Robust parameter design for constrained randomization lifetime improvement experiments
Several process parameters affect product reliability. Traditional reliability improvement methods primarily focus on maximizing product lifetime, often overlooking the variation in product lifetime. Manufacturers, however, aim to produce products with minimal variations in their performance. Robust...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-03-01
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| Series: | Journal of Management Science and Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096232024000593 |
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| author | Shanshan Lv Yichen Zhao Sen Li Guodong Wang Xueqing Wang |
| author_facet | Shanshan Lv Yichen Zhao Sen Li Guodong Wang Xueqing Wang |
| author_sort | Shanshan Lv |
| collection | DOAJ |
| description | Several process parameters affect product reliability. Traditional reliability improvement methods primarily focus on maximizing product lifetime, often overlooking the variation in product lifetime. Manufacturers, however, aim to produce products with minimal variations in their performance. Robust parameter design offers an effective strategy to help manufacturers enhance product reliability while reducing process variations. In practice, reliability experiments frequently involve constrained randomization due to the selection of specific experimental protocols. This study proposes a framework to achieve robust product reliability under a constrained randomization experiment. To consider random effects, we develop a Bayesian method-based Weibull non-linear mixed model for the lifetime response. Important factors are identified according to Bayesian posterior credible intervals. Subsequently, we propose an integrated multi-objective optimization model to determine the optimal factor levels. This model simultaneously considers minimizing the total costs of the manufacturer, maximizing the product lifetime, and minimizing the lifetime variance. An industrial thermostat experiment is conducted to validate the proposed method. Compared to existing approaches, the proposed method demonstrates superior performance in reducing variance and total cost, particularly for long warranty periods. Finally, we discuss the practical implications of the optimal solutions for manufacturers, finding that variations remain tolerable within a certain range. |
| format | Article |
| id | doaj-art-c96e50a143f947319cebcefbe0cca3c6 |
| institution | Kabale University |
| issn | 2096-2320 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Management Science and Engineering |
| spelling | doaj-art-c96e50a143f947319cebcefbe0cca3c62025-02-08T05:00:09ZengKeAi Communications Co., Ltd.Journal of Management Science and Engineering2096-23202025-03-01101126141Robust parameter design for constrained randomization lifetime improvement experimentsShanshan Lv0Yichen Zhao1Sen Li2Guodong Wang3Xueqing Wang4School of Economics and Management, Hebei University of Technology, Tianjin, 300401, ChinaSchool of Economics and Management, Hebei University of Technology, Tianjin, 300401, ChinaSchool of Economics and Management, Hebei University of Technology, Tianjin, 300401, ChinaDepartment of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou, 450015, ChinaSchool of Management, Tianjin University of Technology, Tianjin, 300384, China; Corresponding author.Several process parameters affect product reliability. Traditional reliability improvement methods primarily focus on maximizing product lifetime, often overlooking the variation in product lifetime. Manufacturers, however, aim to produce products with minimal variations in their performance. Robust parameter design offers an effective strategy to help manufacturers enhance product reliability while reducing process variations. In practice, reliability experiments frequently involve constrained randomization due to the selection of specific experimental protocols. This study proposes a framework to achieve robust product reliability under a constrained randomization experiment. To consider random effects, we develop a Bayesian method-based Weibull non-linear mixed model for the lifetime response. Important factors are identified according to Bayesian posterior credible intervals. Subsequently, we propose an integrated multi-objective optimization model to determine the optimal factor levels. This model simultaneously considers minimizing the total costs of the manufacturer, maximizing the product lifetime, and minimizing the lifetime variance. An industrial thermostat experiment is conducted to validate the proposed method. Compared to existing approaches, the proposed method demonstrates superior performance in reducing variance and total cost, particularly for long warranty periods. Finally, we discuss the practical implications of the optimal solutions for manufacturers, finding that variations remain tolerable within a certain range.http://www.sciencedirect.com/science/article/pii/S2096232024000593Robust parameter designRandom effectsReliability improvementBayesian methodologyThe cost of the manufacturer |
| spellingShingle | Shanshan Lv Yichen Zhao Sen Li Guodong Wang Xueqing Wang Robust parameter design for constrained randomization lifetime improvement experiments Journal of Management Science and Engineering Robust parameter design Random effects Reliability improvement Bayesian methodology The cost of the manufacturer |
| title | Robust parameter design for constrained randomization lifetime improvement experiments |
| title_full | Robust parameter design for constrained randomization lifetime improvement experiments |
| title_fullStr | Robust parameter design for constrained randomization lifetime improvement experiments |
| title_full_unstemmed | Robust parameter design for constrained randomization lifetime improvement experiments |
| title_short | Robust parameter design for constrained randomization lifetime improvement experiments |
| title_sort | robust parameter design for constrained randomization lifetime improvement experiments |
| topic | Robust parameter design Random effects Reliability improvement Bayesian methodology The cost of the manufacturer |
| url | http://www.sciencedirect.com/science/article/pii/S2096232024000593 |
| work_keys_str_mv | AT shanshanlv robustparameterdesignforconstrainedrandomizationlifetimeimprovementexperiments AT yichenzhao robustparameterdesignforconstrainedrandomizationlifetimeimprovementexperiments AT senli robustparameterdesignforconstrainedrandomizationlifetimeimprovementexperiments AT guodongwang robustparameterdesignforconstrainedrandomizationlifetimeimprovementexperiments AT xueqingwang robustparameterdesignforconstrainedrandomizationlifetimeimprovementexperiments |