Abstract
Supply chain risk management (SCRM) is considered increasingly important for strategic decision making in manufacturing firms around the world. Bayesian Belief Networks (BBN) provide a means to probabilistically and quantitatively represent the risks present in the supply chain and to proactively manage their vulnerabilities. To model supply chain activities, discrete event simulation (DES) modeling has been a widely used tool. Combining these two methods of analysis could provide companies with an incredibly powerful tool for proactive SCRM. This paper presents the development of such an approach. BBN based risk modeling has been conducted for an industrial partner. In parallel, a discrete event simulation model of supply chain activities has been developed. Probabilities of changes in supply chain KPIs obtained from the risk model are used to quantitatively inform the DES. In this way, a means to analyze the dynamic impact of risk on supply chain performance has been demonstrated.
| Original language | English |
|---|---|
| State | Published - 2013 |
| Event | 22nd International Conference on Production Research, ICPR 2013 - Parana, Brazil Duration: Jul 28 2013 → Aug 1 2013 |
Conference
| Conference | 22nd International Conference on Production Research, ICPR 2013 |
|---|---|
| Country/Territory | Brazil |
| City | Parana |
| Period | 7/28/13 → 8/1/13 |
Keywords
- Bayesian belief network
- Discrete event simulation
- Risk assessment
- Supply chain risk management
ASJC Scopus subject areas
- Computer Science Applications
- Industrial and Manufacturing Engineering
- Control and Systems Engineering