Building Predictive Maintenance Solutions Using IoT and AI

This comprehensive training program equips participants with essential competencies in optimizing maintenance process by utilizing IoT device to collect real time data and analyzing it to develop predictive models for the machine breakdown. Participants will develop proficiency in utilizing programming language and microcontroller to collect data from selected sensor and transferring it to the cloud database, cleaning the data, analyzing the data, and developing the predictive model for the machine maintenance.

Upon completion, participants will be able to:

• To build a secure data pipeline from the factory floor to a cloud/local database.

• To develop a predictive maintenance (PdM) model using machine learning.

• Establish PLC-to-IoT communication using available PLC or OPC-UA protocols.

• Program microcontrollers to capture vibration and temperature data.

• Clean and analyze industrial time-series data using Python.

• Deploy an anomaly detection model that triggers maintenance alerts.

• Calibrate pneumatic pressure settings to achieve optimal grip force specifications for specific applications.

Duration

3 Days

Methodology

Lecture; Practical Session; Discussion and Q&A. A specially designed training kit will be used.

Target Audience

Suitable for individuals who wish to develop predictive model for their machine maintenance process.

Course Level

Intermediate to Advanced — a hands-on engineering program that builds on existing electrical wiring and programming knowledge.

Pre-requisites

Have basic electrical wiring and programming language knowledge.

Training Kit & Tools

A specially designed training kit will be used, including a Conveyor System Kit, IIoT (ifm sensors with IO-Link Master), and a Raspberry Pi data gateway with monitor for dashboard display. Software: VS Code, Python 3.x (pandas, lifelines, matplotlib/seaborn). Estimated cost: RM 6K–RM 7K per training kit.