A Material Requirements Planning System for Integrated Supply Chains
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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

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

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A Material Requirements Planning System for Integrated Supply Chains A Material Requirements Planning System for Integrated Supply Chains Presentation Transcript

  • A MRP SYSTEM FORINTEGRATED SUPPLY CHAINS CONFENIS 2012, Ghent, September 20th 2012
  • 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
  • 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
  • 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)
  • 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
  • EVALUATION SCENARIO
  • 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)
  • DATA MODEL
  • 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
  • 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)