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A Material Requirements Planning System for Integrated Supply Chains

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Wim Laurier, A Material Requirements Planning System for Integrated Supply Chains

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A Material Requirements Planning System for Integrated Supply Chains

  1. 1. A MRP SYSTEM FORINTEGRATED SUPPLY CHAINS CONFENIS 2012, Ghent, September 20th 2012
  2. 2. GOALS• Implementation of supply chain synchronization strategies that abstract from enterprise boundaries • mitigate the bullwhip effect• Support decentralized and volatile organizational/supply chain models • stable IT environment in dynamic supply chain • replace failing or delayed supply chain partners at runtime• Shared data environment • Data reuse by all IS in the enterprise/supply chain
  3. 3. INFORMATION SYSTEM INTEGRATION• Many IS were not built to exchange information with other IS• Many IS have their own “ontology” • Mapping issues between application ontologies • Interface obsolescence: Termination business partnership • Interface inadequacy: New business partner
  4. 4. REQUIREMENTS• Single ontology (avoid mapping issues)• Harmonized data model (shared data environment) • Support customer and supplier role of each supply chain partner • Support process and exchange data• Data maintained by individual supply chain partners (decentralized) • Support an “outside” view on enterprise data• IS does not rely on predefined process/supply chain schema (volatile organizational/supply chain model)
  5. 5. APPROACH• REA Ontology (single ontology) • “Inside view” that covers • customer an supplier perspective on “exchanges” and • processes. • “Outside view” (ISO OeBTO standard)• Reuseof data-model for product traceability (data reuse) • Does not require a predefined process/supply chain schema • Allows abstraction from enterprise boundaries
  6. 6. EVALUATION SCENARIO
  7. 7. EVALUATION• Incorporation of lead times (∑event duration)• Incorporation of BOM and lot sizes (Q increment/decrement)• Incorporation of stock levels (QOH resource group) and forecasts• Order/forecast creates a wave of orders/forecasts throughout the supply chain (see Bullwhip effect) • The wave of orders can be weakened/stopped by (sufficient) stock levels or forecasts• Choice of “best” supplier among available suppliers (dynamic/ volatile supply chain)
  8. 8. DATA MODEL
  9. 9. CONCLUSION• It is possible to build a shared data environment that• integrates supply and demand information of several trading partners • “inside” and “outside” view on process/supply chain data (abstract from enterprise boundaries)• in a decentralized and • coordinated solely by messages between supply chain partners• dynamic/volatile supply chain • choice of supplier can vary without human interaction
  10. 10. FUTURE WORK• Implement visibility rules that protect an individual supply chain partner’s competitive advantage• Add modules to obtain an ERP system (e.g. capacity planning, forecasting)• Integrate MRP/ERP application with other REA-based applications (e.g. traceability, accounting) to build an enterprise/supply chain wide shared data environment• Expand the capabilities of the enterprise/supply chain wide information system (e.g. workflow management in the supply chain)

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