June 22, 2008
June 22, 2008
June 25, 2008
13.170.1 - 13.170.8
An Advanced Quality Engineering Course for Technology Graduate Curriculum
Introduction Due to fierce competition and globalized marketplace, companies are forced to operate on their lowest possible profit margin. In this context, it is argued that quality and variety are the critical order winning factors for any product types. However, introducing a new variety also introduces large variability in the product during manufacturing. This deteriorates the performance leading to significant product quality and reliability problems. A large number of recalls and warranty expenditures in various industries are indicators of poor product quality. To avoid such problems quality engineers and engineering technologist are required to apply various online and offline quality engineering and management tools both during design and manufacturing stage. Among the offline quality control techniques, the most popular techniques are design of experiments and Taguchi methods. Likewise, the statistical process control (SPC) technique is known as online quality control.
The SPC techniques can detect the ‘in-control’ and ‘out-of –control’ situation. If there are problems due to assignable causes (or out-of control situation), the control charts can be very handy tools in terms of detecting the causes. However, a process being ‘in-control’ does not necessarily guarantee a good part all the time. Therefore, in order to minimize the variability and also to optimize the product performance we need to redesign the product and process by building quality into them. To achieve that level of quality we need the techniques like experimental design and other off-line quality improvement techniques.
Competency gap While there is no disagreement among academicians and practitioners on the importance of quality engineering to industry, it has not been given enough attention in most engineering curricula except in industrial engineering. Although the extent of topic may vary by discipline, per ABET Criteria 3(b) (c), which states that all should have the ability to design and conduct experiments and to analyze and interpret data skills1. Several educators and researchers in the past have studied the competencies gaps in the manufacturing engineering and manufacturing technology curricula. Lahidji and Albayyari2 have conducted a survey on the competencies in the Manufacturing Engineering Technology programs. Their finding suggests that quality engineering is one of the thirteen major competency gaps found in the graduates of manufacturing engineers. In the same study, Lahidji3 quotes that 69% of the respondents from industry rated quality as very important skills set that they would like to see in new manufacturing engineers. David Wells4 suggests process engineering, product engineering, quality engineering, and production engineering as the essence of manufacturing engineering. While these papers primarily focused on undergraduate curriculum, the similar examples are found true in the graduate curriculum as well. Further, certainly need of quality engineering course in the graduate curriculum has been recognized and is a part of majority of the industrial and manufacturing engineering, systems engineering, and engineering management programs5-8. Unfortunately, industrial and manufacturing technology graduate programs are still lacking a major course in advance quality engineering such as design of experiments.
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