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Lean Quality Management
Published in Jong S. Lim, Quality Management in Engineering, 2019
After we have identified the root causes of the problem and process, we need to devise a method to improve the problem and process by eliminating the major root causes. At the same time, we have to determine the right parameters to improve. For this purpose, quality engineering tools like FMEA (Failure Mode and Effects Analysis), FTA (Fault Tree Analysis), DOE (Design of Experiment), and SQC (Statistical Quality Control) can be used. As for improvement options and methods, we can use the scientific problem management methodology described in Chapter 6.
Overview of Quality
Published in Abdul Razzak Rumane, Quality Management in Oil and Gas Projects, 2021
Feigenbaum (1991) defines quality engineering technology as “the body of technical knowledge for formulating policy and for analyzing and planning product quality in order to implement and support that quality system which will yield full customer satisfaction at minimum cost” (p. 234).
Using Taguchi and neural network approaches in the optimum design of product development process
Published in International Journal of Computer Integrated Manufacturing, 2020
Ming-Chyuan Lin, Guo-Peng Qiu, Xue Hua Zhou, Chien-Nan Chen
Product design is critically important to manufacturing. Although most manufacturers do not explicitly stress enhancement of product design, their efforts to improve product quality and increase productivity have integrated certain experience and knowledge that might be used to increase the efficiency and effectiveness of product design. Recently, computer and information technology has delivered great progress in the area of computer-aided design (CAD) and computer-aided manufacturing (CAM), computer-integrated manufacturing (CIM) and these tools are widely used by many industries to remain competitive in international markets by shortening the design cycle and improving product efficiency (Prasad1996). Furthermore, many enterprises emphasise continuous improvements in product quality. Thus, product design and quality improvement should represent a best match in designs for the product and its manufacturing system. Established industrial engineering design strategies, such as the strategic approach to product design (SAPD), axiomatic design approach, and manufacturing design have been applied to the study of manufacturing and production systems to reduce manufacturing costs, improve product quality, and increase productivity (Stoll 1999; Suh 2001; Dong, Yang, and Wang 2010). Current approaches for improving product quality and robustness include concurrent engineering (CE), quality engineering (QE), quality design (QD), value analysis (VA) and innovation, and failure mode and effect analysis (FEMA), among others (Prasad 1996; Morrison 2001; Chen et al. 2011). Since many new products are merely incremental improvements or modifications of existing products, Cross (2008) stressed the importance of systematic approaches to the product design process to assist the designer in enhancing the effectiveness of the final design solution.