crema newsletter i - h2020 crema project · crema, together with c2net, has successfully organised...
TRANSCRIPT
CREMA, together with C2NET, has successfully organised and
executed the 1st CREMA/C2NET Industrial Workshop in Spain.
To keep pace with the needs of the manufacturing industry of the future, companies
need to flexibly react to changing demands and be able to manage production
capacities in a rapid and efficient way requiring agile collaboration among supply
chain partners. Innovative solutions to allow industrial companies to incorporate faster
and more efficient decision making looking for a better use of manufacturing assets
are demanded.
A total of 80 people coming from different manufacturing industries from the
Basque Region and surroundings joined the first CREMA/C2NET Industrial
Workshop in Spain. The Basque Country is one of the main industrialised regions of
Spain and therefore the speeches given by CREMA, and C2NET, were addressed
directly to the potential users of CREMA fulfilling one of the main objectives of the
project. A stunning and futuristic place, the Orona Foundation Auditorium, was
selected for this purpose. Orona is one of the biggest Spanish manufacturers of lifts,
escalators and other products such as moving walks. Both projects used their R&D
facilities to have a joint session for exchange of information, impressions and
research topics.
Topics and discussions of the Industrial workshop, with recognised speakers
coming from the Basque Government and the EU Industry, were very well received
and provoked the audience to think about the outcomes of the two projects and
potential benefits to invest in latest ICT solutions coming from R&D projects.
Please take a minute to visit www.crema-project.eu for more information about us
and our goals, contact us at [email protected] or watch our video in YouTube!
Cloud-based Rapid Elastic MAnufacturing
Edition 2—2016
Welcome
Since starting this innovative H2020
project in January 2015, we aimed at
CREMA standing out as the project with
the biggest impact and the best exploita-
tion in all the projects we have wit-
nessed before. Participating in other
Factories of the Future FP7-projects
before, we knew the potential pitfalls,
challenges and hidden levers to press to
make CREMA more successful.
The first year of CREMA was exclu-
sively about defining use-cases, talking
to industry partners, visiting their facto-
ries, trying to understand the actual real-
world problems. Also, streamlining what
had been written in the proposal into a
more effective plan to have a tangible
impact on our industry culminated in
shifting the dissemination efforts towards
this business plan in 2016, in parallel to
starting the implementation phase.
With this newsletter, the end of the
project Y2 is approaching. We’ve set
high expectations, and we’re pushing
hard to keep them. It was, and still is, a
tour de force. The project partners are
fully dedicated and try to achieve more
than was expected from the start, they
work pragmatically to achieve the mile-
stones, they combine forces of multiple
tasks for putting a stronger focus on
exploitation, and they’ve had much more
physical meetings to factories than in
any project so far.
We’re looking forward to the 2nd EC
review, to be able to continue the fruitful
work and provide a competitive product
for improving information and collabora-
tion in factories. In a nutshell, to realise
tomorrows vision today.
Tim Dellas, CREMA Coordinator
CREMA Newsletter
CREMA/C2NET Collaboration Team
Implementation of the Predictive Maintenance Use Case demonstrator is performed with a Fagor mechanical press machine that contains a Goizper Clutch Brake component
The demonstrator is located in Fagor Arrasate facilities in the
Basque country and it is based on a real mechanical press ma-
chine. This Use Case is focused on the clutch brake failure
modes and downtimes of the press machine caused by this
critical component.
In order to capture
clutch brake’s data to
enable its diagnosis,
several sensors have
been installed on the
machine during the
last year in CREMA
project. Most of the
sensors have been
installed within the
clutch brake, but
some others have
been installed in
specific points which
provide interesting
data for performing
the clutch brake’s
diagnosis.
Temperature sen-
sors, pressure trans-
ducers, encoder,
inductive sensors,
opto coupler and a
flow meter give the
actual health data of
the clutch brake. This
data is sent to a data
logger which has
been installed and
programmed during
the year in order to
receive information
from these sensors
and from the ma-
chine PLC. This data
logger generates a
data file per machine stroke ready to transfer the file to CREMA
platform for further data processing.
During the next year, the validation of the diagnostics and
process data must be performed. In fact, real machine failure
modes will be simulated in the press machine, and the result of
the diagnosis will be evaluated. Some of the failure modes will
be simulated by software while some others will be forced in the
press machine demonstrator in Fagor Arrasate. Apart from this,
alarm detection and prediction will be elaborated while the press
is monitored from Fagor and Goizper offices. Fagor Arrasate
and Goizper are willing to get proper results during the valida-
tion in 2017.
Implementation of the Automotive Use Case demonstrator is well underway with a live robot cell and real-time asset location tracking throughout the test zone reflecting the scenario to be applied to the Tenneco Belgium shop floor
Progress on implementing the Tenneco Automotive Use Case
has been quick off the blocks with the Industrial hardware imple-
mentation, at the Waterton Technology Centre, having been
completed within the first two months. This sees a fully enclosed
ABB Robotics cell installed
and commissioned, along
with zones for testing of
products and shipping pro-
ducts. In addition a Siemens
S7 PLC controller has been
used along with Fortis
4DIAC units to collect dis-
crete and analogue sensor
data from the robot produc-
tion and testing processes.
In the months following,
an Industreweb 4.0 Micro
Server has been installed
running Industreweb Global
and Collect that will interfa-
ce with all shop floor data
sources through a range of
protocols. Currently, the
service interfaces provided
by Industreweb will be con-
sumed by the CREMA pro-
cess runtime in order to test
the orchestration of the
production process. In addi-
tion, focus is being placed
on the optimisation features
of CREMA, and how selec-
tion of the most appropriate
production assets to meet
customer demand and qua-
lity targets. The Industreweb
4.0 Display will also be used
to pull appropriate data and
alerts from the CREMA
Cloud Storage, Big Data
Analytics and Monitoring
components to keep Operators aware of the status of production
and any errors or issues. In October the Smart Factory platform
from project partner Ubisense was installed and commissioned
in the Automotive pilot laboratory. This now tracks products and
tooling assets to an accuracy of 10cm and allows both error
proofing, and asset finding functionality to be carried out in real-
time.
The next 6 months will see the final integration with the CRE-
MA platform and the start of system testing for the final valida-
tion - both Tenneco Belgium and Technical Partner Control 2K
[TANet] have high hopes for the exploitable outcomes.
1 Industreweb: http://www.industreweb.co.uk
Hernani
Saarbrücken
Automotive use case powered by
Machinery Maintenance use case powered by
CREMA in Action: the Industry side
Vienna
Brussels
Manufacturing Ontology CDM-Core in OWL2 To enable semantic interoperation and optimisation of service-based processes, CREMA
developed the largest publicly available manufacturing domain ontology CDM-Core in the
standard formal ontology language OWL2. CDM-Core covers the CREMA use case do-
mains of metal press maintenance and automotive exhaust production, and leverages
many relevant standard vocabularies and ontologies. The practical applicability and quali-
ty of CDM-Core according to common criteria of verification and validation were success-
fully evaluated and approved by the user partners.
Optimisation of Service-Based Processes For the optimisation of service-based manufacturing processes at design time, CREMA
developed an innovative solution called ODERU that integrates pattern-based semantic
process service composition planning with QoS-based constraint optimisation problem
solving. This will be applied to both CREMA use cases in support of an optimal organisa-
tion of machinery maintenance and OEE maximisation for exhaust production processes.
Scientific Research in CREMA
Elastic manufacturing process landscapes have been introduced, together with a re-
search agenda on methodologies, instrumentation and toolsets for Cloud manufacturing.
From a technical point of view, research on elastic stream processing and the Internet of
Things (IoT) has been performed, along with the VISP (Vienna Platform for Stream Pro-
cessing) ecosystem for stream processing, which can be used to process distributed data
streams in a cost-efficient way. Further work conducted covered the usage of (private
and public) cloud resources to be able to realise the large-scale Cloud manufacturing
landscapes supported by CREMA. Apart from computational resources, also Cloud-
based storage solutions have been developed in CREMA, which allow avoiding the ven-
dor lock-in when storing data in the public Cloud.
Want to know more? Visit the CREMA Wiki website.
The Academic side
Technology of the Year
Business Activity Monitoring solutions aiming business process monitoring
BAM systems are useful monitoring tools but it is important to know what it is really worth to monitor. The combination between simple business rules and complex business rules could be a perfect approach for almost any enterprise.
Business process monitoring is one of the best ways to increase flexibility and respond more rapidly to changing markets. The
actual market forces enterprises to track these changes in real-time so that they can react to the real needs. Various
monitoring tools known as Business intelligence can be used to facilitate these purposes. However, regular dashboard like
applications that tend to provide real-time charts are not useful enough to improve all business aspects, as they do not actually
report the current state of business processes. For that aim, more specific monitoring tools are needed and this is where
business activity monitoring comes.
Business activity monitoring, also known as BAM is a tool with the aim of monitoring business activities, such as operations,
processes and transactions to take better business decisions. A current BAM solution provides KPIs based dashboard that
helps evaluating the current status of the processes. The main goal of BAM solutions is to monitor real-time business metrics
and detect events, filter them and trigger business process management solutions. The main difference between BAM and BI
solutions is that BAM solutions are developed for reporting rather than analysing information while Business intelligence is
used in future predictions.
As the main objective of the BAM systems is to report the actual status of the business, various criteria need to be set in order
to evaluate them. In many cases the criteria selected to evaluate the current situation are the well-known business rules. A
business rule defines or constraints some aspects of business and resolves to either true or false. These kinds of rules
evaluate the precise moment where a condition is reached and in many cases the use of these kind of rules are more than
enough to evaluate the process’ status.
However, when various given conditions need to be taken into account, the simple business rules are not enough. In many
situations, organisations need to control the previous values of a given business rule instead of evaluating just a single KPI
value. In the same way, a time slot could be considered for those rules as an alarm is just triggered when a precise condition
has been met during a batch time. When we talk about this kind of rules, we are talking about complex rules.
Technically speaking the difference between the simple business rules and complex business rules is that the simple business
rules are recommended for stateless processing, where there is not pre-processing, while complex business rules are used
when there is a correlation between the events over a time slot.
Want to know more? Visit the CREMA Wiki website and follow this link.
Partners
Factsheet Program: H2020 Budget: €5.3M Start: January 2015 End: December 2017
Cloud-based Rapid Elastic MAnufacturing Copyright © CREMA Project Consortium. All Rights Reserved
Grant Agreement No.: 637066
The next year the CREMA team will be focused on the following activities:
What will be done next year?
Concept, Requirements and Specification
Business Innovation Model
Market Watch and State-of-the-Art review
Architecture, Functional Specs, Security &
Privacy, Integration
Security and privacy concerns will be made available
Software integration
Manufacturing, Virtualisation & Interoperability
Harmonisation: Transformation services will be available in the
Marketplace for their usage in the Process Designer
Cloud Storage: Implementation of privacy awareness and multi-instance-
service
CPS Sensors: Integration with Marketplace; creation of more CPS services
Services Abstraction: Refinement of abstraction templating system
Cloud Manufacturing Process and Optimisation
Process Designer: Design of complex Manufacturing processes will be
possible
Process Engine: Several independent running Process Engines will
enhance the scalability of the process execution functionality
(Re-)Leasing: A sophisticated resource optimisation will be provided
Optimisation: Integrated functional and QoS-driven optimisation of service-
based business process models at runtime
Cloud Manufacturing Collaboration,
Knowledge and Stakeholder Interaction
Marketplace: CPS-Scheduling and Booking will be available accompanied
by the connection to payment processors
Monitoring: The monitoring and alerting component will be integrated with
the rest components of CREMA for predictive maintenance Big Data: Predictive analysis functionality will be added
Collaboration: Smart Glasses implementation and integration
Dashboard: Ticketing system incl. FAQ style system for CPS,
implementing Security and Privacy system
Use Case I: Machinery Maintenance
CREMA solution validated within the Machinery Maintenance use case
Feedback to developers
Use Case II: Automotive
CREMA solution validated within the Automotive use case
Feedback to developers
Impact
CREMA Business Plan
Plan and organise second CREMA Workshop
On-going collaboration with other projects, especially C2NET
CREMA Crossword
Across Down
1. CREMA Monitoring and Alerting
1. CREMA Data Model, Model Library and Pro-files
6. CREMA Cloud Process and Messaging Runtime Environment
4. CREMA Cloud Collaborative Process
2. CREMA Service Virtualisation and
7. CREMA Dashboard and Visualisation
9. CREMA Marketplace and Monetisation
3. CREMA Cyber-Physical Systems, Sensor Abstraction and Virtualisation
8. CREMA Design and Runtime Optimisation
10. CREMA Manufacturing Big Data,
5. CREMA On-Demand Service Leasing and
11. CREMA Agile Personal Collaboration Environment