An analysis of risks and vulnerabilities in supply networks

Sakli, Leila; Hennet, Jean-Claude; Mercantini, Jean-Marc

doi:10.3182/20140824-6-za-1003.02045

Cited by 7 publications

(8 citation statements)

References 12 publications

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“…These indicators tend to cluster around variability, inventory, lead time, performance (time and magnitude), and cost [21]. Indicators can also be used to counter the bullwhip effect, or the phenomenon in which forecasts yield supply chain inefficiencies which ultimately bring about vulnerabilities [24]. Fig.…”

Section: Supply Chain Model Developmentmentioning

confidence: 99%

Enabling better supply chain decisions through a generic model utilizing cause-effect mapping

Rovito

Rhodes

2016

2016 Annual IEEE Systems Conference (SysCon)

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Supply chains are critical to delivering components and products safely, affordably, and securely. However, these complex networks of suppliers, manufacturers, and customers are vulnerable to internal and external disruptions and subject to exploitation. This can result in adverse impacts to the system and inhibit value delivery. This paper presents a new generic electronics supply chain model that can reveal information regarding system vulnerabilities and opportunities for decisionmakers to intervene. The model draws upon a previouslydeveloped Cause-Effect Mapping (CEM) analytic technique and assists with making decisions affecting complex systems, including those operating in resource-constrained environments. Elements of System Security Engineering (SSE) and Trusted Systems and Networks (TSN) analysis are taken into consideration to provide a greater understanding of security concerns and impacts to a supply chain focusing on electronicsfor the defense industry. The model, adaptable to a diversity of systems and capable of recognizing non-obvious sources of vulnerability, can be used by systems engineers to provide a holistic view of a complex supply chain. The model facilitates the communication of information regarding supply chain vulnerabilities to decision-makers and other individuals, as described in specific use cases. *

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Section: Supply Chain Model Developmentmentioning

confidence: 99%

Enabling better supply chain decisions through a generic model utilizing cause-effect mapping

Rovito

Rhodes

2016

2016 Annual IEEE Systems Conference (SysCon)

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“…A study that generalizes this order policy was also proposed by Gilbert et al [17]. The ARMA model also allows the chain to represent a widely known vulnerability in the field of supply chain, known as the bullwhip effect [5] [16] [1]. It represents the amplification phenomenon of demand variability in the stages upstream in the supply chain.…”

Section: Model Of the Supply Chainmentioning

confidence: 99%

“…At the other end of the feasibility intervals, the level of the stock and the quantity delivered cannot have negative values. To take these constraints into account, Sakli et al [5] present a saturated ARMA model, in which the dynamic equations (2), (3) are replaced by the following non-linear equations.…”

Section: The Constrained Modelmentioning

confidence: 99%

“…In this research, we focus on uncertainties about the quality of supplied components and the demand, and try to analyze the vulnerability of the supply chain due to the variation in the quality of the product supplied. In a previous work [5], we have proposed a model based on ARMA time series to study supply chain vulnerabilities under demand uncertainty. The choice of ARMA time series can be argued by the fact that such model takes into account both the random nature of the system and its history.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, supply chains are sensitive to local disturbances and uncertainties related to demand [1] supplies [2] or information [3], [4]. Several studies have been conducted to analyze the topic of risk especially in the context of the supply chain [5] [6]. In general, risk is a combination of a probability of occurrence of an adverse event and a measure of the severity of the consequences of this event in terms of damage or injury (ISO / CEI73) [7].…”

Section: Introductionmentioning

confidence: 99%

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Impact of Changes in Quality of Deliveries on the Vulnerability of Supply Chains

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Risks and Resilience of Collaborative Networks

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Part 10: Performance and OptimizationInternational audienceThe main objectives of the study are to present the vulnerability of the supply chain related to the change in the quality of the products supplied, and propose solutions to mitigate its disturbance. We use ARMA (Auto Regressive Moving Average) time series to model a supply chain with one supplier and one retailer. We then analyze how changes in the quality of products delivered by the supplier may affect the system variables, taking into account the system constraints and the uncertain demand from customers. A quality predictor can then be introduced in the model to improve the resilience of the chain

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Pharmaceutical supply chain reliability and effects on drug shortages

Tucker

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2022

Computers & Industrial Engineering

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An analysis of risks and vulnerabilities in supply networks

Cited by 7 publications

References 12 publications

Enabling better supply chain decisions through a generic model utilizing cause-effect mapping

Enabling better supply chain decisions through a generic model utilizing cause-effect mapping

Impact of Changes in Quality of Deliveries on the Vulnerability of Supply Chains

Pharmaceutical supply chain reliability and effects on drug shortages

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