Advancing the Performance of Complex Manufacturing Systems Through Agent-Based Production Control

Ever increasing competition is driving the efforts to improve productivity throughout nearly all domains. In the manufacturing context, digitalization of value networks and creation of autonomous, self-optimizing systems – a vision coined ‘Industrie 4.0 – is an approach that promises competitive edge over other players. One field in which this vision could lead to great productivity potentials is order scheduling and sequencing in high variety, high volume manufacturing businesses like the automobile industry. A viable technology to realize the expected gains in productivity are software agents and multi-agent systems, since they provide autonomy, flexibility, adaptiveness, and robustness to unforeseeable events. This paper proposes an agent-based control architecture that enables communication between resources and customer orders within a car body shop, so that they can negotiate the best alternative schedule and order sequence in case of disturbances. The proposed architecture allows improvement of overall production system performance in terms of output, resource utilization, delivery reliability and others. Further, the paper describes the implementation and simulation of the multi-agent system with JADE framework and discusses the simulation results, which show that significant productivity leaps can be achieved.

[1]  H. Lorenz,et al.  Jena Research Papers in Business and Economics Sequencing Mixed-Model Assembly Lines : Survey , Classification and Model Critique , 2007 .

[2]  Rainer Unland,et al.  Software Agent Systems , 2015 .

[3]  Nicole Schmidt,et al.  Identification of “Industrie 4.0” component hierarchy layers , 2016, 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA).

[4]  Lars Mönch,et al.  Agentenbasierte Produktionssteuerung komplexer Produktionssysteme , 2006, Wirtschaftsinformatik.

[5]  Reza Tavakkoli-Moghaddam,et al.  A New Approach for Mixed-Model Assembly Line Sequencing , 2006, OR.

[6]  Nils Boysen,et al.  Level-Scheduling bei Variantenfließfertigung: Klassifikation, Literaturüberblick und Modellkritik , 2007 .

[7]  Alain Bernard,et al.  Product Variety Management , 1998 .

[8]  Gerald Scheffels The Pearl Chain Logistics Concept , 2012, JOT-International Surface Technology.

[9]  T. Bauernhansl Die Vierte Industrielle Revolution – Der Weg in ein wertschaffendes Produktionsparadigma , 2014 .

[10]  Ambra Calá,et al.  Design pattern for agent based production system control — A survey , 2017, 2017 13th IEEE Conference on Automation Science and Engineering (CASE).

[11]  Adriana Giret A multi agent methodology for holonic manufacturing systems , 2005, AAMAS '05.

[12]  Nicole Schmidt,et al.  Description Means for Information Artifacts Throughout the Life Cycle of CPPS , 2017, Multi-Disciplinary Engineering for Cyber-Physical Production Systems.

[13]  Christine Solnon,et al.  The car sequencing problem: Overview of state-of-the-art methods and industrial case-study of the ROADEF'2005 challenge problem , 2008, Eur. J. Oper. Res..

[14]  Hendrik Van Brussel,et al.  Towards robust and efficient planning execution , 2008, Eng. Appl. Artif. Intell..

[15]  Moritz Roidl Kooperation und Autonomie in selbststeuernden Systemen , 2010 .

[16]  Nils Boysen,et al.  Resequencing of mixed-model assembly lines: Survey and research agenda , 2012, Eur. J. Oper. Res..

[17]  Karl-Heinz Waldmann,et al.  Operations Research Proceedings 2006 , 2007 .

[18]  Bhaba R. Sarker,et al.  Designing a mixed-model, open-station assembly line using mixed-integer programming , 2001, J. Oper. Res. Soc..

[19]  Birgit Vogel-Heuser,et al.  Einsatz von Softwareagenten am Beispiel einer kontinuierlichen, hydraulischen Heizpresse , 2013 .

[20]  Reza Tavakkoli-Moghaddam,et al.  Mixed-Model Assembly Line Sequencing Using Real Options , 2006, OR.

[21]  Michael Wooldridge,et al.  Multiagent Systems for Manufacturing Control: A Design Methodology , 2010 .

[22]  Axel Wagenitz,et al.  Simulationsgestützte Optimierung für die distributionsorientierte Auftragsreihenfolgeplanung in der Automobilindustrie , 2011 .

[23]  Reza Tavakkoli-Moghaddam,et al.  A Multi-Objective Particle Swarm for a Mixed-Model Assembly Line Sequencing , 2006, OR.

[24]  Agostino Poggi,et al.  Developing Multi-agent Systems with JADE , 2007, ATAL.

[25]  Matthias Holweg,et al.  Linking Product Variety to Order-Fulfillment Strategies , 2004, Interfaces.

[26]  Peter J. Stuckey,et al.  Explaining Flow-Based Propagation , 2012, CPAIOR.

[27]  Alessandro Birolini Reliability Engineering: Theory and Practice , 1999 .

[28]  Wilmjakob Herlyn,et al.  PPS im Automobilbau , 2012 .

[29]  Birgit Vogel-Heuser,et al.  Industrie 4.0 in Produktion, Automatisierung und Logistik , 2014 .

[30]  Nils Boysen,et al.  A decomposition approach for the car resequencing problem with selectivity banks , 2013, Comput. Oper. Res..