A genetic algorithm for the design of job rotation schedules considering ergonomic and competence criteria
- 593 Downloads
Job rotation is an organizational strategy increasingly used in manufacturing systems as it provides benefits to both workers and management in an organization. Job rotation prevents musculoskeletal disorders, eliminates boredom and increases job satisfaction and morale. As a result, the company gains a skilled and motivated workforce, which leads to increases in productivity, employee loyalty and decreases in employee turnover. A multi-criteria genetic algorithm is employed to generate job rotation schedules, with considering the most adequate employee-job assignments to prevent musculoskeletal disorders caused by accumulation of fatigue. The algorithm provides the best adequacy available between workers and the competences needed for performing the tasks. The design of the rotation schedules is based not only on ergonomic criteria but also on issues related to product quality and employee satisfaction. The model includes the workers’ competences as a measure for the goodness of solutions.
KeywordsJob rotation Competences Musculoskeletal disorders
Unable to display preview. Download preview PDF.
We thank the Universidad Politécnica de Valencia for its support of this research through its Research and Development Program 2009 and financing through the project PAID-06-09/2902. The Universidad Politécnica de Valencia has funded the translation of this work.
- 1.Podniece Z (2008) Work-related musculoskeletal disorders: prevention report. European Agency for Safety and Health at Work, BelgiumGoogle Scholar
- 3.Emodi T, Zhang WJ, Lang SYT, Bi ZM (2007) A framework for modeling and analysis of human repetitive operations in a production assembly line. International SAE Digital Human Modeling for Design and Engineering Conference And Exhibition, University District Seattle, Washington, USACrossRefGoogle Scholar
- 4.Huang HJ (1999) Job rotation from the employees’ point of view. Res Hum R M 7:75–85Google Scholar
- 5.Eriksson T, Ortega J (2006) The adoption of job rotation: testing the theories. Ind Labor Relat Rev 59:653–666Google Scholar
- 7.Cunningham BJ, Eberle T (1990) A guide to job enrichment and redesign. Personnel 67:56–61Google Scholar
- 9.Jonsson B (1988) Electromyographic studies of job rotation. Scand J Work Environ Health 14:108–109Google Scholar
- 10.Hazzard L, Mautz J, Wrightsman D (1992) Job rotation cuts cumulative trauma cases. Personnel 71:29–32Google Scholar
- 18.Nanthavanij S, Kullpattaranirun T (2001) A genetic algorithm approach to determine minimax work assignments. Int J Ind Eng Theor 8:176–185Google Scholar
- 19.Kullpattaranirun T, Nanthavanij S (2005) A heuristic genetic algorithm for solving complex safety-based work assignment problems. Int J Ind Eng Theor 12:45–57Google Scholar
- 23.Spencer L, Spencer S (1993) Competence at work: models for superior performance. Wiley, New YorkGoogle Scholar
- 25.Triggs DD, King PM (2000) Job rotation: an administrative strategy for hazard control. Prof Saf 45:32–34Google Scholar
- 26.Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor, MichiganGoogle Scholar
- 27.Emodi T, Zhang WJ (2008) Injury analysis in assembly and production lines: a state of the art review. Int J Ergon Hum Factors 30:11–38Google Scholar
- 32.Davis L (1991) Handbook of genetic algorithms. Van Nostrand Reinhold, New YorkGoogle Scholar
- 34.Rodgers SH (1986) Ergonomic design for people at work. Van Nostrand Reinhold, New YorkGoogle Scholar
- 35.Rodgers SH (1992) A functional job analysis technique. Occup Med State Art 7:679–711Google Scholar