|
| << vorige | volgende >> |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 33 van 129 gevonden artikelen
| Titel: |
Association rule-generation algorithm for mining automotive warranty data |
| Auteur: |
Buddhakulsomsiri, J. Siradeghyan, Y. Zakarian, A. Li, X. |
| Verschenen in: |
International journal of production research |
| Paginering: | Jaargang 44 (2006) nr. 14 pagina's 2749-2770 |
| Jaar: |
2006-07-15 |
| Inhoud: |
A new association rule-generation algorithm is presented for mining automotive warranty data. The algorithm uses elementary set concept and database manipulation techniques to develop useful relationships between product attributes and causes of failure. These relationships (knowledge) are represented using IF-THEN association rules, where the IF portion of the rule includes set of attributes representing product features (e.g. production date, repair date, mileage-at-repair, transmission, engine type, etc.) and the THEN portion of the rule includes set of attributes that represent decision outcome (e.g. problem-related labor code). Once association rules are developed, the algorithm applies a statistical analysis technique to evaluate the significance of each rule. The rules that pass the significance test are reported in a solution. Application of the association rule-generation algorithm is presented with a data-mining case study from the automotive industry. The knowledge (rules) extracted from the automotive warranty data are used to identify root causes of a particular warranty problem or to develop useful conclusions. Detailed discussion on the source and characteristics of warranty data is also presented. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 33 van 129 gevonden artikelen
| << vorige | volgende >> |