The construction and application of Six Sigma quality indices

Chen, Kuen‐Suan; Chen, Hsi-Tien; Chang, Tsang-Chuan

doi:10.1080/00207543.2016.1246763

Cited by 65 publications

(40 citation statements)

References 62 publications

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“…Due to the important role played in manufacturing systems, IJPR has dedicated considerable attention to Six Sigma, and a significant branch of research dealing with tools and methods to support Six Sigma activities can be identified. Among them, work on process capability indexes for the determination of process quality levels has aimed at providing valuable references by which to guide efforts targeted at improvement (Chen, Chen, and Chang 2017). Wu, Jiao, and He (2009) have worked on innovating conventional statistical process control methods for quality control, demonstrating the potential in decision support, not only for manufacturing systems, but also for non-manufacturing contexts, such as supply chain management, office administration and the health care industry.…”

Section: Six Sigma Tools and Methods Developmentmentioning

confidence: 99%

How IJPR has addressed ‘lean’: a literature review using bibliometric tools

Ciano

Pozzi

Rossi

et al. 2019

International Journal of Production Research

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The aim of this study is to investigate the body of literature on lean published by the International Journal of Production Research (IJPR), which has been interested in the subject since its dawn. This review adopted a dynamic and quantitative bibliometric method composed of the keywords co-occurrence network and keywords burst detection. The analyses performed on keywords co-occurrence networks highlighted how research in IJPR has addressed research on lean over time and allowed a comparison with the consolidated research streams in literature. The burst detection completed the analysis highlighting the trends and most recent research areas characterising IJPR publications. The outcomes of this study reflected the evergreen relevance of lean; indeed, the latest research trajectories identified in IJPR stressed its link with the increasingly topical issues concerning industry 4.0, sustainability and remanufacturing. The analysis recognised in 'lean Six Sigma', and specifically in its support to the service sector, an under-considered topic, hence a scope that offers room for further study, in accordance with IJPR objectives.

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Section: Six Sigma Tools and Methods Developmentmentioning

confidence: 99%

How IJPR has addressed ‘lean’: a literature review using bibliometric tools

Ciano

Pozzi

Rossi

et al. 2019

International Journal of Production Research

View full text Add to dashboard Cite

show abstract

“…This study is based on six-sigma DMAIC quality methodology which provides information about the decision-making power for particular type of problem and the most significant tool for improvement of that type of problem in which data used must come from a stable process (under statistical control: Chen et al 2017).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Six-sigma application in tire-manufacturing company: a case study

et al. 2017

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Globalization, advancement of technologies, and increment in the demand of the customer change the way of doing business in the companies. To overcome these barriers, the six-sigma define-measure-analyze-improvecontrol (DMAIC) method is most popular and useful. This method helps to trim down the wastes and generating the potential ways of improvement in the process as well as service industries. In the current research, the DMAIC method was used for decreasing the process variations of bead splice causing wastage of material. This six-sigma DMAIC research was initiated by problem identification through voice of customer in the define step. The subsequent step constitutes of gathering the specification data of existing tire bead. This step was followed by the analysis and improvement steps, where the six-sigma quality tools such as cause-effect diagram, statistical process control, and substantial analysis of existing system were implemented for root cause identification and reduction in process variation. The process control charts were used for systematic observation and control the process. Utilizing DMAIC methodology, the standard deviation was decreased from 2.17 to 1.69. The process capability index (C p ) value was enhanced from 1.65 to 2.95 and the process performance capability index (C pk ) value was enhanced from 0.94 to 2.66. A DMAIC methodology was established that can play a key role for reducing defects in the tiremanufacturing process in India.

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“…Apparently, the SSQIs proposed by Chen et at. [11] can be seen as the function of accuracy index and precision index; therefore, they can adequately display the causes of poor process quality (i.e., insufficient accuracy or insufficient precision) to determine the factors of process performance. Based on this, the indices can be re-defined as the following:…”

Section: Manufacturing Process Quality Evaluation Indexmentioning

confidence: 99%

“…Only when all quality characteristics meet the required level can the product be regarded as satisfactory. The manufacturing process performance evaluation chart proposed by Chen et al [11] can be used to simultaneously evaluate nominal-the-best, the-larger-the-better, and the-smaller-the-better quality characteristics. δ is used as the x-coordinate and γ is used as the y-coordinate to analyze whether the accuracy and precision of process quality characteristics meet the required level.…”

Section: Construction Of Evaluation Model Of Manufacturing Process Qumentioning

confidence: 99%

“…This facilitates the implementation of manufacturing process analysis and improvements by quality control personnel. Based on Chen et al [11], this paper adapts their proposition of Six Sigma Quality Indices (SSQIs) containing LTB, STB, and NTB and uses it as the evaluation tool. By virtue of this, quality control personnel can implement their manufacturing 3 of 15 process analysis and improvement with relative ease.…”

Section: Introductionmentioning

confidence: 99%

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A Model for Evaluating the Performance of the Bearing Manufacturing Process

Chen

Hsu

et al. 2019

Applied Sciences

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Reliability and product process quality are essential in meeting market demand and enhancing competitiveness in the machine tool industry. In addition, manufacturing time performance is also one of the important indices. Therefore, this paper focuses on process quality and manufacturing time and defines a manufacturing time performance index to feedback the acceptance rate of the manufacturing time. The process performance evaluation chart delineated the observations of variations in various workstations, and, hence, in controlling the stability of the work process. The Six Sigma quality indices are constructed by the process accuracy indices and precision indices are represented by X-axis and Y-axis respectively. The process quality evaluation chart evaluates the level of the process quality, as well as proposes the direction of improvement. The manufacturing time performance—Z-axis is used to assess whether the manufacturing time performance meets the requirements. The process performance evaluation chart constructed by this paper makes it easier for researchers to observe which workstations have a process variation in the process, to control the stability of the process effectively, to provide the improvement reference for staff on the scene and to enhance the competitiveness of the industry.

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The construction and application of Six Sigma quality indices

Cited by 65 publications

References 62 publications

How IJPR has addressed ‘lean’: a literature review using bibliometric tools

How IJPR has addressed ‘lean’: a literature review using bibliometric tools

Six-sigma application in tire-manufacturing company: a case study

A Model for Evaluating the Performance of the Bearing Manufacturing Process

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