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Tesla Motors Quality Engineering Application And Implementation, Nick Kwan
Tesla Motors Quality Engineering Application And Implementation, Nick Kwan
Industrial and Manufacturing Engineering
Tesla Motors, in Winter 2013 during the author’s coop,had a variety of potential improvement areas regarding their quality engineering team. There were too many overall defects on the vehicles. Those defects were recognized as the cars were passing through inspection, coming off the line, as well as brought by customers to after-purchase service. One of the defects was the Charge-port Door Malfunction, in which the door of the Model S would not open on command. An additional defect was the Windshield Wiper Malfunction, in which the fluid was not hitting the car at the desired angle. Both of these defects …
Robust Parameter Design In Complex Engineering Systems:, Gregory Boylan
Robust Parameter Design In Complex Engineering Systems:, Gregory Boylan
All Dissertations
Many industrial firms seek the systematic reduction of variability as a primary means for reducing production cost and material waste without sacrificing product quality or process efficiency. Despite notable advancements in quality-based estimation and optimization approaches aimed at achieving this goal, various gaps remain between current methodologies and observed in modern industrial environments. In many cases, models rely on assumptions that either limit their usefulness or diminish the reliability of the estimated results. This includes instances where models are generalized to a specific set of assumed process conditions, which constrains their applicability against a wider array of industrial problems. However, …
Modeling And Optimization Of Stochastic Process Parameters In Complex Engineering Systems, Paul Goethals
Modeling And Optimization Of Stochastic Process Parameters In Complex Engineering Systems, Paul Goethals
All Dissertations
For quality engineering researchers and practitioners, a wide number of statistical tools and techniques are available for use in the manufacturing industry. The objective or goal in applying these tools has always been to improve or optimize a product or process in terms of efficiency, production cost, or product quality. While tremendous progress has been made in the design of quality optimization models, there remains a significant gap between existing research and the needs of the industrial community. Contemporary manufacturing processes are inherently more complex - they may involve multiple stages of production or require the assessment of multiple quality …