nust orssa 2011 k. r. chilumani, s. b. mangena, e. g. mtetwa
TRANSCRIPT
NUST
ORSSA 2011Supply Chain
Management Information Systems: An Artificial
Intelligence PerspectiveK. R. Chilumani, S. B. Mangena, E. G.
Mtetwa
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
1. Introduction2. Supply Chain Management Information
Systems Challenges3. A Common Ontology for Supply Chain
Management Information Systems4. Intelligent Agents 5. The Possible Solution6. Conclusion
Presentation Contents:
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Supply Chain Management is:matching supply and demand
profits and costsefficient integration
1. Introduction
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Information is very vital in the supply chain:
right place & time.efficiency (output : input)
customer demand.
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Integrated supply chain requires continuous information (Teigen & Fox, 1997).
forward flow of materials and backward flow of information
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Companies use Supply chain management information systems for e-business
business models and processes motivated by Information and Communication Technology
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
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disparate software/ hardware
incompatible data formats.Pools/silos of informationirregularities in data interchange
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
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Current integration solutions:Enterprise Integration Architecture◦Data Layer (database replication)
Business Process Management◦Information Portal
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
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Solution: Wrap / integrate heterogeneous systems
Common Ontology◦Knowledge representation
Intelligent Agents◦Data format conversion
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
2. Supply Chain Management Information Systems Challenges
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
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Proprietary Software applications
Subsystems(ERP, ASP, PDM) vendors.
business context and cultures
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
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restricted access to information
current environment requires shared information
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
incorporate available information to better efficient supply chain (Kadadevaramath et al, 2011).
information sharing in a non-invasive manner
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
3. A Common Ontology for Supply Chain Management Information Systems
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
shared understandingformalUsed by intelligent agents
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
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4. The Intelligent Agents
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Objective functionPeer reviewLearn
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
5. The Possible Solution: supply chain management software and intelligent agents
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Heterogeneous systems (1, 2, ..., N).
Native autonomous Intelligent Agents i, ii, ..., n
human counterparts
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Integrated Heterogeneous Systems Architecture
System 1
System N
Intelligent Agent i
Intelligent Agent n
Common Ontology
Artificial Intelligence
System
Intelligent Agent ii
System 2
E-Business System
…
…
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
1. EDI guidelines/Standards VS non-invasive
2. scalability & flexibility VS robust/ Learning
3. coded parameters VS inference notifications
Enterprise Integration Architecture or Business Process Management feature VSImprovement offer by Intelligent Agents
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
4. switch to other internet applications VS profitable features such as searching and filtering of documents on the internet.
5. past with restricted access VS current shared information environment.
Enterprise Integration Architecture or Business Process Management feature VSImprovement offer by Intelligent Agents
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
information flow challenges in e-business systems that have heterogeneous architectures can be circumvented by using intelligent agents that are aware of a common ontology.
6. Conclusion
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
This approach answers the question of where and how we can improve the supply chain management information systems interoperability.
6. Conclusion (cont.)
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
The impact of seamlessly passing information:
Reduction of the bullwhip effect.
Ease of collaboration.Catalysis of globalisation.
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
The ability to make useful inferences to help supply chain executives is an added advantage of the use of intelligent agents.
6. Conclusion (end)
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Fikes, R. & Farquahr, A. (1999) Distributed Repositories of Highly Expressive Reusable Ontologies. IEEE Intelligent Systems and their Applications, 14 (2), 73-79.
Gruber, T. R. (1995) Toward Principles for the Design of Ontologies Used for Knowledge Sharing. International Journal Human-Computer Studies, 43 (5-6), 907-928.
Iosif, V. Mika, P. Larsson, R. Akkermans, H. & Sure, Y. (2003) Handbook on Ontologies in Information Systems. In: Ontology-based Content Management in a Virtual Organization, Series International Handbooks on Information Systems, Verlag, Berlin D, Springer, 447–471.
References
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Kadadevaramath, R., Mohanasundaram, K.M., Rameshkumar, K., Chandrashekhar, B. (2011) Multi Echelon Supply Chain Optimization Using Particle Swarm Intelligence Algorithm, Journal for Manufacturing Science and Production, 8(2-4), 199–212.
Pena, J. (2008) e-Business and the Supply Chain Management, Business Intelligence Journal, 1, 77-90.
Rosse, C. & Mejino, J. L. V. Jr. (2003) A Reference Ontology for Bioinformatics: The Foundational Model of Anatomy, Journal of Biomedical Informatics, 36, 478–500.
References (cont.)
Supply Chain Management Information Systems: An Artificial Intelligence PerspectiveNUST
ORSSA 2011
Sato G. Y., Silva de Azevedo H. J., Barthès J. A. (2011) Agent and multi-agent applications to support distributed communities of practice: a short review, Autonomous Agents and Multi-Agent Systems, 23.
Teigen, R. & Fox, M. S. (1997), Agent Based Design and Simulation of Supply Chain Systems. Proceedings of WET-ICE, IEEE Computer Society Press.
References (end)
NUST
ORSSA 2011
Thank You
Supply Chain Management Information Systems: An Artificial
Intelligence Perspective