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  • Open Access

    ARTICLE

    Automotive Service Quality Investigation Using a Grey-DEMATEL Model

    Phi-Hung Nguyen*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4779-4800, 2022, DOI:10.32604/cmc.2022.030745

    Abstract In today’s fast-challenging business environment, automobile manufacturers are required to supply customers with high-quality vehicles at competitive prices. However, existing research on factors influencing service quality lacks a detailed and systematic understanding, and there is no consensus study on causal relationship and measuring the weights of service quality factors in the automotive manufacturing industry. This study provides an integrated technique for evaluating the automotive service quality in the context of VinFast-the Vietnamese leading brand. First, the Grey Theory System (GTS) is utilized to estimate the subjective views of the decision maker (DM) and overcome incomplete and vague decision information. Then,… More >

  • Open Access

    ARTICLE

    New Hybrid EWMA Charts for Efficient Process Dispersion Monitoring with Application in Automobile Industry

    Xuechen Liu1, Majid Khan2, Zahid Rasheed3, Syed Masroor Anwar4,*, Muhammad Arslan5

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1171-1195, 2022, DOI:10.32604/cmes.2022.019199

    Abstract The EWMA charts are the well-known memory-type charts used for monitoring the small-to-intermediate shifts in the process parameters (location and/or dispersion). The hybrid EWMA (HEWMA) charts are enhanced version of the EWMA charts, which effectively monitor the process parameters. This paper aims to develop two new uppersided HEWMA charts for monitoring shifts in process variance, i.e., HEWMA1 and HEWMA2 charts. The design structures of the proposed HEWMA1 and HEWMA2 charts are based on the concept of integrating the features of two EWMA charts. The HEWMA1 and HEWMA2 charts plotting statistics are developed using one EWMA statistic as input for the… More >

  • Open Access

    ARTICLE

    IIoT Framework Based ML Model to Improve Automobile Industry Product

    S. Gopalakrishnan1,*, M. Senthil Kumaran2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1435-1449, 2022, DOI:10.32604/iasc.2022.020660

    Abstract In the automotive industry, multiple predictive maintenance units run behind the scenes in every production process to support significant product development, particularly among Accessories Manufacturers (AMs). As a result, they wish to maintain a positive relationship with vehicle manufacturers by providing 100 percent quality assurances for accessories. This is only achievable if they implement an effective anticipatory strategy that prioritizes quality control before and after product development. To do this, many sensors devices are interconnected in the production area to collect operational data (humanity, viscosity, and force) continuously received from machines and sent to backend computers for control operations and… More >

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