A Service-Oriented Approach for Holonic Manufacturing Control and Beyond

The Holonic Manufacturing Execution System (HMES), developed at K.U.Leuven, utilizes a service-oriented approach to control manufacturing operations in real time. This chapter first explains how manufacturing control emerges from interaction between intelligent products and intelligent resources. Services play a key role in this interaction and form a decoupling point between the generic control system and application-specific elements. To illustrate that this service-oriented approach allows applying the same concepts and principles to various domains, several applications in manufacturing, open-air engineering, robotics and logistics are described. Finally, the chapter describes how supporting services, such as maintenance, can be seamlessly integrated with the core activities of the system.

[1]  Paulo Leitão,et al.  Holonic and Multi-Agent Systems for Manufacturing , 2011, Lecture Notes in Computer Science.

[2]  Duncan McFarlane,et al.  Rationales for Holonic Manufacturing Control , 1999 .

[3]  Hendrik Van Brussel,et al.  Deadlock avoidance in flexible flow shops with loops , 2001, J. Intell. Manuf..

[4]  Dirk Cattrysse,et al.  A Holonic Chain Conveyor Control System: An Application , 2009, HoloMAS.

[5]  Pius J. Egbelu,et al.  Scheduling of inbound and outbound trucks in cross docking systems with temporary storage , 2008, Eur. J. Oper. Res..

[6]  Duncan McFarlane,et al.  Developments in holonic production planning and control , 2000 .

[7]  Paul Valckenaers,et al.  PROSA and delegate MAS for open-air engineering processes , 2011, ETFA2011.

[8]  Bernard P. Zeigler,et al.  A multimodel methodology for qualitative model engineering , 1992, TOMC.

[9]  Louis Y. Tsui,et al.  A microcomputer based decision support tool for assigning dock doors in freight yards , 1990 .

[10]  Radu F. Babiceanu,et al.  Development and Applications of Holonic Manufacturing Systems: A Survey , 2006, J. Intell. Manuf..

[11]  Bruce M. Woodworth,et al.  A HEURISTIC ALGORITHM FOR RESOURCE LEVELING IN MULTI-PROJECT, MULTI-RESOURCE SCHEDULING , 1975 .

[12]  Nils Boysen,et al.  Truck scheduling at zero-inventory cross docking terminals , 2010, Comput. Oper. Res..

[13]  Dirk Cattrysse,et al.  Intelligent Products in the Supply Chain Are Merging Logistic and Manufacturing Operations , 2011 .

[14]  Hendrik Van Brussel,et al.  On Applying the PROSA Reference Architecture in Multiagent Manufacturing Control Applications , 2006, Multiagent Systems and Software Architecture.

[15]  Douglas L. McWilliams.  Genetic-based scheduling to solve the parcel hub scheduling problem , 2009, Comput. Ind. Eng..

[16]  Vincent C. S. Wiers,et al.  The complexity of scheduling in practice , 1996 .

[17]  Hendrik Van Brussel,et al.  Intelligent Products: Intelligent Beings or Agents? , 2008, BASYS.

[18]  Hendrik Van Brussel,et al.  Engineering manufacturing control systems using PROSA and delegate MAS , 2008, Int. J. Agent Oriented Softw. Eng..

[19]  Hendrik Van Brussel,et al.  Networked manufacturing control: An industrial case , 2010 .

[20]  Rachid Alami,et al.  An Architecture for Autonomy , 1998, Int. J. Robotics Res..

[21]  Stéphane Viollet,et al.  Toward Optic Flow Regulation for Wall-Following and Centring Behaviours , 2006 .

[22]  Paul Valckenaers,et al.  Holonic Manufacturing Execution Systems , 2005 .

[23]  Erik Demeulemeester,et al.  A branch-and-bound procedure for the multiple resource-constrained project scheduling problem , 1992 .

[24]  Tara Estlin,et al.  CLARAty: Challenges and Steps toward Reusable Robotic Software , 2006 .

[25]  Luc Bongaerts,et al.  Holonic manufacturing systems: - architectural and manufacturing control issues , 2000 .

[26]  Hendrik Van Brussel,et al.  Intelligent products: Agere versus Essere , 2009, Comput. Ind..

[27]  Sanjay E. Sarma,et al.  Auto ID systems and intelligent manufacturing control , 2003 .

[28]  Michael Luck,et al.  Multi-Agent Systems and Applications , 2001, Lecture Notes in Computer Science.

[29]  John J. Bartholdi,et al.  Reducing Labor Costs in an LTL Crossdocking Terminal , 2000, Oper. Res..

[30]  Tom Holvoet,et al.  Beliefs, desires and intentions through the environment , 2006, AAMAS '06.

[31]  Danny Weyns,et al.  Patterns of Delegate MAS , 2009, 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems.

[32]  Hendrik Van Brussel,et al.  A Case Study for Modular Plant Control , 2003, HoloMAS.

[33]  Hendrik Van Brussel,et al.  Multi-agent Coordination and Control Using Stigmergy Applied to Manufacturing Control , 2001, EASSS.

[34]  Hendrik Van Brussel,et al.  Multi-Agent Manufacturing Control: An Industrial Case Study , 2003 .

[35]  Hendrik Van Brussel,et al.  Pheromone based emergent shop floor control system for flexible flow shops , 1999, Artif. Intell. Eng..

[36]  Hendrik Van Brussel,et al.  PROSA and Delegate MAS in Robotics , 2011, HoloMAS.

[37]  Kees Jan Roodbergen,et al.  Positioning of goods in a cross-docking environment , 2008, Comput. Ind. Eng..

[38]  Dirk Cattrysse,et al.  Towards holonic control for cross-docks , 2010 .

[39]  Botond Kádár,et al.  Agent Based Architectures for Mastering Changes and Disturbances in Manufacturing , 1998, IEA/AIE.

[40]  Dirk Cattrysse,et al.  Bio-inspired coordination and control in self-organizing logistic execution systems , 2011, 2011 9th IEEE International Conference on Industrial Informatics.

[41]  Luc Bongaerts,et al.  Reference architecture for holonic manufacturing systems: PROSA , 1998 .

[42]  Hans Wortmann,et al.  Planning systems in the next century ( I ) , 1997 .

[43]  Alex J. Ruiz-Torres,et al.  Scheduling with flexible resources in parallel workcenters to minimize maximum completion time , 2007, Comput. Oper. Res..

[44]  Gilbert Laporte,et al.  Vehicle routing with cross-docking , 2009, J. Oper. Res. Soc..

[45]  Hendrik Van Brussel,et al.  A multi-agent supply network control framework , 2007 .