Modeling the tradeoff between inventory and capacity to optimize return on assets in production scheduling

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Authors dc:creator

• Wu, Cindy (Cindy Hsin-ying)
• González Duhart Muñoz de Cote, José Antonio

Advisor dc:contributor.advisor

• Bruce C. Arntzen.

• Engineering Systems Division.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/81110

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/81110