Alifa Izzan Akhsani, R. Sarno, Dwi Sunaryono, Tantya A. Giranita, K. R. Sungkono
{"title":"PT. P生产过程优化调度方法的比较","authors":"Alifa Izzan Akhsani, R. Sarno, Dwi Sunaryono, Tantya A. Giranita, K. R. Sungkono","doi":"10.1109/iSemantic50169.2020.9234203","DOIUrl":null,"url":null,"abstract":"This study aims to determine scheduling methods to optimize the manufacturing production process. One of which way to optimize the manufacturing process is to ensure that the production capacity is used optimally. Scheduling planning is a tool to allocate capacity and resources for the process from time to time. The author proposes the earliest due date (EDD) scheduling method to be compared with critical ratio (CR) and first come first serve (FCFS) method for optimizing the manufacturing production process on PT.P. Several tests are conducted to prove the performance of the scheduling method, with regard to scheduling parameters and their impact on the manufacturing production process. The scheduling parameters referred to are Flow Time, Makespan, Tardiness, and Late Jobs. For its effect on the manufacturing production process, the utility value of the machine capacity used will be measured while using the scheduling method. The test results obtained from the earliest due date method (EDD) succeeded in producing the value of makespan 3.41% shorter, and the mean flow time is 0.70% shorter. This method also improved the utility of the machine, on average 2.34% better than other methods without increasing the mean tardiness and the number of late jobs overall.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Comparison of Scheduling Methods for Optimization Production Processes on PT. P\",\"authors\":\"Alifa Izzan Akhsani, R. Sarno, Dwi Sunaryono, Tantya A. Giranita, K. R. Sungkono\",\"doi\":\"10.1109/iSemantic50169.2020.9234203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to determine scheduling methods to optimize the manufacturing production process. One of which way to optimize the manufacturing process is to ensure that the production capacity is used optimally. Scheduling planning is a tool to allocate capacity and resources for the process from time to time. The author proposes the earliest due date (EDD) scheduling method to be compared with critical ratio (CR) and first come first serve (FCFS) method for optimizing the manufacturing production process on PT.P. Several tests are conducted to prove the performance of the scheduling method, with regard to scheduling parameters and their impact on the manufacturing production process. The scheduling parameters referred to are Flow Time, Makespan, Tardiness, and Late Jobs. For its effect on the manufacturing production process, the utility value of the machine capacity used will be measured while using the scheduling method. The test results obtained from the earliest due date method (EDD) succeeded in producing the value of makespan 3.41% shorter, and the mean flow time is 0.70% shorter. This method also improved the utility of the machine, on average 2.34% better than other methods without increasing the mean tardiness and the number of late jobs overall.\",\"PeriodicalId\":345558,\"journal\":{\"name\":\"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iSemantic50169.2020.9234203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iSemantic50169.2020.9234203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Scheduling Methods for Optimization Production Processes on PT. P
This study aims to determine scheduling methods to optimize the manufacturing production process. One of which way to optimize the manufacturing process is to ensure that the production capacity is used optimally. Scheduling planning is a tool to allocate capacity and resources for the process from time to time. The author proposes the earliest due date (EDD) scheduling method to be compared with critical ratio (CR) and first come first serve (FCFS) method for optimizing the manufacturing production process on PT.P. Several tests are conducted to prove the performance of the scheduling method, with regard to scheduling parameters and their impact on the manufacturing production process. The scheduling parameters referred to are Flow Time, Makespan, Tardiness, and Late Jobs. For its effect on the manufacturing production process, the utility value of the machine capacity used will be measured while using the scheduling method. The test results obtained from the earliest due date method (EDD) succeeded in producing the value of makespan 3.41% shorter, and the mean flow time is 0.70% shorter. This method also improved the utility of the machine, on average 2.34% better than other methods without increasing the mean tardiness and the number of late jobs overall.