Abstract
Modern manufacturing systems often cannot efficiently cope with rapid changes in market demands. A main challenge is the inability of current manufacturing systems to utilize the capabilities and capacities of manufacturing resources efficiently due to inefficient data models and adaptation algorithms. To deal with transiently changing market demands, manufacturing systems often either under-provision or over-provision resources. However, both under-provisioning and over-provisioning incur unnecessary costs. The lack of sufficient resources leads to missing opportunities for new work, and over-provisioning incurs a cost by wasting investment, time, maintenance, and other unused resources.
In this work, we optimize manufacturing configurations using the known capabilities and capacities of manufacturing equipment. In particular, the work provides an object-oriented data model that complements a manufacturing systems’ semantic model and the mathematical formalization of the data model for the multi-demand satisfaction problem.
The proposed methodology is validated by optimizing the planning for small-box hinged product assemblies in aerospace manufacturing. This product family comprises rudders and elevators, which share commonalities in functionality, size, and build philosophy. Therefore, they can be assembled in a reconfigurable environment with common pick and place, drilling, fastening, and inspection procedures.
