Periodic Reporting for period 1 - MODAPTO (MODULAR MANUFACTURING AND DISTRIBUTED CONTROL VIA INTEROPERABLE DIGITAL TWINS)
Berichtszeitraum: 2023-01-01 bis 2024-06-30
The MODAPTO project envisions flexible industrial systems composed of modules enhanced by distributed intelligence via interoperable Digital Twins (DTs) based on industrial standards. Moreover, it materializes enables collective intelligence within modular production schemes for effective module and production line design, reconfiguration and decision support. Motivated by the six principles of Reconfigurable Manufacturing Systems, MODAPTO aims at materializing reconfigurability through the joint use of all principles and not by considering it as an isolated vision of each one. To that end, MODAPTO focuses on two technological pillars:
1. Distributed Intelligence & Control via Interoperable Digital Twins
2. Modular Production Framework & Toolkit
Within MODAPTO, each production module is augmented by a DT offering additional distributed intelligence functionalities. MODAPTO standardizes the module’s interface via AAS to enable coordination with other modules and systems. MODAPTO also proposes a framework for production design and reconfiguration supported by collective intelligence tools.
MODAPTO will be implemented in 3 industrial UCs involving 4 manufacturers at 3 different levels to showcase its versatility and applicability. UC1 targets the development of production modules (robots) with novel sustainability capabilities, while UC2 production reconfiguration and optimization even for single lots. UC3 targets the timely set up of press shop lines and coordination with robots and AGVs to handle supply chain disruptions in collaboration with the producer of semi-finished product kits.
MODAPTO aims at substantial KPI improvements related to efficiency, cost, quality, energy and sustainability. Moreover, MODAPTO will develop business models facilitating its transferability to other sectors and the adoption of its industrial strategies, especially by SMEs, while supporting knowledge transfer via workforce and trainers’ training activities.
1. Distributed Intelligence & Control via Interoperable Digital Twins
2. Modular Production Framework & Toolkit
Within MODAPTO, each production module is augmented by a DT offering additional distributed intelligence functionalities. MODAPTO standardizes the module’s interface via AAS to enable coordination with other modules and systems. MODAPTO also proposes a framework for production design and reconfiguration supported by collective intelligence tools.
MODAPTO will be implemented in 3 industrial UCs involving 4 manufacturers at 3 different levels to showcase its versatility and applicability. UC1 targets the development of production modules (robots) with novel sustainability capabilities, while UC2 production reconfiguration and optimization even for single lots. UC3 targets the timely set up of press shop lines and coordination with robots and AGVs to handle supply chain disruptions in collaboration with the producer of semi-finished product kits.
MODAPTO aims at substantial KPI improvements related to efficiency, cost, quality, energy and sustainability. Moreover, MODAPTO will develop business models facilitating its transferability to other sectors and the adoption of its industrial strategies, especially by SMEs, while supporting knowledge transfer via workforce and trainers’ training activities.
The MODAPTO project started on January 1st 2023, with the first Reporting Period spanning from January 2023 until June 2024, aligns with months M1 – M18 respectively.
This reporting period has served to crystallize the project's strategic approach, showcasing its initial value through the preliminary outcomes of User Requirements and KPIs, achieving an initial version of system architecture and already working on the final version. Also, actions related to tools' development following the requirements of Pilot users has initiated in the technical Work Packages.
In accordance with contractual obligations outlined for the first reporting period, the project successfully executed the following key activities and achieved the milestones of the 18 Months:
- A comprehensive set of User Requirements and KPIs, derived from the needs of manufacturing sites, constituting a set of more than 25 User Stories and Use Cases.
- Development of the first version of the architecture.
- Advanced work towards the final version of the architecture – to be completed in M22.
- Design algorithms and initial versions of Smart Services to be deployed as Digital Twins.
- Smart services in the categories of monitoring, simulation, co-simulation, optimization, co-optimization, self-awareness, predictive maintenance, analytics, sustainability analytics, virtual commissioning
- Development of the functional components to serve as the platform for deploying the MODAPTO DTs
- Development and initial integration of Evaluation and Decision Support tools
- Design, development and initial integration of the Production Knowledge Base
- Advances in interoperability and standardization actions related to tools
- Initial advances in IPR considerations and development of business models to adopt in the project
This reporting period has served to crystallize the project's strategic approach, showcasing its initial value through the preliminary outcomes of User Requirements and KPIs, achieving an initial version of system architecture and already working on the final version. Also, actions related to tools' development following the requirements of Pilot users has initiated in the technical Work Packages.
In accordance with contractual obligations outlined for the first reporting period, the project successfully executed the following key activities and achieved the milestones of the 18 Months:
- A comprehensive set of User Requirements and KPIs, derived from the needs of manufacturing sites, constituting a set of more than 25 User Stories and Use Cases.
- Development of the first version of the architecture.
- Advanced work towards the final version of the architecture – to be completed in M22.
- Design algorithms and initial versions of Smart Services to be deployed as Digital Twins.
- Smart services in the categories of monitoring, simulation, co-simulation, optimization, co-optimization, self-awareness, predictive maintenance, analytics, sustainability analytics, virtual commissioning
- Development of the functional components to serve as the platform for deploying the MODAPTO DTs
- Development and initial integration of Evaluation and Decision Support tools
- Design, development and initial integration of the Production Knowledge Base
- Advances in interoperability and standardization actions related to tools
- Initial advances in IPR considerations and development of business models to adopt in the project
- Developed, and implemented a concept for the mapping between the Digital Twin Definition Language (DTDL) specification and the AAS specification and evaluated it using a commonly used example
- A novel solution method on developing Digital Models of the assets (production modules) which may be enhanced with dynamic/executable simulation parts supporting the decisions for sustainable modular production was developed and tested
- In the context of one of MODAPTO Pilots two formal models are proposed, namely a MILP that incorporates transportation times but not buffers and a Constraint Program (CP) that handles both, given a sequence of all jobs per machine.
- With respect to predictive maintenance, the project achieved the definition of an evolutionary based algorithm for dynamic grouping of maintenance action; The algorithm addressed specific constraints of a Pilot Use Case and proposed a new maintenance planning with grouped action
- With respect to its third Pilot, MODAPTO has prescribed all optimization-related aspects of the collaboration of the Kitting Robot System (KRS) with the smart Kit Holders (KHs) and have identified the underlying combinatorial optimization problem as the bipartite TSP.
- A novel solution method on developing Digital Models of the assets (production modules) which may be enhanced with dynamic/executable simulation parts supporting the decisions for sustainable modular production was developed and tested
- In the context of one of MODAPTO Pilots two formal models are proposed, namely a MILP that incorporates transportation times but not buffers and a Constraint Program (CP) that handles both, given a sequence of all jobs per machine.
- With respect to predictive maintenance, the project achieved the definition of an evolutionary based algorithm for dynamic grouping of maintenance action; The algorithm addressed specific constraints of a Pilot Use Case and proposed a new maintenance planning with grouped action
- With respect to its third Pilot, MODAPTO has prescribed all optimization-related aspects of the collaboration of the Kitting Robot System (KRS) with the smart Kit Holders (KHs) and have identified the underlying combinatorial optimization problem as the bipartite TSP.