Palm biomass supply management : a predictive analysis tool

Tang, Jiang Ping (2018) Palm biomass supply management : a predictive analysis tool. PhD thesis, University of Nottingham.

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Abstract

The flourishing of oil palm industry has always been regarded as a double-edged sword. While it has significantly contributed to the economic growth, it is, nonetheless, disputably unsustainable as it is a land-intensive industry and causing disposal problems by leaving behind massive waste. To strengthening the industry’s competitive advantage and offsetting its drawbacks, this thesis presents a forward-looking framework – Biomass Supply Value Chain (BSVC)– to put emphasis on the value creation for the biomass industry. It aims to enhance the current biomass supply chain by harnessing the emerging technological advancement of artificial intelligence (AI), as well as by incorporating game theory to examine the strategic arrangement of the industry players. The proposed framework is capable of optimising the procurement process in the supply chain management: first, by identifying biomass properties for optimum biomass utilisation through the developed Biomass Characteristic Index (BCI); second, by applying AI into supply chain-related tasks for aiding better decision-making and problem-solving; and third, by adopting game theory in analysing strategic options, and providing appropriate strategies to minimise uncertainty and risk in procurement process. The “value” as suggested in the BSVC does not merely refer to a narrow economic sense, but is an all-encompassing value concerning non-monetary utility values, including sustainability, environmental preservation and the appreciation of the biomass industry.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Lam, Hon Loong
Keywords: biomass characteristics index, artificial neural network, game theory
Subjects: T Technology > TP Chemical technology
Faculties/Schools: UNMC Malaysia Campus > Faculty of Engineering
UNMC Malaysia Campus > Faculty of Engineering > Department of Chemical and Environmental Engineering
Item ID: 52325
Depositing User: TANG, JIANG PING
Date Deposited: 25 Jul 2018 04:40
Last Modified: 07 May 2020 18:02
URI: http://eprints.nottingham.ac.uk/id/eprint/52325

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