Mathematical model of productivity performance of a plastic cell phone housing - Rajalingam Sokkalingam (2013)
Mathematical model of productivity performance of a plastic cell phone housingThis research was conducted in the injection molding production department and it makes a significant contribution in the areas of injection molding industry and academic work. The research is an attempt to find ways to achieve high productivity performance by applying mathematical modelling and statistical methods to develop an integrated solution by combining technical and human factors in the injection molding industry. This is accomplished through a case study carried out in two phases. The aim of phase 1 is to determine the optimal injection molding process parameters setting by Design of Experimental (DOE) based methods that could be set to maintain the dimensions of the length and width of a cell phone housing as close to the target values of length (93.49 mm) and width (45.93 mm) as possible. The quality control tools were used to identify the critical injection molding process parameters, namely, mould temperature, injection pressure and screw rotation speed which can minimize the shrinkage defect. The statistical results and analysis are used to provide better interpretation of the experiments. The significant factors affecting the responses were identified by using ANOVA. Subsequently, the mathematical model equations were developed for predicted responses. The optimal process parameters setting was found to be: mould temperature at 90 , injection pressure at 2331 kg/cm2 and screw rotation speed at 123 mm/sec, by using response surfaces and contour plots. Verification and confirmation runs were carried out to ensure the achievability and stability of the determined optimal process parameters setting against the target dimensions of the length and width. The aim of phase 2 is to improve the daily productivity performance by evaluating three performance indicators, namely, production capacity, reject rate and process yield of the injection molding department, especially before and after the payday, and during working days in long holiday periods. The daily production data collected from injection molding production floor was used to obtain the daily productivity performance indicators. Subsequently, the One-Sample t-test was applied as a statistical tool to evaluate the daily productivity performance indicators. The appropriate payday was identified as every fourth Monday of the month. It was also found that all the daily productivity performance indicators did not reach the “Normal” level during working days in long holiday periods.