Model of production planning and scheduling in shop floor based on collaboration and competition

2002 ◽  
Vol 7 (1) ◽  
pp. 77-81 ◽  
Author(s):  
Liu Shi-ping ◽  
Rao Yun-qing ◽  
Zhang Jie ◽  
Li Pei-gen
2018 ◽  
Vol 66 (6) ◽  
pp. 492-502 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
Rajesh Kumar ◽  
Sujil A

Abstract In a highly competitive environment, effective production is one of the key issues which can be addressed by efficient production planning and scheduling in the manufacturing system. This paper develops an agent-based architecture which enables integration of production planning and scheduling. In addition, this architecture will facilitate real time production scheduling as well as provide a multi-agent system (MAS) platform on which multiple agents will interact to each other. A case study of job-shop manufacturing system (JMS) has been considered in this paper for implementing the concept of MAS. The modeling of JMS has been created in SimEvents which integrates an agent-based architecture developed by Stateflow to transform into dynamic JMS. Finally, the agent-based architecture is evaluated using utilization of each machine in the shop floor with respect to time.


2015 ◽  
Vol 9 (3) ◽  
pp. 209-209 ◽  
Author(s):  
Nobuhiro Sugimura ◽  
Koji Iwamura ◽  
Tomohiko Maeda

This issue focuses on production planning and scheduling for production system and the related problems that have arisen in these areas in the last half century as digital computer systems developed. These problems relate to production management, production planning, shop floor control, product design and process planning. In the first stage of production planning and scheduling systems R&D, optimization is a key issue that has been widely discussed and many theories and optimization algorithms proposed. Rule-based methods are discussed as potential solutions to these problems. With rapid advances in computer and information processing technologies and performance, tremendous progress has been made in the areas of production systems such as production planning, production scheduling, advances production systems (APS), enterprise resource planning (ERP), just-in time (JIT) processes, the theory of constraint (TOC), product data management (PDM) and computer-aided design / manufacturing / engineering (CAD/CAM/CAE). This special issue addresses the latest research advances, applications, and case studies in production planning and scheduling covering such as decentralized and autonomous production systems, distributed simulation models, robust capacity planning models, wireless sensor networks for production systems and applications to automotive component and steel production. We hope that learning about these advances will enable readers to share their own experience and knowledge in technology, new developments and the potential applications of production planning and scheduling methods and solutions.


Kybernetes ◽  
2015 ◽  
Vol 44 (5) ◽  
pp. 705-720 ◽  
Author(s):  
Yanting Ni ◽  
Yi Wang

Purpose – In a mixed flow production environment, interactions between production planning and scheduling are critical for mixed flow distributed manufacturing management. The purpose of this paper is to assist manufacturers in achieving real-time ordering and obtaining integrated optimization of shop floor production planning and scheduling for mixed flow production systems. Design/methodology/approach – A double decoupling postponement (DDP) approach is presented for production dispatch control, and an integrated model is designed under an assemble to order (ATO) environment. To generate “optimal” lots to fulfil real-time customer requests, constant work in progress (CONWIP) and days of inventory dispatching algorithms are embedded into the proposed DDP model, which can deal with real-time ordering and dynamic scheduling simultaneously. Subsequently, a case study is conducted, and experiments are carried out to verify the presented method. Findings – The proposed DDP model is designed to upgrade a previous CONWIP method in the case study company, and the proposed model demonstrates better performance for the integration of production planning and scheduling in mixed flow manufacturing. As a result, the presented operation mechanism can reflect real-time ordering information to shop floor scheduling and obtain performance metrics in terms of reliability, availability and maintainability. Research limitations/implications – The presented model can be further proliferated to generic factory manufacturing with the proposed logic and architecture. Originality/value – The DDP model can integrate real-time customer orders and work in process information, upon which manufacturers can make correct decisions for dispatch strategies and order selection within an integrated system.


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