Dynamic assessment of control system designs of information shared supply chain network experiencing supplier disruption

Thomas, Anu; Mahanty, Biswajit

doi:10.1007/s12351-018-0435-9

Cited by 12 publications

(8 citation statements)

References 92 publications

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“…ALX (Ivanov, 2019 ) and MATLAB Simulink (Thomas & Mahanty, 2021 ) are widely used to solve disruption problems fulfilling the above criteria. We selected the ALX tool due to its end-to-end supply chain analytics feature (Dolgui & Ivanov, 2021 ; Ivanov, 2019 ).…”

Section: Methodsmentioning

confidence: 99%

“…Optimization (He & Zhuang, 2016 ) and simulation (Thomas & Mahanty, 2021 ) are fundamental approaches to solving CSC disruption. Optimization and simulation were traditionally used separately (EI Raoui et al, 2018a ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Some studies recommend reconfiguring the supply chain is the most common method to reduce operational and distribution risks (Durowoju et al, 2021 ). Thomas and Mahanty ( 2021 ) stated that those firms who identify CSC disruption early and reconfigure the process on time have efficiently worked over their competitors because they secure the materials and information from different suppliers to ensure a win–win situation. A win–win situation is achieved through profound and substantial research that helps understand resiliency and agility across the two stages, i.e., during the lockdown and “New Normal” (Caballero-Morales, 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

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RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

et al. 2023

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The global–local supply chains are affected by the forward and downward propagation of COVID-19. The pandemic disruption is a low-frequency and high-impact (black swan) event. Adapting to the “New Normal” situation requires adequate risk mitigation strategies. This study proposes a methodology to implement a risk mitigation strategy during supply chain disruptions. Random demand accumulation strategies are considered to identify the disruption-driven challenges under different pre and post-disruption scenarios. The best mitigation strategy and the optimal location of distribution centers to maximize the overall profit were determined using simulation-based optimization, greenfield analysis, and network optimization techniques. The proposed model is then evaluated and validated using appropriate sensitivity analysis. The main contribution of the study is to (i) perform cluster-based supply chain disruption analysis, (ii) propose a resilient and flexible model to illustrate the proactive and reactive measures for the ripple effect, (iii) prepare the supply chain for future pandemic-like crises, and (v) reveal the relationship between the pandemic impact and supply chain resilience. A case study of an ice cream manufacturer is used to demonstrate the proposed model.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

et al. 2023

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“…e companies seek to increase the SC performance that prevents vulnerability [22]. e importance of accessing and sharing supply chain disruption information is essential for the proper deployment of disruption reduction strategies [23]. Because of the importance of this issue and reduction of systems' disruption effects, the authors of [24][25][26] examined the disruption recovery problems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraints (23) expresses that it is possible to use overcapacity of suppliers that are not disrupted under any disruption scenario, and the total amount of order of raw material cannot exceed the supplier's capacity.…”

Section: Mathematical Modelmentioning

confidence: 99%

A Robust Mathematical Model for Sustainable and Resilient Supply Chain Network Design: Preparing a Supply Chain to Deal with Disruptions

et al. 2021

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Supply chains suffer from serious vulnerabilities and disruptions with increasing global crises, including pandemics and natural disasters. Dynamic and complex supply chain environments have constantly led companies to modern management approaches such as resilience to address disruptions. Besides, the sustainability approach enhances the strength of the supply chain in disruptions by considering economic, social, and environmental aspects. This paper develops a mathematical model for designing a supply chain network considering resilience and sustainability. In this model, suppliers were exposed to disruption with different probabilities. The model has three objectives: minimizing total costs and maximizing suppliers’ social and environmental scores. A robust scenario-based stochastic programming approach has been used for potential disruption scenarios. The multiobjective model is solved by the ε -constraint method in GAMS software. The numerical results show the performance of the model in a different situation. Also, the robust scenario-based stochastic programming approach allows the average performance of the supply chain in each objective to improve.

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Modelling Critical Success Factors for the Implementation of Industry 4.0 in Indian Manufacturing MSMEs

Mohanta

Mahanty

2021

IFIP Advances in Information and Communication Technology

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Dynamic assessment of control system designs of information shared supply chain network experiencing supplier disruption

Cited by 12 publications

References 92 publications

RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

A Robust Mathematical Model for Sustainable and Resilient Supply Chain Network Design: Preparing a Supply Chain to Deal with Disruptions

Modelling Critical Success Factors for the Implementation of Industry 4.0 in Indian Manufacturing MSMEs

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