Detection Of Manufacturing Defects Research Articles

Manufacturing Defect Detection in Ceiling Fans using Image processing

During manufacturing process of ceiling fans there may be possibility that any step of manufacturing process can be skipped or improper completion due to malfunctioning of the system. In manufacturing process of fans, the outer plate, stator, rotor, axle and other parts are manufactured and assembled. If the winding machine is not working properly and improper windings is done and no-one can acknowledge that winding machine is not working properly then the whole batch should be designed with defect and this will surely create negative impact on the production process of the industry. So this proposed work will overcome this problem. This paper guides to detect whether the windings are proper or not and detection is carried out by taking picture of armature-windings. If there is any problem in the windings then our system will generate an alert so that other armatures can be protected from failures. Manual results are not so accurate all the time but in manufacturing process we need high accuracy. For this skilled labor is required and for skilled labor we have to pay more, this automated system reduce the need of skilled labor. If fan manufacturing industries use this image processing system then this will be very helpful in increasing production of fans within the completion time with more accuracy

Experimental study of flexible injection to manufacture parts of strong curvature

Flexible injection (FI) is a new process for the manufacture of high performance composites, which consists of injecting a thermosetting resin through a fibrous reinforcement contained in the lower chamber of a double cavity mold. Resin is injected in the lower cavity, which is sealed by a membrane, and then a compaction fluid is injected in the upper chamber to compress the reinforcement. This new composite manufacturing technique, which allows a limited and controlled deformation of the flexible membrane during processing, was shown to be very effective in reducing filling times in the case of planar or slightly curved geometries. In the present study, flexible injection is applied to strongly curved parts, namely here a composite rectangular panel with two 90° corners. After setting up an experimental procedure to produce the stair-shaped components out of fiberglass and vinylester resin, longitudinal cross-sections of the parts are analyzed to assess the quality of the final product in both the flat and curved zones. This characterization method allows detecting manufacturing defects such as thickness gradients or resin-rich zones. Such defects are likely to induce geometrical deformations of the component and may decrease its mechanical performance. Therefore they ought to be minimized to improve the overall quality of the part. Modifications of the manufacturing procedure are proposed in this article to decrease the importance of process-induced defaults and improve the performance of the flexible injection. POLYM. COMPOS., 2011. © 2011 Society of Plastics Engineers

A novel manufacturing defect detection method using association rule mining techniques

In recent years, manufacturing processes have become more and more complex, and meeting high-yield target expectations and quickly identifying root-cause machinesets, the most likely sources of defective products, also become essential issues. In this paper, we first define the root-cause machineset identification problem of analyzing correlations between combinations of machines and the defective products. We then propose the Root-cause Machine Identifier (RMI) method using the technique of association rule mining to solve the problem efficiently and effectively. The experimental results of real datasets show that the actual root-cause machinesets are almost ranked in the top 10 by the proposed RMI method.

Sensitivity of the Electromagnetic Acoustical Technique for Testing Railway Rails by the Mirror-Shadow Method

A study of the sensitivity of the electromagnetic acoustical (EMA) technique for detecting manufacturing defects of railway rails by a mirror-shadow method (MSM) has been carried out. It has been found that the sensitivity of the MSM with the EMA technique using bulk shear ultrasonic waves is, in certain cases, considerably higher than the sensitivity of the traditional “wet” echo-pulse method or mirror-shadow method with the use of longitudinal waves. Therefore, in order to renovate or design new technical means of ultrasonic acceptance testing of rails in factories, it is advisable to use the mirror-shadow method of testing with bulk elastic shear waves polarized normally to the direction of rail rolling. This would make it possible to reduce the acceptance of intolerable internal flaws of manufacturing origin.

An analogue test response compaction technique using delta–sigma modulation

An analogue and mixed-signal Built-In-Self-Test (BIST) scheme suitable for detecting manufacturing defects in embedded linear macros is presented. The BIST scheme uses a delta–sigma (ΔΣ) modulator and a binary counter to perform an analogue test response compaction technique. This technique produces a signature for a circuit under test, which relates to the amplitude and frequency of the analogue response. Fault simulations performed on a two-stage CMOS operational amplifier and a continuous-time state variable filter have shown that a fault coverage (>80%) is attainable. These simulation results suggest that the probability of any fault masking occurring using the proposed compression technique is insignificant.