Lot size determination for finite horizon under the effect of productivity and quality learning process

ABSTRACT

Traditional models for determining economic production quantity assume a constant production rate. One result of this assumption is that the number of units produced in a given period is constant. The constant production rate assumption is not valid whenever an operator begins production of a new product, changes to a new machine and restarts after a long break, or implements a new production process. In such situations, the learning effect on production planning and inventory management cannot be ignored. The conventional Wright's learning curve is a curve that solely depicts productivity increasing at a constant percentage as a cumulative number of units are produced. Thus, in addition to the productivity learning process, the quality learning process should also be considered. With the recent development of learning curves that simultaneously take into account quality and productivity, a modified production inventory model has been built to periodically determine the optimal lot size for a finite plan horizon. The productivity considered is the unit production time, while the quality concerned is the unit standard deviation of the production quality level. For the purposes of explanation and comparison, four cases are introduced in this research, and examples are provided for demonstration.

KEYWORDS:

• Learning effect
• lot sizing
• process planning
• cost and quality
• finite plan horizon

Disclosure statement

No potential conflict of interest was reported by the authors

Additional information

Notes on contributors

Angus Jeang

Angus Jeang received his B.S. degree in Industrial Engineering from Chun Yuan University (Taiwan , ROC) and received his M.S. degree in Industrial Engineering from Kansas State University (USA). He was then employed by the Nuclear Division if Siemens Gammasonics, Inc. in Desplaines, Illinois (USA), serving as a manufacturing engineer. After he received his Ph.D. in Industrial and Manufacturing Engineering from Wayne State University, Detroit, Michigan (USA), he got a teaching position at Industrial Engineering of Feng Chia University, Taichung, Taiwan, ROC. Then, he acted as head of department for a period of time. Currently, he is a full professor of this department. In addition, he is a member of the Industrial Engineering (IIE) and the Society of Manufacturing Engineering (SME). His specialized areas are in robust design for product development and process planning, production process and inventory management PERT, CPM, and scheduling, & hospital management.

Abdur Rahim

Dr. Abdur Rahim is a professor of Quantitative Methods, Faculty of Business Administration, University of New Brunswick (UNB) Fredericton, Canada. He joined the UNB in 1983. He received his B.Sc. (Honors) and M.Sc. in Statistics from the University of Dhaka, D.S. in Operations Research from the University of Rome, M.Sc. in Systems Theory from the University of Ottawa and Ph.D in Industrial Engineering from the University of Windsor. Since 1994, Dr. Rahim has been adjunct visiting Professor at King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. He is a member of the Editorial Boards for Economic Quality Control, the Journal of Quality in Maintenance Engineering, the Journal of Quality Engineering and Technology, and the International Journal of Production Research. Dr. Rahim has authored and co-authored more then one hundred research papers in operations research, statistical process control, production planning, inventory control, maintenance and TQM in reputed scholarly journals. He has co-edited books on the emerging field of quality control, were published by Kluwer Academic Publishers. One presents a broad survey of optimization in quality control and focuses on industrial and national competitiveness; while the other focuses on integrated models in production planning, inventory control, and warranty analysis and maintenance policy. In recognition of his performance in research on integrated optimization modelling in quality control, production planning and control, inventory control and maintenance, Dr. Rahim has been awarded continuous funding from Natural Science and Engineering Council of Canada (NSERC) since joining UNB. He has been active in conduction international conferences on industrial engineering and operation management (IEOM) at various parts of the world.