{"title":"Activity on arrow (AOA) network model to enable mold productivity optimization","authors":"Lim Ming Siong","doi":"10.1109/IEMT.2016.7761987","DOIUrl":null,"url":null,"abstract":"This paper is to discuss an engineering optimization method to fully utilize the mold equipment and deliver its maximum productivity yet no compromising on both product and equipment quality. A network model, which using activity on arrow (AOA), is constructed for the activities in the entire molding process starting with loading till offloading of the magazine. The network becomes complicated when 2 mold presses are in production mode simultaneously where only a universal toolset, such as preheater and degator is required to accommodate both presses concurrently. In this case, slack times often happen where certain activities need to wait for the activities to complete before it starts. This non-productive waiting time is one of the seven wastes in lean manufacturing concept. A “dummy” is used to indicate as a precedence activity of another activity in this network model. By considering all the activities time of the entire network, the “critical path” can be identified. Critical path illustrate focus area of the entire mold process which reflecting the opportunity for productivity improvement. By tabulating down the time for each activity in the critical path, a decision can be made when the opportunity is identified. The model can be further expanded to 3 presses model where the critical path and the slack time vary accordingly. A simple program are developed with entry data of the mold equipment capability and process parameter to ease the calculation. The output of the program will present the critical path and expected crashing area.","PeriodicalId":237235,"journal":{"name":"2016 IEEE 37th International Electronics Manufacturing Technology (IEMT) & 18th Electronics Materials and Packaging (EMAP) Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 37th International Electronics Manufacturing Technology (IEMT) & 18th Electronics Materials and Packaging (EMAP) Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMT.2016.7761987","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper is to discuss an engineering optimization method to fully utilize the mold equipment and deliver its maximum productivity yet no compromising on both product and equipment quality. A network model, which using activity on arrow (AOA), is constructed for the activities in the entire molding process starting with loading till offloading of the magazine. The network becomes complicated when 2 mold presses are in production mode simultaneously where only a universal toolset, such as preheater and degator is required to accommodate both presses concurrently. In this case, slack times often happen where certain activities need to wait for the activities to complete before it starts. This non-productive waiting time is one of the seven wastes in lean manufacturing concept. A “dummy” is used to indicate as a precedence activity of another activity in this network model. By considering all the activities time of the entire network, the “critical path” can be identified. Critical path illustrate focus area of the entire mold process which reflecting the opportunity for productivity improvement. By tabulating down the time for each activity in the critical path, a decision can be made when the opportunity is identified. The model can be further expanded to 3 presses model where the critical path and the slack time vary accordingly. A simple program are developed with entry data of the mold equipment capability and process parameter to ease the calculation. The output of the program will present the critical path and expected crashing area.