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

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Abstract

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.

Section snippets

Introdution

Changes in the manufacturing industry have been implemented as a response to more global and expansive marketing. Production rates are increasing based on new technology and better production efficiency. This intensification of the work seems to be influencing job contents and the rates of work-related musculoskeletal disorders. It has long been suggested that technological changes tend to increase the incidence of musculoskeletal disorders in particular occupations (Ohara et al., 1976; Bammer,

Subjects

Four healthy, skilled, female workers took part in this study. They were highly experienced employees in this multinational company for producing office products. They worked in a pencil packing operation and their job experience allowed them to change jobs within the manual, semi-automated and automated packing processes. They were screened for musculoskeletal disorders by a physiotherapist to ensure normal pattern of motion without compensation from other segments. Their ages ranged from 23

Frequency of the movements performed

The means, standard deviations and minimum and maximum values for the deviations (minimum 5°) from the neutral in movement direction for all types of movement were computed at the three packing operations. These are presented in Table 1, Table 2 for the right and left hands respectively. The numbers presented in Table 1, Table 2 represent the average values obtained for ten samples of ten second periods for every subject.

According to the data in Table 1, the most frequent change in movement

Discussion

The frequency of movement was very high in the three production systems analysed — manual, semi-automated and automated. Jobs lasted only a few seconds, and shorter sub-cycles are relatively common in industrial activities (Mathiassen and Winkel, 1991; Marras and Schoenmarklin, 1991). In the present study the work cycles varied on average from 1.24 s (semi-automated operations) to 8.11 s (manual operations). Highly repetitive work was defined by Silverstein et al. (1986) as a job performed in

Acknowledgements

This study was supported by FAPESP (Proc. No. 1997/4765-7). The authors are grateful to BIOMETRICS for the addition made to the prototype software, and to FABER-CASTELL for access to their industry.

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