An industrial quality control study on Marivel's Pillow - Agbay, Michael M. (College of Engineering, 2004)
The study analyzed the production and quality systems of Marivel's Pillows. The purpose of the study is to check if the production processes of the company are in statistical control. The study focused on the Type A pillows of the company, specifically the Extra Large and the Throw Pillows which make up the bulk of the company's sales. The management told the researchers that the weight and dimensions of the pillow are the factors to consider since both are critical factors when it comes to deciding whether a pillow is of good quality. The researchers utilized the Statistical Process Control to analyze the data gathered. For the dimensions and weight of the pillows, variable control charts were used. On the other hand, attribute control chart (p chart) was used for the fraction of nonconforming products. Most of the processes were out of control. The main causes of these are operator carelessness and lack of commitment to maintaining good quality and production machine errors. It was also found that the processes are incapable of producing the specifications set by the customers. In order to increase capability, the company must make its process averages at the center of the specification limits and reduce variability. With the completion of the study, several recommendations to improve the quality systems of the company were proposed by the group. With regards to the weight, the company should invest on a more sensitive weighing scale worth approximately PhP3000 and assign a single person to do the weighing of the fibers. For the dimensions, the group proposed that the company conduct regular tune-ups for both sewing and cutting machines. Lastly, the group recommended that the company should practice the use of Statistical Process Control. Marivel's Pillow frequently inspects for the quality of their product throughout all stages of production, but they do not analyze nor interpret their long term performance , or even measure the variability in their process.