Research and Simulation of Supply Chain Disruption Based on Contract

Qi, Lian; Jia, Su

doi:10.4028/www.scientific.net/amm.380-384.4815

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…For example, it has been claimed that system dynamics may be the best way to study phenomena such as how a small fluctuation at one end of supply chain is amplified as it proceeds throughout the chain (Moraga et al, 2008). The importance of simulating supply chains using system dynamics has been emphasized in various studies (Lian & Jia, 2013), (Minegishi & Thiel, 2000), (Sterman, 2000) and (Towill, 1993). Aelker et al (2013) discuss how the trend towards globalization has increased the complexity involved in managing supply chains.…”

Section: Literature Reviewmentioning

confidence: 99%

Proactive inventory policy intervention to mitigate risk within cooperative supply chains

Kurano¹,

McKay²,

Black³

2014

10.5267/j.ijiec

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This exploratory paper will investigate the concept of supply chain risk management involving supplier monitoring within a cooperative supply chain. Inventory levels and stockouts are the key metrics. Key to this concept is the assumptions that (1) out-of-control supplier situations are causal triggers for downstream supply chain disruptions, (2) these triggers can potentially be predicted using statistical process monitoring tools, and (3) carrying excess inventory only when needed is preferable as opposed to carrying excess inventory on a continual basis. Simulation experimentation will be used to explore several supplier monitoring strategies based on statistical runs tests, specifically "runs up and down" and/or "runs above and below" tests. The sensitivity of these tests in detecting non-random supplier behavior will be explored and their performance will be investigated relative to stock-outs and inventory levels. Finally, the effects of production capacity and yield rate will be examined. Results indicate out-of-control supplier signals can be detected beforehand and stock-outs can be significantly reduced by dynamically adjusting inventory levels. The largest benefit occurs when both runs tests are used together and when the supplier has sufficient production capacity to respond to downstream demand (i.e., safety stock) increases. When supplier capacity is limited, the highest benefit is achieved when yield rates are high and, thus, yield loss does not increase supplier production requirements beyond its available capacity.

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Section: Literature Reviewmentioning

confidence: 99%