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A MRP SYSTEM FOR
INTEGRATED 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)

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A Material Requirements Planning System for Integrated Supply Chains

  • 1. A MRP SYSTEM FOR INTEGRATED SUPPLY CHAINS CONFENIS 2012, Ghent, September 20th 2012
  • 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. 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. 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. 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
  • 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)
  • 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. 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)