Lifetime performance evaluation model based on quick response thinking

• Autorzy: Chiou Kuo-Ching , Chen Kuen-Suan

Identyfikatory

DOI

10.17531/ein.2022.1.1

• Języki publikacji: EN

Abstrakty

EN

In practice, lifetime performance index CL has been a method commonly applied to the evaluation of quality performance. L is the upper or lower limit of the specification. The product lifetime distribution is mostly abnormal distribution. This study explored that the lifetime of commodities comes from exponential distribution. Complete data collection is the primary goal of analysis. However, the censoring type is one of the most commonly used methods due to considerations of manpower and material cost or the timeliness of product launch. This study adopted Type-II right censoring to find out the uniformly minimum variance unbiased (UMVU) estimator of the lifetime performance index CL and its probability density function. Afterward this study obtained the 100×(1-α)% confidence interval of the lifetime performance index CL as well as created the uniformly most powerful (UMP) test and the power of the test for the product lifetime performance index. Last, this study came up with a numerical example to demonstrate the suggested method as well as the application of the model.

Słowa kluczowe

EN

lifetime performance index; Type-II right censoring; UMVU estimators; UMP test

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2022
• Tom: Vol. 24, no. 1
• Strony: 1--6
• Opis fizyczny: Bibliogr. 36 poz., rys.

Twórcy

autor

Chiou Kuo-Ching

• Chaoyang University of Technology, Department of Finance, Taichung 41349, Taiwan, R. O. C.

• https://orcid.org/0000-0003-2617-5856

autor

Chen Kuen-Suan

• National Chin-Yi University of Technology, Department of Industrial Engineering and Management, Taichung 411030, Taiwan, R. O. C
• Asia University, Institute of Innovation and Circular Economy, Asia University, Taichung 41354, Taiwan,R. O. C.
• Chaoyang University of Technology, Department of Business Administration, Chaoyang University of Technology, Taichung 41349, Taiwan, R. O. C

• https://orcid.org/0000-0002-1091-6392

Bibliografia

• 1. Alsaedi BSO, Abd El-Raouf MM, Hafez EH, Almaspoor Z, Alamri OA, Alanazi K A, Khosa SK. Decision-Making for the Lifetime Performance Index. Computational Intelligence and Neuroscience 2021: 3005067, https://doi.org/10.1155/2021/3005067.
• 2. Bedbur S, Mies F. Confidence bands for exponential distribution functions under progressive type-II censoring. Journal of statistical computation and simulation 2021: 1-21, https://doi.org/10.1080/00949655.2021.1931211.
• 3. Borgoni R, Zappa D. Model-based process capability indices: The dry-etching semiconductor case study. Quality and Reliability Engineering International 2020; 36(7): 2309-2321, http://doi.org/10.1002/qre.2698.
• 4. Celik N, Guloksuz CT. A new lifetime distribution. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2017; 19 (4): 634-639, http://doi.org/10.17531/ein.2017.4.18.
• 5. Chen KS, Chiou KC, Yu CM. Lifetime performance index of electronic products. Microelectronics Reliability 2020; 113: 113941, https://doi.org/10.1016/j.microrel.2020.113941.
• 6. Chen KS, Huang CF, Chang TC. A mathematical programming model for constructing the confidence interval of process capability index Cpm in evaluating process performance: An example of five-way pipe. Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers, Series A 2017; 40(2): 126-133, https://doi.org/10.1080/02533839.2017.1294996.
• 7. Chen KS, Wang CH, Tan KH. Developing a fuzzy green supplier selection model using Six Sigma quality indices. International Journal of Production Economics 2019; 212: 1-7, https://doi.org/10.1016/j.ijpe.2019.02.005.
• 8. Dey S, Sharma VK, Anis MZ, Yadav B. Assessing lifetime performance index of Weibull distributed products using progressive type II right censored samples. International Journal of System Assurance Engineering and Management 2017; 8(2): 318-333, https://doi.org/10.1007/s13198-016-0437-z.
• 9. EL-Helbawy AA, AL-Dayian GR, Rezk HR. Bayesian approach for constant-stress accelerated life testing for Kumaraswamy Weibull distribution with censoring. Pakistan Journal of Statistics and Operation Research 2016; 12 (3): 407-428, https://doi.org/10.18187/pjsor.v12i3.1171.
• 10. Ershadi MJ, Qhanadi Taghizadeh O, Hadji Molana SM. Selection and performance estimation of green lean six sigma projects: A hybrid approach of technology readiness level, data envelopment analysis, and ANFIS. Environmental Science and Pollution Research 2021;28(23): 29394-29411, https://doi.org/10.1007/s11356-021-12595-5.
• 11. Hon CW, Wu JW, Cheng CH. Computational procedure of performance assessment of lifetime index of businesses for the pareto lifetime model with the right type II censored sample. Applied Mathematics and Computation 2007; 184(2): 336-350, https://doi.org/10.1016/j.amc.2006.05.199.
• 12. Kirkos, E. Airbnb listings’ performance: Determinants and predictive models. European Journal of Tourism Research 2022; 30: 3012.
• 13. Lee BL, Crunk SM, Khan M, Fairley WB. Prediction for a Future Number of Failures Based on Right Censored Data with Indeterminate Survival Times and Censoring Status. International Journal of Applied Science and Engineering 2018; 15(1): 47-57, https://doi.org/10.6703/IJASE.201802_15(1).047.
• 14. Lee ET. Statistical Methods for Survival Data Analysis (2nd ed). New York: John Wiley and Sons, 1992.
• 15. Lee JY, McFadden KL, Lee MK, Gowen CR. U. S. hospital culture profiles for better performance in patient safety, patient satisfaction, six sigma, and lean implementation. International Journal of Production Economics 2021; 234: 108047, https://doi.org/10.1016/j.ijpe.2021.108047.
• 16. Lee WC, Wub JW, Hong CW. Assessing the lifetime performance index of products with the exponential distribution under progressively type II right censored samples. Journal of computational and applied mathematics 2009; 231 (2): 648-656, https://doi.org/10.1016/j.cam.2009.04.018.
• 17. Lo W, Yang CM, Lai KK, Li SY, Chen CH. Developing a novel fuzzy evaluation model by one-sided specification capability indices. Mathematics 2021; 9(10): 1076, https://doi.org/10.3390/math9101076.
• 18. Martinsen K, Assuad CSA, Kito T, Matsumoto M, Reddy V, Guldbrandsen-Dahl. S. Closed loop tolerance engineering modelling and maturity assessment in a circular economy perspective. Sustainable Production, Life Cycle Engineering and Management 2021: 297-308, https://doi.org/10.1007/978-981-15-6779-7_21.
• 19. Miller RG. Survival Analysis. New York: John Wiley and Sons, 1981.
• 20. Mutlu HT, Yildiz MS. Determination of the optimal warranty policy and period from the manufacturer’s/seller’s perspective. Communications in Statistics: Simulation and Computation 2021, https://doi.org/10.1080/03610918.2021.1941110.
• 21. Niveditha A, Joghee R. Six sigma quality evaluation of life test data based on weibull distribution. International Journal of Quality and Reliability Management 2021; 38(4): 1005-1022, https://doi.org/10.1108/IJQRM-01-2020-0014.
• 22. Qayyum S, Ullah F, Al-Turjman F, Mojtahedi M. Managing smart cities through six sigma DMADICV method: A review-based conceptual framework. Sustainable Cities and Society 2021; 72: 103022, https://doi.org/10.1016/j.scs.2021.103022.
• 23. Ramadan SZ, Ramadan KZ. Bayesian simple step-stress acceleration life testing plan under progressive type-I right censoring for exponential life distribution. Modern Applied Science 2012; 6 (3): 91-99, https://doi.org/10.5539/mas.v6n3p91.
• 24. Salmasnia A, Baratian M, Ghazanfari M, Fallah-Ghadi H. Optimisation of two-dimensional warranty region under preventive maintenance over product lifetime by considering both manufacture and consumer's point of views. International Journal of Quality Engineering and Technology 2021; 8(3): 306-323, https://doi.org/10.1504/IJQET.2021.116754.
• 25. Sarpiri MN, Gandomani TJ. A case study of using the hybrid model of scrum and six sigma in software development. International Journal of Electrical and Computer Engineering 2021; 11(6): 5342-5350, https://doi.org/10.11591/ijece.v11i6.pp5342-5350.
• 26. Shen A, Guo J, Wang Z, Zhang Q. Sensitivity analysis of objective Bayesian evaluation under random right censoring and Weilbull distribution. Systems Engineering and Electronics 2017; 39(8): 1891-1897, https://doi.org/10.3969/j.issn.1001-506X.2017.08.32.
• 27. Sutagundar A, Sangulagi P. Fog computing based information classification in sensor cloud-agent approach. Expert Systems with Applications 2021; 182: 115232, https://doi.org/10.1016/j.eswa.2021.115232.
• 28. Tong LI, Chen KS, Chen HT. Statistical testing for assessing the performance of lifetime index of electronic components with exponential distribution. International Journal of Quality & Reliability Management 2002; 19(7): 812-824, https://doi.org/10.1108/02656710210434757.
• 29. Wang CC, Chen KS, Wang CH, Chang PH. Application of 6-sigma design system to developing an improvement model for multi-process multi-characteristic product quality. Proceedings of the Institution of Mechanical Engineers Part B – Journal of Engineering Manufacture 2011; 225(7): 1205-1216, https://doi.org/101177/2041297510393464.
• 30. Wang FK, Bizuneh B, Cheng XB. New control charts for monitoring the Weibull percentiles under complete data and Type‐II censoring. Quality and Reliability Engineering International 2018; 34 (3): 403-416, https://doi.org/10.1002/qre.2261.
• 31. Wang S, Chiang JY, Tsai TR, Qin Y. Robust process capability indices and statistical inference based on model selection. Computers and Industrial Engineering 2021; 156: 107265, https://doi.org/10.1016/j.cie.2021.107265.
• 32. Wu CC, Chen LC, Chen YJ. Statistical Inferences for the Lifetime Performance Index of the Products with the Gompertz Distribution under Censored Samples. Communications in Statistics: Simulation and Computation 2016, 45(4): 1318-1336, https://doi.org/10.1080/03610918.2013.827710.
• 33. Wu JW, Hong CW. The assessment of quality performance of lifetime index of exponential products with fuzzy data under progressively type ii right censored sample. ICIC Express Letters, Part B: Applications 2018; 9(11): 1101-1107, https://doi.org/10.24507/icicelb.09.11.1101.
• 34. Yu CM, Chen KS, Lai KK, Hsu CH. Fuzzy Supplier Selection Method Based on Smaller-The-Better Quality Characteristic. Applied Science 2020; 10: 3635, https://doi.org/10.3390/app10113635.
• 35. Yu CM, Lai KK, Chen KS, Chang TC. Process-quality evaluation for wire bonding with multiple gold wires. IEEE Access 2020; 8: 106075-106082, https://doi.org/10.1109/ACCESS.2020.2998463.
• 36. Zhu T, Yan Z, Peng X A. Weibull failure model to the study of the hierarchical Bayesian reliability. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2016, 18 (4): 501-506, http://dx.doi.org/10.17531/ein.2016.4.4.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).