Search query: Cleaning after semiconductor manufacturing CMP process

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abstract: Objectives: Cleaning validation is the procedure used to ensure that the cleaning process has eliminated the residues of drug substance from on the equipment surface after manufacture. A simple, sensitive, robust, and accurate high performance liquid chromatographic method was developed for the quantitative estimation of dipyridamole in swab samples obtained from the equipment surface after the manufacture of dipyridamole modified release capsules. Materials and Methods: The method was developed by using a Hypersil BDS C18 (150x4.6 mm, 5 mm) column with mobile phase containing a mixture of buffer (potassium dihydrogen phosphate buffer, pH 7.0+ 0.05) and methanol in the ratio of 30:70 v/v. Flow rate was 1.5 mL/min, column temperature was 45degC, and injection volume was 5 mL. Results: The method was validated and a specificity study was conducted to prove that there was no interference from blank and swab blank at the retention time of dipyridamole. The limit of detection and limit of quantification (LOQ) were established by using a series of linearity solutions and were found to be 0.041 mg/mL and 0.124 mg/mL, respectively. The method precision at the LOQ level was 8.6% relative standard deviation (RSD) method precision was 0.2% RSD, and ruggedness was 0.3% RSD. The method was accurate from the concentration of 0.13 mg/mL to 21.80 mg/mL and the recovery results met the acceptance criteria. The linearity of the method was found from 0.12 mg/mL to 20.14 mg/mL and the r2 value was 0.997. The robustness for the flow rate, wavelength, column temperature, buffer pH, and mobile phase ratio variations was tested, and all the system suitability parameters were met. Conclusion: The method validation was performed as per the regulatory requirements and guidelines. The validation parameters met the acceptance criteria and the proposed method can be applied for the intended routine swab analysis.
author_names: Sriram Valavala

Nareshvarma Seelam

Subbaiah Tondepu

Vivekanandan Sundaramurthy
title: Cleaning Method Validation for Estimation of Dipyridamole Residue on the Surface of Drug Product Manufacturing Equipment Using Swab Sampling and by High Performance Liquid Chromatographic Technique
venue: Turkish journal of pharmaceutical sciences
year: 2020

abstract: A radio frequency microelectromechanical system switch (MSS) manufactured by the complementary metal oxide semiconductor (CMOS) process is presented. The MSS is a capacitive shunt type. Structure for the MSS consists of coplanar waveguide (CPW) lines, a membrane, and springs. The membrane locates over the CPW lines. The surface of signal line for the CPW has a silicon dioxide dielectric layer. The fabrication of the MSS contains a CMOS process and a post process. The MSS has a sacrificial oxide layer after the CMOS process. In the post processing, a wet etching of buffer oxide etch (BOE) etchant is employed to etch the sacrificial oxide layer, so that the membrane is released. Actuation voltage for the MSS is simulated using the CoventorWare software. The springs have a low stiffness, so that the actuation voltage reduces. The measured results reveal that actuation voltage for the MSS is 10 V. Insertion loss for the MSS is 0.9 dB at 41 GHz and isolation for the MSS is 30 dB at 41 GHz.
author_names: Zung-You Tsai

Po-Jen Shih

Yao-Chuan Tsai

Ching-Liang Dai
title: Manufacturing and Testing of Radio Frequency MEMS Switches Using the Complementary Metal Oxide Semiconductor Process
venue: Sensors
year: 2021

abstract: Chemical mechanical polishing/planarization (CMP) is one of the most important fabrication technologies in the semiconductor industry. CMP is used to achieve planar surfaces and remove excess deposited material from the wafer. During CMP, a chemical "slurry" containing abrasive particles and chemical reagents is deposited on the polishing pad. The polishing pad is then pressed against the rotating wafer. The combined action of the polishing pad and chemical slurry results in material removal and planarization of the wafer surface. Modeling of the CMP process allows detection of potential planarization defects in chips before manufacturing. Accurate computation of pressure distribution across the wafer surface is crucial for accurate modeling of the CMP process. The pressure distribution calculation is usually done using the Hertz contact theory and Chekina model, which involves computations of direct and inverse fast Fourier transforms (FFT and IFFT) and pad displacements updates. In this paper, we adopted an obstacle problem approach for calculating the pressure distribution across the wafer/die surface for CMP modeling. In an obstacle problem, the pad is assumed to be an elastic membrane with fixed boundaries that is displaced by the wafer surface. The goal is to find the equilibrium position for the pad and calculate the pressure distribution over the surface in contact. The main advantage of this approach is that computations of FFT and IFFT and recalculations of the pad displacements can be avoided. This can lead to a more accurate model that is independent of pad displacement update method. The approach is tested on several examples. The results show correct physical behaviour and are in agreement with expectations.
author_names: Davit Piliposyan

Ruben Ghulghazaryan

Martin Poghosyan

Hayk H Nersisyan
title: Pressure calculation using obstacle problem for CMP modeling
year: 2020

abstract: Abstract. Background: Although the wet cleaning process has been widely used in semiconductor device manufacturing due to its convenience, it faces theoretical limits. That is, when the size of the objected particle is smaller than 100 nm, it is buried in the stagnant layer where there is substantially no fluid flow. Aim: Only small particles below the stagnant layer <100 nm) is removed without any damage to the fine patterns or substrate: pattern collapse, critical dimension shift, and optical property shift. Approach: Utilizing unique characteristics of water: volume expansion when freezing, solid (ice) is lighter than liquid (water) and particles adhered the substrate is peeled off from the substrate and rise to the water surface along with the surrounding ice. Results: By repeating the cycle of cooling, thawing, and rinsing, polystyrene sphere particle of 80 nm in diameter can be removed with high particle removal efficiency (PRE >90 and no negative influences on the pattern or substrate. Conclusions: A new cleaning method for very small <100 nm) particles is proposed with high PRE and low damage. This method is thought to be applied to every process if water can infiltrate into the gap between the particles and the substrate.
author_names: Keiiti Hattori

Daisuke Matsushima

Kensuke Demura

Masaya Kamiya
title: Particle and pattern discriminant freeze cleaning method
year: 2020

abstract: Maintenance in manufacturing has been developed and researched in the last few decades at a very rapid rate. It's a major step in process control to build a decision tool that detects defects in equipment or processes as quickly as possible to maintain high process efficiencies. However, the high complexity of machines, and the increase in data available in almost all areas, makes research on improving the accuracy of fault detection via data mining more and more challenging issue in this field. In our paper we present a new predictive model of semiconductor failures, based on machine learning approach, for predictive maintenance in industry 4.0. The framework of our model includes: Dataset and data acquisition, data preprocessing in three phases (over sampling, data cleaning, and attribute reduction with principal component analysis (PCA) technique and CfsSubsetEval technique) data modeling, evaluation model and implementation model. We used SECOM dataset to develop four different models based on four algorithms (Naive Bayesian, C4.5 Decision tree, Multilayer perceptron (MLP) Support vector machine) according to the five metrics (True Positive rate, False Positive rate, Precision, F Mesure and Accuracy) We implemented our new predictive model with 91, 95% of accuracy, as a new efficient predictive model of semiconductor failures. Keywords Machine learning; semiconductor; predictive maintenance; industry 4.0
author_names: Yousef El Mourabit

Youssef El

Hicham Zougagh

Younes Wadiai
title: Predictive System of Semiconductor Failures based on Machine Learning Approach
year: 2020

abstract: (c) 2020 Johnson Matthey Circular economy (CE) thinking has emerged as a route to sustainable manufacture, with related cradle to cradle implications requiring implementation from the design stage. The challenge lies in moving manufacturing environments away from the traditional linear economy paradigm, where materials, energy and water have often been designed to move out of the system and into receivership of waste management bodies after use. Recent applications of industrial digital technologies (IDTs: for example internet of things, data driven modelling, cyber physical systems, cloud manufacturing, cognitive computing) to manufacturing may be instrumental in transforming manufacturing from linear to circular. However, although IDTs and CE have been the focus of intensive research, there is currently limited research exploring the relationship between IDTs and the CE and how the former may drive the implementation of CE. This article aims to close the knowledge gap by exploring how an IDT (data driven modelling) may facilitate and advance CE principles within process manufacturing systems, specifically waste valorisation and process resilience. These applications are then demonstrated through two real world manufacturing case studies: (a) minimising resource consumption of industrial cleaning processes and (b) transforming wastewater treatment plants (WWTPs) into manufacturing centres.
author_names: Oliver J Fisher

Nicholas James Watson

Josep Escrig

Rachel L Gomes
title: Intelligent Resource Use to Deliver Waste Valorisation and Process Resilience in Manufacturing Environments Moving towards sustainable process manufacturing
year: 2020

abstract: Heavy forgings are the core components of major equipment and even play an indispensable role in national security and the national economy. Traditionally, heavy forgings are usually manufactured with ingots of more than 100 tons. However, there are serious macroscopic segregation, shrinkage porosity and other defects in heavy forgings due to size effect of metal solidification process, which seriously affect the quality of heavy forgings and have become a worldwide problem. Avoiding the traditional concept in which a heavy forging must be created using a large steel ingot, Institute of Metal Research, Chinese Academy of Sciences first put forward a novel technology to manufacture heavy high quality forgings by additive forging (AF) Small sized slabs with excellent quality are used as the base elements. After surface cleaning, stacking, assembling, vacuum packaging, and deformation process characterized by pressure forging and multi directional forging at high temperature, the homogenized heavy forgings can be obtained with completely healed interface, which realizes the new manufacturing technology of "by making greatly small" Through in depth research on the microstructural evolution and bonding mechanism of the interface, we found the self decomposition phenomenon of interface oxides. With the decomposed oxygen ions diffusing toward the matrix, oxide particles precipitated around both sides of the interface, forming the particle precipitation zone (PPZ) As the holding time increased, the width of the PPZ increased and the oxide precipitates in the PPZ transformed from MnCr x Al2 x O4 to Mn x Al3 x O4 and finally to g Al2O3, depending on the local oxygen activity. After holding for 24 h, the interfacial oxides completely decomposed and only a few nano scale g Al2O3 oxide precipitates remained dispersed far away from the bonding interface, leading to the recovery of the mechanical properties of the bonding joints. This recovery mechanism should be of great importance to the engineering application of Additive Forging. Besides, we illustrated the dynamic recrystallization (DRX) mechnism of the bonding interface. The bonding of joints is related with interfacial grain boundary (IGB) bulging process, which is considered as a nucleation process of DRXed grain under different deformation environments. During recrystallization process, the bonded interface moved due to strain induced boundary migration (SIBM) process. Stored energy difference (caused by accumulation of dislocations or difference of subgrain size at the bonding interface) was the dominant factor for SIBM during DRX. This technology has been applied to hydroelectric alloy steel spindles (110 tons in weight) and nuclear power stainless steel giant rings (15.6 m in diameter) which plays an important role in promoting the rapid development of high end equipment in China and ensuring the independence and control of core materials for major equipment.
author_names: Mingyue Sun

Bijun Xie

Jianyang Zhang

Longzhe Zhao

Dian-zhong Li

Yiyi Li
title: Research advances on homogenization manufacturing of heavy components by metal additive forging
year: 2020

abstract: Abstract Objective This work aimed to analyze how the Lean methodology has caused changes in organizational processes in a logistics company. Methodology A descriptive and qualitative research was carried out in one of the branches of a large logistics operator located in the city of Vinhedo (SP) Questionnaires were applied and interviews were conducted with logistics experts, organization leaders, Lean Manufacturing managers and operators, coming to a total of 100 respondents, including organizational change factors such as Kaizen application for process improvement, 5S's for organization and cleaning and Kanban for production control. Results It was evident that factors such as productivity, quality, organization, among others were factors for the implantation of the methodology in the company. Corporative results The results revealed that after the implementation of Lean management, there were changes such as a better understanding of the proposed methodology, reorganization of processes and gain in productivity and quality, thus raising the level of competitiveness of the organization. Keywords Organizational change, Lean Manufacturing, Logistics.
author_names: Ester Eliane Jeunon

Francisco Antonio de Oliveira Junior

Leon Duarte

Eloisa Helena Rodrigues Guimaraes
title: Lean manufacturing implantation impacts: a study on a large logistics operator
year: 2020

abstract: Manufacturing processes of custom implant abutments may contaminate their surfaces with micro wear deposits and generic pollutants. Such particulate debris, if not removed, might be detrimental and provoke inflammatory reactions in peri implant tissues. Although regulatory guidelines for adequate cleaning, disinfection, or sterilization exist, there does not appear to be a consistent application and data on the amount and extent of such contaminants is lacking. The aim of the present in vitro study was to evaluate the quality and quantity of processing related surface contamination of computer aided design/computer aided manufacturing (CAD/CAM) abutments in the state of delivery and after ultrasonic cleaning. A total of 28 CAD/CAM monotype and hybrid abutments were cleaned and disinfected applying a three stage ultrasonic protocol (Finevo protocol) Before and after cleaning, the chemical composition and the contamination of the abutments were assessed using scanning electron microscopy (SEM) dispersive X ray spectroscopy (EDX) and computer aided planimetric measurement (CAPM) In the delivery condition, monotype abutments showed a significantly higher amount of debris compared to hybrid abutments (4.86 6.10% vs. 0.03 0.03% p 0.001) The polishing process applied in the laboratory after bonding the hybrid abutment components reduces the surface roughness and thus contributes substantially to their purity. The extent of contamination caused by computer aided manufacturing of custom abutments can be substantially minimized using a three stage ultrasonic protocol.
author_names: Peter Gehrke

Cyrus Abazari

Kai Schlichter

Carsten Fischer

Dirk U Duddeck

Georgios E Romanos

Paul Weigl
title: Qualitative and Semi Quantitative Assessment of Processing Related Surface Contamination of One and Two Piece CAD/CAM Abutments before and after Ultrasonic Cleaning
venue: Materials
year: 2020

abstract: With the continuous trend of new technologies in semiconductor manufacturing assembly, challenges and issues are unavoidable. This paper presents an improvement done in quad flat noleads (QFN) leadframe package to resolve the quantity of unit rejection due to leads scratch underneath the leadframe. Moreover, the reject manifestation was captured after wirebonding process. Parameter optimization particularly for the second bond with the combination of bond force and bond scrubbing parameters was done to totally eliminate this type of issue after wirebonding process. With the wirebonding process optimization and improvement done, a reduction of 95 percent of leads scratch occurrence was achieved.
author_names: Jonathan C Pulido

Frederick Ray I Gomez

Edwin M Graycochea Jr
title: Lead Scratch Resolution through Wirebonding Process Optimization on QFN Packages
year: 2020