Building a C control chart – A novel and practical method for practitioners

Sanchez-Marquez, Rafael; Vivas, José Manuel Jabaloyes

doi:10.1016/j.cie.2021.107428

Cited by 17 publications

(7 citation statements)

References 31 publications

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“…Additionally, these three important quality characteristics all fall into the category of the large-the-better (LTB) quality characteristics. Borgoni et al [4] and Sanchez-Marquez et al [5] have demonstrated that the process capability index is a convenient and effective tool for evaluating product quality. As noted by Wang et al [6], many statisticians and quality engineers have invested in doing research on process capability indices to raise products' process quality.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Evaluation Model for Products with Multifunctional Quality Characteristics: Case Study on Eco-Friendly Yarn

Chen,

Huang,

Chiou

et al. 2024

Mathematics

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Numerous advanced industrial countries emphasize green environmental protection alongside athletic healthcare. Many world-renowned sports brands are actively developing highly functional, environmentally friendly, and aesthetically pleasing products. For example, in the production of sports shoes, the eco-friendly yarn process is one of the important processes. This process involves multiple crucial larger-the-better quality characteristics closely tied to the functionality of sports shoes. Facing green environmental regulations and external competitors, it is evidently an imperative issue for enterprises to consider how to improve the quality of newly developed products, increase product value, and lower rates of both rework and scrap to accomplish the goals of saving energy and minimizing waste. Aiming to solve this problem, this study proposed a fuzzy evaluation model for products with multifunctional quality characteristics to assist the sporting goods manufacturing industry in evaluating whether all functional quality characteristics of its products meet the required quality level. This study first utilized the larger-the-better Six Sigma quality index concerning environmental protection for evaluation and then proposed product evaluation indicators for the eco-friendly yarn. Since the parameters of these indicators have not yet been determined, sample data need to be used for estimation. Enterprises require rapid response, so that the sample size is relatively small. Sampling error will increase the risk of misjudgment. Therefore, taking suggestions from previous studies, this study constructed the fuzzy evaluation model based on confidence intervals of quality indicators for the eco-friendly yarn. This method incorporated previous experience with data, thereby enhancing assessment accuracy.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Evaluation Model for Products with Multifunctional Quality Characteristics: Case Study on Eco-Friendly Yarn

Chen,

Huang,

Chiou

et al. 2024

Mathematics

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“…Indeed, process capability indices are common tools utilized by companies to gauge process quality. They can be offered to internal process engineers to assess process quality as well as viewed as communication tools for sales departments in external companies [4][5][6][7]. The two most widely used capability indices, C P and C PK , as Kane [8] suggested, are displayed below:…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Testing Model Built on Confidence Interval of Process Capability Index CPMK

Lo,

Huang,

Chen

et al. 2024

Axioms

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A variety of process capability indices are applied to the quantitative measurement of the potential and performance of processes in manufacturing. As it is easy to understand the formulae of these indices, this method is easy to apply. Furthermore, a process capability index is frequently utilized by a manufacturer to gauge the quality of a process. This index can be utilized by not only an internal process engineer to assess the quality of the process but also as a communication tool for an external sales department. When the manufacturing process deviates from the target value T, the process capability index CPMK can be quickly detected, which is conducive to the promotion of smart manufacturing. Therefore, this study applied the index CPMK as an evaluation tool for process quality. As noted by some studies, process capability indices have unknown parameters and therefore must be estimated from sample data. Additionally, numerous studies have addressed that it is essential for companies to establish a rapid response mechanism, as they wish to make decisions quickly when using a small sample size. Considering the small sample size, this study proposed a 100 (1 − α)% confidence interval for the process capability index CPMK based on suggestions from previous studies. Subsequently, this study built a fuzzy testing model on the 100 (1 − α)% confidence interval for the process capability index CPMK. This fuzzy testing model can help enterprises make decisions rapidly with a small sample size, meeting their expectation of having a rapid response mechanism.

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“…Process Capability Indices (PCIs) are measurements frequently adopted by the industry for process quality evaluation [1][2][3]. They are not just communication tools between sales and customers; for process engineers, they are useful means of evaluating, analyzing, and improving processes [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Monitoring, Evaluation, and Improvement Model for Process Precision and Accuracy

Tsai,

Chiou,

Chen

et al. 2023

Applied Sciences

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Process Capability Indices (PCIs) are devices widely used in the industry to evaluate process quality. The commonly used process capability indices all contain accuracy indices and precision indices. As the accuracy index is closer to zero, the process accuracy is higher. The precision index mainly represents the extent of process variation. As the value is smaller, the process variation is smaller, that is, the precision is higher. In fact, process capability indices are the functions of accuracy indices and precision indices. Obviously, as long as accuracy indices and precision indices are controlled, the process capability indices can be controlled as well. Therefore, this study first derived accuracy and precision control charts to observe not only process accuracy but also process precision. Then, this study adopted in-control data to acquire a 100 (1 − α)% confidence region of an accuracy index and a precision index, with which statistical tests were performed. Subsequently, according to the definition of the six sigma quality level, both indices were examined. Furthermore, based on the testing results, suggestions for process improvement were proposed, including correcting the direction of process deviation and deciding whether to reduce process variation. Finally, this study demonstrated the applicability of the proposed model using an empirical example.

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Building a C control chart – A novel and practical method for practitioners

Cited by 17 publications

References 31 publications

Fuzzy Evaluation Model for Products with Multifunctional Quality Characteristics: Case Study on Eco-Friendly Yarn

Fuzzy Evaluation Model for Products with Multifunctional Quality Characteristics: Case Study on Eco-Friendly Yarn

Fuzzy Testing Model Built on Confidence Interval of Process Capability Index CPMK

Monitoring, Evaluation, and Improvement Model for Process Precision and Accuracy

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