Supply chain lessons from the catastrophic natural disaster in Japan

Park, Youngwon; Hong, Paul; Roh, James Jungbae

doi:10.1016/j.bushor.2012.09.008

Cited by 204 publications

(103 citation statements)

References 17 publications

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“…Considering that many real supply networks are highly intertwined (Atalay et al, ; Brintrup et al, ), this constitutes a major challenge for stability. For instance, the disruption in the supply of a specific paint pigment from a common supplier deep in the network led to an industry‐wide cascade in the automotive industry (Park, Hong, & Roh, ). Strategies such as strong aggregate capacity planning processes, multisourcing, and investment in capacity “cushions,” may be advocated to address or mitigate the effects of such instabilities.…”

Section: Resultsmentioning

confidence: 99%

Identifying dynamical instabilities in supply networks using generalized modeling

Demirel

MacCarthy

Ritterskamp

et al. 2019

J of Ops Management

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Supply networks need to exhibit stability in order to remain functional. Here, we apply a generalized modeling (GM) approach, which has a strong pedigree in the analysis of dynamical systems, to study the stability of real‐world supply networks. It goes beyond purely structural network analysis approaches by incorporating material flows, which are defining characteristics of supply networks. The analysis focuses on the network of interactions between material flows, providing new conceptualizations to capture key aspects of production and inventory policies. We provide stability analyses of two contrasting real‐world networks—that of an industrial engine manufacturer and an industry‐level network in the luxury goods sector. We highlight the criticality of links with suppliers that involve the dispatch, processing, and return of parts or sub‐assemblies, cyclic motifs that involve separate paths from a common supplier to a common firm downstream, and competing demands of different end products at specific nodes. Based on a critical discussion of our findings in the context of the supply chain management literature, we generate five propositions to advance knowledge and understanding of supply network stability. We discuss the implications of the propositions for the effective management, control, and development of supply networks. The GM approach enables fast screening to identify hidden vulnerabilities in extensive supply networks.

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Section: Resultsmentioning

confidence: 99%

Identifying dynamical instabilities in supply networks using generalized modeling

Demirel

MacCarthy

Ritterskamp

et al. 2019

J of Ops Management

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show abstract

“…, 4 ), where ∈ , ∈ (see Table 1). The local nondisruption probability (level = 3), 3 Given local nondisruption probabilities, 3 , ∈ , the probabilities for the remaining local disruption levels = 0, 1, 2 were calculated as follows: Thus, 0 ≤ 1 ≤ 2 ≤ 3 , which reflects a realworld relation among probabilities of disruption occurrence at different levels (e.g., [8]). …”

Section: Computational Examplesmentioning

confidence: 99%

“…While the probability of flow disruptions is very low, their business impact can be huge. For example, flow disruptions in the electronics supply chains due to the great East Japan earthquake of 11 March 2011 and then the catastrophic October flooding in Thailand, where many component manufacturers were concentrated, resulted in huge losses of major electronics producers (e.g., Park et al [3] and Haraguchi and Lall [4]). Similar losses were experienced by the automotive industry (e.g., Fujimoto and Park [5], Matsuo [6], and Marszewska [7]).…”

Section: Introductionmentioning

confidence: 99%

Stochastic versus Deterministic Approach to Coordinated Supply Chain Scheduling

Sawik

2017

Mathematical Problems in Engineering

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The purpose of this paper is to consider coordinated selection of supply portfolio and scheduling of production and distribution in supply chains under regional and local disruption risks. Unlike many papers that assume the all-or-nothing supply disruption pattern, in this paper, only the regional disruptions belong to the all-or-nothing disruption category, while for the local disruptions all disruption levels can be considered. Two biobjective decision-making models, stochastic, based on the wait-and-see approach, and deterministic, based on the expected value approach, are proposed and compared to optimize the trade-off between expected cost and expected service. The main findings indicate that the stochastic programming wait-and-see approach with its ability to handle uncertainty by probabilistic scenarios of disruption events and the much simpler expected value problem, in which the random parameters are replaced by their expected values, lead to similar expected performance of a supply chain under multilevel disruptions. However, the stochastic approach, which accounts for all potential disruption scenarios, leads to a more diversified supply portfolio that will hedge against a variety of scenarios.

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“…Among its main products are microcomputers, memories, large-scale integrated circuits and logic integrated circuits that are used in a number of industries. Renesas supplies between 20 to 40 percent of automotive microcontrollers worldwide [27,28,29,30,31]. These microcontrollers are a critical part of engine-control units, transmission controls, safety devices, navigation and communications within a car and are highly customized [27,32].…”

Section: The Renesas Casementioning

confidence: 99%

Transferability of Self-Healing Principles to the Recovery of Supply Network Disruptions – The Case of Renesas Electronics

Brüning¹,

Buchholz²,

Bendul³

2014

Procedia CIRP

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The topic of supply network disruption recovery has started to receive great attention within the academic as well as the business world. This is due to increasingly complex supply networks and the rise of natural and man-made disasters in quantity and severity. In this paper, the topic is approached in an interdisciplinary bio-inspired way. The transferability of biological self-healing principles to the recovery of supply network disruptions is analysed and first propositions are derived. A single case study of the Japanese microcontroller company Renesas Electronics is analysed with regard to the developed propositions. A strategically important plant of Renesas was severely damaged by the triple disaster in Japan in 2011 which led to a disruption of the company's supply network. Five out of six propositions regarding the transferability of biological self-healing are, at least partly, proven. Furthermore, the importance of close collaboration within a network of suppliers, customers and competitors is emphasized. The results make further research in this academically still underdeveloped field promising, especially with regard to implications and strategies for supply chain risk managers.

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Supply chain lessons from the catastrophic natural disaster in Japan

Cited by 204 publications

References 17 publications

Identifying dynamical instabilities in supply networks using generalized modeling

Identifying dynamical instabilities in supply networks using generalized modeling

Stochastic versus Deterministic Approach to Coordinated Supply Chain Scheduling

Transferability of Self-Healing Principles to the Recovery of Supply Network Disruptions – The Case of Renesas Electronics

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