Cloud Manufacturing Model to Optimise Manufacturing Performance

PhD Thesis


Francis Xavier, R. 2019. Cloud Manufacturing Model to Optimise Manufacturing Performance. PhD Thesis University of East London School of Architecture, Computing and Engineering
AuthorsFrancis Xavier, R.
TypePhD Thesis
Abstract

Being predicted as the future of modern manufacturing, cloud-based manufacturing has drawn the attention of researchers in academia and industry. Researches are being done towards transforming every service in to cloud based service-oriented manufacturing mode in the manufacturing industry. There are many challenges that would arise when travelling towards this paradigm shift which is being addressed by researchers, but there are very few researches that concentrate on the elastic capability of cloud. Elastic capability makes this paradigm unique from all the other approaches or technologies. If elasticity is not achievable then the necessity of migrating to cloud is unnecessary. So, it is imperative to identify if at all it is necessary to adopt cloud-based manufacturing mode and discuss the issues and challenges that would arise to achieve elasticity when shifting to this emerging manufacturing paradigm. This research explores the importance of adopting cloud-based manufacturing mode to improve manufacturing performance based on the competitive priorities such as cost, quality, delivery and flexibility and proposes an elasticity assessment tool to be included in the cloud-based manufacturing model for the users to assess the challenges and issues on the realisation of elasticity on the context of manufacturing, which is the novelty of this research. The contribution to knowledge is a clear understanding of the necessity of cloud based elastic manufacturing model in the manufacturing environment for the manufacturing SMEs to gain a competitive advantage by achieving the competitive priorities such as low-cost, high-quality, and on-time delivery. Finally, the research suggests the best combination of manufacturing parameters that has to be emphasised to improve the manufacturing performance and gain a competitive advantage.

Year2019
PublisherUniversity of East London
Digital Object Identifier (DOI)doi:10.15123/uel.873q1
File
License
File Access Level
Anyone
Publication dates
PrintMay 2019
Publication process dates
Deposited07 May 2020
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https://repository.uel.ac.uk/item/873q1

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