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Sunderesh S. Heragu, Gerald W. Evans, and Gail W. DePuy Department of Industrial Engineering

Modeling, Analysis and Solution of the Manufacturing and Distribution Activities at Alcoa Engineered Products. Sunderesh S. Heragu, Gerald W. Evans, and Gail W. DePuy Department of Industrial Engineering University of Louisville Louisville, KY 40292. Background.

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Sunderesh S. Heragu, Gerald W. Evans, and Gail W. DePuy Department of Industrial Engineering

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  1. Modeling, Analysis and Solution of the Manufacturing and Distribution Activities at Alcoa Engineered Products Sunderesh S. Heragu, Gerald W. Evans, and Gail W. DePuy Department of Industrial Engineering University of Louisville Louisville, KY 40292

  2. Background • Alcoa Engineered Products (AEP) is interested in developing an optimal or near-optimal strategy for its manufacturing and distribution activities • AEP manufactures extruded aluminum products at eight US manufacturing locations. Some of the manufacturing is sourced from partners in Brazil and China • All products are extruded and then undergo one of several operations • The plants have a subset of the following processing capabilities – mill finish, anodizing, painting, and fabrication • The make-to-stock (MTS) items are stored in depots located in or near two manufacturing plants • The MTS and Make-to-order (MTO) items are shipped to markets that fall into five categories: distribution, building and construction, commercial transportation, industrial and consumer, and automotive

  3. What is required? • Detailed analysis of the operations at each of the eight manufacturing plants, distribution of products from these plants to the five markets listed above • Specifically, AEP would like to determine: • The products are to be manufactured at each of the plants • The products are to be sourced from global partners • If and where specific products are to be inventoried • Where to locate (new) distribution facilities, and • The network over which products are to be shipped so that the manufacturing, distribution and inventory costs can be minimized and customer service levels can be improved

  4. Approach • A linear, mixed-integer mathematical programming model to be developed • Model consists of two components - resource allocation and distribution center location • Resource allocation component allows scarce resources to be allocated optimally across the entire system • The distribution center location component minimizes the sum of warehousing and transportation costs while maintaining an acceptable customer service

  5. Decision Variables • Number of units of each product type to be produced in each period at each manufacturing location • Inventory of each product type at each location in each period • Quantities to be shipped from each plant to each distribution center to customers in each planning period • The number of distribution centers and their locations

  6. Objective Function • Minimizing cost and improving customer service levels

  7. Constraints • Equipment capacity constraints • Labor constraints • Projected sales constraints • Inventory level constraints • Distribution center capacity constraints • Customer demand constraints • Number of distribution centers constraint

  8. Deliverables • Development of appropriate linear, mixed-integer programming models and algorithms • Related decision support tools that include: • client-specific front-end for data entry • model generation in CPLEX specific format, and • client-specific back-end for results generation

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