Joint Optimization Of Demand And Resources Allocations In Decentralized Manufacturing

In the era of globalized manufacturing, traditional centralized approaches face the challenges posed by various disruptions such as geopolitical influences, pandemics, and natural emergencies. In response to these challenges, Industry 5.0, a new concept built around human-centricity, sustainability, and resilience, offers a solution to such problems. Decentralized Autonomous Manufacturing (DAM), which is aligned with the principles of Industry 5.0, facilitates enhanced mass individualization and resilience. Each facility in a DAM system is independent, and each facility has its machines equipped with the capabilities required to produce the allocated demand types. This paper proposes a joint optimization model to allocate different types of demand points to DAM facilities while optimizing the number of machines and the upgrades required for the capabilities of each facility. The model minimizes the total cost of the system, including the costs of opening facilities, the operational expenses and upgrades of the machine capabilities, the transportation costs, and the penalties for delays. Numerical experiments are conducted to highlight the cost savings of our proposed model compared to having one centralized facility and various facilities closest to each demand point. We also analyze the impact of various parameters on decision variables. The findings highlight the significance of having an open facility in the area closest to high-demand product types, particularly when demand points are of similar types. Conversely, when dealing with diverse product types, demand types with lower demand rates and higher upgrade costs tend to be clustered in one facility.