Modelling, simulation and evaluation of centralised and decentralised food manufacturing scenarios

Almena-Ruiz, Alberto ORCID: 0000-0003-0497-3232 (2020). Modelling, simulation and evaluation of centralised and decentralised food manufacturing scenarios. University of Birmingham. Ph.D.

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Abstract

Current long-rigid centralized supply chains, responsible for high energy consumption and environmental impact, might become outdated in a near future. Many theoretical studies, predicting a shift on companies’ strategical approach to the market based on scaling down and decentralization to reach mass differentiation, can be found in literature.

This work demonstrates that the shift on manufacturing paradigm can be studied as an engineering problem. Process system engineering methodology is implemented to develop a modelling tool, capable to generate trusted practical data for common and alternative manufacturing scale scenarios with increasing degree of decentralisation, i.e. Single plant production, Multiple plant production, Distributed Manufacturing, Food Incubator, and Home manufacturing. The tool is used to perform a techno-economic and environmental assessment for three food products of distinct characteristics, namely dry cereal porridge, sandwich bread and ice cream. The processing alternatives are first designed and studied separately for each food, to identify the benefits and tradeoffs associated to decentralised production methods. Variations on economic, social and environmental impact parameters along a wide range of production rates –e.g. 0.01 to 50,000 kg/h– are evaluated, and a UK demand framework is used to check the performance of the alternative production methods in a realistic scenario. A final comparison among the three items is performed to study how each scale differently functions for the production of each food studied.

The output of this research is to offer a robust tool that might assist companies in the complex decision between centralized or decentralized manufacturing systems for real market opportunities.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):