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Bangalore, India
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Last M.,Ben - Gurion University of the Negev | Sinaiski A.,Ben - Gurion University of the Negev | Subramania H.S.,Technical Center India Pvt Ltd
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

Unexpected failures occurring in new cars during the warranty period increase the warranty costs of car manufacturers along with harming their brand reputation. A predictive maintenance strategy can reduce the amount of such costly incidents by suggesting the driver to schedule a visit to the dealer once the failure probability within certain time period exceeds a pre-defined threshold. The condition of each subsystem in a car can be monitored onboard vehicle telematics systems, which become increasingly available in modern cars. In this paper, we apply a multi-target probability estimation algorithm (M-IFN) to an integrated database of sensor measurements and warranty claims with the purpose of predicting the probability and the timing of a failure in a given subsystem. The multi-target algorithm performance is compared to a single-target probability estimation algorithm (IFN) and reliability modeling based on Weibull analysis. © 2010 Springer-Verlag Berlin Heidelberg.

Routray A.,Indian Institute of Technology Kharagpur | Rajaguru A.,Indian Institute of Technology Kharagpur | Singh S.,Technical Center India Pvt. Ltd
2010 IEEE International Conference on Automation Science and Engineering, CASE 2010 | Year: 2010

In this paper, we propose a data-driven method to detect anomalies in operating Parameter Identifiers (PIDs) and in the absence of any anomaly, classify faults in automotive systems by analyzing PIDs collected from the freeze frame data. We first categorize the operating parameter data using automotive domain knowledge. The dataset thus obtained is then analyzed using Principal Component Analysis (PCA) and Independent Component Analysis (ICA) for finding coherence among the PIDs. Then we use clustering algorithms based on both linear distance and information theoretic measures to assign coherent PIDs to the same class or cluster. A comparative analysis of the behavior of PIDs belonging to the same cluster can now be made for detecting anomaly in PIDs. Since a system fault is characterized by the values by of all PIDs across all the clusters, we use the joint probability distribution of the independent components of all PIDs to characterize the fault and find the divergence between the joint distributions of training and test data to classify faults. The proposed method can analyze available parameter data, categorize PIDs into informative or non-informative category, and detect fault condition from the clusters. We demonstrate the algorithm by way of an application to operating parameter data collected during faults in catalytic converters of vehicles. © 2010 IEEE.

Rajpathak D.,Technical Center India Pvt. Ltd. | Chougule R.,Technical Center India Pvt. Ltd.
International Journal of Computer Integrated Manufacturing | Year: 2011

Data inconsistency and data mismatch are critical problems that limit data interoperability and hinder smooth operation of a distributed business. An ontology represents a semantic model that explicitly describes various entities and their properties of a domain of discourse and acts as a vehicle for seamless data integration and exchange. The existing methodologies for ontology development fail to provide a comprehensive coverage for different steps, e.g. pre-development, development and post-development, which are necessary for successfully developing ontologies. We propose a generic and comprehensive methodology that puts ontology engineering on a firm scientific foundation and at the same time provides a collaborative environment for effective knowledge sharing and reuse. Furthermore, our approach also provides a way for automatically extracting frequent terms from the data to construct an ontology in a bottom-up fashion. The performance of our methodology has been evaluated by developing different ontologies to solve the real life applications, e.g. fault diagnosis and root cause investigation and spare parts maintenance. © 2011 Taylor & Francis.

Ramani A.,Technical Center India Pvt Ltd
Structural and Multidisciplinary Optimization | Year: 2011

A heuristic approach to handle strength constraints based on material failure criteria in multi-material topology optimization is presented. This is particularly advantageous if different materials have different failure criteria. The change in the material failure function in an element due to a contemplated material change is estimated without the need for expensive matrix factorizations. This change is used along with the changes to the objective and deflection-based constraint functions, computed using pseudo-sensitivities, to determine a single aggregated ranking parameter for the element. Elements are ranked on the basis of their ranking parameters and this rank is used to modify the material ID-s of a few top-ranked elements during an optimization iteration. The working of the algorithm is demonstrated on a few example problems showing its effectiveness and utility in deriving optimal topologies with multiple materials in the presence of stress and strain-based failure criteria, in addition to the conventional stiffness-based constraints. © 2010 Springer-Verlag.

Subramania H.S.,Technical Center India Pvt. Ltd. | Khare V.R.,Technical Center India Pvt. Ltd.
Decision Support Systems | Year: 2011

Data mining has been a key technology in the warranty sector for mass manufacturers to understand and improve product quality, reliability and durability. Cost savings is an important aspect of business which calls for processes that are error proof. Pattern classification methods applied to the diagnostic data could help build error proof processes by improving the diagnostic technology. In this paper we present a case study from the automotive warranty and service domain involving a human-in-the-loop decision support system (HIL-DSS). The automotive manufacturers offer warranties on products, made of parts from different suppliers, and rely on a dealer network to assess warranty claims. The dealers use diagnostic equipment manufactured by third parties and also draw on their own expertise. In addition, a subject matter expert (SME) assesses these collective decisions to distinguish between inaccurate diagnoses by the dealers or an inadequate decision algorithm in the diagnostic equipment. Altogether this makes a comprehensive HIL-DSS. The proposed methodology continuously learns from collective decision making systems, enhances the diagnostic equipment, adds to the knowledge of dealers and minimizes the SME involvement in the review process of the overall system. Improving the diagnostic equipment helps in better warranty servicing, whereas improvements in the human expert knowledge help prevent field error and avoid customer dissatisfaction due to improper fault diagnosis. © 2010 Elsevier B.V. All rights reserved.

Simulations of evolution of cure-induced stresses in a viscoelastic thermoset resin are presented. The phenomenology involves evolution of resin modulus with degree of cure and temperature, the development of stresses due to crosslink induced shrinkage, and the viscoelastic relaxation of these stresses. For the simulations, the detailed kinetic and chemo-thermo-rheological models for an epoxy-amine thermoset resin system, described in Eom et al. (Polym. Eng. Sci. 2000, 40, 1281) are employed. The implementation of this model into the simulation is facilitated by multiphysics simulation strategies. The trends in simulated cure-induced stresses obtained using the full-fledged viscoelastic model are compared with those obtained from two other equivalent material models, one involving a constant elastic modulus, and the other involving a cure-dependent (but time-invariant) elastic modulus. It is observed that the viscoelastic model not only results in lower estimates of cure-induced stresses, but also provides subtle details of the springback behavior. Copyright © 2012 Wiley Periodicals, Inc.

Rajpathak D.G.,Technical Center India Pvt. Ltd.
Computers in Industry | Year: 2013

In automotive domain, overwhelming volume of textual data is recorded in the form of repair verbatim collected during the fault diagnosis (FD) process. Here, the aim of knowledge discovery using text mining (KDT) task is to discover the best-practice repair knowledge from millions of repair verbatim enabling accurate FD. However, the complexity of KDT problem is largely due to the fact that a significant amount of relevant knowledge is buried in noisy and unstructured verbatim. In this paper, we propose a novel ontology-based text mining system, which uses the diagnosis ontology for annotating key terms recorded in the repair verbatim. The annotated terms are extracted in different tuples, which are used to identify the field anomalies. The extracted tuples are further used by the frequently co-occurring clustering algorithm to cluster the repair verbatim data such that the best-practice repair actions used to fix commonly observed symptoms associated with the faulty parts can be discovered. The performance of our system has been validated by using the real world data and it has been successfully implemented in a web based distributed architecture in real life industry. © 2013 Elsevier B.V.

Patham B.,Technical Center India Pvt. Ltd | Foss P.H.,General Motors
Polymer Engineering and Science | Year: 2014

The strength of vibration welds of thermoplastics is governed by the weld zone microstructure, which in turn, is closely tied to the welding process variables, such as the thickness of the weld melt film and the temperature profiles therein. The mathematical model described in this report is aimed at describing the role of the rheology of the melt - specifically the magnitude and shear rate dependence of the melt viscosity - in governing the melt film variables during the steady state penetration phase (Phase III) of vibration welding. The steady state momentum balance and heat transfer within the melt film are solved by using the power law model for viscosity. Closed-form analytical expressions are obtained for estimating the melt film thickness, the shear rates, and the temperature field within the film. This model has been used to estimate weld zone variables for four different polymers displaying a wide range of viscosities and shear thinning behaviors. POLYM. ENG. SCI., 54:499-511, 2014. © 2013 Society of Plastics Engineers.

Azeem M.A.,Indian Institute of Science | Tewari A.,Technical Center India Pvt. Ltd. | Mishra S.,Technical Center India Pvt. Ltd. | Gollapudi S.,Technical Center India Pvt. Ltd. | Ramamurty U.,Indian Institute of Science
Acta Materialia | Year: 2010

Microstructure and microtexture evolution during static annealing of a hot-extruded AZ21 magnesium alloy was studied. Apart from fine recrystallized equiaxed grains and large elongated deformed grains, a new third kind of abnormal grains that are stacked one after the other in a row parallel to the extrusion direction were observed. The crystallographic misorientation inside these grains was similar to that of the fine recrystallized grains. The large elongated grains exhibited significant in-grain misorientation. A self-consistent mechanistic model was developed to describe the formation of these grain morphologies during dynamic recrystallization (DRX). The texture of pre-extruded material, although lost in DRX, leaves a unique signature which manifests itself in the form of these grain morphologies. The origin of abnormal stacked grains was associated with slow nucleation in pre-extruded grains of a certain orientation. Further annealing resulted in large secondary recrystallized grains with occasional extension twins. © 2009 Acta Materialia Inc.

Patham B.,Technical Center India Pvt Ltd | Foss P.H.,General Motors
Polymer Engineering and Science | Year: 2011

Vibration welding offers a robust method for physically joining thermoplastics to fabricate complex hollow assemblies from simpler injection-molded articles without using an external heat source, adhesives, or mechanical fasteners. Vibration welding involves a complex interplay of several phenomenaa solid (Coulomb) friction, melting, high strain-rate, pressure-driven, strong (high-strain) melt flows, solidification, and microstructure developmenta which ultimately govern the strength and integrity of the weld. Defects in the weld region may lead to catastrophic failure of the welded assembly. In this article, the current understanding of the processing- structure-property relationships in the context of vibration welding of thermoplastics and polymer-matrix composites is reviewed. Experimental as well as analytical methods of investigation of the vibration welding process phenomenology are presented. The interrelationships between the microstructure in the weld region and the resulting weld strength and fatigue behavior are then discussed in the light of this phenomenological information for neat polymers, filled polymers, polymer blends, and foams. This review is also aimed at identifying the areas requiring further investigation with regard to understanding vibration welding phenomenology and weld structure-property relationships. © 2010 Society of Plastics Engineers.

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