Implementing i4.0 Tech to Engineering Systems Lab for Smart Manufacturing Learning

Hayder Zghair, Rungun Nathan

Research output: Contribution to journalConference articlepeer-review

Abstract

Managing the manufacturing input such as designs, energy, and raw stock to sustainably operate machinery systems demands real-time data that can be used to control the process and can result in not only economic improvements but contribute to friendly environmental outcomes. The complexity of manufacturing systems and the need for interchangeability presents an ideal environment to implement smart manufacturing technologies with the goal of sustainability. Manufacturing engineering in an educational classroom is a good place to guide through and examine the shift to smart industrial systems using elements of industry 4.0 (i4.0), industrial internet of thing (IIoT), digital cloud, dashboards, data collection and processing along with integrated sensors. In this paper, the authors present a smart manufacturing engineering course developed and implemented. A summary of two offerings of this course is briefly described. It provided high engagement for students that has been observed through the learning process interactions. It also provided a platform to implement IIoT, digital cloud, and real-time data collection to help with the detection of unplanned events and behavior. The setup also provided tools for fast correction response and documentation.

Original languageEnglish (US)
JournalASEE Annual Conference and Exposition, Conference Proceedings
StatePublished - Jun 25 2023
Event2023 ASEE Annual Conference and Exposition - The Harbor of Engineering: Education for 130 Years, ASEE 2023 - Baltimore, United States
Duration: Jun 25 2023Jun 28 2023

All Science Journal Classification (ASJC) codes

  • General Engineering

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