Job Rotation Schedules Research Articles

Effects of progressive levels of industrial automation on force and repetitive movements of the wrist

The purpose of this research was to compare the repetition of wrist movements and force produced by workers when packing pencils in manual, semi-automated and automated industrial operations. The study was conducted in a multinational pencil company which had the three production systems operating simultaneously. Highly skilled workers were in a job rotation schedule between the systems. A portable electrogoniometer set was used for measuring the wrist movements. The software V.3.11 (Biometrics prototype design) was used to compute the number of repetitions of 5° or more motion of the wrist. Highly repetitive tasks were identified in all packaging operations involving the three different and progressive stages of production automation. The highest frequencies and most stereotyped movements were recorded in the semi-automated operations, followed by the manual and automated operations. The operations required force application between 9.1 and 12.3% of maximal voluntary contraction between three operations. These results were analysed using analysis of variance. The analysis showed significant differences in frequencies of wrist motion ( p<0.05) between the production systems. However, force required by the three operations were not significantly different. The findings indicate that partial automation does not necessarily decrease or eliminate motions performed by human operators. Thus the goal of automation and its level must be carefully considerated prior to implementation. Relevance to industry The intensification of the industrial work seems to be influencing job contents, working movements and the rates of musculoskeletal disorders. The study of the relation between repetition and progressive levels of industrial automation may contribute to the understanding of this event.

Designing safe job rotation schedules using optimization and heuristic search

Job rotation is one method that is sometimes used to reduce exposure to strenuous materials handling; however, developing effective rotation schedules can be complex in even moderate sized facilities. The purpose of this research is to develop methods of incorporating safety criteria into scheduling algorithms to produce job rotation schedules that reduce the potential for injury. Integer programming and a genetic algorithm were used to construct job rotation schedules. Schedules were comprised of lifting tasks whose potential for causing injury was assessed with the Job Severity Index. Each method was used to design four job rotation schedules that met specified safety criteria in a working environment where the object weight, horizontal distance and repetition rate varied over time. Each rotation was assigned to a specific gender/lifting capacity group. Five versions of the integer programming search method were applied to this problem. Each version generated one job rotation schedule. The genetic algorithm model was able to create a population of 437 feasible solutions to the rotation problem. Utilizing cluster analysis, a rule set was derived from the genetic algorithm generated solutions. These rules provided guidelines for designing safe job rotation schedules without the use of a computer. The advantages and limitations of these approaches in developing administrative controls for the prevention of back injury are discussed.