Relationship of selective process variables to product quality and customer satisfaction in chair manufacturing
Abstract
The furniture industry is one of the most important in the United States. It employs thousands of people and generates billions of dollars annually in value added manufacturing. Any productivity improvement in this industry will have a significant effect on costs and market competitiveness. Currently, most furniture manufacturers are interested in a strategic approach to the improvement of productivity and quality in their industry. Changing market trends in the furniture industry call for high quality products and efficient manufacturing processes that will promote cost reduction, customer satisfaction, and fulfillment of higher quality standards. The lack of an integrated total quality program in the furniture industry generates many problems. These problems include high levels of work in process and high inventory levels of parts and subassemblies in intermediate stages of the manufacturing process, and long lead times. Poor relationships among suppliers, manufacturers and customers, and the loss of customer confidence result from these problems. The primary purposes in applying these tools are (a) to define the most important variables which affect the manufacturing system, (b) to identify the more important parameters that influence the final quality of the products, and (c) to design a methodology of selection which will help to identify the variables that have important impact in the final product quality. The goal of this research is to identify the most important parameters that influence final quality in chair manufacturing. To apply an appropriate dynamic analysis that permits evaluation of the entire system, and to determine the most important variables in the system. In addition to a linkages analysis among important factors that include quality, cost, and productivity was completed. The results of this linkages analysis were tested through a factorial experiment that permitted the best combination of resources to be found and higher productivity to be obtained.
Degree
Ph.D.
Advisors
Eckelman, Purdue University.
Subject Area
Industrial engineering|Wood|Technology
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