Samantha Islam
University of Cambridge
9 Papers
7 Citations
Samantha Islam is an academic researcher from University of Cambridge. The author has contributed to research in topics: Supply chain & Traceability. The author has an hindex of 4, co-authored 9 publications. Previous affiliations of Samantha Islam include VIT University & Monash University Malaysia Campus.
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Papers
Review on life cycle inventory: methods, examples and applications
TL;DR: In this article, a review on LCI evolution and their various methodological developments are presented along with numerical examples, advantages, disadvantages and application for choosing and applying an appropriate LCI method.
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Food traceability: A generic theoretical framework
TL;DR: In this paper traceability approaches are categorised by an iterative typology, as internal or external and the implementation of traceability systems is organised according to four consolidated principles: identification, data recording, data integration and accessibility.
93
Visualising food traceability systems: A novel system architecture for mapping material and information flow
TL;DR: A novel, material and information flow modelling technique, to visualise FTS architecture, which can support common understanding and iterative implementation of effective FTSs that contextualise food supply chains at multiple levels and provides opportunity to identify points at where inefficiencies can occur so that actions can be taken to mitigate them.
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A Hybrid Traceability Technology Selection Approach for Sustainable Food Supply Chains
TL;DR: A hybrid approach combining the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with integer linear programming to select the optimum traceability technologies for improving sustainable performance in cold food supply chains is presented.
20
Energy management strategy for industries integrating small scale waste-to-energy and energy storage system under variable electricity pricing
TL;DR: In this article, a fuzzy inference system based energy management strategy to produce electricity in low pricing period and utilize it in peak period is proposed by integrating small scale waste-to-energy (WtE) and storage into industry system.
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