A Proposed Maintenance 4.0 Model for Laboratory Ventilation Systems: An Industry 4.0 Approach to Air Quality Management

Ammar Yaser Abdullah, Hossam Eldin Salem, Hazza Muhsen Abdoul Qader Al Ameri, Mansoor Mohammed Alnahdi, Mohamed Okasha, Ibrahim Abdelfadeel Shaban

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Air quality plays a crucial role in the health and well-being of workers, with poor conditions potentially leading to respiratory issues, headaches, fatigue, and decreased productivity. This study utilizes Industry 4.0 configuration to assess air quality in laboratory settings and develop an online maintenance planning model for ventilation systems, termed Maintenance 4.0. In a laboratory at UAE University, air quality monitoring devices were installed to measure parameters such as CO2 emissions, humidity, PM1, PM2.5, PM10, and temperature. Several assessment procedures were employed to enhance the evaluation of ventilation system performance, referencing standards like ASHRAE 62.1, the World Health Organization (WHO) Air Quality Guidelines, and the Environmental Protection Agency (EPA) regulations. Additionally, predictive models were created using the collected data: one to forecast future air quality based on historical trends, and another—a Vector Autoregression (VAR) time series model—to predict air quality for the next 20 readings. The findings provide valuable insights into the current state of laboratory air quality and support the development of improvement strategies. By assessing ventilation performance and suggesting optimal maintenance times, this research benefits laboratory managers, maintenance personnel, and workers, enabling proactive measures through accurate air quality predictions and ultimately enhancing safety and productivity in laboratory environments.

Original languageEnglish
Title of host publication2024 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331529413
DOIs
Publication statusPublished - 2024
Event2024 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2024 - Dubai, United Arab Emirates
Duration: Nov 19 2024Nov 21 2024

Publication series

Name2024 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2024

Conference

Conference2024 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2024
Country/TerritoryUnited Arab Emirates
CityDubai
Period11/19/2411/21/24

Keywords

  • Air quality index (AQI)
  • Indoor air quality (IAQ)
  • Industry 4.0
  • Internet of Things (IoT)
  • Machine learning (ML)
  • Maintenance 4.0

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

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