Application of statistical quality control technique: Applications in the silicone manufacturing industry
Nowadays, silicone rubber material is used for the manufacturing of a wide range of automotive applications, electrical and electronic applications, lighting applications, medical and healthcare applications, cookware, etc. leading to rapid growth in the silicone rubber subsector. Quality-related problems were the major obstacle that leads to customer complaints. Therefore, it is important to review the quality control procedures for the silicone rubber products. In this article, the objectives are mainly focused on the study of the process stability in the ABC Industrial Sdn. Bhd. using statistical quality control tools, the analysis of the most frequently occurring types of defects and the identification of the possible causes of the defects. The result of the studies showed that both filling and packing processes in ABC Industrial Sdn. Bhd. are statistically control. Secondly, the most frequently occurring types of defects identified in both filling and packing process in ABC Industrial Sdn. Bhd. are folding issue at the end of tube, followed by inconsistent filling weight, leaking, seal too tight, mixed colour and wrong tube issues. The possible causes consisted of new operator, careless, lack of focus during work, supplier non-conformance, defective raw material, lack of expert to setup machines, wear and tear, aging of machines, poor working environment, lack of supervision and training, and unclear standard operating procedures (SOPs). Results are beneficial and useful for silicone rubber manufacturing sector for continuous improvement by applying statistical quality control techniques.
Authors
- Jocelyn Qi-Min Teo (ORCID: https://orcid.org/0000-0003-2508-3941)
- Mohd Rashid Ab Hamid (ORCID: https://orcid.org/0000-0002-6297-9483)
Institutions
- Universiti Malaysia Pahang Al-Sultan Abdullah (MY)
Publication Details
- Journal
- Data Analytics and Applied Mathematics (DAAM)
- Published
- 2024-09-30
- DOI
- https://doi.org/10.15282/daam.v5i2.12999
- Primary Topic
- Advanced Statistical Process Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00