Improving Quality Control Plan of Flexible Printed Circuit

2015 ◽  
Vol 789-790 ◽  
pp. 1264-1269
Author(s):  
Ratchapon Nunthaporm ◽  
Parames Chutima

Smart phone market has been growing larger and larger in recent years. This fact makes enormous competitiveness in its supply chain. Therefore, the product quality is the most importance part to improve business competitiveness, especially a flexible printed circuit which is a main assembly component in smart phones. This paper presents the approach to improve the quality control plan of the flexible printed circuit backend process. Failure Mode Effective Analysis (FMEA) was adopted to prioritize the defective and analyze weak points in the original quality control plan. Then, Statistical Process Control (SPC), optimizing inspection method and working procedure of inspection process, were introduced to improve the detection ability of the quality control plan. The results showed that the implementation of the new quality control plan could reduce escaped defective parts and the expense of escaped defect parts significantly.

2020 ◽  
Vol 16 (2) ◽  
pp. 1-34
Author(s):  
Yap Wan Yee ◽  
Mohammad Nishat Akhtar ◽  
Elmi Abu Bakar

Product quality is an important issue in all manufacturing industry nowadays to meet the customers’ requirement. In this regard, most of the factory has a special department namely Quality Control (QC) Department which control the product quality. The studied factory is a flexible printed circuit board manufacturer which is located in Bayan Lepas, Pulau Pinang, Malaysia. QC Department of the studied factory has high amount of work-in-progress (WIP). Therefore, the products have to be sent out to subcontractors for quality inspection. However, this method is not economically effective. Hence, the objective of this study was to develop an improved inspection method which will reduce the overall inspection time of the current inspection method (CIM). By reducing the inspection time, productivity of the department will increase and subsequently reduce the amount of WIP. This study is focused on the improvement of one product only. Before the improved inspection method (IIM) of the selected product was developed, performance of the CIM was evaluated by using one of the graphical productivity analysis charting techniques which is flow process chart. It was found that the IIM was able to reduce the inspection time of whole inspection process by 85.06 sec for every 12 panels inspected.


2015 ◽  
Vol 78 (1) ◽  
Author(s):  
Zuliani Zulkoffli ◽  
Elmi Abu Bakar

This study presented a research on machine vision inspection to define defects on flexible printed circuit (FPC). The images were subjected to image processing system where an elimination-subtraction method used. In this algorithm, 7 types of FPC defects defined and simulated in the system using Specimen 1 and processing time taken for both side inspection was 3.3s. Then, the commercial patent design of FPC was tested as specimen 2 to define short circuit defects on it. The processing time taken by this algorithm on specimen 2 was 0.28s. Comparison on manual inspection and machine vision implementation were carried out and greatly resulted on shorten inspection time to 59.7%. This result shows significant contribution in increasing the efficiency of FPC inspection process. 


Author(s):  
Chao Sun ◽  
Roman Mikhaylov ◽  
Yongqing Fu ◽  
Fangda Wu ◽  
Hanlin Wang ◽  
...  

Author(s):  
Alexander Miropolsky ◽  
Anath Fischer

The inspection of machined objects is one of the most important quality control tasks in the manufacturing industry. Contemporary scanning technologies have provided the impetus for the development of computational inspection methods, where the computer model of the manufactured object is reconstructed from the scan data, and then verified against its digital design model. Scan data, however, are typically very large scale (i.e., many points), unorganized, noisy, and incomplete. Therefore, reconstruction is problematic. To overcome the above problems the reconstruction methods may exploit diverse feature data, that is, diverse information about the properties of the scanned object. Based on this concept, the paper proposes a new method for denoising and reduction in scan data by extended geometric filter. The proposed method is applied directly on the scanned points and is automatic, fast, and straightforward to implement. The paper demonstrates the integration of the proposed method into the framework of the computational inspection process.


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