{"title":"制造系统精益属性间相互关系的评价方法:以精益企业为例","authors":"S. Srinath, U. Dharmapriya","doi":"10.1109/MERCON.2015.7112348","DOIUrl":null,"url":null,"abstract":"Lean philosophy has received more emphasize during recent times due to its robust features which facilitate productive manufacturing environments in companies regardless of the type of industry. However, enormous approaches taken to implement lean manufacturing systems inside factories, have failed to achieve desired objectives. This is mainly due to the focus on individual lean attributes rather than considering their collective impact on a system. This paper suggested an approach to measure correlations among lean attributes using their degrees of implementation. These correlations will help organizations to identify lean attributes which are interrelated. The quest is how to measure the degree to which each lean attribute has been implemented within the organization. Different companies have varying levels of lean implementations. Therefore identifying the leanness requires the organization to compare itself against a proxy company who has also implemented similar lean attributes. This research suggested an approach to identify a proxy company and then evaluate the degrees of lean attribute implementations of the selected company. The fuzzy membership functions were used to calculate the degrees. These degrees were then used to figure out possible correlations among lean attributes. The research findings showed that visual feedback made available to the factory floor had triggered a positive impact on other lean attributes in most circumstances.","PeriodicalId":373492,"journal":{"name":"2015 Moratuwa Engineering Research Conference (MERCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An approach to evaluate interrelationships among lean attributes of manufacturing systems: A case study based on lean enterprises\",\"authors\":\"S. Srinath, U. Dharmapriya\",\"doi\":\"10.1109/MERCON.2015.7112348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lean philosophy has received more emphasize during recent times due to its robust features which facilitate productive manufacturing environments in companies regardless of the type of industry. However, enormous approaches taken to implement lean manufacturing systems inside factories, have failed to achieve desired objectives. This is mainly due to the focus on individual lean attributes rather than considering their collective impact on a system. This paper suggested an approach to measure correlations among lean attributes using their degrees of implementation. These correlations will help organizations to identify lean attributes which are interrelated. The quest is how to measure the degree to which each lean attribute has been implemented within the organization. Different companies have varying levels of lean implementations. Therefore identifying the leanness requires the organization to compare itself against a proxy company who has also implemented similar lean attributes. This research suggested an approach to identify a proxy company and then evaluate the degrees of lean attribute implementations of the selected company. The fuzzy membership functions were used to calculate the degrees. These degrees were then used to figure out possible correlations among lean attributes. The research findings showed that visual feedback made available to the factory floor had triggered a positive impact on other lean attributes in most circumstances.\",\"PeriodicalId\":373492,\"journal\":{\"name\":\"2015 Moratuwa Engineering Research Conference (MERCon)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Moratuwa Engineering Research Conference (MERCon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MERCON.2015.7112348\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Moratuwa Engineering Research Conference (MERCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MERCON.2015.7112348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An approach to evaluate interrelationships among lean attributes of manufacturing systems: A case study based on lean enterprises
Lean philosophy has received more emphasize during recent times due to its robust features which facilitate productive manufacturing environments in companies regardless of the type of industry. However, enormous approaches taken to implement lean manufacturing systems inside factories, have failed to achieve desired objectives. This is mainly due to the focus on individual lean attributes rather than considering their collective impact on a system. This paper suggested an approach to measure correlations among lean attributes using their degrees of implementation. These correlations will help organizations to identify lean attributes which are interrelated. The quest is how to measure the degree to which each lean attribute has been implemented within the organization. Different companies have varying levels of lean implementations. Therefore identifying the leanness requires the organization to compare itself against a proxy company who has also implemented similar lean attributes. This research suggested an approach to identify a proxy company and then evaluate the degrees of lean attribute implementations of the selected company. The fuzzy membership functions were used to calculate the degrees. These degrees were then used to figure out possible correlations among lean attributes. The research findings showed that visual feedback made available to the factory floor had triggered a positive impact on other lean attributes in most circumstances.