Open AccessHybrid flow shop scheduling problem in ubiquitous manufacturing environment
Author(s) -
Wu Xiuli,
Li Jing,
Sun Lin
Publication year - 2019
Publication title -
iet collaborative intelligent manufacturing
Language(s) - English
Resource type - Journals
ISSN - 2516-8398
DOI - 10.1049/iet-cim.2018.0016
Subject(s) - scheduling (production processes) , computer science , flow shop scheduling , job shop scheduling , distributed computing , wireless , real time computing , material requirements planning , genetic algorithm scheduling , industrial engineering , production (economics) , computer network , engineering , operations management , telecommunications , routing (electronic design automation) , economics , macroeconomics
As a new smart manufacturing mode, Internet of manufacturing things could collect information from production line and help to make a timely and accurate decision. However, this new mode poses new challenges to production operation management. This article focuses on the hybrid flow shop scheduling problem in ubiquitous manufacturing environment. Advanced wireless devices such as radio frequency identification are deployed to enable interconnection and perception among workers, materials and equipment in shop floor. The scheduling optimisation models for the planning layer and the scheduling layer are established, respectively. The evolutionary game algorithm is proposed to optimise the assignment of daily production tasks in the planning layer. According to the real‐time situations of various production resources, the non‐dominated sorted genetic algorithm is utilised to optimise the real‐time scheduling of daily tasks in the scheduling layer. Between the two layers, real‐time production information is exchanged by advanced wireless devices. Finally, two production scenarios in off‐season and peak‐season are presented. The experimental results verify the efficiency and the effectiveness of the proposed approach under different production conditions.