{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/156034"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/156034","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Minimizing Total Delivered Cost of Stamped Assemblies Through Sourcing Optimization","abstract":"This thesis presents an optimization model for identifying alternate and cost-competitive assembly sourcing strategies in the automotive industry, focusing on the \"Make vs. Buy\" decision-making process for a multinational automotive OEM. A “Make vs. Buy” process evaluates the strategic benefits and cost advantages derived from in-sourcing or out-sourcing a production process. Typically, one in-source scenario is evaluated, but capacity constraints may limit the opportunity to in-source. To combat capacity constraints, the optimization model was developed to evaluate sourcing production processes from other plants within the OEM’s manufacturing network. The sourcing strategy evaluates production scenarios for multi-process stamped assemblies undergo. Utilizing a mixed integer programming framework derived from the knapsack problem, the model evaluates all production scenarios to minimize total costs while adhering to capacity and capability constraints. Results demonstrate the model's effectiveness in identifying cost-saving and alternate sourcing strategies. Future work may explore extending the model to encompass broader geographical and operational complexities within the automotive sector.","abstract_html":"This thesis presents an optimization model for identifying alternate and cost-competitive assembly sourcing strategies in the automotive industry, focusing on the "Make vs. Buy" decision-making process for a multinational automotive OEM. A “Make vs. Buy” process evaluates the strategic benefits and cost advantages derived from in-sourcing or out-sourcing a production process. Typically, one in-source scenario is evaluated, but capacity constraints may limit the opportunity to in-source. To combat capacity constraints, the optimization model was developed to evaluate sourcing production processes from other plants within the OEM’s manufacturing network. The sourcing strategy evaluates production scenarios for multi-process stamped assemblies undergo. Utilizing a mixed integer programming framework derived from the knapsack problem, the model evaluates all production scenarios to minimize total costs while adhering to capacity and capability constraints. Results demonstrate the model's effectiveness in identifying cost-saving and alternate sourcing strategies. 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