In todays global market there is a continuous pressure on the Original Equipment Manufacturers (OEM's) to improve service processes that directly relate to the customer satisfaction. Aftersales -service is a critical business process that has a significant impact on the consumers perception about the brand and the product quality. A recent study by J.D. Power and associates revealed that customer satisfaction with the dealer service and the cost of service/repair have significant impact (over 20%) on the notion of customer satisfaction. Also, incorrect service results in poor QRD (quality, reliability and durability) that in turn increases customer dissatisfaction. On the other hand, in the last couple of decades, the use of electronic systems in automotives has grown rapidly. This growth is driven by the growing requirements for environmental protection and demands from the consumers to improve fuel economy, comfort and safety. As a result, the amount of software embedded in a vehicle increased to tens of millions of lines of codes. Such a complex nature of modern vehicle systems often restricts service technicians ability to diagnose the problem accurately in a short time.In this paper, we propose a novel integrated framework combining association rule mining, case-based reasoning and text mining that can be used to continuously improve service and repair in an automotive domain. The developed framework enables identification of anomalies in the field that cause customer dissatisfaction and performs root cause investigation of the anomalies. It also facilitates identification of the best practices in the field and learning from these best practices to achieve lean and effective service. Association rule mining is used for the anomaly detection and the root cause investigation, while casebased-reasoning in conjunction with text mining is used to learn from the best practices. The integrated system is implemented in a web based distributed architecture and has been tested on real life data.


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    Titel :

    An integrated framework for effective service and repair in the automotive domain: An application of association mining and case-based-reasoning


    Beteiligte:

    Erschienen in:

    Computers in Industry ; 62 , 7 ; 742-754


    Erscheinungsdatum :

    2011


    Format / Umfang :

    13 Seiten, 6 Bilder, 5 Tabellen, 28 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch





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