An Empirical Analysis of a Process Design Considering Worker's Cognition

작업자의 인지를 고려한 공정 설계에 대한 실증 연구

  • 김연민 (울산대학교 산업경영공학부)
  • Received : 2015.08.11
  • Accepted : 2015.12.07
  • Published : 2016.04.15


This study suggests a process design using cognitive processes. Job characteristic model for job design and recent cognitive engineering studies for process design are reviewed briefly. By using these concepts, the lean production system is re-interpreted in terms of cognitive engineering and the latent dimensions of the lean production system are revealed as the application of cognitive engineering principles. An integrated process design framework for cognitive manufacturing system using job characteristic model is suggested for the effective design of manufacturing system. Propositions for empirical analysis of this model are also analyzed through a questionnaire survey. Propositions are (1) experiential cognition and motivation potential affect the ability, role perception, and need for achievement of the operator in the manufacturing system, (2) the ability, role perception, and need for achievement of the operator affect the job performance. Both propositions are supported by correlation analysis and path analysis.


  1. Black, J. T. and Hunter, S. (2003), Lean Manufacturing Systems and Cell design, Society of Manufacturing Engineers.
  2. Bullemer, P. T. and Nimmo, I. (1994), Understanding and supporting abnormal situation management in industrial process control environments : a new approach to training, Proc. of IEEE Systems, Man and Cybernetics Conference, 391-396.
  3. Davy, J., White, R., Merritt, N., and Gritzmacher, K. (1992), A derivation of the underlying constructs of just-in-time management systems, Academy of Management Journal, 35(3) 653-670.
  4. De Greene, K. B. (1991), Large technology-based systems and the need for paradigm shift, Technological Forecasting and Social Change, 39, 349-362.
  5. Grief, M. (1991), The Visual Factory, Productivity Press, Cambridge, Massachusetts.
  6. Hackman, J. R. and Oldham, G. R. (1976), Motivation through the design of work : test of a theory, Organizational Behavior and Human Performance, 16, 250-279.
  7. Leschziner, V. and Green, A. I. (2013), Thinking about food and sex : Deliberate cognition in the routine practices of a field, Sociological Theory, 31(2), 116-144.
  8. MacDuffie, J. (1997), The road to 'Root Cause' : Shop-floor problemsolving at three auto assembly plants, Management Science, 43(4) 479-502.
  9. Norman, D. A. (1993), Things that makes us smart, Addison Wesley.
  10. Norman, D. A. (1988), The design of everyday things, Basic books.
  11. Oh, Y. K. et al. (2015), Modeling and implementation of the affordancebased human-machine collaborative system, Journal of the Korean Institute of Industrial Engineers, 41(1), 34-42.
  12. Rasmussen, J., Pejtersen, A. M., and Goodstein, L. P. (1994), Cognitive Systems Engineering, Wiley Interscience.
  13. Sakakibara, S., Flynn, B., Schroder, R., and Morris, W. (1997), The impact of just-in-time manufacturing and its infrastructure on manufacturing performance, Management Science, 43(9), 1246-1257.
  14. Sengupta, K. and Abdel-Hamid, T. K. (1993), Alternative conceptions of feedback in dynamic decision environments : An experimental investigation, Management Science, 39(4), 411-428.
  15. Shea, K. (2010), The cognitive factory, Advanced Engineering Informatics, 24. 241-242.
  16. Snell, S. A. and Jr. Dean, J. W. (1992), Integrated manufacturing and human resource management : a human capital perspective, Academy of Management Journal, 35(3), 467-504.
  17. Steers, R. and Black, S. (1994), Organizational Behavior, Harper Collins, Fifth ed.
  18. Wickens, C. (1999), Engineering Psychology and Human Performance, Prentice Hall, 3rd ed.
  19. Woods, D. (1994), Human Computer Interaction in Complex Systems, Unpublished Notes, The Ohio States University.