Supply Chain Risk Management: An Enterprise View and a Survey of Methods

Polyviou, Mikaella; Ramos, George; Schneller, Eugene S.

doi:10.1007/978-3-031-09183-4_2

International Series in Operations Research &Amp; Management Science

2022

DOI: 10.1007/978-3-031-09183-4_2

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Supply Chain Risk Management: An Enterprise View and a Survey of Methods

Mikaella Polyviou

George Ramos²,

Eugene S. Schneller³

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2023

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Cited by 1 publication

(3 citation statements)

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“…Internal sources generally include production delays, equipment breakdown, or accidents, while external sources mainly include pandemics, cyber-attacks, natural disasters, production or quality problems at the suppliers' plants, or transportation accidents [68].…”

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confidence: 99%

“…This stage of the process involves assessing these factors for the identified risks from the risk identification stage [66]. Additionally, in this stage, the risks are ranked based on the enterprise's risk threshold or tolerance [68].…”

mentioning

confidence: 99%

“…Risk monitoring: This stage involves assessing the efficacy of the risk treatment strategies that have been developed or implemented in the previous stage. It also includes identifying ways to improve and update the stages of the risk management process based on the learning gathered [66,68].…”

mentioning

confidence: 99%

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Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling

Faezipour,

Pourreza

2023

Sustainability

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The prevalence of skin diseases remains a concern, leading to a rising demand for the advancement of smart, portable, and non-invasive automated systems and applications. These sought-after technologies allow for the screening of skin lesions through captured images, offering improved and accessible healthcare solutions. Clinical methods include visual inspection by dermatologists; computer-aided vision-based image analysis at healthcare settings; and, lastly, biopsy tests, which are often costly and painful. Given the rise of artificial intelligence-based techniques for image segmentation, analysis, and classification, there remains a need to investigate the resiliency of personalized smartphone (hand-held) skin screening systems with respect to identified risks. This study represents a unique integration of distinct fields pertaining to smart vision-based skin lesion screening, resiliency, risk assessment, and system dynamics. The main focus is to explore the dynamics within the supply chain network of smart skin-lesion-screening systems. With the overarching aim of enhancing health, well-being, and sustainability, this research introduces a new framework designed to evaluate the resiliency of smart skin-lesion-screening applications. The proposed framework incorporates system dynamics modeling within a novel subset of a causal model. It considers the interactions and activities among key factors with unique mapping of capability and vulnerability attributes for effective risk assessment and management. The model has been rigorously tested under various case scenarios and settings. The simulation results offer insights into the model’s dynamics, demonstrating the fact that enhancing the skin screening device/app factors directly improves the resiliency level. Overall, this proposed framework marks an essential step toward comprehending and enhancing the overall resiliency of smart skin-lesion-screening systems.

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Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling

Faezipour,

Pourreza

2023

Sustainability

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Supply Chain Risk Management: An Enterprise View and a Survey of Methods

Cited by 1 publication

References 58 publications

Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling

Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling

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