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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Pandey, Vijay Kumar
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Computer Science & IT Engineering

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Journal : IAES International Journal of Artificial Intelligence (IJ-AI)

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Intelligent automation computational modelling for contextual consulting services using Industry 4.0 Pandey, Vijay Kumar; Rathore, Neeraj; Bhosale, Narayan P
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2557-2565

Abstract

The methodology towards operational management and service delivery associated with consulting firms, irrespective of any business domain, are less revisited in perspective from the automation-based process management. Adoption of Industry 4.0 has been attempted by various researchers from the business process management; however, there are less evidence of any computational model towards it. Apart from this, existing models are accompanied by various loopholes which makes its further challenging to analyze it on practical environment. Hence, the proposed study introduces a novel computational and analytical framework which is capable of performing the predictive modelling in order to meet the contextual service development and delivery demands in distributed environment. The novelty of this model is its inclusion of contextual data aggregation, contextual constraint analysis, predictive maintenence, and self-adjusting machine which are core attributes of Industry 4.0 automation standards. The study outcome shows that proposed system offers 20% cost reduction and 89% of minimized service delivery time in contrast to existing related work. Same has been also observed in benchmarked outcomes with state-of-art models.
Framework for contextual consulting practices in adherence for decentralized data-driven decision making Pandey, Vijay Kumar; Rathore, Neeraj; Bhosale, Narayan P.
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2546-2556

Abstract

With the rising adoption of technological advancement and industry-based automation standards, the area of consulting firms is gradually evolving to keep up this pace towards incorporating sophisticated analytical operation for facilitating value-added consulting services. Review of existing practices of consulting firm shows increasing adoption of analytical process which leads to complex form of operation towards knowledge discovery of consulting data. Hence, this manuscript introduces a framework of contextual consulting practices where the core idea is to incorporate a baseline structure of knowledge discovery associated with consulting data in adherence of industry 4.0 automation standards. The framework takes the input of streamed consulting diversified data governed by a template-based entry-points where the consulting data is subjected to series of transformation operation that not only preprocess the consulting data but also optimizes the data to enhance its data quality. The study model is implemented in MATLAB considering an extensive analytical framework towards data-driven decision making and decentralization to exhibit proposed model to offer better analytical performance in contrast to existing study models.
Co-Authors Bhosale, Narayan P Bhosale, Narayan P. Rathore, Neeraj