Periodic Reporting for period 1 - Plooto (Product Passport through Twinning of Circular Value Chains)
Reporting period: 2023-01-01 to 2024-06-30
Plooto expands, integrates and applies novel technologies in circular value chains with the aim to maximize SDR use. The approach initially foreseen and actually taken during the first half of the project is to draw specific requirements from three disjoint value chains (CFRP, WEEE, Citrus) and from a variety of scientific domains (industry commons and knowledge graphs, AI and analytics, data spaces, optimization, governance) to offer replicable systems facilitating digital product passports through intertwined digital replicas of processes and products (digital twins). The challenges motivating this work are related to the fact that traceability across the value chain is pivotal for shifting towards circular and resilient production processes. Such challenges include the connection of traceability to sustainability and business objectives and KPIs, the deployment of key prerequisites on data and technology, the support for a collaboration ecosystem and a rapid test-and-learn approach with measurable impact. Aside all these, Plooto envisions significant research advances in all scientific topics listed above plus transformative business models for circularity.
A thorough review of literature on circular and resilient information systems have been carried out to identify relevant KPIs.
A design science approach was adopted for prescriptive knowledge on traceability data and digital service to define the Plooto system architecture.
A novel data modelling method has been developed, named Information Modelling Framework (IMF), based on the ISO 81346, with the scope to make the data modelling easier and interoperable without the need of specialized personnel.
In parallel, a unified data model for harmonized data collection has been established, and extraction/loading processes have been developed, deployed, and tested. Initial research has been performed towards IDSA-compliant communication between the Citrus processing industrial data lake and external components, providing an alternative route to the unified Plooto platform.
A holistic approach that addresses the three main pillars of governance in supply chain collaboration (sustainability, business, and data/models) has been defined. It is aligned with the sustainability framework that forms the basis for the balanced scorecard.
The analytics for the Citrus processing pilot have been designed and developed in a modular, containerized way to enable potentially autonomous infrastructure. This has been integrated in the Plooto platform, and it will connect with the Process Modelling and Simulation and the Lifecycle Analysis modules. Similarly, the analytics for WEEE have been designed and developed to isolate the different functionalities and allow a future independent use of each component.
A holistic Mixed Integer Linear Programming (MILP) model to optimise the material flows and cost within a value network recovering and reusing magnets from WEEE has been introduced. It integrates the proposed policies and directives of the European Commission, aiming to devise a strategy that efficiently blends secondary and virgin magnetic materials to minimize total energy costs.
A design science approach was adopted for prescriptive knowledge on traceability data and digital service to define the Plooto system architecture.
A novel data modelling method has been developed, named Information Modelling Framework (IMF), based on the ISO 81346, with the scope to make the data modelling easier and interoperable without the need of specialized personnel.
In parallel, a unified data model for harmonized data collection has been established, and extraction/loading processes have been developed, deployed, and tested. Initial research has been performed towards IDSA-compliant communication between the Citrus processing industrial data lake and external components, providing an alternative route to the unified Plooto platform.
A holistic approach that addresses the three main pillars of governance in supply chain collaboration (sustainability, business, and data/models) has been defined. It is aligned with the sustainability framework that forms the basis for the balanced scorecard.
The analytics for the Citrus processing pilot have been designed and developed in a modular, containerized way to enable potentially autonomous infrastructure. This has been integrated in the Plooto platform, and it will connect with the Process Modelling and Simulation and the Lifecycle Analysis modules. Similarly, the analytics for WEEE have been designed and developed to isolate the different functionalities and allow a future independent use of each component.
A holistic Mixed Integer Linear Programming (MILP) model to optimise the material flows and cost within a value network recovering and reusing magnets from WEEE has been introduced. It integrates the proposed policies and directives of the European Commission, aiming to devise a strategy that efficiently blends secondary and virgin magnetic materials to minimize total energy costs.
DT standards, industry commons and knowledge graphs for circular traceability. The foundation for the circular traceability is available at https://www.mdpi.com/2071-1050/16/1/396(opens in new window). Also, a method for producing the Plooto ontology automatically have been developed (see https://ceur-ws.org/Vol-3647/SemIIM2023_paper_13.pdf(opens in new window)).
Business models, strategy and guidelines for digital circularity. Plooto can generate new revenue streams, through 1) new channels e.g. a marketplace, 2) new assets such as data and smart products, 3) pay per use/recurring subscription services and outcome-based models. Novel technologies (e.g. DPP) enable Plooto assets to provide economic benefits, i.e. 1) cost reduction through more efficient use of materials thanks to traceability and re-use, 2) revenue generation through new business models, new service offerings and recycled material 3) operational efficiency through supply chain optimization.
AI and Analytics for circularity. Different forecasting and anomaly detection algorithms have been tested including ARIMA/Residual Analysis and Isolation Forest. Continuous evaluation of combined techniques, aiming to better incorporate expert knowledge of real-life manufacturing and provide a supply chain view, with a focus on environmental sustainability and circularity is ongoing. This component has been integrated for WEEE within the Plooto platform and can compute energy consumption based on measurable process parameters.
RM-recovery and Waste Data Space. Our approach considers governance across data, business, and AI models for various aspects such as: supply chain collaboration, data sharing, and DPP information sharing. Additionally, AI model passports (explainable AI) are being incorporated as part of the governance services, applied on top of each DT layer.
Adjustable robust optimisation for production operation and waste treatment. A generic MILP model has been introduced and validated to assess the robustness of the proposed solutions under specific fluctuations in the energy cost. A two-stage stochastic model that extends the deterministic MILP is adopted to offer additional resilience in circular planning.
Design Science Theory for CRIS. Cutting-edge technologies and tools to enable real-time decision-making, monitoring, and certification of materials and products, facilitating sustainable and resilient manufacturing practices have been adopted. The CRIS has been deployed as part of digital transformation efforts and represents a strategic move to meet the growing demands for sustainability and resilience.
Governance for circular value chains. The pilot requirements related to data and value network collaboration and DPP models to IDS specifications have been analysed and used to derive the IDS compliant architecture and data models. Finally, basic processes (Discoverability, Negotiation, and Data Exchange) and implemented initial collaboration model between Plooto users have been defined to facilitate the collaboration and data sharing beyond Plooto.
Business models, strategy and guidelines for digital circularity. Plooto can generate new revenue streams, through 1) new channels e.g. a marketplace, 2) new assets such as data and smart products, 3) pay per use/recurring subscription services and outcome-based models. Novel technologies (e.g. DPP) enable Plooto assets to provide economic benefits, i.e. 1) cost reduction through more efficient use of materials thanks to traceability and re-use, 2) revenue generation through new business models, new service offerings and recycled material 3) operational efficiency through supply chain optimization.
AI and Analytics for circularity. Different forecasting and anomaly detection algorithms have been tested including ARIMA/Residual Analysis and Isolation Forest. Continuous evaluation of combined techniques, aiming to better incorporate expert knowledge of real-life manufacturing and provide a supply chain view, with a focus on environmental sustainability and circularity is ongoing. This component has been integrated for WEEE within the Plooto platform and can compute energy consumption based on measurable process parameters.
RM-recovery and Waste Data Space. Our approach considers governance across data, business, and AI models for various aspects such as: supply chain collaboration, data sharing, and DPP information sharing. Additionally, AI model passports (explainable AI) are being incorporated as part of the governance services, applied on top of each DT layer.
Adjustable robust optimisation for production operation and waste treatment. A generic MILP model has been introduced and validated to assess the robustness of the proposed solutions under specific fluctuations in the energy cost. A two-stage stochastic model that extends the deterministic MILP is adopted to offer additional resilience in circular planning.
Design Science Theory for CRIS. Cutting-edge technologies and tools to enable real-time decision-making, monitoring, and certification of materials and products, facilitating sustainable and resilient manufacturing practices have been adopted. The CRIS has been deployed as part of digital transformation efforts and represents a strategic move to meet the growing demands for sustainability and resilience.
Governance for circular value chains. The pilot requirements related to data and value network collaboration and DPP models to IDS specifications have been analysed and used to derive the IDS compliant architecture and data models. Finally, basic processes (Discoverability, Negotiation, and Data Exchange) and implemented initial collaboration model between Plooto users have been defined to facilitate the collaboration and data sharing beyond Plooto.