Abstract
Refurbishment and remanufacturing are the industrial processes whereby used products or parts that constitute the product are restored. Remanufacturing is the process of restoring the functionality of the product or a part of it to “as-new” quality, whereas refurbishment is the process of restoring the product itself or part of it to “like-new” quality, without being as thorough as remanufacturing. Within this context, the EU-funded project RECLAIM presents a new idea on refurbishment and remanufacturing based on big data analytics, machine learning, predictive analytics, and optimization models using deep learning techniques and digital twin models with the aim of enabling the stakeholders to make informed decisions about whether to remanufacture, upgrade, or repair heavy machinery that is toward its end-of-life. The RECLAIM project additionally provides novel strategies and technologies that enable the reuse of industrial equipment in old, renewed, and new factories, with the goal of saving valuable resources by recycling equipment and using them in a different application, instead of discarding them after use. For instance, RECLAIM provides a simulation engine using digital twin in order to predict maintenance needs and potential faults of large industrial equipment. This simulation engine keeps the virtual twins available to store all available information during the lifetime of a machine, such as maintenance operations, and this information can be used to perform an economic estimation of the machine's refurbishment costs. The RECLAIM project envisages developing new technologies and strategies aligned with the circular economy and in support of a new model for the management of large industrial equipment that approaches the end of its design life. This model aims to reduce substantially the opportunity cost of retaining strategies (both moneywise and resourcewise) by allowing relatively old equipment that faces the prospect of decommissioning to reclaim its functionalities and role in the overall production system.
Highlights
The industrial sector in Europe is very important as a “driver of sustainable growth and employment” (EP (2019))
The decision support framework (DSF) for the optimization of refurbishment and remanufacturing process in itself is a significant step beyond the state of the art in the provisioning of infrastructure, tools, and services for experimentation in the digital manufacturing domain
The RECLAIM framework ensures that the remanufacturing and refurbishing interventions make a positive contribution toward business and toward the environment
Summary
The industrial sector in Europe is very important as a “driver of sustainable growth and employment” (EP (2019)). Refurbishment and remanufacturing are activities of the circular economy model, the purpose of which is to keep the high value of products and materials, as opposed to the currently employed economic model, targeting the extension of equipment and materials’ life and reducing the unnecessary and wasteful use of resources These two activities, along with health status monitoring, are the key elements for lifetime extension and reuse of large industrial equipment. Its ultimate objective is to preserve valuable resources by reusing equipment instead of discarding it In this context, the project will develop new models and strategies for repairing and upgrading equipment and redesigning factory layouts to benefit the manufacturing sector from an economic perspective.
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