Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Nguyen, Trung Thanh; Duong, Quoc-Dung; Mia, Mozammel

doi:10.1177/09544054211001014

Cited by 16 publications

(10 citation statements)

References 33 publications

(28 reference statements)

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“…The carbon emissions of each reworked or scrapped product are multiplied by that percentage so that the number of saved carbon emissions can be converted and calculated. In addition to lessening carbon emissions, this process can lower the cost of loss caused by reworking or scrappage and increase the value of the product [23,28].…”

Section: Discussionmentioning

confidence: 99%

“…Improving process quality can decrease the ratios of reworking and scrappage during the process of production, as well as reduce the frequency of maintenance or replacement after purchase. Consequently, not only does this lessen the cost of rework, scrap, and maintenance, as well as the harm caused by environmental pollution, but it also contributes to the sustainability of enterprises and that of the environment [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics

Chen

Huang

et al. 2022

Sustainability

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The concept of Industry 4.0 was first proposed by the German government in 2011. As the Internet of Things (IoT) becomes more prevalent and big data analysis technology becomes more mature, it is beneficial for the manufacturing industry to integrate and apply the related technologies to pursue the goal of smart manufacturing. Taiwan’s machine tool industry and downstream machine-tool purchasers, who are scattered around the world, have formed a machine-tool industry chain. To help the machine-tool industry and the suppliers of important components boost their process capabilities, ensure the final product quality of machine tools and improve the process capabilities of the entire industry chain, this study used radar charts to present the statistical testing information of the process capabilities of all quality characteristics, so that managers could have more complete information when evaluating and selecting appropriate suppliers. As noted in many studies, improving product quality and availability can reduce not only the rate of reworking and scrappage during production but also the frequency of maintenance or replacement of components after purchase. As a result, the loss of costs caused by reworking, scrappage, and maintenance can be diminished, carbon emissions can be lowered, and environmental pollution can be reduced as well, which will help to achieve sustainable operation in the entire machine tool industry chain.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics

Chen

Huang

et al. 2022

Sustainability

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“…Therefore, many well-known sports brands are proactively developing new products highlighting high functionality, environmental friendliness, and pleasing appearance. In addition, plenty of research has also indicated that good process quality can not only improve product yield and product value but also lower rates of rework and scrap [1][2][3]. Since enterprises are confronting the regulatory pressure of green environmental protection and competition from external rivals, they need to contemplate how to boost the quality of newly developed products, increase product value, and minimize Mathematics 2024, 12, 1446 2 of 11 rates of both rework and scrap to reach the goals of conserving energy and reducing waste.…”

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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“…Some studies have pointed out that improving the process quality of the product can reduce an increase in the cost expenditure caused by the reworks of defective products as well as can lower energy loss and carbon emissions [8][9][10][11]. According to the concept of Taguchi loss function, when the process quality of components for machining machines is not good and the size of the processed product deviates too far from the target value, the failure rate of the product will rise after the product is sold.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Evaluation and Improvement Decision-Making Model for Machining Operation Performance

Chen

Tsaur

et al. 2023

Applied Sciences

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Taiwan is a major exporter and producer of machinery and machine tools in the world. There are at least hundreds of components for various machining machines. According to the concept of Taguchi loss function, when the process quality of the spare parts of machining machines is not good, the failure rate will increase after the product is sold, resulting in an increase in maintenance costs and carbon emissions. As the environment of the Internet of Things (IoT) becomes more common and mature, it is beneficial for manufacturers of machining machines to collect relevant information about process data from outsourcers, suppliers, and machining machine factories. Effective data analysis and application can help the machining machine industry move towards smart manufacturing and management, which can greatly reduce the average number of failures per unit time for all sold machines. Therefore, this paper developed a practical evaluation and improvement decision-making model for the machining operation performance to help machining machine manufacturers find out the components that often fail and improve them, so as to reduce the total loss caused by machine failures. This paper first defined the machining operation performance index for the machining machines and discussed the characteristics of this operation performance index. Subsequently, the confidence interval of the index was deduced, a fuzzy evaluation model based on this confidence interval was proposed, and decision-making rules regarding whether to make any improvement was established. The fuzzy evaluation and improvement decision-making model for the operation performance of machining machines proposed in this paper will contribute to various tool industries to boost their process quality, reduce costs, and lower carbon emissions, in order to achieve sustainable management of enterprises and the environment.

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Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Cited by 16 publications

References 33 publications

Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics

Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics

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

Fuzzy Evaluation and Improvement Decision-Making Model for Machining Operation Performance

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