Pulak Bandyopadhyay

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A Dependency matrix (D-matrix) is a consistent and systematic way to capture hierarchical system-level fault diagnostic information. The D-matrix is derived from a dependency modeling framework to capture the causal relationships between failure modes and symptoms. D-matrices are developed from various sources such as historical field failure data, service(More)
We propose a novel association and text mining system for knowledge discovery (ASTEK) from the warranty and service data in the automotive domain. The complex architecture of modern vehicles makes fault diagnosis and isolation a non-trivial task. The association mining isolates anomaly cases from the millions of service and claims records. ASTEK has shown(More)
This paper addresses the maintenance staffing planning process and the role simulation plays in this process. Feedback control notion is utilized in this personnel planning problem. The research investigates the tradeoffs between maintenance personnel staffing levels and the throughput of a production line. The more reactive maintenance (RM) personnel on(More)
In this paper, we propose a novel integrated framework combining association rule mining, case-basedreasoning 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(More)
In this paper, we develop a method for the quantitative modeling of a Customer Satisfaction Index (CSI) function for consumer vehicles. The mathematical model is evolved using an evolutionary computation technique such that the satisfied and dissatisfied customers are equally distributed on either side of the mean satisfaction level. Instead of relying on a(More)
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