Periodic Reporting for period 2 - COMPOSITION (Ecosystem for Collaborative Manufacturing Processes – Intra- and Interfactory Integration and Automation)
Período documentado: 2018-03-01 hasta 2019-08-31
Requirements of modern production processes stress the need of greater agility and flexibility leading to faster production cycles, increased productivity, less waste and more sustainable production. At the factory level, decisions need to be supported by detailed knowledge about the production process and its interplay with external entities. Unfortunately, historical and live data that generates this knowledge is becoming more and more distributed and few solutions are available that can easily tackle the implied challenges. Moreover, factories are becoming less isolated in the productive web of nations and several suppliers and third party service providers need to be contacted and coordinated to implement decisions taken at the factory level.
In such a worldwide and dynamic environment, the ability of automatizing the preliminary coordination and negotiation activities involved in setting up supply chains for specific needs, in an open marketplace-like fashion, could greatly improve the ability of factories to react on external challenges and driving forces quickly.
COMPOSITION has two main goals: The first goal is to integrate data along the value chain inside a factory into one integrated information management system (IIMS) combining physical world, simulation, planning and forecasting data to enhance re-configurability, scalability and optimisation of resources and processes inside the factory. The second goal is to create a (semi-)automatic ecosystem, which extends the local IIMS concept to a holistic and collaborative system incorporating and inter-linking both the Supply and the Value Chains.
As results, the COMPOSITION IIMS is deployed at three pilot sites for doing predictive maintenance of an oven and a polishing machine, component tracking, visual analytics and intra-factory waste collection route optimization. This incorporated sensor development and deployment for data collection and completion as well as their integration together with existing shopfloor data into an IIMS, development of data management and data analytics procedures, brokerage, factory modelling, simulation and forecasting mechanisms and finally the design and development of different GUIs.
The COMPOSITION intra-factory results are deployed in an agent-based marketplace that allows to semi-automatically negotiate about goods and services of a requestor with the benefit that every entity can step into the bidding process. As such, new business connections can be established. As a second use case of the COMPOSITION ecosystem, ELDIA is able to live monitor container fill-levels off-site for optimized pick-up management. These systems incorporate sensor development, deployment and integration, brokerage, agent and marketplace development including matchmaking as well as GUI design and development.
In such a worldwide and dynamic environment, the ability of automatizing the preliminary coordination and negotiation activities involved in setting up supply chains for specific needs, in an open marketplace-like fashion, could greatly improve the ability of factories to react on external challenges and driving forces quickly.
COMPOSITION has two main goals: The first goal is to integrate data along the value chain inside a factory into one integrated information management system (IIMS) combining physical world, simulation, planning and forecasting data to enhance re-configurability, scalability and optimisation of resources and processes inside the factory. The second goal is to create a (semi-)automatic ecosystem, which extends the local IIMS concept to a holistic and collaborative system incorporating and inter-linking both the Supply and the Value Chains.
As results, the COMPOSITION IIMS is deployed at three pilot sites for doing predictive maintenance of an oven and a polishing machine, component tracking, visual analytics and intra-factory waste collection route optimization. This incorporated sensor development and deployment for data collection and completion as well as their integration together with existing shopfloor data into an IIMS, development of data management and data analytics procedures, brokerage, factory modelling, simulation and forecasting mechanisms and finally the design and development of different GUIs.
The COMPOSITION intra-factory results are deployed in an agent-based marketplace that allows to semi-automatically negotiate about goods and services of a requestor with the benefit that every entity can step into the bidding process. As such, new business connections can be established. As a second use case of the COMPOSITION ecosystem, ELDIA is able to live monitor container fill-levels off-site for optimized pick-up management. These systems incorporate sensor development, deployment and integration, brokerage, agent and marketplace development including matchmaking as well as GUI design and development.
WP1
• Recommendations and outcomes of the 2nd and intermediate review addressed
• Project objectives achieved
• 41 deliverables and 9 milestones with no or slight delay submitted
• Transition and continuation in eFactory project established
WP2
• 124 Requirements have been implemented, 61 of which have been validated by end users, two requirements are under implementation
• 2 new Innovations have been identified
• The COMPOSITION Architecture has been adapted to facilitate new or revised requirements and address identified stakeholder concerns
WP3
• Project objectives related to process modelling, digital factory modelling, simulation and forecasting and decision support were achieved in WP3
• An online BPMN-based monitoring framework has been implemented in T3.1 and is publicly available on project’s GitHub
• The final version of the implemented Digital Factory Model (T3.2) enables the modelling of various factory aspects and the creation of factory instances. The DFM schema is public available
• Various algorithms and methodologies for production and supply chain procedures’ optimization and forecasting has been implemented in T3.3
• A Decision Support System for the production lines of the pilots and a mobile feedback application to communicate with has been developed in T3.4
• 6 scientific publications related to WP3 activities have been presented in international conferences
WP4
• Security Framework technical design and specifications completed
• COMPOSITION blockchain set up
• Security Framework and WSN physical security system deployed
WP5
• Completed the implementation of the tools that were promised to deliver, namely Learning Agents Framework, the Deep Learning Toolkit and the Intra-Factory Interoperability Layer
• Integrated the COMPOSITION Security Framework
• Finalized the design of the HMIs
• Addressed the remarks from 1st and 2nd reviews, which affected all the components
• Deployed and tested all the components first in a protected lab environment and after deployed and tested on premise
• 3 papers to relevant conferences submitted
WP6
WP7
• Existing sensing infrastructure (equipment and environment) examined, gaps identified and data from existing sensors utilised where appropriate
• All deployments integrated, provisioned and commissioned. All are operational within the DSS
• Various collaborations with DIGICOR, NIMBLE, vf-OS and EFFRA as well as IDS conducted
WP8
• Implementation of the COMPOSITION results in the 3 pilots has been evaluated during the Pilot Visits
• Methodology to map the project’s KPIs to the demonstrations implemented
• Methods derived for establishing baselines for each KPI in each pilot
WP9
• Dissemination and communication of COMPOSITION results to stakeholders and target groups via event participation to events, synergies with other FoF projects and EFFRA, social media accounts, project website, EFFRA Innovation Portal. Participation to relevant conferences and other public activities.
• Organisation of 3 webinars, generation of 17 publications
• Renewed market analysis of industrial market segments particularly focusing on the integration of business models with the market segments
• Refined and developed new use cases to map the business models onto the pilots
• Performed a SWOT analysis with USPs for each market segment
• Provided the market analysis and recommendations for partners’ individual exploitation strategies
• Recommendations and outcomes of the 2nd and intermediate review addressed
• Project objectives achieved
• 41 deliverables and 9 milestones with no or slight delay submitted
• Transition and continuation in eFactory project established
WP2
• 124 Requirements have been implemented, 61 of which have been validated by end users, two requirements are under implementation
• 2 new Innovations have been identified
• The COMPOSITION Architecture has been adapted to facilitate new or revised requirements and address identified stakeholder concerns
WP3
• Project objectives related to process modelling, digital factory modelling, simulation and forecasting and decision support were achieved in WP3
• An online BPMN-based monitoring framework has been implemented in T3.1 and is publicly available on project’s GitHub
• The final version of the implemented Digital Factory Model (T3.2) enables the modelling of various factory aspects and the creation of factory instances. The DFM schema is public available
• Various algorithms and methodologies for production and supply chain procedures’ optimization and forecasting has been implemented in T3.3
• A Decision Support System for the production lines of the pilots and a mobile feedback application to communicate with has been developed in T3.4
• 6 scientific publications related to WP3 activities have been presented in international conferences
WP4
• Security Framework technical design and specifications completed
• COMPOSITION blockchain set up
• Security Framework and WSN physical security system deployed
WP5
• Completed the implementation of the tools that were promised to deliver, namely Learning Agents Framework, the Deep Learning Toolkit and the Intra-Factory Interoperability Layer
• Integrated the COMPOSITION Security Framework
• Finalized the design of the HMIs
• Addressed the remarks from 1st and 2nd reviews, which affected all the components
• Deployed and tested all the components first in a protected lab environment and after deployed and tested on premise
• 3 papers to relevant conferences submitted
WP6
WP7
• Existing sensing infrastructure (equipment and environment) examined, gaps identified and data from existing sensors utilised where appropriate
• All deployments integrated, provisioned and commissioned. All are operational within the DSS
• Various collaborations with DIGICOR, NIMBLE, vf-OS and EFFRA as well as IDS conducted
WP8
• Implementation of the COMPOSITION results in the 3 pilots has been evaluated during the Pilot Visits
• Methodology to map the project’s KPIs to the demonstrations implemented
• Methods derived for establishing baselines for each KPI in each pilot
WP9
• Dissemination and communication of COMPOSITION results to stakeholders and target groups via event participation to events, synergies with other FoF projects and EFFRA, social media accounts, project website, EFFRA Innovation Portal. Participation to relevant conferences and other public activities.
• Organisation of 3 webinars, generation of 17 publications
• Renewed market analysis of industrial market segments particularly focusing on the integration of business models with the market segments
• Refined and developed new use cases to map the business models onto the pilots
• Performed a SWOT analysis with USPs for each market segment
• Provided the market analysis and recommendations for partners’ individual exploitation strategies