Decision Support Framework for optimal lifetime extension strategies in manufacturing (e.g. refurbishing, remanufacturing), (DSF Core + Services) based on analytics of heterogeneous real-time industrial data, both raw and processed by sub-services.
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Listing Description
Addressing target audiences and expressing needs
- Collaboration
Further training of models by data scientists on the customer side. Final integrations among software and hardware components is required.
- Public or private funding institutions
- Research and Technology Organisations
R&D, Technology and Innovation aspects
Further training of models by data scientists on the customer side. Final integrations among software and hardware components is required.
Tested in textile bleaching, shoemanufacturing, white goods, welding machine construction, wood furniture manufacturing. Can be replicated in other manufacturing industries.
yes, an adequate circular economy business model is currently being developed in association with the given Decision Support Framework.
Offer Details
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Value Proposition:
Few of the previous studies could help achieve health-based recovery planning at both machine and component level while considering economic and environmental effects. This is a flexible recovery decision support framework (DSF) to assist the machinery operators and machinery manufacturers in making efficient end-of-life decisions at different service-life periods. Machinery lifetime extension, return on investment by avoiding machinery replacement cost, material & resource efficiencyWe move beyond CBM (Condition Base Maintenance) and static wear and service chartsWe take into account information at several layers simultaneously: Manufacturing Execution/Production planning, production process, individual telemtry (i.e. IoT sensing layer).
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Adress:
Birmingham
England
B4 7ET
United Kingdom
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