Reliability prediction of semiconductor devices using modified physics of failure approach

Traditional approaches like MIL-HDBK, Telcordia, and PRISM etc. have limitation in accurately predicting the reliability due to advancement in technology, process, materials etc. As predicting the reliability is the major concern in the field of electronics, physics of failure approach gained considerable importance as it involves investigating the root-cause which further helps in reliability growth by redesigning the structure, changing the parameters at manufacturer level and modifying the items at circuit level. On the other hand, probability and statistics methods provide quantitative data with reliability indices from testing by experimentation and by simulations. In this paper, qualitative data from PoF approach and quantitative data from the statistical analysis is combined to form a modified physics of failure approach. This methodology overcomes some of the challenges faced by PoF approach as it involves detailed analysis of stress factors, data modeling and prediction. A decision support system is added to this approach to choose the best option from different failure data models, failure mechanisms, failure criteria and other factors.Validerad; 2013; 20130312 (aditha

A STUDY OF THE THERMAL CYCLING PERFORMANCE OF SOLDER JOINTS IN AREA ARRAY PACKAGING

For both the electronics manufacturer and consumer, reliability is an essential characteristic defining the quality of the electronic component and system. Gradual degradation of the electronic components decreases efficiency of the system, and lack of reliability can lead to a significant loss. Efforts at achieving better quality and reliability of electronic components involve the inspection of solder joints in area array packaging. It is of note that solder interconnections are the vulnerable parts of circuit board assemblies (CBA), because they are mainly subjected to various assembly process during electronic manufacturing as well as environmental exposure failures during service. Therefore, the reliability of solder joints is a major concern during the entire life of an area array packaging in order to minimize the electronic failure rate that may lead to large losses. This thesis aims to provide a solution that helps to overcome some of the challenges that can occur during the reliability inspection of solder joints in area array packaging. Firstly, by successfully developing a non-destructive monitoring methodology to study the performance of solder joints under thermal cycling test. The quality of the solder joints in this research work from growth to failure was monitored by using a type of ultrasonic inspection called acoustic micro imaging (AMI). Results indicate that provided a suitable AMI parameters is applied, one can generate a 3D reconstruction of the solder joints images to allow and assess the solder joints’ behaviour in flip chip packages. AMI inspection of solder joints show good agreement with the results obtained that was used to examine how the reliability was affected by the geometry and position of the joints. An automatic segmentation technique was developed that allow to characterize and extract distinctive features of solder joints on different area array packages; such features include mean intensity, structural similarities model and histogram intensity of the region of interest of solder joints. The validation experimental results have been statistically implemented using novel geometrical and time domain features extraction methods like area, form factor and standard deviation. The result from these methods were used to extrapolate the solder joint’s fatigue life at normal operating conditions. Moreover, the analysis of variance (ANOVA) was employed to determine the percentage contribution of solder joints parameters on the acquired images. The results indicated that the thickness of the printed circuit board can affect solder joint reliability

Analysis and Evaluation of the Impacts of Predictive Analytics on Production System Performances in the Semiconductor Industry

Problem Statement: Predictive Analytics (PA) may effectively support semiconductor industry (SI) companies in order to manage the special challenges in SI value chains. To discover the implications of PA, the realistic benefits as well as its limitations of its application to semiconductor manufacturing, it is necessary to assess in which ways the application of PA affects the production system (PS) performances. However, based on the literature survey, the influences of PA on the various performance characteristics of an SI PS are not as clear as expected for the efficiently operative application. Besides, the existing performance models are not effective to predict the impacts of PA on the SI PS performances. Therefore, the overall aim of this thesis is to analyse and evaluate the impacts of PA on the SI PS performances and to identify under which conditions a PA application would generate the most significant performance improvements. The focus of this thesis is predictive maintenance (PdM). Research Methodology: Based on a post-positivist philosophy, the thesis applies a deductive research approach using mixed-methods for data collection. The research design has the following stages: (1) theory, (2) hypothesis, (3) state of research, (4) case study and (5) verification. Main Achievements: (1) The systematic literature review is carried out to identify the gaps of the existing research and based on these findings, a conceptual framework is proposed and developed. (2) The existing performance models are analysed and evaluated against their applicability to this study. (3) A causal loop model for SI PS is generated based on the assessment of experts with industrial engineering and equipment maintenance expertise. (4) An expert system is developed and evaluated in order to investigate transitive and contradictory effects of PdM on SI PS performances. (5) A simulation model is developed and validated for investigating the strengths and limitations of PdM regarding SI PS performances under different circumstances. Results: The results of the logical inference study show that PdM has 34 positive effects as well as 4 contradictory effects on SI PS performance characteristics. Based on the various simulation experiments, it has been found that (1) ’Mean Time to Repair’ decreases only if PdM supports proportionate reduction of failures and repair times. (2) Logistics performance improves only if the underlying workcenter is limited in capacity or the four partners are nonsynchronous. (3) PdM supports optimal cost decreases for workcenters where the degree of exhausting wear limits can be most effectively improved and (4) the degree of yield improvement gained by PdM is dependent on the operation scrap rate. However, (5) if a workcenter has overcapacity, PdM will potentially worsen PS performances, even if the particular workcenter performance can be improved. These new insights advance existing knowledge in production managements when adopting predictive technologies at SI PS in order to improve PS performances. The findings above enable SI practitioners to justify a PdM investment and to select suitable workcenters in order to improve SI PS performances by applying the proposed PdM. Contributions: The main contributions of this PhD project can be divided into practical application and theoretical work. The contributions from the theoretical perspective are: 1) The critical review and evaluation of the state of the research for PA in the context of semiconductor manufacturing and the models for predicting and evaluating SI PS performances. 2) A new framework for investigating the implications of PA on the challenges such as gaining high utilizations and controlling the variability in production processes in SI value chains. 3) The new knowledge about transitive and contradictory effects of PdM on SI PS performances, which indicates that PdM can be used to improve PS performances beyond a single machine. 4) The new knowledge about strengths and limitations of PdM in order to improve SI PS performances under particular circumstances. The contributions from the practical application perspective are: 1) A practical method for identifying workcenters where PdM delivers the most significant benefits for SI PS performances. 2) An expert system that provides a comprehensive knowledge base about causes and effects within SI PS in order to justify a PdM investment. 3) A concise review of important PA applications, their capabilities for the wafer fabrication and the most suited PA methods. These findings can be adopted by SI practitioners