KUALA LUMPUR, 8 April 2026 – A collaboration between Universiti Sains Malaysia (USM) and AMC Cincaria Sdn. Bhd. has delivered an automated vision-guided spraying system that significantly improves manufacturing efficiency and quality control in fireproof beacon production.

The system marks a step forward in Malaysia’s shift toward smart manufacturing, reducing reliance on manual processes through real-time automation and artificial intelligence.

Developed under Associate Professor Dr. Muhammad Firdaus Akbar Jalaludin Khan of USM’s School of Electrical and Electronic Engineering, the system addresses long-standing issues in manual coating, including inconsistent quality, material wastage and human error in defect detection.

It integrates automated spraying with machine vision, enabling real-time inspection and adaptive process control on the production line.

The platform uses image processing and AI-based models to detect coating defects with higher accuracy. Machine learning and neural networks enable automated classification of quality, while controlled imaging conditions ensure consistent industrial performance.

The impact has been immediate. Production time per unit dropped from 200 seconds to 45 seconds, improving throughput by nearly 90 percent. Efficiency rose from 65 percent to 90 percent, while rejection rates fell from 15 percent to below 2 percent. Material wastage was reduced from 50 percent to 15 percent, with manpower reduced from three operators to one. Annual revenue increased from RM 618,000.00 to RM 1 million after deployment.

AMC Cincaria Sdn. Bhd. supported the project by providing production facilities, operational data and industrial feedback, enabling direct transition from prototype to full deployment.

USM Vice-Chancellor Dato' Seri Dr. Ir. Abdul Rahman Mohamed said the development demonstrates the university’s ability to translate research into industry impact.
“This reflects USM’s strength in delivering research that goes beyond the laboratory into real industrial application. It strengthens productivity, quality assurance and supports Malaysia’s move toward intelligent manufacturing systems.”

AMC Cincaria representative Aslan Hamid Sultan said the system exceeded expectations by enabling real-time defect detection and correction during spraying, improving stability and reducing manual intervention.

The system has also been adapted for use in the automotive sector, demonstrating its broader industrial potential.
The project aligns with the Rancangan Pendidikan Tinggi Malaysia (RPTM) 2026–2035, supporting digital transformation, industry-led innovation, and workforce development.

By shifting inspection from manual judgment to data-driven automation, the collaboration introduces a scalable model for modern manufacturing.

In essence, the system positions machine vision-based automation as a practical tool for industrial transformation, strengthening productivity and reinforcing Malaysia’s competitiveness in advanced manufacturing.

Source: Professor Ir. Dr. Srimala Sreekantan, School of Materials & Mineral Resources Engineering / Text: Privinkumar Jayavanan, Media & Public Relations Centre (MPRC) / Editing: Associate Professor Dr. Shaik Abdul Malik Mohamed Ismail, Senior Editorial Consultant @ MPRC USM / Photo: Muhamad Faris Dawisy Mohammad Rafiq, Media & Public Relations Centre (MPRC)