Quality Improvement and Warranty Cost Containment: Better Answers are in the Text

Paper #:
  • 2004-01-2666

Published:
  • 2004-10-26
Citation:
Barkai, J., "Quality Improvement and Warranty Cost Containment: Better Answers are in the Text," SAE Technical Paper 2004-01-2666, 2004, https://doi.org/10.4271/2004-01-2666.
Author(s):
Affiliated:
Pages:
7
Abstract:
The automotive industry is plagued with quality concerns and with quality and warranty management issues. As shown in the table below, the industry spends on average more than 2% of its product revenues on warranty costs that total over $10 billion per year. (Source: InformationWeek March 30, 2004) With average warranty reserve exceeding $700 for a vehicle with a typical profit margin of only $175, and market pressure to provide longer and more comprehensive warranties, OEMs and Tier I suppliers carry longer term liabilities and are under increased financial pressure.Increased visibility to product quality, underscored by the TREAD Act warranty data reporting requirements and the FASB warranty disclosure rules, will continue to add to the pressure on OEMs to improve initial quality and significantly improve their ability to quickly detect and correct quality problems.But despite the noticeable results of the concentrated effort by North American manufacturers to improve initial quality, these improvements alone will not suffice to address lifecycle quality in any significant way. Increasing vehicle complexity, frequent new model introductions, and an intricate supply chain will continue to burden the industry and will lessen the impact of initial quality improvement on the bottom line.In addition to improving designed-in quality, OEMs must develop strategies and tools to recognize problems sooner, analyze them faster, and be able to consistently and efficiently focus on those that have the greatest contribution and the most impact on customer satisfaction and on the bottom line.This paper describes a quality management paradigm that facilitates an agile and responsive quality driven organization. This paradigm is centered on replacing the existing coding system by comprehensive mining of failure information from all available repositories, focusing on extracting information from free text repositories that provide more detailed information about problem characteristics than do the codes currently being used.
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