Call for Paper - August 2019 Edition
IJCA solicits original research papers for the August 2019 Edition. Last date of manuscript submission is July 20, 2019. Read More

Evaluation of a Harmony Search Algorithm for Manual Lifting Tasks Optimization

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
Authors:
Serap Ulusam Seçkiner, Yunus Eroğlu
10.5120/ijca2015907442

Serap Ulusam Seçkiner and Yunus Eroğlu. Article: Evaluation of a Harmony Search Algorithm for Manual Lifting Tasks Optimization. International Journal of Computer Applications 131(6):10-17, December 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Serap Ulusam Seçkiner and Yunus Eroğlu},
	title = {Article: Evaluation of a Harmony Search Algorithm for Manual Lifting Tasks Optimization},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {131},
	number = {6},
	pages = {10-17},
	month = {December},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

This paper presents near optimal solution method to find safe work place design using harmony search algorithm. Revised NIOSH equations are considered to minimize relative estimate of the physical stress associated with a manual-lifting job. The proposed algorithm will assist occupational safety and health practioners in evaluating lifting tasks and reducing the incidence of low back injuries in workers.

References

  1. A. Garg, S. Boda, K. T. Hegmann, J. S. Moore, J. M. Kapellusch, P. Bhoyar, M. S. Thiese, A. Merryweather, G. Deckow-Schaefer, D. Bloswick, and E. J. Malloy, “The NIOSH Lifting Equation and Low-Back Pain, Part 1 Association With Low-Back Pain in the BackWorks Prospective Cohort Study,” Hum. Factors J. Hum. Factors Ergon. Soc., vol. 56, no. 1, pp. 6–28, Feb. 2014.
  2. X. Xu, C.-C. Chang, G. S. Faber, I. Kingma, and J. T. Dennerlein, “Estimation of 3-D peak L5/S1 joint moment during asymmetric lifting tasks with cubic spline interpolation of segment Euler angles,” Appl. Ergon., vol. 43, no. 1, pp. 115–120, Jan. 2012.
  3. S. Srivastava, K. Srivastava, N. Swati, Y. K. Anand, and V. Soamidas, “Designing lifting task in shoe industry using genetic algorithm,” in 2010 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2010, pp. 502–506.
  4. N. A. Nelson and R. E. Hughes, “Quantifying relationships between selected work-related risk factors and back pain: a systematic review of objective biomechanical measures and cost-related health outcomes,” Int. J. Ind. Ergon., vol. 39, no. 1, pp. 202–210, 2009.
  5. S. Singh and S. Kumar, “Factorial analysis of lifting task to determine the effect of different parameters and interactions,” J. Manuf. Technol. Manag., vol. 23, no. 7, pp. 947–953, Sep. 2012.
  6. D. Hoy, P. Brooks, F. Blyth, and R. Buchbinder, “The Epidemiology of low back pain,” Best Pract. Res. Clin. Rheumatol., vol. 24, no. 6, pp. 769–781, Dec. 2010.
  7. M.-L. Lu, T. Waters, E. Krieg, and D. Werren, “Efficacy of the Revised NIOSH Lifting Equation to Predict Risk of Low Back Pain Associated With Manual Lifting A One-Year Prospective Study,” Hum. Factors J. Hum. Factors Ergon. Soc., p. 0018720813513608, Dec. 2013.
  8. W. S. Marras, S. A. Lavender, S. A. Ferguson, R. E. Splittstoesser, and G. Yang, “Quantitative Dynamic Measures of Physical Exposure Predict Low Back Functional Impairment:,” Spine, vol. 35, no. 8, pp. 914–923, Apr. 2010.
  9. K. Matsudaira, H. Konishi, K. Miyoshi, T. Isomura, K. Takeshita, N. Hara, K. Yamada, and H. Machida, “Potential Risk Factors for New Onset of Back Pain Disability in Japanese Workers: Findings From the Japan Epidemiological Research of Occupation-Related Back Pain Study,” Spine, vol. 37, no. 15, pp. 1324–1333, Jul. 2012.
  10. J. L. Vandergrift, J. E. Gold, A. Hanlon, and L. Punnett, “Physical and psychosocial ergonomic risk factors for low back pain in automobile manufacturing workers,” Occup. Environ. Med., vol. 69, no. 1, pp. 29–34, Jan. 2012.
  11. B. J. Carnahan and M. S. Redfern, “Application of genetic algorithms to the design of lifting tasks,” Int. J. Ind. Ergon., vol. 21, no. 2, pp. 145–158, Feb. 1998.
  12. P. G. Dempsey, “Usability of the revised NIOSH lifting equation,” Ergonomics, vol. 45, no. 12, pp. 817–828, Oct. 2002.
  13. M. L. L. R. Okimoto and E. R. Teixeira, “Proposed procedures for measuring the lifting task variables required by the Revised NIOSH Lifting Equation – A case study,” Int. J. Ind. Ergon., vol. 39, no. 1, pp. 15–22, Jan. 2009.
  14. S. J. Russell, L. Winnemuller, J. E. Camp, and P. W. Johnson, “Comparing the results of five lifting analysis tools,” Appl. Ergon., vol. 38, no. 1, pp. 91–97, Jan. 2007.
  15. T. R. Waters, M.-L. Lu, and E. Occhipinti, “New procedure for assessing sequential manual lifting jobs using the revised NIOSH lifting equation,” Ergonomics, vol. 50, no. 11, pp. 1761–1770, Oct. 2007.
  16. NIOSH, Applications Manual for the Revised NIOSH Lifting Equation (94-110). 1994.
  17. T. R. Waters, V. Putz-Anderson, A. Garg, and L. J. Fine, “Revised NIOSH equation for the design and evaluation of manual lifting tasks,” Ergonomics, vol. 36, no. 7, pp. 749–776, Jul. 1993.
  18. Z. W. Geem, J. H. Kim, and G. V. Loganathan, “A New Heuristic Optimization Algorithm: Harmony Search,” SIMULATION, vol. 76, no. 2, pp. 60–68, Feb. 2001.
  19. K. S. Lee and Z. W. Geem, “A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice,” Comput. Methods Appl. Mech. Eng., vol. 194, no. 36–38, pp. 3902–3933, Sep. 2005.
  20. A. Garg, J. M. Kapellusch, K. T. Hegmann, J. S. Moore, S. Boda, P. Bhoyar, M. S. Thiese, A. Merryweather, G. Deckow-Schaefer, D. Bloswick, and E. J. Malloy, “The NIOSH Lifting Equation and Low-Back Pain, Part 2 Association With Seeking Care in the BackWorks Prospective Cohort Study,” Hum. Factors J. Hum. Factors Ergon. Soc., vol. 56, no. 1, pp. 44–57, Feb. 2014.
  21. C. C. Chang, D. R. Brown, D. S. Bloswick, and S. M. Hsiang, “Biomechanical simulation of manual lifting using spacetime optimization,” J. Biomech., vol. 34, no. 4, pp. 527–532, Apr. 2001.
  22. D. J. Blood and S. J. Ferriss, “Effects of background music on anxiety, satisfaction with communication, and productivity,” Psychol. Rep., vol. 72, no. 1, pp. 171–177, Feb. 1993.
  23. C. J. Cruise, F. Chung, S. Yogendran, and D. Little, “Music increases satisfaction in elderly outpatients undergoing cataract surgery,” Can. J. Anaesth., vol. 44, no. 1, pp. 43–48, Jan. 1997.
  24. D. Evans, “The effectiveness of music as an intervention for hospital patients: a systematic review,” J. Adv. Nurs., vol. 37, no. 1, pp. 8–18, Jan. 2002.
  25. M. S. Minor, T. Wagner, F. j. Brewerton, and A. Hausman, “Rock on! An elementary model of customer satisfaction with musical performances,” J. Serv. Mark., vol. 18, no. 1, pp. 7–18, Jan. 2004.
  26. M. Morrison, S. Gan, C. Dubelaar, and H. Oppewal, “In-store music and aroma influences on shopper behavior and satisfaction,” J. Bus. Res., vol. 64, no. 6, pp. 558–564, Jun. 2011.
  27. C. Thrane, “Music Quality, Satisfaction, and Behavioral Intentions Within a Jazz Festival Context,” Event Manag., vol. 7, no. 3, pp. 143–150, Mar. 2002.
  28. N. R. Sabar and G. Kendall, “Using harmony search with multiple pitch adjustment operators for the portfolio selection problem,” in 2014 IEEE Congress on Evolutionary Computation (CEC), 2014, pp. 499–503.
  29. K. Z. Gao, P. N. Suganthan, Q. K. Pan, T. J. Chua, T. X. Cai, and C. S. Chong, “Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives,” J. Intell. Manuf., pp. 1–12, Jan. 2014.
  30. M. R. Maheri and M. M. Narimani, “An enhanced harmony search algorithm for optimum design of side sway steel frames,” Comput. Struct., vol. 136, pp. 78–89, May 2014.
  31. X.-S. Yang, “Harmony Search as a Metaheuristic Algorithm,” in Music-Inspired Harmony Search Algorithm, Z. W. Geem, Ed. Springer Berlin Heidelberg, 2009, pp. 1–14.

Keywords

Lifting, Harmony Search Algorithm, Workplace, Design.