Energy Efficient and Intelligent Production Scheduling – Evaluation of a New Production Planning and Scheduling Software

Author(s):  
Agnes Pechmann ◽  
Ilka Schöler ◽  
Rene Hackmann
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.


2004 ◽  
Vol 01 (04) ◽  
pp. 359-371 ◽  
Author(s):  
GIDEON HALEVI

Theoretical production planning and scheduling is actually very simple task: The plant gets orders which defines the product, the quantity and delivery dates. The resources of the plants are known, the product bill of material is known and the task of production scheduling is to make sure that the orders will be ready on time, that's all. It seems strange that in order to meet this simple task, over 100 complex production planning methods were proposed. Some of the outstanding ones are: PICS; MRP; ERP; GT; TOC; FMS; IMS; CIM; CE; JIT; Kanaban; TQM; Agent…, AGILE etc. Yet the search for "THE" method is carried on. In this paper an attempt to analyze why production planning is regarded as a complex task, and why the search for "THE" production planning method is still an open topic for researchers. Furthermore, to demonstrate how introduction of flexibility will restore the simplicity of production planning.


2011 ◽  
Vol 268-270 ◽  
pp. 292-296 ◽  
Author(s):  
Wen Hao Wang ◽  
Qiong Zhu ◽  
Jie Zhang

In the practical application of push-pull based production planning and scheduling architecture, the manufacturing system was found lacking of collaborative mechanism, especially for a networked-manufacturing environment, which requires each individual manufacturer interact and cooperate with each other for a collaborative manufacturing. This paper presents a production planning and scheduling architecture for networked-manufacturing system based on available-to-promise, which can effectively merge forecast-driven production activity with order-driven production activity, thus ensures the steady and prompt supply of material, and also cooperation and mutual benefit of individual manufacturer. This architecture consists of 1) an ATP-based order management and decision-making system, 2) a push-pull based multi-plant master production schedule collaboration model, 3) a pre-reactive collaborative replenishment model, 4) a production scheduling model of unrelated parallel machine and 5) the corresponding production planning and scheduling methods for each model. By combining the concept of ATP, this architecture can not only provide resource planning for networked-manufacturing system, but also offer quick response and promise to customer requests.


2019 ◽  
Vol 27 (2) ◽  
pp. 99-111 ◽  
Author(s):  
Song Zheng ◽  
Jiaxin Gao ◽  
Jian Xu

The production planning is aimed at the formulation and distribution of the overall production plan, while the production scheduling focuses on the implementation of the specific production plan. It is very important to coordinate each other in order to promote the production efficiency of enterprises, but the integrated optimization of production planning and scheduling has great challenges. This article proposes the novel integrated optimization method of planning and scheduling based on improved collaborative optimization. An integrated model of planning and scheduling with collaborative optimization structure is established, and the detailed solution strategy of the novel integrated optimization algorithm is presented. At last, the simulation results show that the proposed integration algorithm of planning and scheduling is competitive in global optimization and practicality.


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