Decision support systems for integrated product and production system design.

Conventional product and production system design procedure is a sequential one where the production system is designed after product development efforts are completed. In most cases, this sequential framework results in either sub-optimal products due to the lack of manufacturing capability to provide the requirements or high production cost due to expensive machine tools. In order to minimize the sensitivity of product performance to manufacturing and assembly variations, an integrated design methodology along with tools to aid optimal decision making is required. The first part of this thesis develops an integrated product design methodology along with tools to aid optimal decision making for robustness. Optimum design of production capacity requires information about the future such as the future market demand and production requirements. Moreover, there is a tradeoff between the cost of a manufacturing system and its quality characteristics, and it is necessary to identify this tradeoff to position products optimally. Therefore, it is important to understand the tradeoffs between the total cost of production affected by the adjustments in production capacity, and the resulting changes in product quality. The second part of this thesis quantifies the economic advantage of using perfect demand forecast, and develops a simulation-based method to aid optimal capacity planning decisions by quantifying the tradeoff between the capital and operating cost of a production facility and the quality of finished products. The potential benefits of using multiple types of machine tools performing the same task with different price and quality characteristics is also demonstrated in this section. The last parts of the thesis study robustness issues against demand uncertainty in capacity planning. Resource sharing through product mix flexibility and part commonality are two important strategies to minimize risk due to uncertainty in the volume mix of demand for firms with product portfolios consisting of multiple products. An integrated decision support system is developed to create robust capacity investment policies against uncertainty in volume mix of demand by adding an optimum amount of flexibility to the production facility. Finally, a method to find various part commonality configurations by analyzing cost-quality tradeoffs of different resource sharing alternatives as a result of a capacity planning problem is presented.Ph.D.Applied SciencesIndustrial engineeringMechanical engineeringOperations researchUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/124450/2/3138193.pd