A genetic algorithm for the design of job rotation schedules considering ergonomic and competence criteria

Abstract

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 employeejob 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.

Job rotation designed to prevent musculoskeletal disorders and control risk in manufacturing industries: A systematic review

“…Of the 14 studies included, only one was rated as good (case-control design) (Roquelaure et al, 1997), six as fair (Balogh et al, 2006; Dawal et al, 2009; Dawal and Taha, 2007; Fredriksson et al, 2001; Guimarães et al, 2012; Sato and Coury, 2009), and seven as poor methodological quality (Asensio-Cuesta et al, 2012a; Asensio-Cuesta et al, 2012b; Carnahan et al, 2000; Diego-Mas et al, 2009; Filus and Okimorto, 2012; Frazer et al, 2003; Tharmmaphornphilas and Norman, 2007a). …”

“…We refer to the second category as “Equation” because the job-rotation schedules were created by a mathematical equation that addresses multiple factors at the same time to more precisely determine the best job-rotation schedules available to workers. The equation accounted for ergonomic aspects of the job and competence of the tasks (Asensio-Cuesta et al, 2012b). …”

When is job rotation perceived useful and easy to use to prevent work-related musculoskeletal complaints?

“…In this case, potential usefulness and ease of use of job rotation can be highlighted with examples of case studies or statistics documenting success cases, in order to reinforce motivation to implement job rotation. In the preparation stage, a multi-criteria genetic algorithm (Asensio-Cuesta et al, 2012) can be applied to design job rotation schemes considering ergonomic, organizational and individual criteria. The presence of facilitators relating to job autonomy, worker characteristics and worker behavior can function as some of these criteria and contribute to potential ease of use.…”

Towards Dynamic and Adaptive Allocation of Staff in a Digital-organized Production Context: An Innovative Perspective from Work Science

“…Existing job rotation programs are focused primarily on managing biomechanical and organizational risks [6]. Analytical models focused on integrating these two perspectives include factors such as details of work contracts (work shifts, part-time, flexible scheduling), worker preferences, level of production, skills, training, physical capacity and experience, as well as the effects of learning [13,[21][22][23][24], exposure to noise, physical workload or anthropometric data [13,22,23,[25][26][27][28][29], age [11,14] and cognitive ergonomic factors such as human reliability or task complexity [27,30,31].…”

“…• Integrating variables from work sciences into existing process scheduling or balancing models via constraints in the model [21,32]; • Treating the staff allocation problem as a multi-criteria/objective decision problem [21,24]; • Building a model based on heuristics or meta-heuristics (artificial intelligence approaches) such as genetic algorithms, the simulated annealing algorithm or ant algorithm [22,25,28] fuzzy logic [27] or particle swarms [26] to integrate certain operational risks into risks identified in work science [6]; • Building a model based on integer (linear or nonlinear)…”