A cost modeling approach using learning curves to study the evolution of technology

• Main Author: Kar, Ashish M. (Ashish Mohan)
• Other Authors: Randolph E. Kirchain, Jr. and Richard Roth.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2007
• Subjects: Materials Science and Engineering.
• Online Access: http://hdl.handle.net/1721.1/39556

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2007. === Page 123 blank. === Includes bibliographical references (p. 109-113). === The present work looks into the concept of learning curves to decipher the underlying mechanism in cost evolution. The concept is not new and has been used since last seven decades to understand cost walk down in various industries. The seminal works defined learning in a narrower sense to encompass reduction in man hours as a result of learning. The work done later expanded this concept to include suppliers, long term contracts, management and some other economic and technological factors. But the basic mechanism in all these study was to look at manufacturing cost in an aggregate sense and use the past data to predict the cost walk down in future. In the present work the focus has shifted from looking at cost in an aggregate manner and understanding it more at a manufacturing level using process based cost modeling. This would give a new perspective to the age old problem of cost evolution. Besides it would also give the line engineers and managers a better insight into the levers which eventually lead to cost reduction at manufacturing level. This is achieved by using learning curves to define the manufacturing parameters based on previous observations. The work further looks at cost evolution for new and non-existent technology for which historic data does not exist. This is achieved by building a taxonomic classification of industry based on certain parameters which can be easily guessed. === by Ashish M. Kar. === S.M.