Adapting Design for Six Sigma (DFSS) Methodology for Diesel Lean NOx Trap (LNT) Catalyst Screening

Paper #:
  • 2016-01-0953

Published:
  • 2016-04-05
DOI:
  • 10.4271/2016-01-0953
Citation:
Ahari, H., Smith, M., Zammit, M., and Walker, B., "Adapting Design for Six Sigma (DFSS) Methodology for Diesel Lean NOx Trap (LNT) Catalyst Screening," SAE Technical Paper 2016-01-0953, 2016, doi:10.4271/2016-01-0953.
Pages:
8
Abstract:
In order to meet LEV III, EURO 6C and Beijing 6 emission levels, Original Equipment Manufacturers (OEMs) can potentially implement unique aftertreatment systems solutions which meet the varying legislated requirements. The availability of various washcoat substrates and PGM loading and ratio options, make selection of an optimum catalyst system challenging, time consuming and costly.Design for Six Sigma (DFSS) methodologies have been used in industry since the 1990s. One of the earliest applications was at Motorola where the methodology was applied to the design and production of a paging device which Consumer Reports called “virtually defect-proof”.[1] Since then, the methodology has evolved to not only encapsulate complicated “Variation Optimization” but also “Design Optimization” where multiple factors are in play.In this study, attempts are made to adapt the DFSS concept and methodology to identify and optimize a catalyst for diesel applications. Lean NOx Trap (LNT) was selected as the catalyst of choice as it could become a development choice in future aftertreatment architecture for above-mentioned emission levels and cold start improvements. Catalysts from multiple washcoat manufacturers’ current production were acquired. Factors such as washcoat type, PGM loading, ratio and component aging were investigated. Catalyst performance was optimized under a specific set of testing conditions.The study proved that the DFSS methodology is a powerful tool that can be adapted for screening large number of catalysts in a relatively short period of time with reduced number of tests, under identical conditions with promising results.
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