Proposal of Industry 5.0-Enabled Sustainability of Product–Service Systems and Its Quantitative Multi-Criteria Decision-Making Method

Abstract

In the wake of Industry 4.0, the ubiquitous internet of things provides big data to potentially quantify the environmental footprint of green products. Further, as the concept of Industry 5.0 emphasizes, the increasing mass customization production makes the product configurations full of individuation and diversification. Driven by these fundamental changes, the design for sustainability of a high-mix low-volume product–service system faces the increasingly deep coupling of technology-driven product solutions and value-driven human-centric goals. The multi-criteria decision making of sustainability issues is prone to fall into the complex, contradictory, fragmented, and opaque flood of information. To this end, this work presents a data-driven quantitative method for the sustainability assessment of product–service systems by integrating analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods to measure the sustainability of customized products and promote the Industry 5.0-enabled sustainable product–service system practice. This method translates the sustainability assessment into a multi-criteria decision-making problem, to find the solution that meets the most important criteria while minimizing trade-offs between conflicting criteria, such as individual preferences or needs and the life cycle sustainability of bespoke products. In the future, the presented method can extend to cover more concerns of Industry 5.0, such as digital-twin-driven recyclability and disassembly of customized products, and the overall sustainability and resilience of the supply chain.

Towards Sustainable Inventory Management: A Many-Objective Approach to Stock Optimization in Multi-Storage Supply Chains

“…This work is also within the scope of the advent Industry 5.0, as the pillars of this new evolution of industrial technology are based on sustainability, human centricity, and resilience [43]. To this end, this research is greatly centred on the pillars of Industry 5.0: human-centric, as the solution outputted by the many-objective optimization model requires a human decision-maker with field expertise; sustainable, as one of the objectives is the reduction in energy consumption; resilient, as the risk of shortage is also minimized, and the optimization is data-driven, based on the production schedule of the company.…”