A systematic approach for supply chain conflict detection with a hierarchical Petri Net extension

Coordinating and managing distributed entities in a supply chain is a challenging task due, in part, to conflicts present in such systems. If not handled effectively, the conflict can degrade the performance of the system as a whole due to the fact that each individual entity may be working towards goals that sub-optimize the integrated system. Therefore, the ability to discover conflicts would be a valuable asset, particularly if the discovery occurred proactively. This paper presents a methodology, extending the concept of basic Petri Nets, to discover supply chain conflict before they occur and cause detrimental effects to system performance. The approach involves linking hierarchical levels of the supply chain system and detecting conflicts occurring when the single entities, each optimized for it own operations, are combined together in a supply chain. These conflicts are not obvious or intuitive in examining the single entities of the supply chain, but when integrated the conflicts are discovered by the methodology. We applied the proposed methodology on a real-world supply chain to illustrate the validity of the tool. Although, further research is needed to fully explore this method of conflict detection, we believe that this research does indeed provide some much needed insight into the daunting task of conflict discovery and therefore proactive handling of these potentially negative occurrences in the supply chain.

[1]  Srini Ramaswamy,et al.  Conflict detection during plan integration for multi-agent systems , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[2]  K. B. Hendricks,et al.  An Empirical Analysis of the Effect of Supply Chain Disruptions on Long‐Run Stock Price Performance and Equity Risk of the Firm , 2005 .

[3]  Paul Chapman,et al.  Identifying and Managing Supply Chain Vulnerability , 2002 .

[4]  A. Tuma,et al.  Using Fuzzy-Directed Agents For Ecological Production Control , 2000, Intell. Autom. Soft Comput..

[5]  Jennifer Blackhurst,et al.  Network-based approach to modelling uncertainty in a supply chain , 2004 .

[6]  Orlando Belo,et al.  Modeling multi-agent systems activities through colored petri nets : an industrial production system case study , 1998 .

[7]  Larry J. Rosenberg,et al.  Toward the Analysis of Conflict in Distribution Channels: A Descriptive Model , 1970 .

[8]  K. Suzanne Barber,et al.  Conflict detection during plan integration based on E-PERT diagrams , 2000, AGENTS '00.

[9]  Daniel Moldt,et al.  Multi-Agent-Systems Based on Coloured Petri Nets , 1997, ICATPN.

[10]  Louis W. Stern,et al.  Distribution channels : behavioral dimensions , 1970 .

[11]  Emil C. Lupu,et al.  Conflicts in Policy-Based Distributed Systems Management , 1999, IEEE Trans. Software Eng..

[12]  Oh Byung Kwon,et al.  A multi-agent intelligent system for efficient ERP maintenance , 2001, Expert Syst. Appl..

[13]  Douglas H. Norrie,et al.  Schema-based conversation modeling for agent-oriented manufacturing systems , 2001, Comput. Ind..

[14]  David F. Pyke,et al.  Multiproduct integrated production—distribution systems☆ , 1994 .

[15]  I. Mitroff,et al.  Preparing for evil. , 2003, Harvard business review.

[16]  Jose Ceroni,et al.  Conflict detection and resolution in distributed design , 2003 .

[17]  MengChu Zhou,et al.  Petri Nets in Flexible and Agile Automation , 1995 .

[18]  James F. Peters,et al.  Coordination of Multiagent Systems with Fuzzy Clocks , 1996 .

[19]  Mike Wright,et al.  Petri net-based modelling of workflow systems: An overview , 2001, Eur. J. Oper. Res..

[20]  S. Chopra,et al.  Managing Risk To Avoid Supply-Chain Breakdown , 2004 .

[21]  Zhibin Jiang,et al.  Supply chain workflow modelling using XML-formatted modular petri nets , 2003 .

[22]  Norio Akamatsu,et al.  A neuro-expert system with a conflict-resolving meta-neural network , 1995 .

[23]  Walter W.C. Chung,et al.  Networked enterprise: A new business model for global sourcing , 2004 .

[24]  Peter Kemper,et al.  Supply chain modelling and its analytical evaluation , 2002, J. Oper. Res. Soc..

[25]  Hsu-Pin Ben Wang,et al.  Conflict detection of automated guided vehicles: a Petri net approach , 1991 .

[26]  MengChu Zhou,et al.  Petri nets and industrial applications: A tutorial , 1994, IEEE Trans. Ind. Electron..

[27]  Nukala Viswanadham,et al.  Performance analysis and design of supply chains: a Petri net approach , 2000, J. Oper. Res. Soc..

[28]  Charles J. Corbett,et al.  Stochastic Inventory Systems in a Supply Chain with Asymmetric Information: Cycle Stocks, Safety Stocks, and Consignment Stock , 2001, Oper. Res..

[29]  J. Venkateswaran,et al.  Impact of modelling approximations in supply chain analysis – an experimental study , 2004 .

[30]  Ming Jian Zuo,et al.  Object-oriented Petri nets with changeable structure (OPNs-CS): analysis on conflicts and deadlocks , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[31]  Dong Yue,et al.  The data mining research of time-series of flow supply chain , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).

[32]  Nicholas R. Jennings,et al.  Foundations of distributed artificial intelligence , 1996, Sixth-generation computer technology series.

[33]  M. Christopher,et al.  Supply chain risk management: outlining an agenda for future research , 2003 .

[34]  Maria Pia Fanti,et al.  Complex Token Petri nets , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[35]  MengChu Zhou,et al.  Introduction to Petri Nets in Flexible and Agile Automation , 1995 .

[36]  Kevin B. Hendricks,et al.  Association Between Supply Chain Glitches and Operating Performance , 2005, Manag. Sci..

[37]  F. Caniato,et al.  Building a Secure and Resilient Supply Chain , 2003 .

[38]  G. Zsidisin,et al.  An Agency Theory Investigation of Supply Risk M anagement , 2003 .

[39]  MengChu Zhou,et al.  A hybrid methodology for synthesis of Petri net models for manufacturing systems , 1992, IEEE Trans. Robotics Autom..

[40]  Mu-Chen Chen,et al.  An association-based clustering approach to order batching considering customer demand patterns , 2005 .

[41]  Feng Chu,et al.  Batch deterministic and stochastic Petri nets. A tool for modeling and performance evaluation of supply chain , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[42]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[43]  Nukala Viswanadham,et al.  Robust supply chain design: a strategic approach for exception handling , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[44]  Kim Seung-Chul,et al.  Flexible bed allocation and performance in the intensive care unit , 2000 .

[45]  Hau L. Lee,et al.  Material Management in Decentralized Supply Chains , 1993, Oper. Res..

[46]  Kevin B. Hendricks,et al.  The effect of supply chain glitches on shareholder wealth , 2003 .

[47]  Chen Ning,et al.  Discovery of sequential patterns from large database in supply chain , 2000, Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393).

[48]  Haiping Xu,et al.  An agent-based Petri net model with application to seller/buyer design in electronic commerce , 2001, Proceedings 5th International Symposium on Autonomous Decentralized Systems.

[49]  Amy P. Felty,et al.  Feature specification and automated conflict detection , 2003, TSEM.

[50]  Hee-Woong Kim,et al.  Modeling Inter- and Intra-Organizational Coordination in Electronic Commerce Deployments , 2001, Inf. Technol. Manag..

[51]  Kunihiko Hiraishi,et al.  A Petri-net-based model for the mathematical analysis of multi-agent systems , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[52]  Ming Dong,et al.  Process modeling and analysis of manufacturing supply chain networks using object-oriented Petri nets , 2001 .

[53]  Nicholas R. Jennings,et al.  Coordination techniques for distributed artificial intelligence , 1996 .