A. Madureira, J. M. Santos, S. Gomes, Bruno Cunha, J. Pereira, I. Pereira
{"title":"Manufacturing rush orders rescheduling: a supervised learning approach","authors":"A. Madureira, J. M. Santos, S. Gomes, Bruno Cunha, J. Pereira, I. Pereira","doi":"10.1109/NaBIC.2014.6921895","DOIUrl":null,"url":null,"abstract":"Contemporary manufacturing scheduling has still limitations in real-world environments where disturbances on working conditions could occur over time. Therefore, human intervention is required to maintain real-time adaptation and optimization and efficiently adapt to the inherent dynamic of markets. This paper addresses the problem of incorporating rush orders into the current schedule of a manufacturing shop floor organization. A set of experiments were performed in order to evaluate the applicability of supervised classification algorithms in the attempt to predict the best integration mechanism when receiving a new order in a dynamic scheduling problem.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NaBIC.2014.6921895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Contemporary manufacturing scheduling has still limitations in real-world environments where disturbances on working conditions could occur over time. Therefore, human intervention is required to maintain real-time adaptation and optimization and efficiently adapt to the inherent dynamic of markets. This paper addresses the problem of incorporating rush orders into the current schedule of a manufacturing shop floor organization. A set of experiments were performed in order to evaluate the applicability of supervised classification algorithms in the attempt to predict the best integration mechanism when receiving a new order in a dynamic scheduling problem.