A framework for supply chain optimization for modular manufacturing with production feasibility analysis

Modular manufacturing is gaining popularity in a variety of industrial applications due to potential cost-savings as well process flexibility that can be achieved with the use small and standardized modules. In this work, framework for supply chain optimization proposed ensures production feasibility help historical data individual modules machine learning-based analysis. A problem formulated where binary variables represent facility locations, integer correspond number modular equipment installed. Results demonstrate tradeoff between centralized distributed effect economies numbers on cost studied by solving problem.