International Journal of Industrial Engineering and Management

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut ero labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco.

GUIDE FOR AUTHORS SUBMIT MANUSCRIPT
Vol. 13 No. 2 (2022)
Original Research Article

Worker Assignment in Dual Resource Constrained Systems Subject to Machine Failures: A Simulation Study

Nuno O. Fernandes
Instituto Politécnico de Castelo Branco
Bio
Matthias Thürer
Jinan University, School of Intelligent Systems Science and Engineering
Bio
Filipe Rodrigues
ISEP - School of Engineering, Polytechnic of Porto
Bio
Luís P. Ferreira
ISEP - School of Engineering, Polytechnic of Porto
Bio
Francisco J. G. Silva
ISEP - School of Engineering, Polytechnic of Porto
Bio
Paulo Ávila
ISEP - School of Engineering, Polytechnic of Porto
Bio

Published 2022-06-30

abstract views: 25 // FULL TEXT ARTICLE (PDF): 0


Keywords

  • Dual Resource Constrained,
  • Machine Failures,
  • Simulation

How to Cite

Fernandes, N. O., Thürer, M., Rodrigues, F., Ferreira, L. P., Silva, F. J. G., & Ávila, P. (2022). Worker Assignment in Dual Resource Constrained Systems Subject to Machine Failures: A Simulation Study. International Journal of Industrial Engineering and Management, 13(2), 110–118. https://doi.org/10.24867/IJIEM-2022-2-305

Abstract

A production system constrained by workers and machines, where machines are not fully staffed and workers can be transferred between machines, is here considered. Previous simulation research on this type of dual resource constrained production systems assumes that machines are fully reliable. However, this is questionable in most practical situations. Discrete event simulation is used as research method to assess the impact of machine failures on where to transfer workers. Experimentation was carried out for different levels of machine availability, worker utilization and worker assignment rules. Results show that the modified operation due date rule for worker assignment improves tardiness related performance for all production situations considered. This rule shifts between a focus on completing jobs on time and a focus on speeding up jobs with short processing time. Results further show that ignoring the machine state at worker assignment may lead to significant performance deterioration. For a machine availability of 97% and a worker utilization of 90%, a deterioration between 101% and 416% on the percentage of tardy jobs was observed, compared to scenarios where machines are always available. However, if the machine state is considered, deterioration ranges only between 11% and 30% under the same conditions. This highlights the need to considered machine availability at worker assigment.

 

Article history: Received (October 17, 2021); Revised (February 23, 2022); Accepted (February 28, 2022); Published online (March 8, 2022) 

PlumX Metrics

Dimensions Citation Metrics