Image Processing for Solar Cell Analysis, Diagnostics and Quality Assurance Inspection

2013 ◽  
pp. 1426-1462
Author(s):  
Michael G. Mauk
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Quality Assurance ◽  
Solar Cell ◽  
Process Development ◽  
Low Cost ◽  
Scale Up ◽  
Image Capturing ◽  
Infrared Cameras ◽  
Primary Focus

Image capturing, processing, and analysis have numerous uses in solar cell research, device and process development and characterization, process control, and quality assurance and inspection. Solar cell image processing is expanding due to the increasing performance (resolution, sensitivity, spectral range) and low-cost of commercial CCD and infrared cameras. Methods and applications are discussed, with primary focus on monocrystalline and polycrystalline silicon solar cells using visible and infrared (thermography) wavelengths. The most prominent applications relate to mapping of minority carrier lifetime, shunts, and defects in solar cell wafers, in various stages of the manufacturing process. Other applications include measurements of surface texture and reflectivity, surface cleanliness, integrity of metallization lines, uniformity of coatings, and crystallographic texture and grain size. Image processing offers the capability to assess large-areas (> 100 cm2) with a non-contact, fast (~ 1 second), and modest cost. The challenge is to quantify and interpret the image data in order to better inform device design, process engineering, and quality control. Many promising solar cell technologies fail in the transition from laboratory to factory due to issues related to scale-up in area and manufacturing throughput. Image analysis provides an effective method to assess areal uniformity, device-to-device reproducibility, and defect densities. More integration of image analysis from research devices to field testing of modules will continue as the photovoltaics industry matures.

Image Processing for Solar Cell Analysis, Diagnostics and Quality Assurance Inspection

2013 ◽  
pp. 338-375
Author(s):  
Michael G. Mauk
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Quality Assurance ◽  
Solar Cell ◽  
Process Development ◽  
Low Cost ◽  
Scale Up ◽  
Image Capturing ◽  
Infrared Cameras ◽  
Primary Focus

Image capturing, processing, and analysis have numerous uses in solar cell research, device and process development and characterization, process control, and quality assurance and inspection. Solar cell image processing is expanding due to the increasing performance (resolution, sensitivity, spectral range) and low-cost of commercial CCD and infrared cameras. Methods and applications are discussed, with primary focus on monocrystalline and polycrystalline silicon solar cells using visible and infrared (thermography) wavelengths. The most prominent applications relate to mapping of minority carrier lifetime, shunts, and defects in solar cell wafers, in various stages of the manufacturing process. Other applications include measurements of surface texture and reflectivity, surface cleanliness, integrity of metallization lines, uniformity of coatings, and crystallographic texture and grain size. Image processing offers the capability to assess large-areas (> 100 cm2) with a non-contact, fast (~ 1 second), and modest cost. The challenge is to quantify and interpret the image data in order to better inform device design, process engineering, and quality control. Many promising solar cell technologies fail in the transition from laboratory to factory due to issues related to scale-up in area and manufacturing throughput. Image analysis provides an effective method to assess areal uniformity, device-to-device reproducibility, and defect densities. More integration of image analysis from research devices to field testing of modules will continue as the photovoltaics industry matures.

scholarly journals Process Development and Scale-up Optimization of the SARS-CoV-2 Receptor Binding Domain-Based Vaccine Candidate, RBD219-N1C1

2020 ◽  
Author(s):  
Jungsoon Lee ◽  
Zhuyun Liu ◽  
Wen-Hsiang Chen ◽  
Junfei Wei ◽  
Rakhi Kundu ◽  
...  
Keyword(s):  
Receptor Binding ◽  
Process Development ◽  
Low Cost ◽  
Scale Up ◽  
Neutralizing Antibody ◽  
Protein Antigen ◽  
Purification Process ◽  
Good Manufacturing Practices ◽  
Purification Methods ◽  
Selection Of

AbstractA SARS-CoV-2 RBD219-N1C1 (RBD219-N1C1) recombinant protein antigen formulated on Alhydrogel® has recently been shown to elicit a robust neutralizing antibody response against SARS-CoV-2 pseudovirus in mice. The antigen has been produced under current good manufacturing practices (cGMP) and is now in clinical testing. Here, we report on process development and scale-up optimization for upstream fermentation and downstream purification of the antigen. This includes production at the 1 and 5 L scale in the yeast, Pichia pastoris, and the comparison of three different chromatographic purification methods. This culminated in the selection of a process to produce RBD219-N1C1 with a yield of >400 mg per liter of fermentation with >92% purity and >39% target product recovery after purification. In addition, we show the results from analytical studies, including SEC-HPLC, DLS, and an ACE2 receptor binding assay that were performed to characterize the purified proteins to select the best purification process. Finally, we propose an optimized upstream fermentation and downstream purification process that generates quality RBD219-N1C1 protein antigen and is fully scalable at a low cost.

scholarly journals Process development and scale-up optimization of the SARS-CoV-2 receptor binding domain–based vaccine candidate, RBD219-N1C1

2021 ◽  
Author(s):  
Jungsoon Lee ◽  
Zhuyun Liu ◽  
Wen-Hsiang Chen ◽  
Junfei Wei ◽  
Rakhi Kundu ◽  
...  
Keyword(s):  
Receptor Binding ◽  
Process Development ◽  
Low Cost ◽  
Scale Up ◽  
Neutralizing Antibody ◽  
Protein Antigen ◽  
Vaccine Antigen ◽  
Yeast Fermentation ◽  
Purification Process ◽  
Purification Methods

Abstract A SARS-CoV-2 RBD219-N1C1 (RBD219-N1C1) recombinant protein antigen formulated on Alhydrogel® has recently been shown to elicit a robust neutralizing antibody response against SARS-CoV-2 pseudovirus in mice. The antigen has been produced under current good manufacturing practices (cGMPs) and is now in clinical testing. Here, we report on process development and scale-up optimization for upstream fermentation and downstream purification of the antigen. This includes production at the 1-L and 5-L scales in the yeast, Pichia pastoris, and the comparison of three different chromatographic purification methods. This culminated in the selection of a process to produce RBD219-N1C1 with a yield of >400 mg per liter of fermentation with >92% purity and >39% target product recovery after purification. In addition, we show the results from analytical studies, including SEC-HPLC, DLS, and an ACE2 receptor binding assay that were performed to characterize the purified proteins to select the best purification process. Finally, we propose an optimized upstream fermentation and downstream purification process that generates quality RBD219-N1C1 protein antigen and is fully scalable at a low cost. Key points • Yeast fermentation conditions for a recombinant COVID-19 vaccine were determined. • Three purification protocols for a COVID-19 vaccine antigen were compared. • Reproducibility of a scalable, low-cost process for a COVID-19 vaccine was shown. Graphical abstract

Accelerating Laboratory Thin Film Photovoltaic Innovation into Commercial Production

2009 ◽  
Vol 1165 ◽  
Author(s):  
Fred H. Seymour
Keyword(s):  
Thin Film ◽  
Alternative Energy ◽  
Process Development ◽  
Low Cost ◽  
Scale Up ◽  
High Volume ◽  
Commercial Production ◽  
Laboratory Research ◽  
Small Scale ◽  
Managing Risk

AbstractAlternative energy sources such as thin film photovoltaics can be accelerated by improving the rapid and successful transition from laboratory research innovation to commercial production. Most laboratory research and development is on a small scale and its production is in small volumes. It focuses on exploration, discovery, and understanding. When the successful innovation is commercialized, both the scale and the volume increase dramatically and the focus shifts to performance, reliability, yield and cost. This transformation can be accelerated by closely managing risk and by integrating the equipment design and the process development. Also, the cadmium telluride photovoltaic technology has properties that make it more amenable to rapid scale up to low cost and high volume manufacturing.

scholarly journals A Comparative Study of Chlorophyll Content Estimation in Barley (Hordeum vulgare L.) Genotypes Based on RGB (Red, Green, Blue) Image Analysis

2021 ◽  
Author(s):  
Ali Guendouz ◽  
Hocine Bendada ◽  
Ramadan Benniou
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Chlorophyll Content ◽  
Mean Squared Error ◽  
Low Cost ◽  
Vegetation Indices ◽  
Photochemical Reactions ◽  
Hordeum Vulgare L ◽  
Processing Techniques ◽  
Barley Genotypes

Background: Chlorophyll is the most important pigment in plant which absorbs light and subsequently transfers its energy to drive the photochemical reactions of photosynthesis. The numerical image processing techniques have been widely used in the analysis of leaf characteristics.Methods: The methods based on RGB (Red, Green and Blue) image analysis may emerge as a new and low-cost method for estimation the chlorophyll content. In this work, we use eight RGB vegetation indices as alternative for chlorophyll content estimation. Result: The student t-test showed that all the RGB indices tested are suitable to estimate the chlorophyll content in barley genotypes. In addition, the results which based on the correlation analysis in combination with the values of root mean squared error (RMSE) demonstrate that the very suitable RGB indices are these with high values of correlation coefficient and lowest values of RMSE. Data collected from barley genotypes leaves indicated that digital image processing technology can be a useful and rapid non-destructive method for assessment of chlorophyll content. Among the RGB indexes tested in this study the 100-(2R-B) and RGRI (R/G) are the most promising index to estimate the chlorophyll content in barley genotypes.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

Constructive Optimisation of the Propeller Type Mixing Devices Using the Virtual and Rapid Prototyping

2017 ◽  
Vol 68 (3) ◽  
pp. 453-458 ◽  
Author(s):  
Daniel Besnea ◽  
Alina Spanu ◽  
Iuliana Marlena Prodea ◽  
Gheorghita Tomescu ◽  
Iolanda Constanta Panait
Keyword(s):  
Rapid Prototyping ◽  
Low Cost ◽  
Scale Up ◽  
Three Dimensional ◽  
Rapid Identification ◽  
Multidisciplinary Optimization ◽  
External Diameter ◽  
Process Industries ◽  
Parametric Cad ◽  
Shaft Torque

The paper points out the advantages of rapid prototyping for improving the performances/constructive optimization of mixing devices used in process industries, here exemplified to propeller types ones. The multidisciplinary optimization of the propeller profile affords its design using parametric CAD methods. Starting from the mathematical curve equations proposed for the blade profile, it was determined its three-dimensional virtual model. The challenge has been focused on the variation of propeller pitch and external diameter. Three dimensional ranges were manufactured using the additive manufacturing process with Marker Boot 3D printer. The mixing performances were tested on the mixing equipment measuring the minimum rotational speed and the correspondent shaft torque for complete suspension achieved for each of the three models. The virtual and rapid prototyping method is newly proposed by the authors to obtain the basic data for scale up of the mixing systems, in the case of flexible production (of low quantities), in which both the nature and concentration of the constituents in the final product varies often. It is an efficient and low cost method for the rapid identification of the optimal mixing device configuration, which contributes to the costs reduction and to the growing of the output.

One-step models for soft computing techniques. Industrial application to image processing in quality assurance process

2015 ◽  
Vol 81 (5-8) ◽  
pp. 771-778 ◽  
Author(s):  
Pascual Noradino Montes Dorantes ◽  
Marco Aurelio Jiménez Gómez ◽  
Gerardo Maximiliano Méndez ◽  
Juan Pablo Nieto González ◽  
Jesús de la Rosa Elizondo
Keyword(s):  
Image Processing ◽  
Quality Assurance ◽  
Soft Computing ◽  
Industrial Application ◽  
Quality Assurance Process ◽  
Soft Computing Techniques ◽  
One Step ◽  
Assurance Process

Real time fall detection using infrared cameras and reflective tapes under day/night luminance

2021 ◽  
pp. 1-16
Author(s):  
E. Ramanujam ◽  
S. Padmavathi
Keyword(s):  
Low Cost ◽  
Age Groups ◽  
Orientation Angle ◽  
Fall Detection ◽  
Living Environment ◽  
Vision Systems ◽  
Ir Camera ◽  
Cluttered Environments ◽  
Infrared Cameras ◽  
Time Fall

Falls are the leading cause of injuries and death in elderly individuals who live alone at home. The core service of assistive living technology is to monitor elders’ activities through wearable devices, ambient sensors, and vision systems. Vision systems are among the best solutions, as their implementation and maintenance costs are the lowest. However, current vision systems are limited in their ability to handle cluttered environments, occlusion, illumination changes throughout the day, and monitoring without illumination. To overcome these issues, this paper proposes a 24/7 monitoring system for elders that uses retroreflective tape fabricated as part of conventional clothing, monitored through low-cost infrared (IR) cameras fixed in the living environment. IR camera records video even when there are changes in illumination or zero luminance. For classification among clutter and occlusion, the tape is considered as a blob instead of a human silhouette; the orientation angle, fitted through ellipse modeling, of the blob in each frame allows classification that detects falls without pretrained data. System performance was tested using subjects in various age groups and “fall” or “non-fall” were detected with 99.01% accuracy.

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