QUALITY IMPROVEMENT USING STATISTICAL PROCESS CONTROL TOOLS IN GLASS BOTTLES MANUFACTURING COMPANY
Journal Title: International Journal for Quality Research - Year 2013, Vol 7, Issue 1
Abstract
In order to survive in a competitive market, improving quality and productivity of product or process is a must for any company. This study is about to apply the statistical process control (SPC) tools in the production processing line and on final product in order to reduce defects by identifying where the highest waste is occur at and to give suggestion for improvement. The approach used in this study is direct observation, thorough examination of production process lines, brain storming session, fishbone diagram, and information has been collected from potential customers and company's workers through interview and questionnaire, Pareto chart/analysis and control chart (p-chart) was constructed. It has been found that the company has many problems; specifically there is high rejection or waste in the production processing line. The highest waste occurs in melting process line which causes loss due to trickle and in the forming process line which causes loss due to defective product rejection. The vital few problems were identified, it was found that the blisters, double seam, stone, pressure failure and overweight are the vital few problems. The principal aim of the study is to create awareness to quality team how to use SPC tools in the problem analysis, especially to train quality team on how to held an effective brainstorming session, and exploit these data in cause-and-effect diagram construction, Pareto analysis and control chart construction. The major causes of non-conformities and root causes of the quality problems were specified, and possible remedies were proposed. Although the company has many constraints to implement all suggestion for improvement within short period of time, the company recognized that the suggestion will provide significant productivity improvement in the long run.
Authors and Affiliations
Yonatan Mengesha Awaj, Ajit Pal Singh, Wassihun Yimer Amedie
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