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Alok K. Choudhary
Researcher at Loughborough University
Publications - 69
Citations - 2719
Alok K. Choudhary is an academic researcher from Loughborough University. The author has contributed to research in topics: Supply chain & Knowledge extraction. The author has an hindex of 26, co-authored 65 publications receiving 2154 citations. Previous affiliations of Alok K. Choudhary include King Saud University & National Institute of Foundry and Forge Technology.
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Data mining in manufacturing: a review based on the kind of knowledge
TL;DR: There is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years, and a review of the literature reveals the progressive applications and existing gaps identified.
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Value stream mapping to reduce the lead-time of a product development process
TL;DR: It is expected that the VSM framework will help the development teams to reduce the PD lead-time by 50% and exploit lean thinking concepts in order to manage, improve and develop the product faster while improving or at least maintaining the level of performance and quality.
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Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach
TL;DR: A novel two-stage hybrid solution methodology is proposed that allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design.
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Risks in Enterprise Cloud Computing: The Perspective of it Experts
TL;DR: The most critical top 10 risks perceived by IT experts were found to be caused by current legal and technical complexity and deficiencies associated with cloud computing, as well as by a lack of preparation and planning of user companies.
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Tactical supply chain planning under a carbon tax policy scheme: A case study
TL;DR: In this article, a tactical supply chain planning model that integrates economic and carbon emission objectives under a carbon tax policy scheme is presented, where a modified cross-entropy solution method is adopted to solve the proposed nonlinear supply-chain planning model.