Journal Published Online: 18 December 2020
Volume 49, Issue 5

A Modified Approach for Six Sigma Quality Assessment of Product with Multiple Characteristics in Intelligent Manufacturing Environments



Process quality and yield are always crucial determinants of a firm’s competitiveness; therefore, monitoring and assessment for process quality are vital aspects of their sustainable development. The Six Sigma quality control is based on defect rate and nonconforming units to eliminate factors that cause process defects. Thus, it has become a powerful instrument for manufacturers to achieve the quality goals of only 3.4 defects per million opportunities. However, the originated Six Sigma program is based on the 1.5σ shift in the process mean to recognize the tendency of processes to shift over the long term and achieve this goal. With the production environment of intelligent manufacturing today, manufacturers keep up to date with production performance and then monitor the distance between the process mean shift and the target value at all times. This makes it possible to adopt a more rigorous standard by decreasing in allowable shift to define the quality level in Six Sigma. For this reason, this paper proposes the redefined Six Sigma quality indexes as an assessment tool and has developed a modified approach for Six Sigma quality assessment of products with multiple characteristics. The proposed method uses more rigorous standards to analyze process quality, thereby allowing manufacturers to provide industry partners or consumers with products of higher quality, meet their needs, and even enhance their own industry competitiveness to continue progressing toward sustainability. We present a real-world example to demonstrate the practical applicability of the proposed approach.

Author Information

Chen, Kuen-Suan
Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung, Taiwan, Republic of China
Chang, Tsang-Chuan
College of Intelligence, National Taichung University of Science and Technology, Taichung, Taiwan, Republic of China
Pages: 19
Price: $25.00
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Stock #: JTE20200371
ISSN: 0090-3973
DOI: 10.1520/JTE20200371