By Topic

Stochastic Model for Manufacturing Cost Estimating

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Abraham, C.T. ; IBM Corporate Headquarters, Armonk, New York 10504, USA ; Prasad, R.D.

The unit manufacturing cost (i.e., its estimator) for a given manufacturing program with stochastic demand and operation yield is assumed to be a random variable. For a simple series production line the probability distribution of the unit manufacturing cost has been derived by either the transform method, which uses Mellin and Laplace transforms, or the method of moments, which uses either the Gram-Charlier series approximation or the Pearson system of frequency curves. The estimates and 90%-confidence intervals for the base manufacturing cost are computed for two device-component products. The model cost estimates are very close to the actual values and the confidence intervals are sufficiently narrow to be useful in applying contingencies to the predictions.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:13 ,  Issue: 4 )