Abstract
Through the digitalization of manufacturing, an abundance of data is available from machines, sensors and operations. This trend requires technical colleges and universities to enhance their syllabus. This paper describes a cloud-based data pipeline for a digital manufacturing lab that utilizes machine-to-machine communication and the internet of things (IoT). The factory model consists of four stations, i.e., a vacuum gripper robot, an automated high-bay warehouse, a sorting line with color detection, and a multi-processing station with an oven, and these stations can demonstrate a fully working digital production line prototype that is in line with Acatech Industrie 4.0 Maturity Index. The Programmable Logic Controller (PLC) on-site passes data via the internet to the Amazon Web Services (AWS) cloud computing platform. Data Analytics uses methods from statistics and machine learning to optimize processes, continuously monitor product quality and improve maintenance of equipment. The factory model and the data pipeline provide an intuitive hands-on learning experience for teaching Industry 4.0 and digital manufacturing at technical colleges and universities.
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Goh, P.J. et al. (2022). Conceptual Design of Cloud-Based Data Pipeline for Smart Factory. In: Ali Mokhtar, M.N., Jamaludin, Z., Abdul Aziz, M.S., Maslan, M.N., Razak, J.A. (eds) Intelligent Manufacturing and Mechatronics. SympoSIMM 2021. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-8954-3_4
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DOI: https://doi.org/10.1007/978-981-16-8954-3_4
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