Application Of Shainin Design Of Experiment In Magnesium Diecasting Quality Improvement

It's the lightest structure metal Magnesium is being increasing used in industry, especially in automobiles. Magnesium castings light weight mass helps reduce automobile weight and achieve lower carbon emission therefore protecting the environment. In the thesis, magnesium casting applications will be discussed on automotive components. Magnesium alloys nowadays have developed so they can be used in various types of automotive roles. This paper will review current production automotive castings as well as new developing technology areas. We can look forward to the future growth of magnesium casting in the automotive field. Toyota recall is a good lesson to Chinese automotive industry. In nowadays when competition becomes increasingly fierce, the company need more focus on quality performance. As traditional hot working, diecasting companies were puzzled for quality issues and casting defects. To find the suitable quality tools which can help company to catch and solve the problems. In my thesis, will discuss to use Shainin DOE (Design of Experiments) to improve quality of magnesium transmission case. The first step is to define the object of study. We analyzed four months quality performance of transmission case, and found that the porosity issue was the top one defect in scrap rate reports. So the porosity is the problem should be figured out (Green Y). In the second stage, we use the Process Failure Mode and Effect Analysis (PFMEA) to search the processes which will affect the object. PFMEA was reviewed by a professional team, and defined the process parameters, the failure modes, the failure effects of each process, and qualified the Severity, the Occurrence, and the Detection, and assessed the Risk Priority Number (RPN). In the third stage, base on the variable family of Green Y, we use Shainin's DOE methods and tools to find out the Red X, Pink X and Pale Pink X. We design the experiments we need and perform it. To use Paired Comparisons and Tukey Test to process the testing data and provide clues to the Red X with their confidence level. Then, through the Variables Search method to find out the key factors. We defined the best level, the worst level, the best limit and the critical limit, and captured the main effects of important factors and the interaction effects between the factors. Then, to use the Full Factorial Analysis method to calculate the main effects and the interaction effects. And use the Analysis of Variance (ANOVA) method to find out the Red X, Pink X, and Pale Pink X, According to the best level of these key factors to perform the process parameters'setup. Finally, to use B versus C to confirm the effectiveness and persistence of the improvement. The result shows our improvement is effective and persistence. Utilize Shainin DOE, is very straight forward, tools are simple to use with calculations and formulas easy to handle. Graduates engineer with basic DOE training will have no problem using these tools. Shainin DOE doesn't need to spend a lot of money and occupy production line long time. During the normal production we can arrange the experiments. This tool can be used in a wide variety of application.