A sustainability-oriented methodology to compare production strategies: The case of AM-based remanufacturing

The implementation of sustainability principles is becoming fundamental for companies, also for creating added value in the production processes. Production managers should not consider only the economic-financial aspects in their decisions, but also the environmental and social implications to extend the benefits to all current and future world populations. This vision requires to develop and apply sustainability-oriented methodologies to compare alternative production strategies. This paper contributes to addressing this problem by proposing a methodology that allows comparing different production strategies by considering their sustainable impact, starting with the definition of their processes. An aggregated sustainability index has been designed for this purpose. Thus, the paper contributes to the literature on the evaluation of sustainability through the development of a methodology, which can be used by the practitioners as a decision support tool to identify the most sustainable production strategy according to the objective of the company and the specific production process considered. Then, the proposed methodology has been applied to compare two different production strategies, i. e., AM-based remanufacturing and the production of new components. A simulation model has been implemented to reproduce the behaviour of the two competing production strategies. Although the results depend on the utilized data, this application showed that it is possible to distinguish different areas of convenience for each strategy. Moreover, findings revealed that the sustainability of the production strategies is strictly connected to the adopted technology and the importance given to the economic, environmental and social aspects by the company

Robotic disassembly of waste electrical and electronic equipment

Waste electrical and electronic equipment (WEEE) is the world’s fastest growing form of waste. Inappropriate disposal of WEEE causes damage to ecosystems and local communities due to hazardous materials and toxic chemicals present in electronic products. High value metals in small quantities are dissipated and embodied energy from manufacturing are lost in shredding and crushing treatments of WEEE. On the other hand, manual disassembly is costly and presents safety concerns for human workers. Therefore, robotic disassembly is an ideal approach to addressing the treatment of WEEE. Despite extensive research in the field, large variations and uncertainties in product structures, models, and conditions is a major limitation to the implementation of automation and robotics in the waste industry. The ability of a robotic disassembly system to learn new product structures and reason about existing knowledge of product structure is vital to addressing this challenge. This thesis explores robotic disassembly for WEEE by building upon an existing research disassembly rig for LCD monitors and expanding it to address other product families. The updated disassembly system utilizes a modular framework consisting of a Cognition module, Perception module, and Operation module, in order to address the uncertainties present in end-of-life (EoL) products. A novel disassembly ontology is designed and developed with an upper and lower ontology structure to represent generic disassembly knowledge and product-family-specific knowledge respectively. Furthermore, a Learning framework enables automated expansion of the ontology using past disassembly experiences and user-demonstration. These presented methodologies form the main function of the Cognition module, which aids the Perception module and instructs the Operation module. The disassembly ontology and Learning framework are verified independently from the rest of the system prior to being integrated and validated with real disassembly runs of LCD monitors and keyboards. As such, the disassembly system’s ability to address both known and unknown EoL product types, as well as learn new product types, is demonstrated

Concurrent Product and Supply Chain Architecture Design Considering Modularity and Sustainability

Since sustainability is a growing concern, businesses aim to integrate sustainability principles and practices into product and supply chain (SC) architecture (SCA) design. Modular product architecture (MPA) is essential for meeting sustainability demands, as it defines detachable modules by selecting appropriate components from various potential combinations. However, the prevailing practice of MPA emphasizes architectural aspects over interface complexity and design production processes for the structural dimension, potentially impending manufacturing, assembly/disassembly, and recovery efficiency. Most MPA has been developed assuming equal and/or fixed relations among modules rather than configuring for SC effectiveness. Therefore, such methods cannot offer guidance on modular granularity and its impact on product and SCA sustainability. Additionally, there is no comparative assessment of MPA to determine whether the components within the configured modules could share multiple facilities to achieve economic benefits and be effective for modular manufacture and upgrade. Therefore, existing modular configuration fails to link modularization drivers and metrics with SCA, hampering economic design, modular recycling, and efficient assembly/disassembly for enhancing sustainability. This study focuses on the study of design fundamentals and implementation of sustainable modular drivers in coordination with SCA by developing a mathematical model. Here, the architectural and interface relations between components are quantified and captured in a decision structure matrix which acts as the foundation of modular clustering for MPA. Again, unlike previous design approaches focused only on cost, the proposed work considers facility sharing through a competitive analysis of commonality and cost. It also evaluates MPA's ease of disassembly and upgradeability by a comparative assessment of different MPA to enhance SCA sustainability. The primary focus is concurrently managing the interdependency between MPA and SCA by developing mathematical models. Consistent with the mathematical model, this thesis also proposes better solution approaches. In summary, the proposed methods provide a foundation for modeling the link between product design and SC to 1) demonstrate how sustainable modular drivers affect the sustainability performance, 2) evaluate the contribution of modularity to the reduction of assembly/disassembly complexity and cost, 3) develop MPA in coordination with SC modularity by trading off modular granularity, commonality, and cost, and 4) identify a sustainable product family for combined modularity considering the similarity of operations, ease of disassembly and upgradability in SCA. Using metaheuristic algorithms, case studies on refrigerators showed that MPA and its methodology profoundly impact SCA sustainability. It reveals that interactions between components with levels based on sustainable modular drivers should be linked with modular granularity for SCA sustainability. Another key takeaway is that instead of solely focusing on cost, facility sharing and ensuring ease of disassembly and upgradeability can help to reap sustainability benefits