Optimizing Product Lifecycle Management with AI: From Development to Deployment

Authors

  • LIU Xi Author

Keywords:

Product Lifecycle Management (PLM), Artificial Intelligence (AI), Ideation, Design, Manufacturing, Distribution, Deployment, Predictive Analytics, Generative Design, Simulation, Predictive Maintenance, Quality Control, Supply Chain Optimization, Customer Service.

Abstract

In the contemporary landscape of rapidly evolving technology and market demands, optimizing product lifecycle management (PLM) has become imperative for companies striving for competitiveness and innovation. This paper explores the integration of artificial intelligence (AI) techniques into the various stages of the product lifecycle, from development to deployment, as a means to enhance efficiency, agility, and quality.The product lifecycle encompasses several stages, including ideation, design, manufacturing, distribution, and post-sales support. AI algorithms and tools offer unique capabilities to streamline processes, extract insights from data, and facilitate decision-making throughout these stages. In the ideation phase, AI-powered predictive analytics can analyze market trends, customer preferences, and competitor strategies to inform product concepts and features. This enables companies to anticipate market needs and tailor their offerings accordingly, reducing the risk of launching unsuccessful products.

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Published

2024-05-07

How to Cite

Optimizing Product Lifecycle Management with AI: From Development to Deployment. (2024). International IT Journal of Research, ISSN: 3007-6706, 2(2), 8-14. https://itjournal.org/index.php/itjournal/article/view/14

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