APPLICATION OF STATISTICAL PROCESS CONTROL TOOLS IN MANUFACTURING INDUSTRIES: THE CASE OF TIKUR ABBAY SHOE FACTORY

Abstract

In the era of quality, working with specified standards is not the ultimate goal of business companies. Executing significant tasks below the standard and delivering products to customers may out the firm from the game truck. Process-out products and delivering services above quality standards, definitely satisfy all types of customers. To deliver quality products and to reach clients’need and satisfaction, improving the process is an ambiguous task of any company. In order to improve the product process, applying statistical process control tools is significant and widely used. The aim of this study is introducing statistical process control tools to the selected company, to identify, control and manage its process related problems. The application initially started after identifying common defect during proposal stage of this research. Direct observation, adaptation time to investigate how the process is going on, interviewing stake holders such as technicians, product managers and quality assurance teams were thoroughly used to apply the most related SPC tools. Primarily, Pareto chart is used to prioritize the defect types, next the cause and effect diagram applied to identify the likely causes of the selected product. From the control chat p chart is calculated and drawn to determine where the process is Cp is calculated to indicate the process capability. After data analyzed by the indicated tools, during the product process, common process problems, such as outdated machine, unused test laboratory machine due to lack of skilled lab technician and unused quality manuals and other problems has been found and frequently causing defect product. Eliminating or reducing such problems through applying the steps of SPC tools, the process may stay in the control limit, become excellent and will provide products which satisfy and excite the needs of customers. The tools also employ visualized data and help the top managers to pass numeric based decisions.