Hairol Nizam Mohd Shah

Implementation of Shape – Based Matching Vision System in Flexible Manufacturing System

This research is regarding the application of a vision algorithm to monitor the operations of a system in order to control the decision making concerning jobs and work pieces recognition that are to be made during system operation in real time. This paper stress on the vision algorithm used which mainly focus on the shape matching properties of the product. The main focus of this paper is on the development of an adaptive training phase of the vision system, which is the creation of a flex- ible Region of Interest capability that is able to adapt to various type of applications and purposes depending on the users’ requirements. Additionally, an independent stand-alone control scheme was used to enable this system to be used in various types of manufacturing configurations. The system was tested on a number of different images with various characteristics and properties to determine the reliability and accuracy of the system in respect to different conditions and combination of different training traits.

Theoretical Analysis on Energy Consumption for Industrial Robots

This paper presents a theoretical analysis on energy consumption for industrial robots. In this project, the industrial robot used is a virtual robot resembling the FANUC LR Mate 200iB robotic arm. The first two joints consume the most electrical energy, this research focuses only on the first two joints. The calculation of the electrical energy consumed is based on a previous established research done by Herman (2009) from Universiti Teknikal Malaysia Melaka (UTeM) in the year 2009. In this research, three different time intervals were used to set the speed of the robotic arm to be at 50%, 100% and 200% speed and they were tested on 10 different angles with 10 time intervals for the 1st and the 2nd robotic joints.