{"title":"基于模糊MCDM技术的双相aln涂层MDC-K工具钢磨损参数优化","authors":"Sunil Kumar, S. Maity, Lokeswar Patnaik","doi":"10.31181/110722105k","DOIUrl":null,"url":null,"abstract":": The present work evaluates the effects of different tribological process parameters on the measured responses such as hardness, coefficient of friction, surface roughness, wear mass loss and wear depth of duplex-TiAlN coated MDC-K tool steel material. The considered tribological process parameters are load, sliding velocity, and sliding distance. A full factorial design with 27 experimental runs is employed and based on the response values, an optimal combination of the tribological process parameters is subsequently determined. Different multi-objective optimization techniques, like overall evaluation criteria and fuzzy-based multi-criteria decision-making methods (fuzzy evaluation based on distance from the average solution, fuzzy technique for order of preference by similarity to ideal solution, and fuzzy complex proportional assessment) are utilized to identify the optimal intermixes of the considered tribological process parameters. Sensitivity analysis with respect to changing weights of the responses is performed to validate the derived rankings of the trials, whereas the results of analysis of variance revealed the most significant parameters were influencing the responses. In addition to this, two different published problems related to optimization of wear parameters were solved using the proposed method to check its capability","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Optimization of Wear Parameters for Duplex-TiAlN Coated MDC-K Tool Steel Using Fuzzy MCDM Techniques\",\"authors\":\"Sunil Kumar, S. Maity, Lokeswar Patnaik\",\"doi\":\"10.31181/110722105k\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": The present work evaluates the effects of different tribological process parameters on the measured responses such as hardness, coefficient of friction, surface roughness, wear mass loss and wear depth of duplex-TiAlN coated MDC-K tool steel material. The considered tribological process parameters are load, sliding velocity, and sliding distance. A full factorial design with 27 experimental runs is employed and based on the response values, an optimal combination of the tribological process parameters is subsequently determined. Different multi-objective optimization techniques, like overall evaluation criteria and fuzzy-based multi-criteria decision-making methods (fuzzy evaluation based on distance from the average solution, fuzzy technique for order of preference by similarity to ideal solution, and fuzzy complex proportional assessment) are utilized to identify the optimal intermixes of the considered tribological process parameters. Sensitivity analysis with respect to changing weights of the responses is performed to validate the derived rankings of the trials, whereas the results of analysis of variance revealed the most significant parameters were influencing the responses. In addition to this, two different published problems related to optimization of wear parameters were solved using the proposed method to check its capability\",\"PeriodicalId\":36055,\"journal\":{\"name\":\"Operational Research in Engineering Sciences: Theory and Applications\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operational Research in Engineering Sciences: Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31181/110722105k\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operational Research in Engineering Sciences: Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31181/110722105k","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
Optimization of Wear Parameters for Duplex-TiAlN Coated MDC-K Tool Steel Using Fuzzy MCDM Techniques
: The present work evaluates the effects of different tribological process parameters on the measured responses such as hardness, coefficient of friction, surface roughness, wear mass loss and wear depth of duplex-TiAlN coated MDC-K tool steel material. The considered tribological process parameters are load, sliding velocity, and sliding distance. A full factorial design with 27 experimental runs is employed and based on the response values, an optimal combination of the tribological process parameters is subsequently determined. Different multi-objective optimization techniques, like overall evaluation criteria and fuzzy-based multi-criteria decision-making methods (fuzzy evaluation based on distance from the average solution, fuzzy technique for order of preference by similarity to ideal solution, and fuzzy complex proportional assessment) are utilized to identify the optimal intermixes of the considered tribological process parameters. Sensitivity analysis with respect to changing weights of the responses is performed to validate the derived rankings of the trials, whereas the results of analysis of variance revealed the most significant parameters were influencing the responses. In addition to this, two different published problems related to optimization of wear parameters were solved using the proposed method to check its capability