Doctor of Philosophy (PhD), Ohio University, 2016, Mechanical and Systems Engineering (Engineering and Technology)

Global supply chain decisions, such as facility location, manufacturing system design, resource allocation, and distribution center location are long-term strategic decisions in nature and involve many uncertainties. Traditionally, a hierarchical approach is used design supply chain networks and manufacturing systems. First, the location of the facilities are determined, and then the manufacturing systems are designed at the selected locations. In this dissertation, a multi-stage supply chain network model is developed where locations of the plants and inner manufacturing system design are determined simultaneously for labor-intensive manufacturing companies. This dissertation aims to develop a decision making framework to integrate manufacturing systems and supply chain network design decisions considering optimal operator assignment and layered cellular manufacturing in mind. The industry studied is fashion jewelry manufacturing where labor cost is one of the major cost factors. Hence, optimizing the number of workers required for each operation, cell, and plant is critical for the cost efficiency of the entire supply chain. The optimal number of operators are determined for each manufacturing process, and then the optimal cell sizes are found for each manpower level using a heuristic procedure. The optimal number of manufacturing cells required to cover the uncertain demand is determined with mathematical modeling, and the designed layered cellular manufacturing systems for manufacturing stages are evaluated using Arena simulation models. The results of these models and methods are used as inputs while finding the optimal locations of the plants and allocating the optimal number of cells, workers, and machines for each selected plant. Different supply chain design alternatives considering various factors such as the shortest lead times, minimum capacity allocations, and multiple shifts are also studied.

Committee: Gursel A. Suer Ph.D. (Advisor) Subjects: Industrial Engineering; Operations Research

Master of Science (MS), Ohio University, 2005, Industrial and Manufacturing Systems Engineering (Engineering)

Several solutions to the cell loading problem in labor intensive cells have been reported in the literature. Even though significant research has been done considering the "operator" factor, very little research is done considering operator skills. This thesis makes an effort to assign operators to various operations by considering operator skill levels and operator-operation times as opposed to the classical approach of using standard times. The objective of the thesis is to perform a single-period analysis which includes testing the effect of variability in operator-operation times, impact of more operator skills, comparison of cell loading strategies, and operator assignment approaches and multi-period analysis which includes comparison of operator assignment approaches and impact of operator learning and forgetting rates on operator skills. Results show that the proposed approach in operator assignment outperforms the classical approach of using standard times when both lot splitting and operator sharing are allowed for the problem considered and in the long run Max-Min approach gives better results than the classical approach and Max approach in terms of skill improvement.

Committee: Gursel Suer (Advisor) Subjects: Engineering, Industrial