Lifetime performance evaluation model based on quick response thinking

Chiou, Kuo-Ching; Chen, Kuen‐Suan

doi:10.17531/ein.2022.1.1

Cited by 11 publications

(10 citation statements)

References 36 publications

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“…Lee and Seo [17] obtained the estimates for the Gompertz parameters under progressive (Pr) censored sample. Similar studies were considered by Ferreira and Silva [14] for Weibull distribution when right CS is available, Starling et al [23] for improving Weibull distribution using generalized type-I CS, Chiou and Chen [8] for lifetime performance index under type-II CS. Also, for accelerated life-time reliability model (ALTM), Wang et al [24] and Asadi et al [3] considered estimation methods under PrC and adaptive PrC respectively.…”

Section: Introductionmentioning

confidence: 54%

Reliability Estimation of Burr Type III Distribution under Improved Adaptive Progressive Censoring with Application to Surface Coating

Asadi¹,

Panahi²,

Anwar³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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The stress-strength reliability (SSRe) model is widely investigated in reliability engineering to determine the probability of the strength component overcomes the stress imposed on it. In this paper, we studied the estimation of SSRe model based on the Burr III distribution under the improved adaptive progressive type-II censoring scheme (IAPrgCS-II). Estimation methods of the SSRe parameters are developed using frequentist and Bayesian approaches. The point and interval estimations using the maximum likelihood are considered to estimate the parameters. Two approximations are applied to compute the Bayes estimates. A simulation study is conducted for the comparison of the methods of estimation. Also, parallel to the development of reliability studies, it is necessary to study its application in different sciences such as engineering. Therefore, the droplet splashing (DrS) data under two wettabilities are proposed as an application of the considered SSRe model and methods. The results show us that the reliability model can be used to amend the quality of coatings.

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Section: Introductionmentioning

confidence: 54%

Reliability Estimation of Burr Type III Distribution under Improved Adaptive Progressive Censoring with Application to Surface Coating

Asadi¹,

Panahi²,

Anwar³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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“…Then, we derive the 100(1 − α)% confidence interval of the machining operation performance index θ OPI . Based on Equations ( 9) and (10), random variable W is distributed as Gamma(n, 1). Therefore, we have…”

Section: Fuzzy Evaluation and Improvement Decision-making Modelmentioning

confidence: 99%

“…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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“…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%

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

Chen

Huang

et al. 2022

Sustainability

Self Cite

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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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Lifetime performance evaluation model based on quick response thinking

Cited by 11 publications

References 36 publications

Reliability Estimation of Burr Type III Distribution under Improved Adaptive Progressive Censoring with Application to Surface Coating

Reliability Estimation of Burr Type III Distribution under Improved Adaptive Progressive Censoring with Application to Surface Coating

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

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

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