The effect of working conditions and gender on human errors in manual assembly line

Product defects in an assembly line can happen due to various reasons, and one of the sources is human error. The occurrence of human errors in manual assembly line can be affected by factors, such as workplace condition/environment, equipment and demographics factors. This study adopted two approac...

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Main Author: Leau, Jia Xin
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Language:English
English
Published: 2015
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Online Access:http://eprints.utem.edu.my/id/eprint/16877/1/The%20Effect%20Of%20Working%20Conditions%20And%20Gender%20On%20Human%20Errors%20In%20Manual%20Assembly%20Line.pdf
http://eprints.utem.edu.my/id/eprint/16877/2/The%20effect%20of%20working%20conditions%20and%20gender%20on%20human%20errors%20in%20manual%20assembly%20line.pdf
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institution Universiti Teknikal Malaysia Melaka
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language English
English
advisor Saptari, Adi

topic H Social Sciences (General)
HF Commerce
spellingShingle H Social Sciences (General)
HF Commerce
Leau, Jia Xin
The effect of working conditions and gender on human errors in manual assembly line
description Product defects in an assembly line can happen due to various reasons, and one of the sources is human error. The occurrence of human errors in manual assembly line can be affected by factors, such as workplace condition/environment, equipment and demographics factors. This study adopted two approaches i.e. lab experiment and case study in industry. In the first part, a three-pin plug assembly line was used to simulate the production. The experiment was conducted in the lab to determine the effect of work pace, working conditions, such as working position, jig design, and component bin position, and gender on human errors during manual assembly. The product defects were identified as the occurrence of nonconformance product due to human error. To minimize the sources of defect from other factors, such as working environment, material defects, working experience and equipment failures, these factors were controlled in the experiments to ensure that the defects obtained were solely due to human error. A total of ten participants had participated in this experiment, five adult males and five females. A full-factorial design of experiment was used and there were sixteen combinations of experimental runs in this research. Results showed that there was a linear correlation between work pace and human error. When the production pace increased over the normal, cycle time decreases, causing time pressure condition which had significant effect on human error. Working position had the second greatest effect on human error, followed by gender difference and component bin position. Jig design had no significant effect on human error. Gender difference contributed to the differences in human errors, where females made fewer errors than males in normal pace as well as in the time pressure environment. However, male had faster cycle time than female. Finally, a fitted model which can describe the relationship between human error and working condition parameters was proposed and validated. This model functions as the predictor of human error when the variables of assembly are known. In the second part, a case study was conducted in an electronic company located in Melaka, Malaysia. This company uses an assembly line to produce their products. The case study only focused on the effect of work pace on the occurrence of human errors that lead to product defects. The other variables, such as working position, component bin position, jig design and gender, were not included as they were not applicable in the workplace of the case study. Based on the results, it was observed that the occurrence of human error was higher when production target is increase above the normal capacity. This situation was recognized that there was a time pressure to the workers. In addition, the number of errors also increased as the production target lower than the normal production capacity. The relationship of product defects and production output can be represented using a U-model, where the number of product defects was higher when the production output was lower or higher than the normal production target. This finding was consistent with the experimental results, where time pressure affects the occurrence of human errors.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Leau, Jia Xin
author_facet Leau, Jia Xin
author_sort Leau, Jia Xin
title The effect of working conditions and gender on human errors in manual assembly line
title_short The effect of working conditions and gender on human errors in manual assembly line
title_full The effect of working conditions and gender on human errors in manual assembly line
title_fullStr The effect of working conditions and gender on human errors in manual assembly line
title_full_unstemmed The effect of working conditions and gender on human errors in manual assembly line
title_sort effect of working conditions and gender on human errors in manual assembly line
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty Of Manufacturing Engineering
publishDate 2015
url http://eprints.utem.edu.my/id/eprint/16877/1/The%20Effect%20Of%20Working%20Conditions%20And%20Gender%20On%20Human%20Errors%20In%20Manual%20Assembly%20Line.pdf
http://eprints.utem.edu.my/id/eprint/16877/2/The%20effect%20of%20working%20conditions%20and%20gender%20on%20human%20errors%20in%20manual%20assembly%20line.pdf
_version_ 1747833906160205824
spelling my-utem-ep.168772022-06-13T12:47:32Z The effect of working conditions and gender on human errors in manual assembly line 2015 Leau, Jia Xin H Social Sciences (General) HF Commerce Product defects in an assembly line can happen due to various reasons, and one of the sources is human error. The occurrence of human errors in manual assembly line can be affected by factors, such as workplace condition/environment, equipment and demographics factors. This study adopted two approaches i.e. lab experiment and case study in industry. In the first part, a three-pin plug assembly line was used to simulate the production. The experiment was conducted in the lab to determine the effect of work pace, working conditions, such as working position, jig design, and component bin position, and gender on human errors during manual assembly. The product defects were identified as the occurrence of nonconformance product due to human error. To minimize the sources of defect from other factors, such as working environment, material defects, working experience and equipment failures, these factors were controlled in the experiments to ensure that the defects obtained were solely due to human error. A total of ten participants had participated in this experiment, five adult males and five females. A full-factorial design of experiment was used and there were sixteen combinations of experimental runs in this research. Results showed that there was a linear correlation between work pace and human error. When the production pace increased over the normal, cycle time decreases, causing time pressure condition which had significant effect on human error. Working position had the second greatest effect on human error, followed by gender difference and component bin position. Jig design had no significant effect on human error. Gender difference contributed to the differences in human errors, where females made fewer errors than males in normal pace as well as in the time pressure environment. However, male had faster cycle time than female. Finally, a fitted model which can describe the relationship between human error and working condition parameters was proposed and validated. This model functions as the predictor of human error when the variables of assembly are known. In the second part, a case study was conducted in an electronic company located in Melaka, Malaysia. This company uses an assembly line to produce their products. The case study only focused on the effect of work pace on the occurrence of human errors that lead to product defects. The other variables, such as working position, component bin position, jig design and gender, were not included as they were not applicable in the workplace of the case study. Based on the results, it was observed that the occurrence of human error was higher when production target is increase above the normal capacity. This situation was recognized that there was a time pressure to the workers. In addition, the number of errors also increased as the production target lower than the normal production capacity. The relationship of product defects and production output can be represented using a U-model, where the number of product defects was higher when the production output was lower or higher than the normal production target. This finding was consistent with the experimental results, where time pressure affects the occurrence of human errors. 2015 Thesis http://eprints.utem.edu.my/id/eprint/16877/ http://eprints.utem.edu.my/id/eprint/16877/1/The%20Effect%20Of%20Working%20Conditions%20And%20Gender%20On%20Human%20Errors%20In%20Manual%20Assembly%20Line.pdf text en public http://eprints.utem.edu.my/id/eprint/16877/2/The%20effect%20of%20working%20conditions%20and%20gender%20on%20human%20errors%20in%20manual%20assembly%20line.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96135 mphil masters Universiti Teknikal Malaysia Melaka Faculty Of Manufacturing Engineering Saptari, Adi 1. Ahmada, N., Taha, Z. and Eu, P., 2006. Energetic requirement, muscle fatigue, and musculoskeletal risk of prolonged standing on female Malaysian operators in the electronic industries: influence of age. Eng e-Trans (University of Malaya), 1, pp.47-58. 2. Alzuheri, A., Luong, L. and Xing, K., 2010. Ergonomics design measures in manual assembly work. In: Engineering Systems Management and Its Applications (ICESMA), 2010 Second International Conference, Sharjah, 30 March - 1April 2010, IEEE. 3. Ardila, A., Rosselli, M., Matute, E. and Inozemtseva, O., 2011. Gender differences in cognitive development. Developmental psychology, 47(4), pp,984-990. 4. Arvidsson, I., Åkesson, I. and Hansson, G. Å., 2003. Wrist movements among females in a repetitive, non-forceful work. Applied ergonomics, 344), pp. 309-316. 5. Badenhorst, F. and Van Tonder, J., 2004. Determining the factors causing human error deficiencies at a public utility company. SA Journal of Human Resource Management, 2(3), pp.62-69. 6. Baines, T. S., Asch, R., Hadfield, L., Mason, J., Fletcher, S. and Kay, J. M., 2005. Towards a theoretical framework for human performance modelling within manufacturing systems design. Simulation modelling practice and theory, 13(6), pp.486-504. 7. Chong, D. S., Van Eerde, W., Chai, K. H. and Rutte, C. G., 2011. A double-edged sword: The effects of challenge and hindrance time pressure on new product development teams. Engineering Management, IEEE Transactions, 58(1), pp.71-86. 8. Chraif, M. and Anitei, M., 2013. Gender Differences in Motor Coordination at Young Students at Psychology. International Journal of Social Science and Humanity, 3(2), pp.147-151. 9. Christensen, H., Søgaard, K., Pilegaard, M. and Olsen, H. B., 2000. The importance of the work/rest pattern as a risk factor in repetitive monotonous work. International Journal of Industrial Ergonomics, 25(4), pp.367-373. 10. Dai, Q., 2006. On relation of manufacturing system, manufacturing mode and manufacturing technology. In: International Technology and Innovation Conference 2006 (ITIC 2006), Hangzhou, China International, 6-7 November 2006, IET. 11. de Looze, M., Bosch, T. and van Dieën, J., 2009. Manifestations of shoulder fatigue in prolonged activities involving low-force contractions. Ergonomics, 52(4), pp. 428-437. 12. Dhafr, N., Ahmad, M., Burgess, B. and Canagassababady, S., 2006. Improvement of quality performance in manufacturing organizations by minimization of production defects. Robotics and Computer-Integrated Manufacturing, 22(5), pp.536-542. 13. Dhillon, B. and Liu, Y., 2006. Human error in maintenance: a review. Journal of Quality in Maintenance Engineering, 12(1), pp.21-36. 14. Dhillon, B. and Shah, A. S., 2007. Availability analysis of a generalized maintainable three-state device parallel system with human error and common-cause failures. Journal of Quality in Maintenance Engineering, 13(4), pp.411-432. 15. Ding, Z., Hon, K. and Shao, F., 2011. A virtual assembly approach for product assemblability analysis and workplace design. In: Proceedings of the 21st CIRP Design Conference, Daejeon, Korea, KAIST. 16. Embrey, D., 2005. Understanding human behaviour and error. Human Reliability Associates, 1, pp.1-10. 17. Escalante, E. J., 1999. Quality and productivity improvement: a study of variation and defects in manufacturing. Quality Engineering, 11(3), pp.427-442. 18. Escorpizo, R. and Moore, A., 2007. The effects of cycle time on the physical demands of a repetitive pick-and-place task. Applied Ergonomics, 38(5), pp.609-615. 19. Ghasemi, A. and Zahediasl, S., 2012. Normality tests for statistical analysis: a guide for non-statisticians. International Journal of Endocrinology and Metabolism, 10(2), pp.486-489. 20. Grabowski, M., You, Z., Zhou, Z., Song, H., Steward, M. and Steward, B., 2009. Human and organizational error data challenges in complex, large-scale systems. Safety Science, 47(8), pp.1185-1194. 21. Grandjean, E. and Kroemer, K. H. 1997. Fitting the task to the human: a textbook of occupational ergonomics, Boca Raton, Florida: CRC press. 22. Grzechca, W., 2011. Cycle Time in Assembly Line Balancing Problem. In: 21st International Conference on Systems Engineering, Las Vegas, Nevada USA, 16-18 August 2011, IEEE. 23. Haatainen, J., 2010. Workplace accidents in Finnish manufacturing maintenance. In: 2010 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Macao, Hong Kong, 7-10 December 2010, IEEE. 24. Hahn, M., Lawson, R. and Lee, Y. G., 1992., The effects of time pressure and information load on decision quality. Psychology & Marketing, 9(5), pp.365-378. 25. Halim, I., Omar, A. R., Saman, A. M. and Othman, I., 2012. Assessment of Muscle Fatigue Associated with Prolonged Standing in the Workplace. Safety and health at work, 3(1), pp.31-42. 26. Hasegawa, T., Inoue, K., Tsutsue, O. and Kumashiro, M., 2001. Effects of a sit–stand schedule on a light repetitive task. International Journal of Industrial Ergonomics, 28(3), pp.219-224. 27. Heidel, D. S., 2008. Manufacturing sector. Journal of safety Research, 39(2), pp.183-186. 28. Heizer, J. H., 1998. Determining responsibility for development of the moving assembly line. Journal of Management History (Archive), 4(2), pp.94-103. 29. Helander, M., 2005. A guide to human factors and ergonomics ,2nd ed., Boca Raton, Florida: Crc Press. 30. Hicks. C. R., 1993. Fundamental Concepts in Design of Experiments, 4th ed., Florida: Saunders College Publishing 31. Hiraiwa, M. and Nakade, K., 2009. Periodicity of Cycle Time in a U-Shaped Production Line with Heterogeneous Workers under Carousel Allocation. Journal of Service Science, 2(4), pp.265-269. 32. Hollnagel, E., 1998. Cognitive reliability and error analysis method (CREAM), Elsevier Science. 33. Hwang, M. I., 1994. Decision making under time pressure: a model for information systems research. Information & Management, 27(4), pp.197-203. 34. Isaksen, J., 2000. Constructing meaning despite the drudgery of repetitive work. Journal of Humanistic Psychology, 40(3), pp.84-107. 35. Ji, P., Sze, M. and Lee, W., 2001. A genetic algorithm of determining cycle time for printed circuit board assembly lines. European journal of operational research, 128(1), pp.175-184. 36. Jo, Y. D. and Park, K. S., 2003. Dynamic management of human error to reduce total risk. Journal of Loss Prevention in the Process Industries, 16(4), pp.313-321. 37. Kalpakjian, S. and Schmid, S. R., 2010. Manufacturing Engineering and Technology, 6th ed., Pearson Education South Asia. 38. Karim, M., Smith, A., Halgamuge, S. and Islam, M. 2008. A comparative study of manufacturing practices and performance variables. International Journal of Production Economics, 112(2), pp.841-859. 39. Karwowski, W. and Marras, W. S., 2003. Occupational Ergonomics: Principles of Work Design, Boca Raton, Florida: CRC Press. 40. Kelly, J. R. and Loving, T. J. 2004. Time pressure and group performance: Exploring underlying processes in the attentional focus model. Journal of experimental social psychology, 40(2), pp.185-198. 41. Khan, A. and Day, A. J.,2002. A knowledge based design methodology for manufacturing assembly lines. Computers & Industrial Engineering, 41(4), pp.441-467. 42. Koskinen, J., Heikkila, T. and Pulkkinen, T., 2010. A Monitoring Concept for Co-operative Assembly Tasks. In: Frontier of Assembly and Manufacturing (Lee, S., Suarez, R. and Choi, B-W.), pp.171-184, Springer Berlin Heidelberg. 43. Kroemer, K. H., 2005. 'Extra-Ordinary'Ergonomics: How to Accommodate Small and Big Persons, The Disabled and Elderly, Expectant Mothers, and Children, Boca Raton, Florida: CRC Press. 44. Latino, R. J., 2007. Defining and Reducing Human Error [online]. Available in: http://www.reliability.com/healthcare/ [Accessed on 7 September 2013]. 45. Latorella, K. A. and Prabhu, P. V., 2000. A review of human error in aviation maintenance and inspection. International Journal of Industrial Ergonomics, 26(2), pp.133-161. 46. Lawton, R. and Parker, D. 1998. Individual differences in accident liability: A review and integrative approach. Human Factors: The Journal of the Human Factors and Ergonomics Society, 40(4), pp.655-671. 47. Li, P.-c., Zhang, L., Chen, G.-h. and Dai, L.-c., 2010. Study on Human Error Expanded Model and Context Influencing Human Reliability in Digital Control Systems. In: 2010 International Conference on E-Product, E-Service and E-Entertainment (ICEEE), Henan, China, 7-9 November 2010, IEEE. 48. Li, Z., Yiqun, W. and Zhiliang, D., 1996. Human error factor identification in complex man-machine systems. In: IEEE International Conference on Systems, Man and Cybernetics, Beijing, China, 14-17 October 1996, IEEE. 49. Liang, G. F., Lin, J. T., Hwang, S. L., Wang, E. M. and Patterson, P., 2010. Preventing human errors in aviation maintenance using an on-line maintenance assistance platform. International Journal of Industrial Ergonomics, 40(3), pp.356-367. 50. Liu, H., Hwang, S. L. and Liu, T. H. 2009. Economic assessment of human errors in manufacturing environment. Safety Science, 47(2), pp.170-182. 51. Malaysian Investment Development Authority (MIDA), 2012. Electrical and Electronics Industry. [online] Available at: http://www.mida.gov.my/ [Accessed on 18 February 2014]. 52. Meister, D., 1989. The nature of human error. In: Global Telecommunications Conference and Exhibition "Communications Technology for the 1990s and Beyond" (GLOBECOM), Dallas, Texas USA, 27-30 November 1989, IEEE. 53. Miguel, A. R., 2006. Human error analysis for collaborative work. PhD Dissertation, University of York. 54. Montgomery, D. C., Peck, E. A. and Vining, G. G., 2012. Introduction to linear regression analysis, 5th ed., New Jersey: John Wiley & Sons. 55. Nee, A. Y. C., Tao, Z. J. and Kumar, A. S., 2004. An advanced treatise on fixture design and planning, World Scientific Publishing Company. 56. Ngcamu, N. S., 2009. Awkward working postures and precision performance as an example of the relationship between ergonomics and production quality. Phd Dissertation, Rhodes University. 57. Nordander, C., Ohlsson, K., Balogh, I., Hansson, G.-Å., Axmon, A., Persson, R. and Skerfving, S., 2008. Gender differences in workers with identical repetitive industrial tasks: exposure and musculoskeletal disorders. International archives of occupational and environmental health, 81(8), pp.939-947. 58. O’Sullivan, L. and Gallwey, T., 2002. Effects of gender and reach distance on risks of musculoskeletal injuries in an assembly task. International Journal of Industrial Ergonomics, 29(2), pp.61-71. 59. Park, K. S. and Jung, K. T., 1996. Considering performance shaping factors in situation-specific human error probabilities. International Journal of Industrial Ergonomics, 18(4), pp.325-331. 60. Paul, S. and Nazareth, D. L., 2010. Input information complexity, perceived time pressure, and information processing in GSS-based work groups: An experimental investigation using a decision schema to alleviate information overload conditions. Decision Support Systems, 49(1), pp.31-40. 61. Paz Barroso, M. and Wilson, J., 2000. Human error and disturbance occurrence in manufacturing systems (HEDOMS): A framework and a toolkit for practical analysis. Cognition, Technology & Work, 2(2), pp.51-61. 62. Rajan, V. N., Sivasubramanian, K. and Fernandez, J. E., 1999. Accessibility and ergonomic analysis of assembly product and jig designs. International Journal of Industrial Ergonomics, 23(5), pp.473-487. 63. Raouf, A., Tsui, C. and El-Sayed, E., 1980. A new heuristic approach to assembly line balancing. Computers & Industrial Engineering, 4(3), pp.223-234. 64. Rasmussen, J., 1982. Human errors. A taxonomy for describing human malfunction in industrial installations. Journal of occupational accidents, 4(2), pp.311-333. 65. Rasmussen, J. 1983. Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. IEEE Transactions on Systems, Man and Cybernetics , SMC-13(3), pp.257-266. 66. Razali, N. M. and Wah, Y. B., 2011. Power comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests. Journal of Statistical Modeling and Analytics, 2(1), pp.21-33. 67. Reason, J., 1990. Human Error . Cambridge: Cambridge University Press. 68. ReliaSoft Corporation, 2010. Determining significant effects in 2k designs with a single replication. [online] Available at: www.weibull.com/hotwire/issue113/relbasics113.htm [Accessed on 7 December 2014]. 69. Rooney, J. J., Heuvel, L. N. V. and Lorenzo, D. K., 2002. Reduce human error. Quality progress, 35(9), pp.27-36. 70. Ruckart, P. Z. and Burgess, P. A., 2007. Human error and time of occurrence in hazardous material events in mining and manufacturing. Journal of hazardous materials, 142(3), pp.747-753. 71. Salmon, P. M., Regan, M. A. and Johnston, I., 2005. Human error and road transport: Phase one–Literature review; No. 256, December 2005, Australia: Monash University 72. Sanders, M. S. and McCormick, E. J., 1993. Human factors in engineering and design, 7th ed., Singapore: McGraw-Hill Book Co-Singapore. 73. Saptari, A., Kamat, S. R., Wan Mahmood, W. H. and Halim, I. 2007., Optimum Workspace Design in A Plug Assembly Line. Journal of Biomechanics, 40(2), pp. 155-162 74. Saptari, A., Lai, W. S. and Salleh, M. R., 2011. Jig design, assembly line design and work station design and their effect to productivity. Jordan Journal of Mechanical and Industrial Engineering, 5(1), pp.9-16. 75. Saurin, T. A., Formoso, C. T. and Cambraia, F. B., 2004. A Human Error Perspective of Safety Planning and Control. In: Proceeding of 12th Conference of the International Group for Lean Construction, Elsinore, Denmark . 76. Sauter, S. L., Murphy, L., Hurrell, J. and Levi, L., 1998. Psychosocial and organizational factors. [online] Available at: http://ilocis.org/documents/chpt34e.htm [Accessed on 10 December 2013]. 77. Schreuder, E. J. and Mioch, T., 2011. The effect of time pressure and task completion on the occurrence of cognitive lockup. In: Proceedings of the International Workshop on Human Centered Processes 2011 (HCP 2011), 10-11 February 2011, Genoa, Italy, . 78. Sedam, M. W., 2008. Human error: a manageable certainty. [online] Available at: http://www.alea.org/public/airbeat/back_issues/nov_dec_2008/Human%20Error.pdf [Accessed on 10 December 2013]. 79. Shi, W., Jiang, F., Zheng, Q. and Cui, J., 2011. Analysis and Control of Human Error. Procedia Engineering, 26, pp.2126-2132. 80. Shikdar, A. and Al-Hadhrami, M., 2005. Operator Performance and Satisfaction in an Ergonomically Designed Assembly Workstation. The Journal of Engineering Research, 2(1), pp.69-76. 81. Shikdar, A. A. and Das, B. 2003. The relationship between worker satisfaction and productivity in a repetitive industrial task. Applied Ergonomics, 34, 603-610. 82. Silverstein, B. A., Fine, L. J. and Armstrong, T. J., 1986. Hand wrist cumulative trauma disorders in industry. British Journal of Industrial Medicine, 43(11), pp.779-784. 83. Stephens, M. P. and Meyers, F. E., 2013. Manufacturing facilities design and material handling, Indiana: Purdue University Press. 84. Stevenson, W. J. and Sum, C. C. 2010. Operation Management : An Asian Perspective, McGraw-Hill Education (Asia). 85. Stockburger, D. W., 2013. Introductory Statistics: Concepts, Models, and Applications [online]. Available at: http://www.psychstat.missouristate.edu/IntroBook3/sbk.htm [Accessed on 7 December 2013]. 86. Stork, S. and Schubö, A., 2010. Human cognition in manual assembly: Theories and applications. Advanced Engineering Informatics, 24(3), pp.320-328. 87. Su, Q., Liu, L. and Whitney, D. E., 2010. A systematic study of the prediction model for operator-induced assembly defects based on assembly complexity factors. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 40(1), pp.107-120. 88. Sylla, C. and Drury, C. G., 1995. Signal detection for human error correction in quality control. Computers in industry, 26(2), pp.147-159. 89. Taib, I. A., McIntosh, A. S., Caponecchia, C. and Baysari, M. T., 2011. A review of medical error taxonomies: A human factors perspective. Safety Science, 49(5), pp.607-615. 90. Trochim, W. M. K. 2006a. Descriptive Statistics [online]. Available at: http://www.socialresearchmethods.net/kb/statdesc.php [Accessed on 7 December 2013]. 91. Trochim, W. M. K. 2006b. The T-Test [online]. Research Methods Knowledge Base. Available at: http://www.socialresearchmethods.net/kb/stat_t.php [Accessed on 24 July 2014]. 92. Tropical Biology Association. 2008. A simple guide to Minitab [online]. Available at: http://www.tropical-biology.org/admin/documents/pdf_files/Skills_series/Minitab%2028My.pdf [Accessed on 25 April 2014]. 93. Van Dyck, C., Frese, M., Baer, M. and Sonnentag, S., 2005. Organizational error management culture and its impact on performance: a two-study replication. Journal of Applied Psychology; Journal of Applied Psychology, 90(6), pp.1228-1240. 94. Vorne Industries Inc., 2014. Takt Time [online]. Available at: http://www.vorne.com/learning-center/takt-time.htm [Accessed on 4 March 2014]. 95. Wang, D. and Shi, K., 2010. The influence of reasoning capacity and time pressure on the information search pattern of career decision making. In: IEEE 2nd Symposium on Web Society (SWS), Beijing, China, 16-17 August 2010, IEEE. 96. Wartenberg, C., Dukic, T., Falck, A. C. and Hallbeck, S., 2004. The effect of assembly tolerance on performance of a tape application task: A pilot study. International Journal of Industrial Ergonomics, 33(4), pp.369-379. 97. Wickens, C. D., Gordon, S. E. and Liu, Y., 2004. An introduction to human factors engineering, 2nd ed., Pearson Education Inc. 98. Work Smart Systems, 2006. Lean Manufacturing & Assembly Line Workstations. [online]. Available at: http://www.worksmartsystems.com/ [Accessed on 3 January 2014]. 99. Wreathall, J., Roth, E., Bley, D. and Multer, J., 2003. Human reliability analysis in support of risk assessment for positive train control. [online] Available at: http://ntl.bts.gov/lib/33000/33600/33684/33684.pdf [Accessed on 14 December 2013]. 100. Yang, L., Su, Q. and Shen, L., 2012. A novel method of analyzing quality defects due to human errors in engine assembly line. In: International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII), Sanya, China, 20-21 October 2012, IEEE. 101. Yang, Q., Jiang, D., Sun, J. and Tong, S., 2010. Cortical synchrony change under mental stress due to time pressure. In: 3rd International Conference on Biomedical Engineering and Informatics (BMEI), Yantai, China, 16-18 October 2010, IEEE. 102. Yeow, P. H. and Nath Sen, R., 2006. Productivity and quality improvements, revenue increment, and rejection cost reduction in the manual component insertion lines through the application of ergonomics. International Journal of Industrial Ergonomics, 36(4), pp.367-377. 103. Young, M. and Stanton, N., 2001. Mental workload: theory, measurement, and application. International encyclopedia of ergonomics and human factors, 1, pp.507-509.