0” refers to the technological evolution from embedded systems to cyber-physical systems. Put simply, Industry 4.0 represents the coming fourth industrial revolution on the way to an Internet of Things, Data and Services. Decentralized intelligence helps create intelligent object networking and independent process management, with the interaction of the real and virtual worlds representing a crucial new aspect of the manufacturing and production process. Industry 4.0 represents a paradigm shift from “centralized” to “decentralized” production - made possible by technological advances which constitute a reversal of conventional production process logic. Simply put, this means that industrial production machinery no longer simply “processes” the product, but that the product communicates with the machinery to tell it exactly what to do.

Figure 1. The four stages of the Industrial Revolution

Industrialization began with the introduction of mechanical manufacturing equipment at the end of the 18th century, when machines like the mechanical loom revolutionized the way goods were made. This first industrial revolution was followed by a second one that began around the turn of the 20th century and involved electrically-powered mass production of goods based on the division of labor. This was in turn superseded by the third industrial revolution that started

during the early 1970s and has continued right up to the present day. This third revolution employed electronics and information and communication technology (ICT) to achieve increased automation of manufacturing processes, as machines took over not only a substantial proportion of the “manual labor” but also some of the “brainwork”. The widespread adaptation by manufacturing industry and traditional production operation of information and communication technology (ICT) is increasingly blurring the boundaries between the real word and the virtual world in what are known as cyber-physical system (CPS). Figure 1 shows the four staged of industrial revolution

1.2. Cyber-Physical SystemCyber-physical systems (CPS) are enabling technologies which bring the virtual and physical worlds together to create a truly networked world in which intelligent objects communicate and interact with each other. Cyber-physical systems represent the next evolutionary step from existing embedded systems. Together with the internet and the data and services available online, embedded systems join to form cyber-physical systems. Cyber-physical systems provide the basis for the creation of an Internet of Things, which combines with the Internet of Services to make Industry 4.0 possible. They are “enabling technologies” which make multiple innovative applications and processes a reality as the boundaries between the real and virtual worlds disappear.

As such, they promise to revolutionize our interactions with the physical world in much the same way that the internet has transformed personal communication and interaction. The interplay between high performance software based embedded systems and dedicated user interfaces which are integrated into digital networks creates a completely new world of system functionality. Modern mobile telephones are perhaps the most obvious example of this, offering as they do a complete bundle of applications and services which completely outstrip the device’s original telephony function. Cyber-physical systems also represent a paradigm break from existing business and market models, as revolutionary new applications, service providers and value chains become possible.

Industry sectors including the automotive industry, the energy economy and, not least, production technology for example, will in turn be transformed by these new value chain models. Global megatrends of globalization, urbanization, demographic change and energy transformation are the transformative forces driving the technological impulse to identify solutions for a world in flux. In the future, cyber-physical systems will make contributions to human security, efficiency, comfort and health in ways not previously imaginable. In doing so, they will play a central part in addressing the fundamental challenges posed by demographic change, scarcity of natural resources, sustainable mobility, and energy change.

1.3. Using the Internet of Things and ServicesThe Internet of Things and Services makes it possible to create networks incorporating the entire manufacturing process that convert factories into a smart environment. Cyber-Physical Production Systems comprise smart machines, warehousing systems and production facilities that have been developed digitally and feature end-to-end ICT-based integration, from inbound logistics to production, marketing, outbound logistics and service. This not only allows

production to be configured more flexibly but also taps into the opportunities offered by much more differentiated management and control processes.

In addition to optimizing existing IT-based processes, Industry 4.0 will therefore also unlock the potential of even more differentiated tracking of both detailed processes and overall effects at a global scale which it was previously impossible to record. It will also involve closer cooperation between business partners (e.g. suppliers and customers) and between employees, providing new opportunities for mutual benefit. Figure 2 shows ICT as innovation motor for all fields of demand-relevance of the internet of the future

Figure 2. ICT as innovation motor for all fields of demand-relevance of the internet of the future. (Source: Germany Trade & Invest 2013 (based on “IKT als Innovationsmotor für alle Bedarfsfelder – die Relevanz des »Internets der Zukunft« in „BERICHT DER PROMOTORENGRUPPE KOMMUNIKATION – IM FOKUS: DAS ZUKUNFTSPROJEKT INDUSTRIE 4.0 HANDLUNGSEMPFEHLUNGEN ZUR UMSETZUNG”, Forschungsunion 2012))

In essence, Industry 4.0 will involve the technical integration of CPS into manufacturing and logistics and the use of the Internet of Things and Services in industrial processes. This will have implications for value creation, business models, downstream services and work organization.

1.4. The Smart FactoryThe deployment of cyber-physical systems in production systems gives birth to the “smart factory.” Smart factory products, resources and processes are characterized by cyber-physical systems; providing significant real-time quality, time, resource, and cost advantages in comparison with classic production systems. The smart factory is designed according to sustainable and service-oriented business practices. These insist upon adaptability, flexibility, self-adaptability and learning characteristics, fault tolerance, and risk management.

High levels of automation come as standard in the smart factory: this being made possible by a flexible network of cyber-physical system-based production systems which, to a large extent, automatically oversee production processes. Flexible production systems which are able to

respond in almost real-time conditions allow in-house production processes to be radically optimized. Production advantages are not limited solely to one-off production conditions, but can also be optimized according to a global network of adaptive and self-organizing production units belonging to more than one operator.

Figure 3. INDUSTRIE 4.0 smart factory pipeline (cloud-based secure networks)

This represents a production revolution in terms of both innovation and cost and time savings and the creation of a “bottom-up” production value creation model whose networking capacity creates new and more market opportunities. Smart factory production brings with it numerous advantages over conventional manufacture and production.

These include: CPS-optimized production processes: smart factory“units” are able to determine and

identify their field(s) of activity, configuration options and production conditions as well as communicate independently and wirelessly with other units;

Optimized individual customer product manufacturing via intelligent compilation of ideal production system which factors account product properties, costs, logistics, security, reliability, time, and sustainability considerations;

Resource efficient production; Tailored adjustments to the human workforce so that the machine adapts to the human

work cycle.

1.5. Industry 4.0 EnvironmentIn a “smart, networked world”, the Internet of Things and Services will make its presence felt in all of the key areas. This transformation is leading to the emergence of smart grids in the field of energy supply, sustainable mobility strategies (smart mobility, smart logistics) and smart health in the realm of healthcare. In the manufacturing environment, vertical networking, end-to-end engineering and horizontal integration across the entire value network of increasingly smart products and systems is set to usher in the fourth stage of industrialization.

Industry 4.0 is focused on creating smart products, procedures and processes. Smart factories constitute a key feature of Industry 4.0. Smart factories are capable of managing complexity, are less prone to disruption and are able to manufacture goods more efficiently.In the smart factory, human beings, machines and resources communicate with each other as naturally as in a social network. Smart products know the details of how they were manufactured and how they are intended to be used. They actively support the manufacturing process, answering questions such as “when was I made?”, “which parameters should be used to process me?”, “where should I be delivered to?” etc. Its interfaces with smart mobility, smart logistics and smart grids will make the smart factory a key component of tomorrow’s smart infrastructures. All these new networks and interfaces offered industry 4.0 within and internet of things and services mean that manufacturing is set to undergo enormous changes in future. (See Figure 4)

Figure 4. Industry 4.0 environment: Smart factories as part of the Internet of things and services.

INDUSTRIE 4.0 will give rise to novel CPS platforms geared towards supporting collaborative industrial business processes and the associated business networks for all aspects of smart factories and smart product life cycles.

The services and applications provided by these platforms will connect people, objects and systems to each other (see Figure 5) and will possess the following features:

• Flexibility provided by rapid and simple orchestration of services and applications, including CPS based software

• Simple allocation and deployment of business processes along the lines of the App Stores model

• Comprehensive, secure and reliable backup of the entire business process• Safety, security and reliability for everything from sensors to user interfaces• Support for mobile end devices• Support for collaborative manufacturing, service, analysis and forecasting processes in

business networks.

Figure 5. The Internet of Things, Services and People – Networking people, objects and systems

This will result in the transformation of conventional value chains and the emergence of new business models. INDUSTRIE 4.0 should therefore not be approached in isolation but should be seen as one of a number of key areas where action is needed. Consequently, INDUSTRIE 4.0 should be implemented in an interdisciplinary manner and in close cooperation with the other key areas.

1.6. What will the future look like under Industry 4.0?INDUSTRIE 4.0 will deliver greater flexibility and robustness together with the highest quality standards in engineering, planning, manufacturing, and operational and logistics processes. It will lead to the emergence of dynamic, real-time optimized, and self-organizing value chains that can be optimized based on a variety of criteria such as cost, availability and resource consumption. This will require an appropriate regulatory framework as well as standardized interfaces and harmonized business processes.

The following aspects illustrate the vision for Industry 4.0:

It will be characterized by a new level of sociotechnical interaction between all the actors and resources involved in manufacturing. This will revolve around networks of manufacturing resources (manufacturing machinery, robots, conveyor and warehousing systems and production facilities) that are autonomous, capable of controlling themselves in response to different situations, self-configuring, knowledge-based, sensor equipped and spatially dispersed and that also incorporate the relevant planning and management systems. As a key component of this vision, smart factories will be embedded into inter-company value networks and will be characterized by end-to-end engineering that encompasses both the manufacturing process and the manufactured product, achieving seamless convergence of the digital and physical worlds. Smart factories will make the increasing complexity of manufacturing processes manageable for the people who work there and will ensure that production can be simultaneously attractive, sustainable in an urban environment and profitable.

The smart products in Industry 4.0 are uniquely identifiable and may be located at all times. Even while they are being made, they will know the details of their own manufacturing process. This means that, in certain sectors, smart products will be able to control the individual stages of their production semi-autonomously. Moreover, it will be possible to ensure that finished goods know the parameters within which they can function optimally and are able to recognize signs of wear and tear throughout their life cycle. This information can be pooled in order to optimize the smart factory in terms of logistics, deployment and maintenance and for integration with business management applications.

In the future under Industry 4.0, it will be possible to incorporate individual customer- and product specific features into the design, configuration, ordering, planning, production, operation and recycling phases. It will even be possible to incorporate last-minute requests for changes immediately before or even during manufacturing and potentially also during operation. This will make it possible to manufacture one-off items and very small quantities of goods profitably.

Implementation of the Industry 4.0 will enable employees to control, regulate and configure smart manufacturing resource networks and manufacturing steps based on situation- and context-sensitive targets. Employees will be freed up from having to perform routine tasks, enabling them to focus on creative, value-added activities. They will thus retain a key role, particularly in terms of quality assurance. At the same time, flexible working conditions will enable greater compatibility between their work and their personal needs.

Implementation of the Industry 4.0 will require further expansion of the relevant network infrastructure and specification of network service quality through service level agreements. This will make it possible to meet the need for high bandwidths for data-intensive applications and for service providers to guarantee run times for time-critical applications.

2. MAIN CHARACTERISTIC

The following four main characteristic of industry 4.0 demonstrate the huge capacity that industry and traditional manufacturing have for change: vertical networking of smart production system, horizontal integration via a new generation of global value chain networks, through-engineering across the entire value chain and the impact of exponential technology

2.1. Vertical networking of smart production system

Figure 6. Vertical networked manufacturing systems

This vertical networking uses CPS to enable plants to react rapidly to changes in demand or stock levels and to faults. Smart factories organize themselves and enable production that is customer-specific and individualizes. This requires data to be extensively integrated. Smart sensor technology is also needed to help with monitoring and autonomous organization.

CPS enable not only autonomous organization of production management but also maintenance management. Resource and products are networked, and materials and parts can be located anywhere and at any time. All processing stages in the production process are logged, with discrepancies registered automatically. Amendments to orders, fluctuations in quality or machinery breakdowns can be dealt with more rapidly. Such process also enable wear and tear materials to be monitored more effectively or pre-empted. All in all, waste reduced.

Significant emphasis is attached to resource efficiency and in particular, the efficient use of materials, energy and human resource. The demands on workers engaged in operational tasks such as production, warehousing, logistics and maintenance are also changing, meaning that new skills in efficient working with CPS are required. Table 1 shows the examples of how companies adapt to industry 4.0 in term of vertical networking.

Table 1. Vertical networking solutions - examplesIT Integration The vertical networking of industry 4.0 requires new IT

solutions. In many cases-existing IT infrastructure are very fragmented and result in poor networking.New, combine solutions need to be developed from a range of components from suppliers of sensors, modules, control system, communication networks, business application and customer-facing applications.

Analytics and data management Industry 4.0 will generate enormous quantities of data. Gathering, analyzing and processing such big data will generate new insight, support decision and create a competitive advantages.

Cloud-based applications The simple networking of cloud-based solutions offers excellent opportunities to host and make efficient use of big data generated by industry 4.0. There are particular advantages for decent rally networked smart-production system, where preciously unimaginable computing power will enable cloud-based application to deliver universal, anytime access to all key data. This makes it simpler to gather, monitor, distribute and analyze data not only between factories but also across the entire global value chain network.

Operational efficiency The effective analysis, assessment and application of data collected from machine and sensors enabled rapid decision-making to improve operational safety, work processes, servicing and maintenance. Transparency not only makes development and production processes more efficient but also offers substantial operational cost reduction for customer.

2.2. Horizontal integration via a new generation of global value chain networks

Figure 7. Horizontal integration through value networks

These new value-creation networks are real-time optimized networks that enable integrated transparency, offer a high level of flexibility to respond more rapidly to problems and faults, and facilitates better global optimizing.

Similar to networked production system, these (local and global) networks provide networking via CPS, from inbound logistic through warehousing, production, marketing and sales to outbound logistic and downstream service. The history of any part or product is logged and can be access at any time, ensuring constant traceability (a concept known as product memory)

This creates transparency and flexibility across entire chains – from purchasing through production sales for example, or from the supplier through the customer. Customer-specific adaptations can be made not only in the production but also in the development, ordering, planning, composition and distribution of products, enabling factors such as quality, time, risk,

price and environmental sustainability to be handled dynamically, in real time and at all stages of the value chain.

This kind of horizontal integration of both customers and business partners can generated completely new business models and new models for corporation, representing a challenge for all those involved. Legal issues and questions of liability and protection of intellectual property are becoming increasingly important. Table 2 shows the examples of how companies adapt to industry 4.0 in term of horizontal integration.

Table 2. Horizontal integration solutions - examplesBusiness model optimization Industry 4.0 means getting to grips with radical new

approaches to business rather than merely making incremental improvement to establish business models. To achieve this companies need to develop new skills, both at individual employee level and within the organization as a whole. A solely top-down approach will create resistance in the organizations, while introducing pockets of innovation within traditional business will provoke a reaction from less engaged employee.

Smart supply chains There will be a particular focus on new models that are tailored more closely to individual customer needs and enable new cooperative models with business partners. The digital transformation will create a single database, making supply chains matter, more transparent and more efficient at every stages, from customer needs to delivery.Research and development, procurement and purchasing, production and sales functions are becoming more closely aligned as digitization advances.

Smart logistics In the wake of digitization, logistic processes will have to become smarter right across new generations of global value chain networkers. This applies to inbound logistic, intra-logistic and outbound logistic.Major challenges are posed by the integration of autonomous technologies, flexible logistic system, new service, new warehousing and distribution models and the interlinking of internal production, pre-assembly and external service provide.

IT security management The high levels of data sharing involved in industry 4.0 will greatly increase the demand made on data security. It needs a tailored risk management system and a security strategy geared to cyber security and aimed at improving operational security and protection from attack right across the value chain Existing factories and structures will have to be equipped and will also have to develop secure solutions for the new networks.

New taxation models In future 3D printing technology will allow the printing of products across countries and continents, with no physical crossing of national borders anymore. This will make new demands in terms of value-added tax and customs duty regulations.

New IP managements Management of intellectual property (IP) will also have to change as a result of the digital transformation to industry 4.0. New business models and new models for cooperation that arise as a result of industry 4.0 will

requires new, individual solution to digital IP issue.A broad application of 3D printing will make special demands in this respect. Issues of intellectual property focus not only on printers, printer technology and materials but also on system and plans.

2.3. Through-engineering across the entire value chain

Figure 8. End-to-end engineering across the entire value chain

The third main characteristic of industry 4.0 is cross disciplinary through engineering across the entire value chain and across the full life cycle of both products and customer.

This engineering occurs seamlessly during the design, development, and manufacture of new products and services. New products need new and/or modified production systems. The development and manufacture of new products and production systems is integrated and coordinated with product life cycles, enabling new synergies to be created between product development and production systems.

Characteristic of this through-engineering is that data and information are also available at all stages of a product’s life cycle, enabling new, more flexible processes to be defined from data via modelling to prototypes and the product stage. Table 3 shows the examples of how companies adapt to industry 4.0 in through-engineering.

Table 3. Through-engineering solutions - examplesInnovation Innovation has traditionally related predominantly to

product offering, but its major potential lies in the area of company structure, processes, networks and profit models, together with customer-facing function, such as new service and distribution channels, new uses for a strong brand and distinctive customer engagement.

Efficient management of innovation The digital transformation to industrial 4.0 will make it possible to improve further the efficiency of innovation management in all these areas.In project portfolio management, industry 4.0 solutions make it easier not only to track the return on investment (ROI) in innovation but also to identify risks by using global comparative project data for monitoring and remedial purpose. In the area of product development, information technology can be used to speed up research and development.

Efficient life cycle management The digital transformation to industry 4.0 will make it possible to provide relevant data for life cycle management at any time and from anywhere. These data will comprise not only information and reports but also the results of big data processing to generate relevant early indicators through the use of artificial intelligence (AI).AI will use global cross-checking and assess the plausibility of generating relevant bases for decision-making supported by data. It will enable companies to understand and meet their customers’ needs better, as well as to customize product cycles.

2.4. The impact of exponential technologyThe fourth main characteristic of industry 4.0 is the impact of exponential technologies as an accelerant or catalyst that allows individualized solutions, flexibility and cost savings in industrial processes.

Figure 9. Exponential technologies

Industry 4.0 already requires automations solutions to be highly cognitive and highly autonomous. Artificial intelligence (AI), advanced robotics and sensor technology have the potential increase autonomy further still and to speed up individualization and flexibilization.

AI cannot only help to plan driverless vehicle routes in factories and warehouses more flexibly, save time and cost in supply chain management (SCM), increase reliability in production or analyses big data, but can also help to find new construction and design solutions or enhance the cooperation between humans and machine to the point of services.

Functional Nanomaterials and Nano sensors can also be used in production control function to make quality and management more efficient or allow the production of next generations robots that work ‘hand-in-hand’ and safely with humans.

Flying maintenance robots in production halls and using drones to make inventories of warehouse stock level and deliver spare parts, at any time of day or night and in any terrain and weather, are further applications that will become simply routines in the autonomous and smart factories of the future.

3D printing (additive manufacturing) is one of the example of an exponential technology that is accelerating industry 4.0. It allows new production solutions (e.g. functionality, higher complexity without additional cost) or new supply chain solutions (e.g. inventory reduction, faster delivery times), or combination of both that lead to disruptive new business models (e.g. disintermediation of supply chain members, customer integration). While 3D printing already exist for all materials (metal, plastic, ceramic, living cell etc.), not all materials fulfill industrial requirements with regards to porosity and other characteristic.

Figure 10. Break-even analysis of conventional manufacturing and 3D printing

3D printing, sensor technology, artificial intelligence, robotics, drones, and nanotechnology are just a few examples of exponentially growing technologies that are radically changing industrial processes, accelerating them and making them more flexible. Table 4 shows the examples of how companies adapt to industry 4.0 in exponential technology.

Table 4. Exponential technology solutions - examplesCorporate venturing Corporate venturing offers companies good

opportunities for investing in new trends at an early stage and for benefitting from disruptive innovation and exponential technologies.Investing in start-ups enables companies to be involved in developing innovations and to secure their long-term competitiveness. Such investment allow early and convenient insight into new technologies.

The learning organization Companies need to become learning organizations if they are to make full use of the potential of exponential technologies in achieving the digital transformation to industry 4.0The use and integration of exponential technologies need to be gradual but steady. Learning is the key to sustainable organizational development. Change that is

too rapid can be counterproductive.New ideas, processes and business segments are most successful when they start off as a niche where learning goes on, and the gradually migrate to the center of the organization to establish themselves as a new leading segments.

3. PRIORITY AREAS FOR ACTION

Through Industry 4.0 it will also be enabling a paradigm shift in human-technology interaction. It will be machines that adapt to the needs of human beings and not vice versa. Smart industrial assistance systems with multimodal user interfaces will bring digital learning technologies directly into the workplace.1

3.1. Standardization and open standards for a reference architecture

If Industry 4.0 is to enable inter-company networking and integration through value networks, the appropriate standards will need to be developed. Standardization efforts will need to focus on stipulating the cooperation mechanisms and the information that is to be exchanged. The complete technical description and implementation of these provisions is referred to as the reference architecture. The reference architecture is thus a general model that applies to the products and services of all the partner companies. It provides a framework for the structuring, development, integration and operation of the technological systems relevant to Industry 4.0. It is provided in the shape of software applications and software services (see e.g. Figure 11).

Figure 11. Reference architecture for connecting the Internet of Things with the Internet of Services

The example of a manufacturing system serves to outline some of the different perspectives that would need to be integrated into a reference architecture:

The perspective of the manufacturing process in terms of processing and transport functions

1 Prof. Dr rer. nat. Dr h. c. mult. Wolfgang Wahlster. CEO of the German Research Center for ArtificialIntelligence (DFKI GmbH). Member of the Communication Promoters Group of the Industry-Science Research Alliance

The perspective of specific networked devices in a manufacturing system, such as (smart) automation devices, field devices, fieldbuses, programmable logic controllers, operating devices, mobile devices, servers, workstations, Web access devices, etc.

The perspective of the software applications in the manufacturing environment, such as data acquisition through sensors, sequential control, continuous control, interlocking, operational data, machine data, process data, archiving, trend analysis, planning and optimization functions, etc.

The perspective of the software applications used by one or more businesses, e.g. for business planning and management, inter-company logistics or supporting value networks, including the relevant interfaces and integration with the manufacturing environment

The engineering perspective in a manufacturing system (Product Lifecycle Management/PLM). For example, this could involve using data derived from the manufacturing process to plan the necessary resources (in terms of both machinery and human resources). It would subsequently be possible to successively optimize machines in terms of their mechanical, electrical and automation technology properties, right up to the point where the manufacturing system is set up and brought online, whilst also taking operation and maintenance into account.

3.2. Managing complex systemsProducts and their associated manufacturing systems are becoming more and more complex. This is a result of increasing functionality, increasing product customization, increasingly dynamic delivery requirements, the increasing integration of different technical disciplines and organizations and the rapidly changing forms of cooperation between different companies.Modelling can act as an enabler for managing this growing complexity. Models are a representation of a real or hypothetical scenario that only include those aspects that are relevant to the issue under consideration. The use of models constitutes an important strategy in the digital world and is of central importance in the context of Industry 4.0.

A fundamental distinction can be drawn between two types of model:

Planning models provide transparency with regard to the creative value-added generated by engineers and thus make it possible for complex systems to be built. An example of a planning model would be a schematic used by an engineer to explain how he or she has implemented appropriate functions to meet the requirements placed on a system. As such, the model contains the engineer’s knowledge.

Explanatory models describe existing systems in order to acquire knowledge about the system through the model. This typically involves using different analysis processes such as simulation. For example, a simulation can be used to calculate a factory’s energy consumption. Explanatory models are often used to validate engineers’ design choices.

The digital world thus exerts a significant influence over real-world design via planning models, whilst the real world also influences the models used in the digital world via explanatory models.

The fact that models usually contain formal descriptions means that they can be processed by computers, allowing the computer to take over routine engineering tasks such as performing calculations or other repetitive jobs. One of the benefits of models is therefore that they allow

manual activities to be automated and enable actions to be performed in the digital world that previously had to be performed in the real world.

Models offer huge potential – and not only in the context of Industry 4.0. For example, they allow the risks involved in a project to be reduced through early detection of errors or early verification of the demands placed on the system and the ability of proposed solutions to meet these demands. Or they can provide a transparent information flow that enables more efficient engineering by improving interdisciplinary cooperation and facilitating more consistent engineering data. Explanatory models that describe interactions and behaviors in the real world are not only useful for validation purposes during the development and design stages. In the future, they will be primarily deployed during the production stage in order to check that production is running smoothly, detect wear and tear without needing to halt production or predict component failure and other disruptions.

3.3. Delivering a comprehensive broadband infrastructure for industry

If CPS are rolled out on a widespread basis, it will in general terms be necessary to build an infrastructure that enables significantly higher-volume and higher-quality data exchange than provided by current communication networks. A core requirement for Industry 4.0 is therefore the enhancement of existing communication networks to provide guaranteed latency times, reliability, quality of service and universally available bandwidth.

High operational reliability and data link availability are crucial for mechanical engineering and automation engineering applications. Guaranteed latency times and stable connections are key, since they have a direct impact on application performance. Network operators should do more to meet the wishes of businesses.

Binding and reliable SLAs (Service Level Agreements) Availability and performance of traffic capacity Support for data link debugging/tracing, especially provision of the relevant technical

aids Provision of widely available/guaranteed traffic capacity (fixed/guaranteed broadband) SMS delivery status notification across all mobile network operators Standardized Application Programming Interfaces (APIs) for provisioning covering all

providers (SIM card activation/deactivation) Tariff management Cost control of mobile service contracts Quality of service (fixed bandwidth) Affordable global roaming Widely available embedded SIM cards Satellite-based solutions for areas with no reception (N.B. in sparsely populated areas).

3.4. Safety and security as critical factors for the success of Industry 4.0

Safety and security are two key aspects with regard to manufacturing facilities and the products they make (see info panel). On the one hand, they should not pose a danger either to people or to the environment (safety), whilst on the other both production facilities and products – and in particular the data and know-how they contain – need to be protected against misuse and

unauthorized access (security). In contrast to security, safety issues have been an important consideration in the design of manufacturing facilities and the products they make for many years. Safety is regulated by a whole host of regulations and standards governing the construction and operation of such systems.

Since information technology first came into contact with mechanics and electronics towards the end of the 1960s (Industry 3.0) there has been a dramatic increase in safety and security requirements in the manufacturing environment. In addition to the fact that it became far more complex to provide hard evidence of operational safety, it gradually became apparent that security was also a problem. Many of the safety and security issues that arose in Industry 3.0 (the “beta version” of Industry 4.0) have yet to be fully resolved. Security measures in particular are often slow to be implemented and frequently only provide partial fixes. With the advent of Industry 4.0, a number of additional safety and security requirements are set to arise. Industry 4.0’s CPS-based manufacturing systems involve highly networked system structures incorporating large numbers of human beings, IT systems, automation components and machines. High-volume and often time-critical data and information exchange occurs between the technological system components, many of which act autonomously.At the same time, a far greater number of actors is involved across the value. However, safety and security are always properties of the entire system. Thus, in addition to operational safety issues, the extensive networks and at least hypothetical potential for third-party access mean that a whole new range of security issues arise in the context of Industry 4.0. It will only be possible to implement Industry 4.0 and get people to accept it if the following points are put into practice:

1. Security by Design as a key design principle. In the past, security against external attacks was usually provided by physical measures such as access restrictions or other centralized security measures. In CPS-based manufacturing systems, it is not enough simply to add security features on to the system at some later point in time. All aspects relating to safety, and in particular security, need to be designed into the system from the outset.

2. IT security strategies, architectures and standards need to be developed and implemented in order to confer a high degree of confidentiality, integrity and availability on the interactions between these highly networked, open and heterogeneous components. They also need to provide an appropriate, reliable and affordable solution for protecting the digital process know-how, intellectual property rights and data in general of each individual manufacturer and operator, both vis-à-vis the outside world and with regard to components belonging to different operators and/or manufacturer’s vis-à-vis each.

In Industry 4.0, it is therefore always necessary to adopt a global approach to safety and security. It is essential to consider the impact of security measures (cryptographic processes or authentication procedures) on safety (time-critical functions, resource availability) and vice versa (“does a particular critical safety function of a subsystem increase the risk of cyber-attacks?”). Firstly, existing factories will have to be upgraded with the safety and security measures needed to meet the new requirements. The typically long service lives of machinery and short innovation cycles, together with heterogeneous and in some cases very old infrastructures that are difficult to network mean that this will not be an easy task. Secondly, solutions for new factories and machinery will have to be developed. The transition from the third to the fourth industrial revolution should be as seamless as possible and should be

implemented in a way that can be clearly understood by all the relevant stakeholders. One key aspect for both pillars of the strategy is for all the actors throughout the entire value chain to reach a consensus on safety and security issues and the relevant architecture before implementation begins.

3.5. Work organization and work design in the digital industrial age

What impact will Industry 4.0 have in the workplace? What responsibilities will have to be met by businesses and society in a decentralized high-tech economy where CPS are commonplace? How should the world of work respond to these changes? In a future characterized by increasing automation and real-time oriented control systems, how can we ensure that people’s jobs are good, safe and fair? The answers to these questions will determine whether or not it is possible to mobilize existing reserves of innovation and productivity and secure a competitive advantage through the widespread deployment of automatically controlled, knowledge-based, sensor-equipped manufacturing systems.

Innovation efforts cannot be allowed to focus exclusively on overcoming the technological challenges. The remit of innovation needs to be consistently widened to include smart organization of work and employees’ skills, since employees will play a key part in implementing and assimilating technological innovations. It is likely that their role will change significantly as a result of the increase in open, virtual work platforms and extensive human-machine and human-system interactions. Work content, work processes and the working environment will be dramatically transformed in a way that will have repercussions for flexibility, working time regulation, healthcare, demographic change and people’s private lives. As a result, in order to achieve successful integration of tomorrow’s technologies they will need to be smartly embedded into an innovative social organization (within the workplace).

3.6. Training and continuing professional development for Industry 4.0

The implementation of Industry 4.0 should result in a labor-oriented socio-technical factory and labor system. This will in turn pose new challenges for vocational and academic training and continuing professional development (CPD). These challenges include the need to expand provision for the developers of manufacturing engineering components and their users. It is likely that Industry 4.0 will significantly transform job and skills profiles as a result of two trends.

Firstly, traditional manufacturing processes characterized by a very clear division of labor will now be embedded in a new organizational and operational structure where they will be supplemented by decision-taking, coordination, control and support service functions.

Secondly, it will be necessary to organize and coordinate the interactions between virtual and real machines, plant control systems and production management systems.

Effectively, what this means is that the convergence of ICT, manufacturing and automation technology and software will result in many tasks now being performed as part of a much broader technological, organizational and social context.

3.7. Regulatory frameworkJust like any other fundamental technological innovation, the new manufacturing processes associated with Industry 4.0 will find themselves confronted with the existing regulatory

framework, a situation that raises two interconnected challenges. On the one hand, uncertainty regarding the legality of a new technology or the associated liability and data protection issues could inhibit its acceptance and slow down the innovation process. Conversely, the de facto power of new technologies and business models can be so great that it becomes almost impossible to enforce existing legislation. Consequently, short technological innovation cycles and the disruptive nature of new technologies can result in the danger of a chronic “enforcement deficit” whereby current regulation fails to keep pace with technological change.

While Industry 4.0 does not, on the whole, tread completely uncharted regulatory territory, it does significantly increase the complexity of the relevant regulatory issues. Two things are required to reconcile regulation and technology: the formulation of criteria to ensure that the new technologies comply with the law and development of the regulatory framework in a way that facilitates innovation. In the context of Industry 4.0, it will often be possible to achieve this through common law contracts. Both factors require the regulatory analysis of new technologies to begin as early as possible during the R&D phase rather than being left until they are already in use. Some challenges are e.g. protecting corporate data, liability, handling personal data, and trade restrictions.

3.8. Resource efficiencyThe nature of manufacturing industry means that it is by far the largest consumer of raw materials in industrialized nations. Together with the private sector, it is also the principal consumer of primary energy and electricity. In addition to the high costs involved, this situation entails risks to the environment and security of supply which need to be minimized by regulation. Consequently, industry is undertaking major efforts to reduce its consumption of energy and resources or find alternative sources. However, these efforts will need to be sustained over many years if they are to have any chance of succeeding. Ultimately, this will involve changes in manufacturing processes and the design of machinery and plant, since these are the only areas where material and energy consumption can really be influenced.

The starting point is the amount of resources that are used by manufacturing companies, both within the company itself and throughout the rest of the value network. It is possible to draw a distinction between three categories of resources and how they are used:

1. Raw materials, additives, operating supplies and all the different kinds of energy carriers, including conversion from one type of energy into another

2. Human resources, i.e. human labor3. Financial resources, i.e. the necessary investment and operating costs

In terms of how these resources are used, it is possible to focus on maximizing the output achieved with a given quantity of resources, or on using the lowest possible quantity of resources to achieve a given output. In the first scenario, the emphasis is on calculating resource productivity, whilst in the second scenario the focus is on calculating resource efficiency. A range of metrics are now available to perform these measurements (Life Cycle Assessments, carbon foot printing, etc.).

4. WHERE IS TAIWAN TECH IN THE INDUSTRY 4.0 PROCESS?

4.1. Competitiveness

4.2. Opportunities and RisksOpportunities for integration and boosting quality and efficiency Risk to data security

4.3. The question of resourcesIT infrastructureTalent

4.4. Potential for individual segmentsCurrent transformation segmentsFuture potential

4.5. Impetus from exponential technologies

REFERENCES

1. Prof. Dr. Henning Kagermann, Prof. Dr. Wolfgang Wahlster, Dr. Johannes Helbig. “Securing the future of German manufacturing industry Recommendations for implementing the strategic initiative INDUSTRIE 4.0 Final report of the Industry 4.0 Working Group”. Acatech – National Academy of Science and Engineering. Germany. April 2013.

2. Dr. Ralf C. Schaepfer, Markus Koch, Dr. Phillip Merkofer. “Industry 4.0: Challenges and solutions for the digital transformation and use of exponential technologies”. Deloitte AG. Zurich. 2014.

3. William MacDougall, “INDUSTRIE 4.0 Smart Manufacturing for the Future”. Germany Trade & Invest, July 2014.