Carlos Mata

Kill ratio calculation for in-line yield prediction

The search for better yields in IC manufacturing calls for a smarter use of the vast amount of data that can be generated by a world class production line.In this scenario, in-line inspection processes produce thousands of wafer maps, number of defects, defect type and pictures every day. A step forward is to correlate these with the other big data- generator area: test. In this paper, we present how these data can be put together and correlated to obtain a very useful yield predicting tool. This correlation will first allow us to calculate the kill ratio, i.e. the probability for a defect of a certain size in a certain layer to kill the die. Then we will use that number to estimate the cosmetic yield that a wafer will have.

The 100% yield explanation approach in Lucent Technologies Madrid

A wealth of advantages arise from breaking down the overall yield into yield components that are easier to work and closer to the manufacturing line environment. We present in this paper our strategy to attempt the 100% yield explanation on our fab and the process of building a pareto that quantifies the impact of each yield component (defects, probe, nothing found, etc...). The most critical one, the defect related, is accounted by a set of knowledge-based automatic software tools that operate in our fab. They quantify it and break it down into the by layer, by defect size and type (ADC) contributions. The step forward of communication and deployment of this yield strategy is a key topic also discussed in the paper. On our way towards the 100% understanding of yield we have learned how to better manage it and taken advantage of many more opportunities to improve it. The strategy has shown to work both for new and mature technologies in our manufacturing line in Lucent Technologies Madrid.

Corrective actions for stainless-steel-particle-related burn-in failures

Metal shorts are the second burn-in failure cause in our production line. Stainless Steel (SS) particles are found in most of the analyzed metal shorts. This work presents the corrective actions implemented to detect, prevent and correct SS particle sources in our production line. The SS particle corrective actions cover from in-line KLA-ADC detection, to hardware/process modification and new wafer backside contamination controls. The main sources are due to 1) the lack of some final point filters in some NEW/old machines; 2) damaged SS mobile pieces; 3) wafer backside contamination. The back-side contamination comes form SS hardware pieces that need to be replaced by other with SS-free surfaces; as the standard LAM-TCP APM-chick. A positive impact in the burn-in failure rate has bene seen after implementing those corrective actions.

SAT0198 Relation of Doppler Ultrasound Synovitis versus Clinical Synovitis with Changes in Native Complement Component Levels in Rheumatoid Arthritis Patients Treated with Biologic Disease-Modifying Antirheumatic Drugs

Background The complement system not only forms part of the innate immunity but also contribute in modulating the adaptive responses [1]. There are evidence suggesting increased level of complement as acute phase reactant mediated by proinflammatory cytokines important in active rheumatoid arthritis (RA) such as interleukin 1 (IL-1), interleukin 6 (IL-6) and tumour necrosis factor-α (TNF-α) [2-5]. Activation of the complement system, by immune complexes or C-reactive protein (CRP), plays an important role in inflammatory activity of RA as shown by significant level of complement degradation products found in the synovial fluid of affected joints in RA [6,7]. Objectives The complement system plays a fundamental role in mediating the activity of rheumatoid arthritis (RA). Biologic therapy can reduce native complement component levels and its activation. We aimed to study the relation of Doppler ultrasound (US) synovitis versus clinical synovitis with changes in native complement component levels in RA patients on biologic therapy. Methods This was a prospective cross-sectional study. Ninety seven consecutive patients with RA on biologic therapy for at least 3 months were recruited. Clinical, laboratory and Doppler US assessments were performed. The Disease Activity Score in 28 joints (DAS28), Simplified Disease Activity Index (SDAI) and a 12-joint US assessment were carried out. Synovitis was semiquantitatively scored in B-mode and power Doppler (PD) mode. Results A significant decrease in native complement (i.e. C3 and C4) and C-reactive protein (CRP) levels was observed. This was highly significant for C3 decrease (p<0.0005), and C4 decrease (p<0.0005). Synovitis detected by PD US showed significant negative association with C3 change (p<0.008), where patients with higher C3 change were more likely to have PD US inactive status on assessment. Correlations between complement levels, CRP levels and their changes with clinical and PD US disease activity. Parameters (mg/dL) DAS28-ESR SDAI Global BM Global PD C3 0.26* −0.04 −0.09 −0.02 C3 change 0.12 −0.01 −0.08 −0.04 C4 0.21* −0.16 −0.13 −0.07 C4 change 0.21* −0.011 −0.03 −0.04 CRP 0.39* 0.40* 0.09 0.19 CRP change 0.18 0.19 0.01 −0.01 * p<0.05. C3, complement 3; C4, complement 4; CRP, C-reactive protein, DAS28-ESR, Disease Activity Score(28)-erythrocyte sedimentation rate; SDAI, Simplified Disease Activity Index; BM, B-mode synovitis; PD, power Doppler synovitis. Conclusions Our results suggested that disease inactive status determined by PD US but not by clinical assessment can be related with decrease in complement in RA patients treated with biologic therapy. References Morgan BP et al. Immunol Lett 2005; 97: 171-9. Miura N et al. J Biol Chem 1987; 262: 7298-305. Andus T et al. Eur J Immunol 1988; 17: 1193-7. Anthony R et al. Eur J Immunol 1989; 19: 1405-12. Ramadori G et al. Eur J Immunol 1988; 18: 1259-64. Kemp PA et al. J Clin Lab Immunol 1992; 37: 147-62. Westedt ML et al. J Rheumatol 1985:12;449-55. Disclosure of Interest M. Montoro Alvarez: None declared, O. Yew Chong: None declared, I. Janta: None declared, B. Serrano: None declared, C. Mata: None declared, L. Martinez: None declared, J. Martinez-Barrio: None declared, M. Hinojosa: None declared, N. Bello: None declared, J. Ovalles: None declared, J. Nieto: None declared, L. Valor: None declared, F. Lopez-Longo: None declared, I. Monteagudo Consultant for: Abbvie, Roche Farma, Bristol-Myers Squibb, Pfizer, UCB, General Electric Healthcare, MSD and Esaote, C. Gonzalez: None declared, J. Garrido: None declared, A. Rosman: None declared, L. Ing Soo: None declared, E. Naredo Grant/research support: Grant/research support: UCB and MSD Consultant for: Abbvie, Roche Farma, Bristol-Myers Squibb, Pfizer, UCB, General Electric Healthcare, and Esaote, L. Carreño: None declared DOI 10.1136/annrheumdis-2014-eular.4379

Wafer level stress data successfully used as early burn-in predictor

We show that a simple post-stress test can provide a good early reliability indicator. The defect types that have been revealed by this post-stress test are two types of conductive particles on metal levels. This early indicator has been of great value when dealing with potentially contaminated wafers/lots and to evaluate and to prioritize the corrective actions to solve the line issues.

Wafer-level stress data successfully used as early burn-in predictor

We show that a simple post-stress test can provide a good early reliability indicator. The defect types that have been revealed by this post-stress test are two types of conductive particles on metal levels. This early indicator has been of great value when dealing with potentially contaminated wafers/lots and to evaluate and to prioritize the corrective actions to solve the line issues.

Web-based procedure to speed-up reaction to in-line inspection alarms

An important point in the in-line yield improvement strategy is to be able to react as soon as possible to the alarms detected, and stop the excursions quickly in order to reduce the impact in yield loss and reliability. Therefore, to improve these requirements, we have developed a procedure, using web-based tools, which we detail in this paper. This exchange of information system permits the operators to easily access the engineers documents. The engineering expertise about the usual problems is concentrated in these documents, which clearly explains the procedures to follow. Using a web interface, operators can complete all necessary data to continue with the investigation through different shifts. This database is easily accessible by engineers and other operators and the information is structured and organized in a uniform and correct way. In this paper we will show the benefits that we have found during the last six months working in production with this procedure.

Toward 100% yield understanding approach in Lucent Technologies Madrid

A wealth of advantages arise form breaking down the overall yield into yield components that are easier to work and closer to the manufacturing line environment. We present in this paper our strategy to attempt the 100 percent yield explanation on our fab and the process of building a pareto that quantifies the impact of each yield component. The most critical one, the defect related, is accounted by a set of knowledge-based automatic software tools that operate in our fab. They quantify it and break it down into the by layer, by defect size and type contributions. The step forward of communication and deployment of this yield strategy is a key topic also discussed in the paper. On our way towards the 100 percent understanding of yield we have learned how to better manage it and taken advantage of many more opportunities to improve it. The strategy has shown to work both for new and mature technologies in our manufacturing line in Lucent Technologies Madrid.