Date of Award

8-2015

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Industrial Engineering

Committee Member

Dr. Scott J. Mason, Committee Chair

Committee Member

Dr. J. Cole Smith

Committee Member

Dr. Mary E. Kurz

Abstract

Consider a paint manufacturing firm whose customers typically place orders for two or more products simultaneously: liquid primer, top coat paint, and/or undercoat paint. Each product belongs to an associated product family that can be batched together during the manufacturing process. Meanwhile, each product can be split into several sublots so that overlapping production is possible in a two-stage hybrid flow shop. Various numbers of identical capacitated machines operate in parallel at each stage. We present a mixed-integer programming (MIP) to analyze this novel integrated batching and lot streaming problem with variable sublots, incompatible job families, and sequence-dependent setup times. The model determines the number of sublots for each product, the size of each sublot, and the production sequencing for each sublot such that the sum of weighted completion time is minimized. Several numerical example problems are presented to validate the proposed formulation and to compare results with similar problems in the literature. Furthermore, an experimental design based on real industrial data is used to evaluate the performance of proposed model. Results indicate that the computational cost of solving the model is high.

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