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dc.contributor.advisorSimchi-Levi, David
dc.contributor.advisorWillems, Sean
dc.contributor.authorHungerford, Scott
dc.date.accessioned2024-01-16T21:52:36Z
dc.date.available2024-01-16T21:52:36Z
dc.date.issued2023-06
dc.date.submitted2023-07-14T19:58:28.813Z
dc.identifier.urihttps://hdl.handle.net/1721.1/153342
dc.description.abstractThe aluminum industry has sustained continuous growth since 1975 and expects to continue this trend with the increased popularity of electric vehicles. With these forecasts in place and the current market conditions, Commonwealth Rolled Products (CRP) is in a unique position to meet the increased market demand and supply auto and industrial product manufacturers with aluminum rolled products. In order for CRP to be able to meet the increased demand, they first must understand the full complexities of their operations and confidently estimate future volumetric capacity they are able to sell. The objective of the internship program with CRP is to provide a quantitative analysis on the current state and future state throughput of the complex continuous line (CCL). The analysis includes a heuristic model to determine the throughput and identify key performance indicators (KPIs) that impact throughput improvement the greatest. This model will recommend a roadmap to achieve a sustainable operations plan and sales forecast that will enable increased manufacturing capabilities. In addition to the heuristic model, a mixed integer program (MIP) will be developed to optimally schedule the product mix to reduce production hours lost to product changeover time. The scheduling of a CCL is considered a single machine scheduling problem (SMSP), and the introduction of transition coils is considered a sequence-dependent setup times (SDSTs) problem. This last portion of the paper will focus on the MIP application to optimally schedule the CCL to reduce transition coils.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright retained by author(s)
dc.rights.urihttps://rightsstatements.org/page/InC-EDU/1.0/
dc.titleEstimating and Optimizing Throughput in an Aluminum Rolling Mill Using Capacity Modeling and Optimization Techniques
dc.typeThesis
dc.description.degreeM.B.A.
dc.description.degreeS.M.
dc.contributor.departmentSloan School of Management
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.identifier.orcid0009-0003-2666-8324
mit.thesis.degreeMaster
thesis.degree.nameMaster of Business Administration
thesis.degree.nameMaster of Science in Civil and Environmental Engineering


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