Robust Design of Dynamic Cell Formation Problem Considering the Workers Interest

Document Type : Original Article

Authors

Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran

Abstract

To enhance agility and quick responding to customers' demand, manufacturing processes are rearrenged according to different systems. The efficient execution of a manufacturing system depends on various factors. Among them, cell design and human issue are the pivotal ones. The proposed model designs cellular manufacturing systems using three objective functions from three different perspectives, to reflect a more realistic picture of the cell formation problem. This paper presents a model with the goals of maximizing the total value of grouping efficacy and minimizing the total costs and total non-interest workers in cells in a dynamic environment for several consecutive periods.  The main idea of the proposed model is enhancing cell efficiency through an assigning the group of workers who have a mutual interest in working with each other. For solving the current model, the revised multi-choice goal programming method has been employed. Finally, computational results and sensitivity analysis are discussed.

Keywords


1. Hut, J. and Molleman, E., “Empowerment and team 
development”, Team Performance Management: An
International Journal, Vol. 4, No. 2, (1998), 53–66.  
2. Bailey, D. E., “Manufacturing improvement team programs in the
semiconductor industry”, IEEE Transactions on Semiconductor
Manufacturing, Vol. 10, No. 1, (1997), 1–10.  
3. Fitzpatrick, E.L. and Askin, R. G., “Forming effective worker
teams with multi-functional skill requirements”, Computers &
Industrial Engineering, Vol. 48, No. 3, (2005), 593–608.  
4. Wirojanagud, P., Gel, E.S., Fowler, J.W. and Cardy, R.,
“Modelling inherent worker differences for workforce planning”,
International Journal of Production Research, Vol. 45, No. 3,
(2007), 525–553.  
5. Li, Q., Gong, J., Tang, J. and Song, J., “Simulation of the model
of workers’ assignment in cellular manufacturing based on the
multifunctional workers”, In 2008 Chinese Control and Decision
Conference, IEEE, (2008), 992–996.  
6. Süer, G.A., Arikan, F. and Babayigit, C., “Effects of different
fuzzy operators on fuzzy bi-objective cell loading problem in
labor-intensive manufacturing cells”, Computers & Industrial
Engineering, Vol. 56, No. 2, (2009), 476–488.  
7. Mahdavi, I., Aalaei, A., Paydar, M.M. and Solimanpur, M.,
“Designing a mathematical model for dynamic cellular
manufacturing systems considering production planning and
worker assignment”, Computers & Mathematics with
Applications, Vol. 60, No. 4, (2010), 1014–1025.  
8. Soolaki, M., “A multi-objective integrated cellular manufacturing
systems design with production planning, worker assignment and
dynamic system reconfiguration”, International Journal of
Industrial and Systems Engineering, Vol. 12, No. 3, (2012), 280–300.  
9. Bagheri, M. and Bashiri, M., “A new mathematical model
towards the integration of cell formation with operator assignment
and inter-cell layout problems in a dynamic environment”,
Applied Mathematical Modelling, Vol. 38, No. 4, (2014), 1237– 1254.  
10. Bootaki, B., Mahdavi, I. and Paydar, M. M., “A hybrid GAAUGMECON method
to solve a cubic cell formation problem
considering different worker skills”, Computers & Industrial
Engineering, Vol. 75, (2014), 31–40.  
11. Liu, C., Wang, J. and Leung, J. Y. T., “Worker assignment and
production planning with learning and forgetting in
manufacturing cells by hybrid bacteria foraging algorithm”,
Computers & Industrial Engineering, Vol. 96, (2016), 162–179.  
12. Sakhaii, M., Tavakkoli-Moghaddam, R., Bagheri, M. and Vatani,
B., “A robust optimization approach for an integrated dynamic
cellular manufacturing system and production planning with
unreliable machines.”, Applied Mathematical Modelling, Vol.
40, No. 1, (2016), 169–191.  
13. Mehdizadeh, E., Niaki, S.V.D. and Rahimi, V., “A vibration
damping optimization algorithm for solving a new multi-objective
dynamic cell formation problem with workers training”,
Computers & Industrial Engineering, Vol. 101, (2016), 35–52.  
14. Niakan, F., Baboli, A., Moyaux, T. and Botta-Genoulaz, V., “A
bi-objective model in sustainable dynamic cell formation problem
with skill-based worker assignment”, Journal of Manufacturing
Systems, Vol. 38, (2016), 46–62.  
15. Feng, H., Da, W., Xi, L., Pan, E. and Xia, T., “Solving the
integrated cell formation and worker assignment problem using
particle swarm optimization and linear programming”,
Computers & Industrial Engineering, Vol. 110, (2017), 126–137.  
16. Arora, J.S., Introduction to optimum design, Elsevier, (2004).
17. Colapinto, C., Jayaraman, R. and Marsiglio, S., “Multi-criteria 
decision analysis with goal programming in engineering,
management and social sciences: a state-of-the art review”,
Annals of Operations Research, Vol. 251, No. 1–2, (2017), 7– 40.