Enhancing manufacturing efficiency through a hybrid Six sigma approach: A case study in automobile mechanical manufacturing
Well-optimized operating conditions of the production process directly impact improving product quality. Electric cylinder equipment operates with high accuracy when supplied with a quality power source with a THD value of less than 5%. This research paper proposes a hybrid Six Sigma based on the fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, the Taguchi method, and direct measurement of power quality. Firstly, the fuzzy TOPSIS method is used in the define phase of Six Sigma to analyze and make decisions to select the core problem point that causes product quality errors. Second, the Taguchi method is applied to the improvement phase to optimize machining conditions and establish and directly measure power quality using the Shunt Adaptive Power Filter (SAPF) device. The research results are that the roughness defect rate has decreased from 100% to zero defects, the lapping process is disposed of, increase in the multivariable process capacity from MCpk0.06 to MCpk2.45, and the profit following continuous improvement is $5580 per year. The THD value of the power source is always measured and controlled to a value below 5%. This Six Sigma hybrid applied research model is considered simple and can be used by many different production and business companies to improve production and business results.
Authors
- Minh Ly Duc (ORCID: https://orcid.org/0000-0003-0200-7153)
- Nguyen Quang Sang (ORCID: https://orcid.org/0000-0003-0239-5264)
- Do Ngoc Hien
Institutions
- Vietnam National University Ho Chi Minh City (VN)
- Ho Chi Minh City University of Education (VN)
- Van Lang University (VN)
- Ho Chi Minh City University of Technology (VN)
Publication Details
- Journal
- Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1177/09544062251378846
- Primary Topic
- Advanced Machining and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00