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.
International Journal of Operational Research, 2017 Vol.28 No.2, pp.263 - 278
Received: 20 Dec 2014
Accepted: 15 Jul 2015
Published online: 10 Jan 2017 *