Implementation Of Vision System For Defects Classification Method Using International Standard Welding Imperfection

Defects are ones of the problems that should be minimized by any manufacturing company.Defects occurrence will decrease the performance of a production system.Defects typically occur in many kinds of product especially in manufacturing field.This research proposes an automated inspection of welding defects particularly the surface defects that are normally inspected manually.In order to inspect the welding product,Metal Inert Gas (MIG) welding has been chosen to be tested using three types of gases which are Carbon Dioxide (CO2),Argon (Ar) and gas mixture (combination of CO2 and Ar).The selection of the three types of gases is because the three types are the most widely used gases in the industry.Currently,many of the companies in Malaysia are implementing manual visual inspection conducted by operators.As welding is a highly repetitive process,the operators will have high hazard exposure.In order to improve the working condition,vision system is proposed.This research proposes a classification of the defects method that involves with image enhancement,image filtering and image segmentation. The classification method is involve with decision tree . A proposed of decision tree is lead to the image determination.In image filtering method,an improved method is applied to get a better picture of the image. The peak signal to noise ratio (PSNR) and mean square error (MSE) is calculated.The result obtained shows that the system is capable to detect welding defects successfully.According to the result,percentage error rate for both situation of the noise shows that the result is less than 30%.In addition,it shows that the most of the result is same with the expertise.Thus,the system is success for the classification of welding defect

Intelligent vision-based navigation system for mobile robot: A technological review

Vision system is gradually becoming more important. As computing technology advances, it has been widely utilized in many industrial and service sectors. One of the critical applications for vision system is to navigate mobile robot safely. In order to do so, several technological elements are required. This article focuses on reviewing recent researches conducted on the intelligent vision-based navigation system for the mobile robot. These include the utilization of mobile robot in various sectors such as manufacturing, warehouse, agriculture, outdoor navigation and other service sectors. Multiple intelligent algorithms used in developing robot vision system were also reviewed

Assessment on Potential Damages of Automotive Brake Caliper Using FMEA Method for the Application of Remanufacturing Process

The repair and restoration stage in remanufacturing is one of the vital phases to ensure the remanufactured component is qualified during the testing stage. The reliability of the component can be evaluated at the very early stage of remanufacturing process, by adopting the FMEA method. The FMEA method is a tool that facilitate the evaluation of reliability of component related to potential failures and damages of the component. An automotive brake caliper is selected as a case exemplary in this study. The FMEA method will be used to confirm the applicability of DED process as one of the repair processes where not all type of failures or damages are suitable to be repaired through DED process. Therefore, this study presents the identification of potential damages or failures of brake caliper and further, analyse the reliability of the component and identify the possible corrective action can be taken. The study shows that the failure modes of a brake pad is irreparable cases that requires part replacement whilst for brake caliper housing shows as having some potential to be repaired using DED process. However, further investigation related to the strength of the component is required to support the FMEA results

Intelligent Vision-Based Navigation System For Mobile Robot: A Technological Review

Vision system is gradually becoming more important. As computing technology advances, it has been widely utilized in many industrial and service sectors. One of the critical applications for vision system is to navigate mobile robot safely. In order to do so, several technological elements are required. This article focuses on reviewing recent researches conducted on the intelligent vision-based navigation system for the mobile robot. These include the utilization of mobile robot in various sectors such as manufacturing, warehouse, agriculture, outdoor navigation and other service sectors. Multiple intelligent algorithms used in developing robot vision system were also reviewed

Classification of weld bead defects based on image segmentation method

Defect is an imperfection that could impair the worth and utility of a finished good. The defects show some disorder of the product and it is opposite the standard or criteria that have been stated. In defining and detecting the defects occur, many ways have been discussed and observed. However, the techniques or ways are not appropriate or not suitable for some condition and situation. In addition, welding process is one of the critical processes in detecting and defining defect to ensure the quality of the weld bead. To overcome the problem in detecting and defining defects, image processing is one of the methods in improving the process of detecting defects. The defects are classified based on automatic thresholding method that automates detecting and defining the defects. This study proposes a Decision Tree-based classification of weld bead defects through segmentation of image. The result obtained shows that the classification is effective in identifying the weld bead defects with 89% accuracy. For future work, the focus will be made to improve the detection accuracy by integrating suitable filters