Johnson, J. A. and Adekunle, A. A. (2016) Human workflow modelling in homogeneous computor networks. In: 2016 10th International Conference on Next Generation Mobile Applications, Security and Technologies (NGMAST). IEEE, pp. 65-71. ISBN 978-1509009503 ISSN 2161-2897 (Online) (doi:https://doi.org/10.1109/NGMAST.2016.21)

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Abstract

Maintaining consistent operational efficiency and productivity levels through effective and reliable workflow processes can be the key to businesses realising long-term profit margins. This can be difficult to achieve if the challenges that affect this dual paradigm are not fully understood. Where human input is an integral part of the business workflow, the existing methods for modelling this human interaction are too abstract in nature and are not appropriate for deriving performance characteristics about human input into the process. This paper introduces a novel approach to classifying humans for the purpose of workflow modelling. Following this classification we further demonstrate that an analytical method, such as queueing theory, can be used to extract the resource utilisation and throughput characteristics of humans engaged in a business workflow processes. The initial results from experimentations indicate that the resource utilisation and throughput levels of humans could provide insight into where performance gains and increased throughput can be made. We do not consider the unique behavioural characteristics of humans that could influence the resource utilisation or throughput rates as part of our current research.

Item Type:	Conference Proceedings
Title of Proceedings:	2016 10th International Conference on Next Generation Mobile Applications, Security and Technologies (NGMAST)
Additional Information:	Conference held from 24-26 August 2016, Cardiff, UK.
Uncontrolled Keywords:	Computor, Homogeneous, Human Workflow Modelling, Queueing Theory, Resource Management
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Engineering (ENG)
Last Modified:	05 Jan 2019 23:49
URI:	http://gala.gre.ac.uk/id/eprint/22366

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