General Motors Increases Its Production Throughput

Jeffrey M. Alden (), Lawrence D. Burns (), Theodore Costy (), Richard D. Hutton (), Craig A. Jackson (), David S. Kim (), Kevin A. Kohls (), Jonathan H. Owen (), Mark A. Turnquist () and David J. Vander Veen ()
Additional contact information
Jeffrey M. Alden: General Motors Corporation, Mail Code 480-106-359, 30500 Mound Road, Warren, Michigan 48090
Lawrence D. Burns: General Motors Corporation, Mail Code 480-106-EX2, 30500 Mound Road, Warren, Michigan 48090
Theodore Costy: General Motors Corporation, Mail Code 480-206-325, 30009 Van Dyke Avenue, Warren, Michigan 48090
Richard D. Hutton: General Motors Europe, International Technical Development Center, IPC 30-06, D-65423 Rüsselsheim, Germany
Craig A. Jackson: General Motors Corporation, Mail Code 480-106-359, 30500 Mound Road, Warren, Michigan 48090
David S. Kim: Department of Industrial and Manufacturing Engineering, Oregon State University, 121 Covell Hall, Corvallis, Oregon 97331
Kevin A. Kohls: Soar Technology, Inc., 3600 Green Court, Suite 600, Ann Arbor, Michigan 48105
Jonathan H. Owen: General Motors Corporation, Mail Code 480-106-359, 30500 Mound Road, Warren, Michigan 48090
Mark A. Turnquist: School of Civil and Environmental Engineering, Cornell University, 309 Hollister Hall, Ithaca, New York 14853
David J. Vander Veen: General Motors Corporation, Mail Code 480-734-214, 30003 Van Dyke Road, Warren, Michigan 48093

Interfaces, 2006, vol. 36, issue 1, 6-25

Abstract: In the late 1980s, General Motors Corporation (GM) initiated a long-term project to predict and improve the throughput performance of its production lines to increase productivity throughout its manufacturing operations and provide GM with a strategic competitive advantage. GM quantified throughput performance and focused improvement efforts in the design and operations of its manufacturing systems through coordinated activities in three areas: (1) it developed algorithms for estimating throughput performance, identifying bottlenecks, and optimizing buffer allocation, (2) it installed real-time plant-floor data-collection systems to support the algorithms, and (3) it established common processes for identifying opportunities and implementing performance improvements. Through these activities, GM has increased revenue and saved over $2.1 billion in over 30 vehicle plants and 10 countries.

Keywords: manufacturing; performance/productivity; production/scheduling; applications (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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