Supply chain optimization under risk and uncertainty: A case study for high-end server manufacturing

Aqlan, Faisal; Lam, Sarah S.

doi:10.1016/j.cie.2015.12.025

Cited by 84 publications

(51 citation statements)

References 20 publications

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“…However, the strategies in this discipline have not yet been clear about how to unify the management of knowledge systemically particularly in the aerospace industry. Alternative methods such as predictive models and risk mitigation have shown a strong capability to build knowledge repositories from past experiences [10]; but remain top down approaches and have not featured any designs of knowledge feedback systems to engineering teams for mitigating potential defect risks.…”

Section: Organizational Managementmentioning

confidence: 99%

Improving Design for Manufacturing implementation in knowledge intensive collaborative environments: An analysis of organisational factors in aerospace manufacturing

Souri

Gao

Owodunni

et al. 2017

2017 IEEE Technology &Amp; Engineering Management Conference (TEMSCON)

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Abstract-Today, the manufacturing industry is under pressure to be able to rapidly come up with innovative designs and produce them in much shorter timeframes in order to keep up with growing customer demands and quickly gain new business. One of the ways used to achieve shorter time to markets for new product developments is by using design for manufacturing (DFM) methods to reduce time and energy going into resolving manufacturing based defects. It is also more vital in today's manufacturing industry to make use of DFM methods much earlier in the product development lifecycle in order to prevent potentially known quality defects from happening and save on costs associated with late design changes. This requires enabling a more systemic feedback cycle of production data for the creation of DFM knowledge repositories as well as overcoming some wider knowledge sharing barriers across the organization. This investigation focuses on how the communications of manufacturing knowledge from production data is affected by factors within the overall organization. The investigation is one of the few that consider the influence of organizational factors on the communication of engineering knowledge as well as the related knowledge sharing barriers. The project is carried out empirically with a large UK based aerospace manufacturing company by gathering data primarily from observations and interviews. This paper presents the findings followed by discussions for improving DFM Knowledge Management in the aerospace industry.

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Section: Organizational Managementmentioning

confidence: 99%

Improving Design for Manufacturing implementation in knowledge intensive collaborative environments: An analysis of organisational factors in aerospace manufacturing

Souri

Gao

Owodunni

et al. 2017

2017 IEEE Technology &Amp; Engineering Management Conference (TEMSCON)

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show abstract

“…Ayvaz and Bolat (2014) formulated a general twophase probabilistic programming formulation to tackle uncertainties in reverse logistics network design. Aqlan and Lam (2016) presented a methodology and a software utility for SC optimization in the presence of uncertainty and risk. Their methodology involves solving a deterministic multiobjective model as well as using a simulation formulation to illustrate the stochastic elements of the SC.…”

Section: Scnd With Parameter Uncertaintymentioning

confidence: 99%

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

Shishebori

Babadi

2017

J Ind Eng Int

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This study investigates the reliable multi-configuration capacitated logistics network design problem (RMCLNDP) under system disturbances, which relates to locating facilities, establishing transportation links, and also allocating their limited capacities to the customers conducive to provide their demand on the minimum expected total cost (including locating costs, link constructing costs, and also expected costs in normal and disturbance conditions). In addition, two types of risks are considered; (I) uncertain environment, (II) system disturbances. A two-level mathematical model is proposed for formulating of the mentioned problem. Also, because of the uncertain parameters of the model, an efficacious possibilistic robust optimization approach is utilized. To evaluate the model, a drug supply chain design (SCN) is studied. Finally, an extensive sensitivity analysis was done on the critical parameters. The obtained results show that the efficiency of the proposed approach is suitable and is worthwhile for analyzing the real practical problems.

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“…manufacturing system) [1]. Simulation and optimization models can be combined through some iterative procedures to achieve the best values for risk reduction by selecting a combination of mitigation strategies [2]. lt is significant that most of the existing methodologies of risk management in production logistics lack inbuilt and practical techniques that take into consideration the complex interactions and dynamic feedback properties, which can meaningfully affect the reliability of risk management results (25].…”

Section: Related Workmentioning

confidence: 99%

Risk information formalisation with graphs

Kamsu-Foguem

Tiako

2017

Computers in Industry

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Supply chain optimization under risk and uncertainty: A case study for high-end server manufacturing

Cited by 84 publications

References 20 publications

Improving Design for Manufacturing implementation in knowledge intensive collaborative environments: An analysis of organisational factors in aerospace manufacturing

Improving Design for Manufacturing implementation in knowledge intensive collaborative environments: An analysis of organisational factors in aerospace manufacturing

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

Risk information formalisation with graphs

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