Oleghe, OmogbaiSalonitis, Konstantinos2020-09-242020-09-242020-09-22Oleghe O, Salonitis K. (2020) A framework for designing data pipelines for manufacturing systems. Procedia CIRP, Volume 93, 2020, pp.724-7292212-8271https://doi.org/10.1016/j.procir.2020.04.016https://dspace.lib.cranfield.ac.uk/handle/1826/15845Data pipelines describe the path through which big data is transmitted, stored, processed and analyzed. Designing an appropriate data pipeline for a specific data driven manufacturing project can be challenging, whereas there is a paucity of frameworks to guide one in the design. In this research we develop a framework for designing data pipelines for manufacturing systems. The framework consists of a template for selecting key layers and components that make up big data pipelines in manufacturing systems. A use case is presented to provide an illustrative guideline for its application. Benefits of the framework and future directions are discussedenAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Article