The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Design for quality manufacturability analysis for common assembly process
Author:	Ramachandra, Suriyanarayanan
View Online:	njit-etd1995-008 (xii, 82 pages ~ 3.8 MB pdf)
Department:	Manufacturing Engineering Division
Degree:	Master of Science
Program:	Manufacturing Systems Engineering
Document Type:	Thesis
Advisory Committee:	Das, Sanchoy K. (Committee chair) Abdel-Malek, Layek (Committee member) Sodhi, R. S. (Committee member)
Date:	1995-01
Keywords:	Quality Control Manufacturing Processes--Design Manufacturing Processes--Quality Control Production Engineering--Design
Availability:	Unrestricted
Abstract:	The globalization of market economy has precipitated a dramatic increase in competition necessitating the need for higher quality products at lower cost in shorter time periods. Shorter life cycles and proliferation of products has made companies integrate all the phases of manufacturing to bring about a superior design. Design for Quality Manufacturability (DFQM) provides a technique to invoke manufacturing and assembly considerations while designing a product. The DFQM architecture identifies factors consisting of several variables that are influenced by certain error catalysts to cause one or more specific defects. A methodology is suggested to identify and quantify these error catalysts to be able to estimate the quality of the design. Some of the assembly processes that are widely used are insertion, riveting, welding, fastening, press-fit, and snap-fit. A detailed study of each of these processes is done to analyze the techniques, capabilities, and limitations. Using the DFQM architecture defect classes and specific defects are identified and analyzed. A correlation matrix is formed to identify the processes that are associated with each specific defect. Cause-Effect analysis using Ishikawa diagrams provide a means of analyzing the characteristics of the relevant processes attributing to each specific defect. These characteristics are grouped to identify the error catalysts that influence the occurrence of the specific defect.