Cost Estimating and Analysis: Balancing Technology and Declining Budgets

ISBN-13: 9781461277279 / Angielski / Miękka / 2011 / 297 str.

Thomas R. Gulledge; William P. Hutzler; Joan S. Lovelace

Opis

Cost analysis and estimating is a vital part of the running of all organizations, both commercial and government. This volume comprises the proceedings of the 1992 conference of the Society for Cost Estimating and Analysis. Individual chapters are written by experts in their respective fields. Consequently, the volume as a whole provides an invaluable and up-to-date survey of the field.

Spis treści

I. Learning and Production Rate.- Learning Curve and Rate Adjustment Models: An Investigation of Bias.- The Production Rate Impact Model: IRATE.- A Bang-Bang Approximation to the Solution of a Learning Augmented Planning Model.- II. Software Economics.- The Software Development Effort Estimation Exponent: An Effort Estimation Model Accounting for Learning and Integration.- Software Cost Estimating Models: A Calibration, Validation, and Comparison.- Cost Estimating for Automated Information Systems.- The Complete COCOMO Model: Basic, Intermediate, Detailed, and Incremental Versions for the Original, Enhanced, Ada, and Ada Process Models of COCOMO.- III. Force Costing.- Calculating the Cost Savings from Reducing Military Force Structure: How to Formulate the Cost Problem.- IV. Systems Cost Analysis.- Cost Analysis of Prototyping Major Weapon Systems Scheduling Using Neural and Symbolic Processing.- Cost Estimating Relations for Space-Based Battle Management, Command, Control, and Communications Systems.- A Review of Estimate at Completion Research.- A CER Approach to Estimating Aircraft Integration Costs.- V. Cost and Production Analysis.- Integrating Cost Analysis and Production System Analysis Using Rapid Modeling Technology.- Policy Formation for National Industries: The Use of Non-Linear Programming Allocation of Joint Costs.- Conceptual Model of an Activity-Based Cost Management System.- VI. Cost Sensitivity Analysis.- Sensitivity Analysis Using Discrete Simulation Models.