Title: Towards optimal engineering multitasking level through stochastic modelling

Authors: Gagandeep Singh; Leo Mougel; Yvan Beauregard; Yaoyao Fiona Zhao

Addresses: Department of Mechanical Engineering, McGill University, Montreal, H3A 0C3, Canada ' Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, H3C 1K3, Canada ' Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, H3C 1K3, Canada ' Department of Mechanical Engineering, McGill University, Montreal, H3A 0C3, Canada

Abstract: Multitasking or task switching has been a topic of interest and research in the field of operations management. There has been a little yet no full proof as to how increasing multitasking levels affect the performance of a whole engineering system. The goal of this paper is to introduce the concept of task switching into a network of engineers which handles and executes the quality complaints of a major aerospace firm and to observe the trends of performance measures such as average lead time, system utilisation and queuing time with increasing multitasking levels. The paper develops a mathematical model based on queuing theory and Jackson networks which is then applied to a discrete events-based simulation model.

Keywords: engineering multitasking; task switching; operational research; queuing theory; utilisation; optimisation; stochastic modelling; multitasking levels; aerospace industry; performance measures; lead times; system utilisation; queuing time; mathematical modelling; queuing theory; Jackson networks; discrete event simulation.

DOI: 10.1504/IJOR.2017.081487

International Journal of Operational Research, 2017 Vol.28 No.2, pp.263 - 278

Received: 20 Dec 2014
Accepted: 15 Jul 2015

Published online: 02 Jan 2017 *

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