A toolbox for the design, planning and operation of manufacturing networks in a mass customisation environment. (July 2015)

• Record Type: Journal Article
• Authors: Mourtzis, Dimitris; Doukas, Michalis; Psarommatis, Foivos
• Is Part Of: Journal of manufacturing systems. Volume 36(2015)
• Page Start: 274
• Page End: 286
• Publication Date: 2015-07
• Subjects: Mass customisation -- Design -- Planning -- Manufacturing networks -- Complexity -- Metaheuristics; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2014.06.004
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: Manufacturing network performance investigation for mass customised products. TS, SA metaheuristic methods are used together with an AI method. Multi-criteria decision making to evaluate the quality of configurations. Robust engineering is used for calibrating the adjustable parameters of the methods. The framework is validated through a real life case from the CNC building industry. Abstract: The task of design, planning and operation of manufacturing networks is becoming more and more challenging for companies, as globalisation, mass customisation and the turbulent economic landscape create demand volatility, uncertainties and high complexity. In this context, this paper investigates the performance of decentralised manufacturing networks through a set of methods developed into a software framework in a toolbox approach. The Tabu Search and Simulated Annealing metaheuristic methods are used together with an Artificial Intelligence method, called Intelligent Search Algorithm. A multi-criteria decision making procedure is carried out for the evaluation of the quality of alternative manufacturing network configurations using multiple conflicting criteria including dynamic complexity, reliability, cost, time, quality and environmental footprint. A comparison of the performance of each method based on the quality of the solutions that it provided is carried out. The statistical design of experiments robust engineering technique is used for the calibration of the adjustable parameters of the methods. Moreover, the impact of demand fluctuation to the operational performance of the alternative networks, expressed thorough a dynamic complexity indicator, is investigated through simulation. The developed framework is validated through a real life case, with data coming from the CNC machine building industry.