Inventory segmentation and production planning for chemical manufacturing

Developing a cyclical schedule for producing multiple items on a single processor under stochastic demand that minimizes total setup and inventory holding costs is an important problem. This problem is faced in many continuous production environments such as chemical or petrochemical production, where the costs of switching production from one item over to another are very high. Due to high changeover costs, each item is produced in large batches and its demand is fulfilled from the finished goods inventory. Holding this inventory incurs inventory carrying costs. Therefore, good production planning policies are required to determine when and how much of each item should be produced so that the total cost of setup changeovers and holding inventory is minimized, while ensuring that sufficient inventory is available to meet customer demand which varies over time. In this thesis, I present the work done to develop production planning policies for a large chemical manufacturing company that operates in the environment described above. The problem described above is called the Economic Lot Scheduling Problem (ELSP) and is known to be NP-hard. So, optimal solutions are hard to find and one has to rely on heuristic procedures to find good solutions.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• Phadnis, Shardul Sharad, 1978-

Advisor dc:contributor.advisor

• Stephen C. Graves.

• 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/1721.1/40114

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/40114