Variation of Work Productivity Performance at Different Levels of Production Standard Time

Abstract:

This study investigated the variation of work productivity performance at different levels of production standard time. Twenty subjects performed repetitive tasks at three different levels of production standard time, corresponding to “normal, “hard” and “very hard”. The work productivity and perceived fatigue were recorded. Analysis of Variance (ANOVA) was performed on the data and the results indicated that work productivity and perceived fatigue were significantly affected by production standard time. The results indicated that there was a decrease in work productivity performance as the perceived fatigue increased. The reduction in work productivity performance is related to the functional incapacity of the workers whereby they are exposed to higher risk of WMSDs in harder production standard time.

• Periodical: Applied Mechanics and Materials (Volume 851)
• Pages: 879-883
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.851.879
• Online since: August 2016
• Authors: Nurhayati Mohd Nur*, Siti Zawiah Md Dawal, Mahidzal Dahari, Nur Faraihan Zulkefli
• Keywords: Performance, Production Standard Time, Work Productivity

References

[1] L. Ho, S. Yap, The link between wages and labour productivity : An analysis of the Malaysian manufacturing industry, Malaysian J. Econ. Stud. 38 (2001) 51–57.

[2] R. S. Escorpizo, A. E. Moore, Quantifying precision and speed effects on muscle loading and rest in an occupational hand transfer task, Int. J. Ind. Ergon. 37(1) (2007) 13–20.

DOI: 10.1016/j.ergon.2006.09.001

[3] C. Nordander, K. Ohlsson, I. Akesson, I. Arvidsson, I. Balogh, G. A. Hansson, U. Strömberg, R. Rittner, S. Skerfving, Risk of musculoskeletal disorders among females and males in repetitive/constrained work, Ergon. 52(10) (2009) 1226–39.

DOI: 10.1080/00140130903056071

[4] K. Jung, O. Kwon, H. You, Development of a digital human model generation method for ergonomic design in virtual environment, Int. J. Ind. Ergon. 39(5) (2009) 744–748.

DOI: 10.1016/j.ergon.2009.04.001

[5] R. Escorpizo, Understanding work productivity and its application to work-related musculoskeletal disorders, Int. J. Ind. Ergon. 38(3–4) (2008) 291–297.

DOI: 10.1016/j.ergon.2007.10.018

[6] E. Bryjolfsson, VII Pillars of Productivity, Optim. Mag. (22) (2005).

[7] S. Allesina, A. Azzi, D. Battini, A. Regattieri, Performance measurement in supply chains: new network analysis and entropic indexes, Int. J. Prod. Res. 48(8) (2010) 2297–2321.

DOI: 10.1080/00207540802647327

[8] T. Bosch, S. E. Mathiassen, B. Visser, M. P. de Looze, J. H. van Dieën, The effect of work pace on workload, motor variability and fatigue during simulated light assembly work, Ergonomics, 54(2) (2011) 154–168.

DOI: 10.1080/00140139.2010.538723

[9] A. Shikdar, B. Das, The relationship between worker satisfaction and productivity in a repetitive industrial task, Appl. Ergon. 34(6) (2003) 603–610.

DOI: 10.1016/s0003-6870(03)00057-7

[10] K. Adams, M. DeBeliso, P. Sevene-Adams, J. Berning, T. Miller, D. Tollerud, Physiological and psychophysical comparison between a lifting task with identical weight but different coupling factors, J. Strength Cond. Res. 24(2) (2010) 307.

DOI: 10.1519/jsc.0b013e3181c8c84e

[11] M. L. Resnick, A. Zanotti, Using ergonomics to target productivity improvement, Comput. Ind. Eng. 33(1–2) (1997) 185–188.

[12] Z. Xu, J. Ko, D. J. Cochran, M. Jung, Design of assembly lines with the concurrent consideration of productivity and upper extremity musculoskeletal disorders using linear models, Comput. Ind. Eng. 62(2) (2012) 431–441.

DOI: 10.1016/j.cie.2011.10.008