{"title":"Blockchain design for optimal joint production and maintenance over multiple periods for oil-filling production lines","authors":"A. Al-Refaie, Ahmad Al-Hawadi","doi":"10.1177/09544054241252854","DOIUrl":null,"url":null,"abstract":"Joint maintenance and production planning result in enhanced system efficiency and a significant reduction in expensive costs. Therefore, this research proposed an integrated blockchain design of two optimization models for the joint scheduling and sequencing of production orders and maintenance jobs over multiple periods with probabilistic and stochastic parameters for the oil-filling process. In the scheduling model, the objective function was to minimize total production and maintenance costs. Further, the sequencing model aimed to minimize the total overtime cost and the sum start times of jobs and orders. The proposed models were implemented on five production lines of five-liter lube oil bottles. Results showed that the developed optimization models effectively achieved concurrent production and maintenance planning at minimal total cost. In practice, this results in effective resource utilization, and saving costly production and maintenance costs. In conclusion, the developed blockchain design is valuable in developing, managing, and controlling optimal joint production and maintenance planning of oil-filling production lines.","PeriodicalId":20663,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/09544054241252854","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
Joint maintenance and production planning result in enhanced system efficiency and a significant reduction in expensive costs. Therefore, this research proposed an integrated blockchain design of two optimization models for the joint scheduling and sequencing of production orders and maintenance jobs over multiple periods with probabilistic and stochastic parameters for the oil-filling process. In the scheduling model, the objective function was to minimize total production and maintenance costs. Further, the sequencing model aimed to minimize the total overtime cost and the sum start times of jobs and orders. The proposed models were implemented on five production lines of five-liter lube oil bottles. Results showed that the developed optimization models effectively achieved concurrent production and maintenance planning at minimal total cost. In practice, this results in effective resource utilization, and saving costly production and maintenance costs. In conclusion, the developed blockchain design is valuable in developing, managing, and controlling optimal joint production and maintenance planning of oil-filling production lines.
期刊介绍:
Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed.
Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing.
Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.