Wim Laurier, 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

6. EVALUATION SCENARIO

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. DATA MODEL

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)