A framework for designing data pipelines for manufacturing systems
Omogbai Oleghe, Konstantinos Salonitis
Abstract
Data 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 discussed.
Topics & Concepts
Pipeline transportPipeline (software)Big dataComputer scienceKey (lock)Systems engineeringEngineeringManufacturing engineeringIndustrial engineeringData miningMechanical engineeringProgramming languageComputer securityDigital Transformation in IndustryManufacturing Process and OptimizationBig Data and Business Intelligence