00000ctm a22000003a 4500 UP-99796217610616146 Buklod 20221018085659.0 a grb 001 u| ta 221018s2001 xx r |||| u| | (iLib)UPD-00194805982 DENG aacr eng LG 993 2001 E66 C375 Capili, Robert Jerome D. A Statistical analysis study on D.Y. Manufacturing Corporation Robert Jerome D. Capili, Nittanee Frances B. Galema, Maria Jann-Ella M. Juan. Diliman, Quezon City College of Engineering 2001 50 leaves Feasibility study Access exclusively for UP IE students. Written permission required from the department head for NON-IE and NON-UP students or researchers Submitted in partial fulfillment of the course requirements in IE 28 : Statistical Analysis for Industrial Engineering Manufacturing companies rely on quality to make their products acceptable to the buying public. Quality of the product depends on conditions during the production process. These factors affecting a quality characteristic can be determined using statistical analysis. D.Y. Manufacturing Corporation produces plastic products such as plastic sheets and blown film made from thermosetting plastics. Their customers are prestigious companies like SM, Philacor, General Electric and Mitsubishi Motors Corporation. The quality of their customer's products is dependent on theirs. It is a must for them to produce good quality products. A major concern for the company is the inherent thickness of their plastic sheets. This study works toward the identification of significant factors present during production that causes deviation from the specified thickness. This study focuses on the 2mm-thick High Impact Polystyrene sheets, which is a major product of the company. The experimental design used in this study is the Three-Factor Factorial Design where the three factors identified were die zone temperature, air pressure in rubber rollers and temperature of steel rollers. The first two factors each have 2 levels while the latter has 3 levels. There are twelve (12) experimental runs with 3 replicates each. This study utilizes the Analysis of Variances and Regression Analysis to determine to which process variable or factor thickness is dependent on. The ANOVA table was used as a test statistic while the model was estimated by Multiple Linear Regression. From the hypothesis test and regression model, the process variables, which affect thickness of the plastic sheet, were the die zone temperature and air pressure of rubber rolls. There also exist interaction effects between the factors. These are the interactions between die zone and steel rolls temperature, between steel rolls temperature and air pressure and lastly, between air pressure and die zone temperature. A possible positive correlation between die zone temperature and thickness was proven using a scatter diagram and the significant level of air pressure which is 36 bar was determined using Duncan's Multiple Range Test. Careful monitoring of the die zone temperature and maintaining constant pressure and temperature throughout the production is recommended to minimize rejects due to deviations from specified thickness of plastic sheets. Statistics. Statistical Analysis for Industrial Engineering IE 28. Galema, Nittanee Frances B. Juan, Maria Jann-Ella M. Thesis FI UP Paper UPD DENG LG 993 2001 E66 C375 Thesis