Technical Library | 2008-11-06 02:17:59.0
For many years Acoustic Micro Imaging (AMI) techniques have been utilized to evaluate the quality of the underfill used to support the solder bump interconnections of Flip Chip type devices. AMI has been established as one of the few techniques that can provide reliability and quality control data, but little has been done to automate the evaluation process for Flip Chip underfill until now.
Technical Library | 2023-05-02 19:16:57.0
1.5 with a 150μm specification window. For 0201 components, the minimum requirement is CpK > 2.0 with a 100μm specification window. The spec window may need to be reduced down to 75μm if the controls for high volume manufacturing are insufficient. Also directly impacting the placement quality is the ability to apply sufficient solder consistently to the board. The goal is to maintain current printing practices, but the effect of powder size will be examined. This paper will evaluate the impact of placement accuracy and solder powder size on 0201 manufacturing quality.
Technical Library | 2023-11-20 17:42:33.0
Zero-defect strategies and increased demands on the production of assemblies are making quality assurance in electronics production increasingly important. Continous miniaturization of components, ever higher packing densities and the associated hard-to-view assembly areas, as well as the increased use of components such as BGAs, QFNs and QFPs, pose a considerable challenge when it comes to high-precision quality control.
Technical Library | 2012-11-27 14:06:48.0
Quality managers and line supervisors are routinely tasked with the responsibility of ensuring that the hand soldering process is under control. The method most commonly used is to measure the idle tip temperature of the soldering station and to use this reading as a benchmark of system compliance. This method, although popular is now being seriously questioned by many industry professionals as being irrelevant in qualifying true system process control. This document aims to present a practical view of what factors are important for successful hand soldering and to suggest an alternative procedure for qualification that is simple, repeatable and directly related to the effectiveness of the soldering station.
Technical Library | 2023-11-20 17:59:32.0
Quality control at Mentzer Electronics in Burlingame, California, includes tracing electronics assembly issues using a Metris XT V real-time X-ray inspection system. This electronics X-ray inspection system allows quality engineers to intuitively navigate through the internal structure of assembled PCBs. In the rapidly evolving electronics industry, Mentzer Electronics uses the acquired insight to speed up and fi ne tune manufacturing processes. Real-time X-ray guarantees that no hidden defects remain in products when turning them out to customers nationwide.
Technical Library | 1999-05-07 10:38:11.0
This paper is a report of a study made to determine the maximum allowable impurities in solder used for wave soldering applications. This report concludes with a list of impurities compiled from actual analyses of solder which caused production problems. A list of recommended maximum allowable impurities will assist in establishing reliable quality controls on the purity level of the solder in a wave soldering machine.
Technical Library | 2007-04-25 21:54:26.0
Globalization and increased competition requires an enterprise to focus on cost reduction, improved manufacturing processes and higher standards of quality. Effective yield management using Enterprise Resource Planning (ERP) systems is crucial for the success of any manufacturing organization. An ERP system provides the infrastructure for consolidating all business operations by integrating the information flow across functions, including production planning and control.
Technical Library | 2013-04-25 11:42:01.0
Specification and control of surface roughness of copper conductors within printed circuit boards (PCBs) are increasingly desirable in multi-GHz designs as a part of signal-integrity failure analysis on high-speed PCBs. The development of a quality-assurance method to verify the use of foils with specified roughness grade during the PCB manufacturing process is also important... First published in the 2012 IPC APEX EXPO technical conference proceedings.
Technical Library | 2024-02-06 14:36:04.0
Quality monitoring for verifiable, high-precision application of adhesives and sealants now begins with detecting the position of the component. Dispensing systems are in continuous use and have to work with 100 percent accuracy. And this level of accuracy must be verifiable. Demands on electronic components continue to escalate as these components also need to operate continuously and flawlessly, especially in the automotive and medical sectors. At the same time, there is increasing pressure to automate as companies are looking to achieve the shortest possible cycle times and maximum output.
Technical Library | 2021-11-22 20:39:44.0
Quality control is a key activity performed by manufacturing companies to verify product conformance to the requirements and specifications. Standardized quality control ensures that all the products are evaluated under the same criteria. The decreased cost of sensors and connectivity enabled an increasing digitalization of manufacturing and provided greater data availability. Such data availability has spurred the development of artificial intelligence models, which allow higher degrees of automation and reduced bias when inspecting the products. Furthermore, the increased speed of inspection reduces overall costs and time required for defect inspection. In this research, we compare five streaming machine learning algorithms applied to visual defect inspection with real world data provided by Philips Consumer Lifestyle BV. Furthermore, we compare them in a streaming active learning context, which reduces the data labeling effort in a real-world context. Our results show that active learning reduces the data labeling effort by almost 15% on average for the worst case, while keeping an acceptable classification performance. The use of machine learning models for automated visual inspection are expected to speed up the quality inspection up to 40%.
