Six Sigma model with implement SAPF to enhance power quality and product quality at induction heat treatment process

This study proposes a model to integrate the Multi-Attribute Decision-Making (MADM) method into the Analysis phase of the Six Sigma (DMAIC) method to improve product quality and optimize processing conditions during high-frequency quenching heat treatment. One of the breakthroughs of the study is the combination of Industry 4.0 technology and the implementation of Shunt Active Power Filter (SAPF) to improve power quality, reduce harmonic distortion (THD), ensure product hardness of 58-62 HRC, and thermal permeability of 1.8-2.2 mm according to standards. Previously, many studies only focused on improving the heat treatment process but did not fully integrate MADM, Six Sigma, and Industry 4.0 technology, nor did any study consider the combination of SAPF to control power quality during high-frequency quenching. Another gap is the lack of quantitative assessment of operator satisfaction after improvement using PLS-SEM. The study applied the Six Sigma DMAIC model combined with MADM to analyze and rank factors affecting product quality. In the improvement phase, the Taguchi method was used to optimize processing conditions, minimizing errors in the production process. At the same time, Industry 4.0 technology and RFID systems were integrated to control production conditions in real time, ensuring the accuracy and reliability of the process. Power quality was improved thanks to the implementation of SAPF, helping to control harmonic distortion (THD) below 5% according to the IEEE 519:2022 standard, minimizing the negative impact of voltage on the heat treatment process. In addition, the study also applied PLS-SEM to measure operator satisfaction after implementing the improved system. The research results show that the rate of substandard products has decreased sharply from 90 to 1%, ensuring hardness of 58-62 HRC and thermal permeability of 1.8-2.2 mm. Power quality is better controlled, with the THD value reduced from more than 34% to less than 5%, meeting the IEEE 519:2022 standard. As a result, production costs are optimized, helping to minimize the waste of raw materials and energy. After implementing the improved system, operators' satisfaction levels have also increased significantly, reflected in the PLS-SEM measurement indicators. More importantly, this research model is not only effectively applied in the precision engineering industry but also has the potential to be expanded to many other industries, especially small and medium-sized manufacturing enterprises, helping them to increase productivity and improve product quality in the context of Industry 4.0.