Modeling the tradeoff between inventory and capacity to optimize return on assets in production scheduling
Name
858279065-MIT.pdf
Description
Full printable version
Size
5.28 MB
Format
Adobe PDF
Checksum (MD5)
6e264e948daa64ba3ae8285412c644e9
Author(s)
Wu, Cindy (Cindy Hsin-ying)
González Duhart Muñoz de Cote, José Antonio
Advisor(s)
Bruce C. Arntzen.
Date Issued
2013
Publisher
Massachusetts Institute of Technology
Abstract
In the agrochemical industry, companies are challenged with an extreme seasonality in demand driven by the crops' growing cycles. Therefore, balancing supply with such fluctuating demand has been a struggle for most companies due to their capacity constraints. One way to accommodate the demand is to stock enough inventory ahead of the peak seasons, while the other is to increase the production capacity so that the companies can react to the changing demand more quickly. However, either alternative comes at a significant cost. This paper examines the optimal mix of production capacity and inventory for a company to meet customers' demand at the highest net present value (NPV) of operating assets value add (OAVA). We use a multi-period, multi-stage, multi-product mixed integer linear optimization model to determine the best combination of resources. Viable resource options include stocking inventory ahead of the peak seasons, enhancing output through overtime, outsourcing production activities to a third party, and acquiring new assets for a particular production stage. The results show that the optimal OAVA comes from a combination of all these viable resources. Additionally, the master production schedule, the resulting inventory levels, and the recommended timings for external resources and asset acquisition are important takeaways from our model. They serve not only as the guidance of the company's day-to-day operations, but also as the quantitative analysis necessary to communicate with stakeholders across different functional teams with potentially conflicting interests.
Description
Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 51-52).
Subjects
Engineering Systems Division.
MIT Department
Massachusetts Institute of Technology. Engineering Systems Division
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