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@article{168494,
        author = {Gbenga Sonoiki},
        title = {The Role of Data Analytics in Optimizing Product Lifecycle Management},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {5},
        pages = {1256-1268},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168494},
        abstract = {Product Lifecycle Management (PLM) is a strategic model that helps manufacturing companies manage a product through its life cycle, right from design to disposal. However, there is a dearth of literature on how has been implemented and optimised within PLM processes to improve productivity and product quality. This study therefore seeks to provide a comprehensive review of the literature on the application of data analytics in enhancing PLM, and the benefits and challenges associated with its implementation. Using a systematic literature review approach, this research examined prior studies from peer-reviewed papers published between 2009 and 2024 from numerous academic databases using the PRISMA model. A broad search was conducted in line topic and after carefully filtering them down, only 62 studies were chosen for analysis. Findings from this study show that data analytics improves decision-making across the various stages of PLM, from concept to design, production, and disposal. More particularly, predictive analytics was found to optimise design and manufacturing processes and allow for real-time changes which enhances cycle time and product quality. Moreover, the study establishes that though data analytics can enhance efficiency and customer interaction with custom services, there are several associated challenges including the costs of implementing the advanced data analytics and data privacy.},
        keywords = {},
        month = {October},
        }