{"title":"过程挖掘和序列聚类在工业问题识别中的应用","authors":"Hamza Saad","doi":"arxiv-2311.15362","DOIUrl":null,"url":null,"abstract":"Process mining has become one of the best programs that can outline the event\nlogs of production processes in visualized detail. We have addressed the\nimportant problem that easily occurs in the industrial process called\nBottleneck. The analysis process was focused on extracting the bottlenecks in\nthe production line to improve the flow of production. Given enough stored\nhistory logs, the field of process mining can provide a suitable answer to\noptimize production flow by mitigating bottlenecks in the production stream.\nProcess mining diagnoses the productivity processes by mining event logs, this\ncan help to expose the opportunities to optimize critical production processes.\nWe found that there is a considerable bottleneck in the process because of the\nweaving activities. Through discussions with specialists, it was agreed that\nthe main problem in the weaving processes, especially machines that were\nexhausted in overloading processes. The improvement in the system has measured\nby teamwork; the cycle time for process has improved to 91%, the worker's\nperformance has improved to 96%,product quality has improved by 85%, and lead\ntime has optimized from days and weeks to hours.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Process Mining and Sequence Clustering in Recognizing an Industrial Issue\",\"authors\":\"Hamza Saad\",\"doi\":\"arxiv-2311.15362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Process mining has become one of the best programs that can outline the event\\nlogs of production processes in visualized detail. We have addressed the\\nimportant problem that easily occurs in the industrial process called\\nBottleneck. The analysis process was focused on extracting the bottlenecks in\\nthe production line to improve the flow of production. Given enough stored\\nhistory logs, the field of process mining can provide a suitable answer to\\noptimize production flow by mitigating bottlenecks in the production stream.\\nProcess mining diagnoses the productivity processes by mining event logs, this\\ncan help to expose the opportunities to optimize critical production processes.\\nWe found that there is a considerable bottleneck in the process because of the\\nweaving activities. Through discussions with specialists, it was agreed that\\nthe main problem in the weaving processes, especially machines that were\\nexhausted in overloading processes. The improvement in the system has measured\\nby teamwork; the cycle time for process has improved to 91%, the worker's\\nperformance has improved to 96%,product quality has improved by 85%, and lead\\ntime has optimized from days and weeks to hours.\",\"PeriodicalId\":501487,\"journal\":{\"name\":\"arXiv - QuantFin - Economics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2311.15362\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.15362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Process Mining and Sequence Clustering in Recognizing an Industrial Issue
Process mining has become one of the best programs that can outline the event
logs of production processes in visualized detail. We have addressed the
important problem that easily occurs in the industrial process called
Bottleneck. The analysis process was focused on extracting the bottlenecks in
the production line to improve the flow of production. Given enough stored
history logs, the field of process mining can provide a suitable answer to
optimize production flow by mitigating bottlenecks in the production stream.
Process mining diagnoses the productivity processes by mining event logs, this
can help to expose the opportunities to optimize critical production processes.
We found that there is a considerable bottleneck in the process because of the
weaving activities. Through discussions with specialists, it was agreed that
the main problem in the weaving processes, especially machines that were
exhausted in overloading processes. The improvement in the system has measured
by teamwork; the cycle time for process has improved to 91%, the worker's
performance has improved to 96%,product quality has improved by 85%, and lead
time has optimized from days and weeks to hours.