Learning and forgetting-based worker selection for tasks of varying complexity

This paper presents an approach for selecting workers for tasks of varying complexity based on individual learning and forgetting characteristics in order to improve system productivity. The performance of a learning and forgetting-based selection (LFBS) policy is examined using simulation and compared to a baseline policy representing criteria used in practice. The effects of factors including worker redundancy and task-tenure on productivity are also examined in the environment of continuously staffed independent tasks. Results demonstrate that the LFBs policy significantly improves productivity relative to common practice and suggests that lower levels of redundancy and shorter task-tenures tend to mitigate some of the negative effects of forgetting.

[1]  David A. Nembhard,et al.  The Effects of Worker Learning, Forgetting, and Heterogeneity on Assembly Line Productivity , 2001, Manag. Sci..

[2]  A. van den Beukel,et al.  Multifunctionality: Driving and constraining forces , 1998 .

[3]  Ezey M. Dar-Ei,et al.  Human learning : from learning curves to learning organizations , 2000 .

[4]  Eric R. Ziegel,et al.  Probability and Statistics for Engineering and the Sciences , 2004, Technometrics.

[5]  Paul M. Bobrowski,et al.  An evaluation of labor assignment rules when workers are not perfectly interchangeable , 1993 .

[6]  C. A. Carnall,et al.  SEMI‐AUTONOMOUS WORK GROUPS AND THE SOCIAL STRUCTURE OF THE ORGANIZATION , 1982 .

[7]  David A. Nembhard,et al.  An individual-based description of learning within an organization , 2000, IEEE Trans. Engineering Management.

[8]  Michael J. Papa,et al.  Perceptual and communicative indices of employee performance with new technology , 1990 .

[9]  Charles E. Lance,et al.  Joint Relationships of Task Proficiency With Aptitude, Experience, and Task Difficulty: A Cross-Level, Interactional Study , 1989 .

[10]  J. Shields,et al.  Retention of Motor Skills. Review , 1978 .

[11]  Tarald O. Kvålseth,et al.  The effect of task complexity on the human learning function , 1978 .

[12]  D. Bates,et al.  Mixed-Effects Models in S and S-PLUS , 2001 .

[13]  Norbert L. Kerr,et al.  Effects of group size, problem difficulty, and sex on group performance and member reactions. , 1978 .

[14]  D A Nembhard,et al.  Heuristic approach for assigning workers to tasks based on individual learning rates , 2001 .

[15]  Larry H Ford,et al.  Knowledge Retention Among Graduates of Basic Electricity and Electronics Schools. , 1983 .

[16]  Bernard C. Y. Tan,et al.  Three important determinants of user performance for database retrieval , 1999, Int. J. Hum. Comput. Stud..

[17]  David A. Nembhard,et al.  The Effects of Task Complexity and Experience on Learning and Forgetting: A Field Study , 2000, Hum. Factors.

[18]  Timothy D. Fry,et al.  Modeling simultaneous worker learning and forgetting in dual resource constrained systems , 1999, Eur. J. Oper. Res..

[19]  Louis E. Yelle.  THE LEARNING CURVE: HISTORICAL REVIEW AND COMPREHENSIVE SURVEY , 1979 .

[20]  David A. Nembhard,et al.  An empirical comparison of forgetting models , 2001, IEEE Trans. Engineering Management.

[21]  M. Drenth.  San Juan, Puerto Rico , 2001 .

[22]  Nancy Lea Hyer,et al.  Cellular manufacturing in the U.S. industry: a survey of users , 1989 .

[23]  Joseph D. Hagman,et al.  Retention of Military Tasks: A Review , 1983 .

[24]  Jos A. C. Bokhorst,et al.  Long-term allocation of operators to machines in manufacturing cells , 2000 .

[25]  Mustafa Uzumeri,et al.  Experiential learning and forgetting for manual and cognitive tasks , 2000 .

[26]  Manoj K. Malhotra,et al.  An evaluation of worker assignment policies in dual resource-constrained job shops with heterogeneous resources and worker transfer delays , 1994 .

[27]  C. Lance,et al.  Moderators of Skill Retention Interval/Performance Decrement Relationships in Eight U.S. Air Force Enlisted Specialties , 1998 .