{"title":"PostgreSQL:关系型数据库结构在药物片剂生产过程中的容许批量大小上的应用","authors":"Michael Simonis , Stefan Nickel","doi":"10.1016/j.simpa.2024.100720","DOIUrl":null,"url":null,"abstract":"<div><div>Multi-level capacitated lot-sizing problems with linked lot sizes and backorders (MLCLSP-L-B) are used in pharmaceutical tablets manufacturing processes to right-size material production lots so that costs are kept at a minimum, production resource capacities are not exceeded, and customer demand is fulfilled. Uncertain demand behavior characterizes today’s global tablets market. Pharmaceutical companies request solution approaches that solve the MLCLSP-L-B with probabilistic demand. Implementing this model in industrial applications for tablets manufacturing systems requires efficient data processing due to the amount of data and the capability to store simulated demand scenarios. This paper covers the first integration of the MLCLSP-L-B with probabilistic demand and Relational Database Structures (RDS). Modeling techniques for the RDS to process massive data are outlined. A virtual environment provides the implementation software PostgreSQL and infrastructure environment. Additionally, numerical experiments with research data are used to evaluate the agility and efficiency of the developed RDS.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100720"},"PeriodicalIF":1.3000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PostgreSQL: Relational database structures application on capacitated lot-sizing for pharmaceutical tablets manufacturing processes\",\"authors\":\"Michael Simonis , Stefan Nickel\",\"doi\":\"10.1016/j.simpa.2024.100720\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Multi-level capacitated lot-sizing problems with linked lot sizes and backorders (MLCLSP-L-B) are used in pharmaceutical tablets manufacturing processes to right-size material production lots so that costs are kept at a minimum, production resource capacities are not exceeded, and customer demand is fulfilled. Uncertain demand behavior characterizes today’s global tablets market. Pharmaceutical companies request solution approaches that solve the MLCLSP-L-B with probabilistic demand. Implementing this model in industrial applications for tablets manufacturing systems requires efficient data processing due to the amount of data and the capability to store simulated demand scenarios. This paper covers the first integration of the MLCLSP-L-B with probabilistic demand and Relational Database Structures (RDS). Modeling techniques for the RDS to process massive data are outlined. A virtual environment provides the implementation software PostgreSQL and infrastructure environment. Additionally, numerical experiments with research data are used to evaluate the agility and efficiency of the developed RDS.</div></div>\",\"PeriodicalId\":29771,\"journal\":{\"name\":\"Software Impacts\",\"volume\":\"22 \",\"pages\":\"Article 100720\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software Impacts\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2665963824001088\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Impacts","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665963824001088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
PostgreSQL: Relational database structures application on capacitated lot-sizing for pharmaceutical tablets manufacturing processes
Multi-level capacitated lot-sizing problems with linked lot sizes and backorders (MLCLSP-L-B) are used in pharmaceutical tablets manufacturing processes to right-size material production lots so that costs are kept at a minimum, production resource capacities are not exceeded, and customer demand is fulfilled. Uncertain demand behavior characterizes today’s global tablets market. Pharmaceutical companies request solution approaches that solve the MLCLSP-L-B with probabilistic demand. Implementing this model in industrial applications for tablets manufacturing systems requires efficient data processing due to the amount of data and the capability to store simulated demand scenarios. This paper covers the first integration of the MLCLSP-L-B with probabilistic demand and Relational Database Structures (RDS). Modeling techniques for the RDS to process massive data are outlined. A virtual environment provides the implementation software PostgreSQL and infrastructure environment. Additionally, numerical experiments with research data are used to evaluate the agility and efficiency of the developed RDS.