{"title":"多科摩重型机械设备有限公司:备件供应链管理","authors":"A. Narayanan, S. Seshadri","doi":"10.1108/CASE.CSCMP.2018.000008","DOIUrl":null,"url":null,"abstract":"This case study is designed to explore the challenges of forecasting and inventory management in spare parts industry. Most items in this industry have lumpy, intermittent, erratic and slow demand patterns. Traditional forecasting techniques cannot be applied to this group. Also most textbook methods on inventory planning, assumes the demand is normally distributed – which is also not the case in spare parts industry. Strategies can be tested for the demand data provide for about 40 items","PeriodicalId":294349,"journal":{"name":"Council of Supply Chain Management Professionals Cases","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Dockomo Heavy Machinery Equipment Ltd.: Spare Parts Supply Chain Management\",\"authors\":\"A. Narayanan, S. Seshadri\",\"doi\":\"10.1108/CASE.CSCMP.2018.000008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This case study is designed to explore the challenges of forecasting and inventory management in spare parts industry. Most items in this industry have lumpy, intermittent, erratic and slow demand patterns. Traditional forecasting techniques cannot be applied to this group. Also most textbook methods on inventory planning, assumes the demand is normally distributed – which is also not the case in spare parts industry. Strategies can be tested for the demand data provide for about 40 items\",\"PeriodicalId\":294349,\"journal\":{\"name\":\"Council of Supply Chain Management Professionals Cases\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Council of Supply Chain Management Professionals Cases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/CASE.CSCMP.2018.000008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Council of Supply Chain Management Professionals Cases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/CASE.CSCMP.2018.000008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dockomo Heavy Machinery Equipment Ltd.: Spare Parts Supply Chain Management
This case study is designed to explore the challenges of forecasting and inventory management in spare parts industry. Most items in this industry have lumpy, intermittent, erratic and slow demand patterns. Traditional forecasting techniques cannot be applied to this group. Also most textbook methods on inventory planning, assumes the demand is normally distributed – which is also not the case in spare parts industry. Strategies can be tested for the demand data provide for about 40 items