Abstract

In this thesis, a production and inventory planning model for mixed make-to-order (MTO) make-to-stock (MTS) production system in garment industry. Where the dominant production is typically for the Make-to-order production and the make-to-stock production is penetrating the mainstream production (MTO) as a way of enhancing the revenues and maintaining a positive cash flow, that are often degraded due to either seasonality of demands or production planning challenges. The model considers capacity planning for the mixed environment when there are predictable fluctuating demands. Due to the nature of the clothing business, it is challenging for a garment manufacturer to cope with seasonal changes while having the best capacity utilization. The literature acknowledges production planning in the garment industry. While a little focus was for capacity planning for seasonal fluctuating demands. Mathematical programming for capacity planning in a mixed MTO and MTS garment-manufacturing environment is a viable approach that can provide effective management decisions that can help the garment industry to strive in today’s competitive pace. The proposed model considers distributing the available capacity between MTO and MTS production and the implications of the costs and revenues for different capacity distribution. Decisions made on the production amounts, inventory levels and generated revenues are attained. The model was verified and validated by applying it to a local ready- made garment factory. The results ensured the validity of the proposed model. When analysis was made to the parameters that influence the decisions, it was found that distributing the capacity between MTO and MTS with different percentages had significant impact on the revenues and costs. The model was very sensitive to the increases in the fabric price and subcontracting costs while the overall net profits were not significantly affected by the changes in the inventory holding cost. Last, this work is useful in helping garment manufacturers adapt rapidly to seasonal changes by deploying their capacity effectively in favor of their projected seasonal plans.

Department

Mechanical Engineering Department

Degree Name

MS in Mechanical Engineering

Date of Award

2-1-2018

Online Submission Date

January 2018

First Advisor

Abdelmaguid, Tamer F.

Committee Member 1

Abdelmaguid, Tamer F.

Committee Member 2

ElTawil, Amr

Document Type

Thesis

Extent

84 p.

Rights

The author retains all rights with regard to copyright. The author certifies that written permission from the owner(s) of third-party copyrighted matter included in the thesis, dissertation, paper, or record of study has been obtained. The author further certifies that IRB approval has been obtained for this thesis, or that IRB approval is not necessary for this thesis. Insofar as this thesis, dissertation, paper, or record of study is an educational record as defined in the Family Educational Rights and Privacy Act (FERPA) (20 USC 1232g), the author has granted consent to disclosure of it to anyone who requests a copy.

IRB

Not necessary for this item

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