AI-Powered Data Insights in Product Lifecycle Management: Driving Innovation and Efficiency

The integration of Artificial Intelligence in Product Lifecycle Management (PLM) is revolutionizing how organizations manage and optimize their product development processes. This comprehensive article examines the transformative impact of AI technologies on PLM systems, focusing on advanced analytics, process optimization, and intelligent decision support capabilities. It explores key technological implementations including machine learning applications, natural language processing, and computer vision integration, highlighting their roles in enhancing design accuracy and manufacturing efficiency. Through detailed analysis of data architecture requirements and a case study in the automotive sector, the article demonstrates how AI-powered PLM systems are driving innovation and operational excellence. It also addresses critical technical and organizational challenges while providing practical solutions for successful implementation. Looking ahead, the article identifies emerging trends in PLM evolution, including semantic technologies, advanced digital twins, and human-AI collaboration frameworks, offering insights into the future direction of intelligent product lifecycle management systems.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-02-10
DOI
https://doi.org/10.32628/cseit251112185
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

AI-Powered Data Insights in Product Lifecycle Management: Driving Innovation and Efficiency

Nishant Kapoor
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Big Data and Business Intelligence
article

AI-Powered Data Insights in Product Lifecycle Management: Driving Innovation and Efficiency

Nishant Kapoor
article en

Abstract

The integration of Artificial Intelligence in Product Lifecycle Management (PLM) is revolutionizing how organizations manage and optimize their product development processes. This comprehensive article examines the transformative impact of AI technologies on PLM systems, focusing on advanced analytics, process optimization, and intelligent decision support capabilities. It explores key technological implementations including machine learning applications, natural language processing, and computer vision integration, highlighting their roles in enhancing design accuracy and manufacturing efficiency. Through detailed analysis of data architecture requirements and a case study in the automotive sector, the article demonstrates how AI-powered PLM systems are driving innovation and operational excellence. It also addresses critical technical and organizational challenges while providing practical solutions for successful implementation. Looking ahead, the article identifies emerging trends in PLM evolution, including semantic technologies, advanced digital twins, and human-AI collaboration frameworks, offering insights into the future direction of intelligent product lifecycle management systems.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(1)
Capgemini (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 97%
Big Data and Business Intelligence
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