Identifying and mitigating supply chain risks using fault tree optimization. (1st February 2020)
- Record Type:
- Journal Article
- Title:
- Identifying and mitigating supply chain risks using fault tree optimization. (1st February 2020)
- Main Title:
- Identifying and mitigating supply chain risks using fault tree optimization
- Authors:
- Sherwin, Michael D.
Medal, Hugh R.
MacKenzie, Cameron A.
Brown, Kennedy J. - Abstract:
- Abstract: Although supply chain risk management and supply chain reliability are topics that have been studied extensively, a gap exists for solutions that take a systems approach to quantitative risk mitigation decision making and especially in industries that present unique risks. In practice, supply chain risk mitigation decisions are made in silos and are reactionary. In this article, we address these gaps by representing a supply chain as a system using a fault tree based on the bill of materials of the product being sourced. Viewing the supply chain as a system provides the basis to develop an approach that considers all suppliers within the supply chain as a portfolio of potential risks to be managed. Next, we propose a set of mathematical models to proactively and quantitatively identify and mitigate at-risk suppliers using enterprise available data with consideration for a firm's budgetary constraints. Two approaches are investigated and demonstrated on actual problems experienced in industry. The examples presented focus on Low-Volume High-Value (LVHV) supply chains that are characterized by long lead times and a limited number of capable suppliers, which make them especially susceptible to disruption events that may cause delays in delivered products and subsequently increase the financial risk exposure of the firm. Although LVHV supply chains are used to demonstrate the methodology, the approach is applicable to other types of supply chains as well. Results areAbstract: Although supply chain risk management and supply chain reliability are topics that have been studied extensively, a gap exists for solutions that take a systems approach to quantitative risk mitigation decision making and especially in industries that present unique risks. In practice, supply chain risk mitigation decisions are made in silos and are reactionary. In this article, we address these gaps by representing a supply chain as a system using a fault tree based on the bill of materials of the product being sourced. Viewing the supply chain as a system provides the basis to develop an approach that considers all suppliers within the supply chain as a portfolio of potential risks to be managed. Next, we propose a set of mathematical models to proactively and quantitatively identify and mitigate at-risk suppliers using enterprise available data with consideration for a firm's budgetary constraints. Two approaches are investigated and demonstrated on actual problems experienced in industry. The examples presented focus on Low-Volume High-Value (LVHV) supply chains that are characterized by long lead times and a limited number of capable suppliers, which make them especially susceptible to disruption events that may cause delays in delivered products and subsequently increase the financial risk exposure of the firm. Although LVHV supply chains are used to demonstrate the methodology, the approach is applicable to other types of supply chains as well. Results are presented as a Pareto frontier and demonstrate the practical application of the methodology. … (more)
- Is Part Of:
- IISE transactions. Volume 52:Number 2(2020)
- Journal:
- IISE transactions
- Issue:
- Volume 52:Number 2(2020)
- Issue Display:
- Volume 52, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 52
- Issue:
- 2
- Issue Sort Value:
- 2020-0052-0002-0000
- Page Start:
- 236
- Page End:
- 254
- Publication Date:
- 2020-02-01
- Subjects:
- Supply chain management -- risk -- optimization -- fault tree
Industrial engineering -- Periodicals
Systems engineering -- Periodicals
Industrial engineering
Systems engineering
Electronic journals
Periodicals
670.285 - Journal URLs:
- http://www.tandfonline.com/uiie ↗
http://www.tandfonline.com/openurl?genre=journal&stitle=uiie20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/24725854.2019.1630865 ↗
- Languages:
- English
- ISSNs:
- 2472-5854
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12143.xml