Production planning and performance optimization of reconfigurable manufacturing systems using genetic algorithm

2010 ◽  
Vol 54 (1-4) ◽  
pp. 373-392 ◽  
Author(s):  
Morteza Abbasi ◽  
Mahmoud Houshmand
Keyword(s):  
Genetic Algorithm ◽  
Production Planning ◽  
Performance Optimization ◽  
Manufacturing Systems ◽  
Reconfigurable Manufacturing Systems ◽  
Reconfigurable Manufacturing ◽  
And Performance

Produktionsplanung in RMS/Production Planning in RMS - System for Production Process Planning in Reconfigurable Manufacturing Systems (RMS)

2015 ◽  
Vol 105 (04) ◽  
pp. 209-214
Author(s):  
A. Hees ◽  
K. Zellner ◽  
G. Reinhart
Keyword(s):  
Production Planning ◽  
Process Planning ◽  
Data Model ◽  
Manufacturing Systems ◽  
Reconfigurable Manufacturing Systems ◽  
Reconfigurable Manufacturing ◽  
Manufacturing Companies ◽  
New Approach ◽  
Short Intervals ◽  
Dynamic Markets

Zur Sicherung der Wettbewerbsfähigkeit in dynamischen Märkten müssen produzierende Unternehmen ihre Produktionssysteme in häufigen Intervallen anpassen. Ein Ansatz, diesen Herausforderungen zu begegnen, sind rekonfigurierbare Produktionssysteme (englisch: Reconfigurable Manufacturing Systems – RMS). Vorgestellt wird ein neuer Ansatz für die Produktionsplanung und -steuerung (PPS) in RMS – bestehend aus einem Datenmodell, einem Konfigurationsmanagement und einer Planungsmethode.   Manufacturing companies have to adapt their manufacturing systems in frequent and short intervals to secure their competitiveness in dynamic markets. One approach to ensure companies’ success are Reconfigurable Manufacturing Systems (RMS). In this context, a new approach for production planning (PPC) in RMS, consisting of a data model, a configuration management and a planning method, is described in this paper.

scholarly journals A Production Planning Method to Optimally Exploit the Potential of Reconfigurable Manufacturing Systems

Procedia CIRP ◽  
2017 ◽  
Vol 62 ◽  
pp. 181-186 ◽  
Author(s):  
Andreas Hees ◽  
Christina Bayerl ◽  
Brian Van Vuuren ◽  
Corné S.L. Schutte ◽  
Stefan Braunreuther ◽  
...  
Keyword(s):  
Production Planning ◽  
Manufacturing Systems ◽  
Planning Method ◽  
Reconfigurable Manufacturing Systems ◽  
Reconfigurable Manufacturing

scholarly journals A Pareto-based genetic algorithm for multi-objective scheduling of automated manufacturing systems

2020 ◽  
Vol 12 (1) ◽  
pp. 168781401988529 ◽  
Author(s):  
Xin Zan ◽  
Zepeng Wu ◽  
Cheng Guo ◽  
Zhenhua Yu
Keyword(s):  
Genetic Algorithm ◽  
Performance Optimization ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Automated Manufacturing ◽  
Scheduling Problems ◽  
Automated Manufacturing Systems ◽  
Multi Objective ◽  
Automated Manufacturing System ◽  
And Performance

This work focuses on multi-objective scheduling problems of automated manufacturing systems. Such an automated manufacturing system has limited resources and flexibility of processing routes of jobs, and hence is prone to deadlock. Its scheduling problem includes both deadlock avoidance and performance optimization. A new Pareto-based genetic algorithm is proposed to solve multi-objective scheduling problems of automated manufacturing systems. In automated manufacturing systems, scheduling not only sets up a routing for each job but also provides a feasible sequence of job operations. Possible solutions are expressed as individuals containing information of processing routes and the operation sequence of all jobs. The feasibility of individuals is checked by the Petri net model of an automated manufacturing system and its deadlock controller, and infeasible individuals are amended into feasible ones. The proposed algorithm has been tested with different instances and compared to the modified non-dominated sorting genetic algorithm II. The experiment results show the feasibility and effectiveness of the proposed algorithm.

Optimal Part Family and Production Module Planning for Reconfigurable Manufacturing Systems

2006 ◽  
Author(s):  
Jian Liu ◽  
Derek M. Yip-Hoi ◽  
Wencai Wang ◽  
Li Tang
Keyword(s):  
Manufacturing Systems ◽  
Optimization Procedure ◽  
Cost Effective ◽  
System Level ◽  
Reconfigurable Manufacturing Systems ◽  
Reconfigurable Manufacturing ◽  
Market Demand ◽  
Individual Module ◽  
Reconfiguration Planning ◽  
And Performance

Manufactures are adopting Reconfigurable Manufacturing Systems (RMS) to better cope with frequently changing market conditions, which place tremendous demands on a system’s flexibility as well as its cost-effectiveness. Considerable efforts have been devoted to the development of necessary tools for the system level design and performance improvement, resulting in approaches to designing a single RMS. In this paper, a methodology for cost-effective reconfiguration planning for multi-module-multi-product RMS’s that best reflect the market demand changes is proposed. Formulated as an optimization procedure, reconfiguration planning is defined as the best reallocation of part families to production modules in an RMS and the best rebalancing of the whole system and each individual module to achieve minimum related cost and simultaneously satisfy the market demand. A Genetic Algorithm (GA) approach is proposed to overcome the computational difficulties caused by the problem complexity. Effectiveness of the proposed methodology is demonstrated with a case study.

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