Intelligent Solutions in Ergonomics, Manufacturing and Sports Technology

Training, research and development in machine learning, automation and robotics, simulation and modeling, and sports technology. (002769122-V)

HRDF MyCOID: 20173481604


Deep Learning Surface Defect Inspection System
GUI of Deep Learning Surface Defect Detection System with Intuitive Interface

Deep Learning Surface Defect Detection System

Artificial Intelligence has become a game changer in nearly every domain in the last few years. In Production and Manufacturing, the power of Deep Learning is increasingly becoming a game changer with automation that is faster, cheaper and more superior. Visual inspection is a high priority activity in many industries due to the potentially high cost of any errors that may arise via inspection such as injury, fatality, loss of expensive equipment, scrapped items, rework, or a loss of customers. Visual inspection errors typically range from 20% to 30% which often then not can be attributed to human error. Although the errors can be reduced through training and practice, it cannot be completely removed. Automated Visual inspection removes the need for human involvement resulting in automated systems that easily surpasses the standard of manual inspection.

Existing machine vision systems tolerate some variation in a part’s appearance due to scaling, rotation, and pose distortion. However it fails to assess the vast possibility of variation and deviation between very visually similar images. In contrast Deep learning-based systems are good at addressing complex surface and cosmetic defects, like scratches and dents on parts that are turned, brushed, or shiny.

Our Deep Learning Surface Defect Detection System was developed to provide a system that is easy to set up. The steps involve capturing images of defect samples, training the images, evaluation of prediction models and real time deployment. The speed of prediction depends on the hardware used particularly the CPU and GPU specifications. Typically prediction is performed at 0.07s per frame. Shown in the figures is a an example of a machine based on our system to detect surface defects. System components include multiple high speed cameras, bright led lighting, PLC and CPU/GPU. Other applications include surface defect detection on PVC flooring, aluminium fins and wafers.

For further inquiries please contact Dr Zahari Taha (


Dr Zahari Taha is a Chartered Engineer (UK), Member Institution of Engineering Designers (UK), Fellow Academy Sciences Malaysia and Fellow and Board Member Asia Pacific Industrial Engineering and Management Society. He was formerly a Professor at the Faculty of Engineering, Universiti Malaya and Faculty of Manufacturing Engineering, Universiti Malaysia Pahang. He has more than 30 years of experience in education, research and development in machine learning, automation and robotics, and simulation and modelling. Dr Zahari has published over 300 papers and graduated over 70 PhD and Masters students. He has produced numerous software and hardware solutions for industry and universities.

Zayd Zahari graduated with a Bachelor in Engineering (Manufacturing) from Universiti Malaya in 2007 and a Masters in Business Administration (Strategic Management) from University Technology Malaysia in 2014. He has 10 years experience working in companies such as HICOM TECK SEE MFG SDN. BHD, TRIO TECH (M) SDN. BHD.,ALTERAXIS SDN. BHD and INTISARI TUAH SDN. BHD . His core competencies include: Laravel, Vue.js, PHP, Javascript, HTML, CSS, MySQL, Planning & Strategy, Operations Management, Pre Sales, RFI / RFP’s,Project Management, Needs assessment, Security & Compliance, Change Management, Customer Support & Satisfaction, Resource Optimization, Planning & Budgeting, Procurement, Vendor Management, Stakeholder Management, Service Delivery and People Development


Machine Design and Prototyping

Design and prototype development of new machines

Machine Vision Applications

Development of Machine Vision system for various applications such as defect detection, parts differentiation etc

Machine Learning Software Development

Software development for the application of machine learning algorithms

Industrial Automation and Robotics Application

Consultation and studies on industrial automation and robotics solutions

Simulation and Modeling

Consultation and studies on simulation and modeling of manufacturing systems

IOT Solutions

Development of IOT applications

Deep learning Tube Surface Defect Inspection System
Simulation of an AGV system in FlexSIM
ORANGE machine learning data visualization


Introduction to Machine Learning (One day Course)

Machine Learning involves the use of algorithms to build a good and useful approximation to data and then make a determination or prediction. However machine learning can be very complex and most people are not trained to program or do not have the time to do so. Orange is an open source machine learning and data visualization toolkit that does not require programming skills. It is suitable for both novice and expert. It is packed with features for data analytics and has a large toolbox for machine learning. In this course participants will have hands on training exploring various types of data with Orange. Participants are also encouraged to bring their own data. The course is opened to participants from any background.

Introduction To Industry 4.0 (One Day Course)

Industrial Revolution 4.0 is going to have a major impact on the future of Malaysia. Knowledge and skills of the core technologies of Industrial Revolution 4.0 are essential in order fulfil the requirements of the workforce of the future. This is particularly so when the economy is badly affected by COVID-19. Therefore, it is imperative to understand basic principles of Industry 4.0 to meet the challenges facing the manufacturing industry in post COVID-19. The concerted objective of the course is the basic knowledge for Industry 4.0 in manufacturing. The course will consist of four parts

● Design and Planning of Automated Production Facilities via Simulation and Modeling

● Automated Quality Control with Deep Learning and Machine Vision

● AGVs and Industrial Robots

● Industrial Internet of Things (IIOT)

An Introduction to Industrial Internet of Things (IIoT) (One Day Course)

The Internet of things (IoT) will have a significant impact on manufacturing. It helps to create new technologies to solve problems, enhance operations, and increase productivity. IoT can be explained as a network of physical objects, systems, platforms and applications that contain embedded technology to communicate and share intelligence with each other, the external environment and with people. (IoT) impact on Industrial Automation is very high and it makes us to use tablet computers, smart phones, virtualized systems, and cloud storage of data and so on. IoT generates a large amount of data for in manufacturing. This gives rise to Big Data. Big Data are large sets of data that may be analysed computationally to reveal patterns, trends and association, especially relating to human behaviour and interactions. The combination of Big Data and IoT is called Industrial IoT (IIoT) . The objectives of this course are to give an understanding of Industrial Internet of Things IIoT and to be able to develop basic applications of IIOT using Thingspeak and Blynk


Online Courses

  1. Introduction to Industrial Internet of Things(RM500) - Aug 11, 2020
  2. Introduction to Machine Learning (RM500) - Aug 13, 2020
  3. Introduction to Industry 4.0 (RM500) - Aug 18, 2020

Normal Courses (Venue : Kuantan, maximum participant =10)

  1. Introduction to Industrial Internet of Things(RM500) - September 8, 2020
  2. Introduction to Industry 4.0 (RM500) - September 9, 2020

Online courses will be conducted from 10.30am to 12.30pm and 2.30 to 4.30pm. Reference materials will be emailed to participants. Practical materials will be couriered to participants. Courses will be conducted on Google Meet with a limit of 5 participants.

Email: Tel/WhatsApp: +60125138779 or +60172111763

Kuala Lumpur:

4-3A, Jalan Pandan 3/7, 55100 Kuala Lumpur, Malaysia


DR67, Kampung Kuala Pahang, 26660 Pekan, Pahang, Malaysia