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41	Vliv množství pájky a izotermálního stárnutí na vodivost pájeného spoje / Solder Joint Conductivity - Influence of Solder Volume and Isothermal Aging Mach, Ladislav January 2012 (has links) The master thesis analyses electrical conductivity of lead-free solder joints. The test method design for monitoring the electrical conductivity of the soldered joint is described in the practical part. Simulated BGA package with four pin (BGA4) is used for experiments. Tested PCBs are subjected to isothermal aging and current load. During isothermal aging is measured electrical conductivity and optical microscope is used for intermetallic layer (IMC) growth observation. Two types of surface finish (OSP and ENIG) are used for tests and three diameters of solder terminal balls (solder alloy SAC405). The influence of the ratio area connection / solder volume (ratio S / V) on lead-free solder joints conductivity was evaluated.
42	Spolehlivost bezolovnatých pájek a vybrané způsoby odhadu jejich životnosti / Reliability of Lead-free Solders and the Selected Methods to Estimate its Lifetime Švecová, Olga January 2012 (has links) The doctoral thesis is focused on reliability of lead-free solder SAC 305. Knowledge in the field of fatigue models used in determining the lifetime of solder joints are observed in this thesis. Also such methods of predicting reliability as numerically-analytical methods or reliability experimental tests are mentioned. Practical results of reliability measurement are presented. Experimental data served as the foundation for determining empirical coefficients for the fatigue model based on deformation induced by creep of the solder, which was implemented in the ANSYS environment. Results from different methods were compared and conclusions discussing the suitability of the presented prediction methods are formulated.
43	Analýza defektů na DPS za použití moderních optických metod / Analysis of Defects on PCB Using Modern Optical Method Vala, Martin January 2016 (has links) This diploma thesis is focused on detecting of defects on BGA (Ball Grid Array) components using of X-ray. Defects are formed during reflow BGA components during assembly, but also later due to mechanical and thermal stress. Therefore, there is an overview of defects and methods of diagnosis of BGA packages eg .: modern X-ray defect detection or micro sections. There is disclosed a device NORDSON DAGE XD7600NT its operation and setup. The device enables advanced methods of scanning called X-plane. For creating 3D models used reconstructive software called CERA, which uses raw data from the method of X-Plane.
44	Prognostics for Condition Based Maintenance of Electrical Control Units Using On-Board Sensors and Machine Learning Fredriksson, Gabriel January 2022 (has links) In this thesis it has been studied how operational and workshop data can be used to improve the handling of field quality (FQ) issues for electronic units. This was done by analysing how failure rates can be predicted, how failure mechanisms can be detected and how data-based lifetime models could be developed. The work has been done on an electronic control unit (ECU) that has been subject to a field quality (FQ) issue, determining thermomechanical stress on the solder joints of the BGAs (Ball Grid Array) on the PCBAs (Printed circuit board assembly) to be the main cause of failure. The project is divided into two parts. Part one, "PCBA" where a laboratory study on the effects of thermomechanical cycling on solder joints for different electrical components of the PCBAs are investigated. The second part, "ECU" is the main part of the project investigating data-driven solutions using operational and workshop history data. The results from part one show that the Weibull distribution commonly used to predict lifetimes of electrical components, work well to describe the laboratory results but also that non parametric methods such as kernel distribution can give good results. In part two when Weibull together with Gamma and Normal distributions were tested on the real ECU (electronic control unit) data, it is shown that none of them describe the data well. However, when random forest is used to develop data-based models most of the ECU lifetimes of a separate test dataset can be correctly predicted within a half a year margin. Further using random survival forest it was possible to produce a model with just 0.06 in (OOB) prediction error. This shows that machine learning methods could potentially be used in the purpose of condition based maintenance for ECUs. machine learning random forest random survival forest condition based maintenance cbm reliability solder joint failure thermomechanical cycling ECU lifetime prediction data-driven statistics BGA PCBA field quality maintenance truck bus vehicle Probability Theory and Statistics Sannolikhetsteori och statistik Transport Systems and Logistics Transportteknik och logistik Robotics Robotteknik och automation Control Engineering Reglerteknik

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