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Engineering design leadtime drivers analysis

IP.com Disclosure Number: IPCOM000128110D
Original Publication Date: 1999-Dec-31
Included in the Prior Art Database: 2005-Sep-14
Document File: 4 page(s) / 18K

Publishing Venue

Software Patent Institute

Related People

Nestor Alejandro Macias Anaya: AUTHOR [+3]

Related Documents

http://theses.mit.edu:80/Dienst/UI/2.0/Describe/0018.mit.theses/1999-84: URL

Abstract

Leadtinie is one of the most important performance metrics in the engineering design organization of General Motors' Truck Group. Because of the many variables that influence leadtime. it is not clear where efforts should be focused to improve leadtime. Quantitative models for the variables affecting leadtime were developed and by quantifying their relative impact on overall duration the key variables were identified. Key variables address time spent in design rework. time waiting for informational definition, time waiting for resources, and the base design time for a new vehicle program. The variables influencing leadtime are captured in an influence diagram. The influence diagram shows the relationships among the variables and is supported by quantitative models that can demonstrate design leadtime sensitivity to changes in the model's variables and parameters. In addition, the analysis provides qualitative insight which is useful for framing, recommendations about specific improvement tasks or projects. The analysis of this thesis focused on leadtime delays. The variables related to the turnover of certain designers, to the time waiting for information from design center (styling) and to the time waiting for information from suppliers are the key drivers of leadtime for the engineering systems on the critical path of a program. Moreover. the considerable variance that is observed in overall leadtime indicates that control of variability in the company s development processes will also lead to significant system improvements. A second part of this thesis includes an analysis of action plans to reduce re-staffing delay.

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Engineering Design Leadtime Drivers Analysis

by

Nistor Alejandro Macfas Anaya
B.S. Mechanical-Electrical Engineering Instituto Tecnolbgico y de Estudios Superiores de Monterrey,1993
Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering
Sloan School of Management

at the Massachusetts Institute of Technology

May 1999
SIGNATURE OF author: [[signature omitted]]

MIT Sloan School of Management Department of Mechanical Engineering May, 1999 CERTIFIED BY: [[SIGNATURE OMITTED]]

MIT Sloan School of Management Thesis Supervisor Professor Steven Eppinger
MIT Sloan School of Management Thesis Supervisor ACCEPTED BY: [[SIGNATURE OMITTED]]

Lawrence S. Abeln Director of Master's Program MIT Sloan School of Management BOMIN
Chairman Graduate Committee Department of Mechanical Engineering ARCHIVES MASSACHUSETTS INSTITUTE OF TECHNOLOGY LIBRARIES JUL 12 1999

Massachusetts Institute of Technology Page 1 Dec 31, 1999

Page 2 of 4

Engineering design leadtime drivers analysis

[2]

Engineering Design Leadtime Drivers Analysis

By

Nestor Alejandro Macias Anaya

Submitted to the Sloan School of Management and the Department of Mechanical Engineering in partial fulfillment of the requirements for the degrees of:

Master of Science in Management and Master of Science in Mechanical Engineering

ABSTRACT

Leadtinie is one of the most important performance metrics in the engineering design organization of General Motors' Truck Group. Because of the many variables that influence leadtime. it is not clear where efforts should be focused to improve leadtime. Quantitative models for the variables affecting leadtime were developed and by quantifying their relative impact on overall duration the key variables were identified. Key variables address time spent in design rework. time waiting for informational definition, time waiting for resources, and the base design time for a new vehicle program. The variables influencing leadtime are captured in an influence diagram. The influence diagram shows the relationships among the variables and is supported by quantitative models that can demonstrate design leadtime sensitivity to changes in the model's variables and parameters. In addition, the analysis provides qualitative insight which is useful for framing, recommendations about specific improvement tasks or projects. The analysis of this thesis focused on leadtime delays. The variables related to the turnover of certain designers, to the time waiting for information from design center (styling) and to the time waiting for information from suppliers are the key drivers of leadtime for the engineering systems on the critical path of a program. Moreover. the conside...