scholarly journals Development of Machine Vision to Increase the Level of Automation in Indonesia Electronic Component Industry

2021 ◽  
Vol 54 (2) ◽  
pp. 253-262
Author(s):  
Hendi Herlambang ◽  
Humiras Hardi Purba ◽  
Choesnul Jaqin
Keyword(s):  
Machine Vision ◽  
Manufacturing Systems ◽  
Ccd Camera ◽  
Quality Data ◽  
Structural Quality ◽  
Work Activity ◽  
Vision Inspection ◽  
Level Of Automation ◽  
Inspection Data ◽  
The Impact

Human involvement in the assembly part manufacturing process is still relatively high. However, automation solutions are not flexible enough to be applied to manufacturing systems. It is essential to evaluate each work activity so that automation can be implemented effectively. We developed an automatic vision inspection using machine vision. The level of automation (LoA) in the company increases, and the impact caused by process failures on manual systems can be eliminated during inspection activities. The automation level increase in the inspection area is described and analyzed using the Hierarchy Task Analysis (HTA). Inspection data process activity and quality data are collected to determine the CCD camera selection, lamp selection, and lens selection. Three quality objectives, such as geometric quality, surface quality, and structural quality, are identified automatically using machine vision. Furthermore, after applying machine vision, an analysis of current LoA conditions and future LoA conditions is carried out. The results showed that the application of machine vision could increase the Level of Automation in the product inspection activity by 81.8%. There is a strong correlation (R = 0.924) between manual measurements carried out by operators and machine vision.

The Impact of Missing and Error-Prone Auxiliary Information on Sparse-Matrix Sub-Population Parameter Estimates

Methodology ◽  
2015 ◽  
Vol 11 (3) ◽  
pp. 89-99 ◽  
Author(s):  
Leslie Rutkowski ◽  
Yan Zhou
Keyword(s):  
Sparse Matrix ◽  
Small Body ◽  
Auxiliary Information ◽  
Poor Quality ◽  
Quality Data ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Population Parameter ◽  
Conditioning Model ◽  
The Impact

Abstract. Given a consistent interest in comparing achievement across sub-populations in international assessments such as TIMSS, PIRLS, and PISA, it is critical that sub-population achievement is estimated reliably and with sufficient precision. As such, we systematically examine the limitations to current estimation methods used by these programs. Using a simulation study along with empirical results from the 2007 cycle of TIMSS, we show that a combination of missing and misclassified data in the conditioning model induces biases in sub-population achievement estimates, the magnitude and degree to which can be readily explained by data quality. Importantly, estimated biases in sub-population achievement are limited to the conditioning variable with poor-quality data while other sub-population achievement estimates are unaffected. Findings are generally in line with theory on missing and error-prone covariates. The current research adds to a small body of literature that has noted some of the limitations to sub-population estimation.

Backside Emission Microscopy for Integrated Circuits on Heavily Doped Substrate

1998 ◽  
Author(s):  
Ching-Lang Chiang ◽  
Neeraj Khurana ◽  
Daniel T. Hurley ◽  
Ken Teasdale
Keyword(s):  
Integrated Circuits ◽  
Ccd Camera ◽  
Preparation Technique ◽  
Absorption Data ◽  
Ir Radiation ◽  
Heavily Doped ◽  
Emission Microscopy ◽  
Diffraction Patterns ◽  
Emission Detection ◽  
The Impact

Abstract Backside emission microscopy on heavily doped substrate materials was analyzed from the viewpoint of optical absorption by the substrate and sample preparation technique. Although it was widely believed that silicon is transparent to infrared (IR) radiation, we demonstrated by using published absorption data that silicon with doping levels above 5 x 1018cm-3 is virtually opaque, leaving only a narrow transmission window around the energy bandgap. Because the transmission depends exponentially on the thickness of die, thinning to below 100µm is shown to be required. Even an advanced IR sensor such as HgCdTe would find little light to detect without thinning the die. For imaging the circuit, an IR laser-based system produced poor images in which the diffraction patterns often ruined the contrast and obscured the image. Hence, a precise, controlled die thinning technique is required both for emission detection and backside imaging. A thinning and polishing technique was briefly described that was believed to be applicable to most ceramic packages. A software technique was employed to solve the image quality problem commonly encountered in backside imaging applications using traditional microscope light source and a scientific grade CCD camera. Finally, we showed the impact of die thickness on imaging circuits on a heavily doped n type substrate.

scholarly journals Modeling Building Stock Development

2021 ◽  
Vol 13 (2) ◽  
pp. 723
Author(s):  
Antti Kurvinen ◽  
Arto Saari ◽  
Juhani Heljo ◽  
Eero Nippala
Keyword(s):  
Model Development ◽  
Housing Demand ◽  
Quality Data ◽  
Building Stock ◽  
Test Arena ◽  
Climate Targets ◽  
Wide Range ◽  
Key Variables ◽  
The Impact

It is widely agreed that dynamics of building stocks are relatively poorly known even if it is recognized to be an important research topic. Better understanding of building stock dynamics and future development is crucial, e.g., for sustainable management of the built environment as various analyses require long-term projections of building stock development. Recognizing the uncertainty in relation to long-term modeling, we propose a transparent calculation-based QuantiSTOCK model for modeling building stock development. Our approach not only provides a tangible tool for understanding development when selected assumptions are valid but also, most importantly, allows for studying the sensitivity of results to alternative developments of the key variables. Therefore, this relatively simple modeling approach provides fruitful grounds for understanding the impact of different key variables, which is needed to facilitate meaningful debate on different housing, land use, and environment-related policies. The QuantiSTOCK model may be extended in numerous ways and lays the groundwork for modeling the future developments of building stocks. The presented model may be used in a wide range of analyses ranging from assessing housing demand at the regional level to providing input for defining sustainable pathways towards climate targets. Due to the availability of high-quality data, the Finnish building stock provided a great test arena for the model development.

scholarly journals Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

2021 ◽  
Author(s):  
Shwet Ketu ◽  
Pramod Kumar Mishra
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Class Imbalance ◽  
Imbalanced Data ◽  
Classification Algorithm ◽  
Quality Data ◽  
Pollution Level ◽  
Classification Problems ◽  
Chi Square ◽  
The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

Modelling of 10 Gbps Free Space Optics Communication Link Using Array of Receivers in Moderate and Harsh Weather Conditions

2017 ◽  
Vol 38 (3) ◽  
Author(s):  
Amit Gupta ◽  
Nagpal Shaina
Keyword(s):  
Free Space ◽  
Weather Conditions ◽  
Quality Data ◽  
Laser Source ◽  
Communication Link ◽  
Free Space Optical ◽  
Space Optics ◽  
Received Power ◽  
Adverse Weather ◽  
The Impact

AbstractIntersymbol interference and attenuation of signal are two major parameters affecting the quality of transmission in Free Space Optical (FSO) Communication link. In this paper, the impact of these parameters on FSO communication link is analysed for delivering high-quality data transmission. The performance of the link is investigated under the influence of amplifier in the link. The performance parameters of the link like minimum bit error rate, received signal power and Quality factor are examined by employing erbium-doped fibre amplifier in the link. The effects of amplifier are visualized with the amount of received power. Further, the link is simulated for moderate weather conditions at various attenuation levels on transmitted signal. Finally, the designed link is analysed in adverse weather conditions by using high-power laser source for optimum performance.

scholarly journals Integration of different-quality data in short-term mining planning

2015 ◽  
Vol 68 (2) ◽  
pp. 221-227 ◽  
Author(s):  
Cristina Paixão Araújo ◽  
João Felipe Coimbra Leite Costa
Keyword(s):  
Mineral Exploration ◽  
Quality Data ◽  
Imprecise Data ◽  
Short Term ◽  
Mining Operations ◽  
Different Types ◽  
Block Models ◽  
The Impact ◽  
Block Distribution ◽  
Ordinary Cokriging

AbstractDecisions, from mineral exploration to mining operations, are based on grade block models obtained from samples. This study evaluates the impact of using imprecise data in short-term planning. The exhaustive Walker Lake dataset is used and is considered as the source for obtaining the true grades. Initially, samples are obtained from the exhaustive dataset at regularly spaced grids of 20 × 20 m and 5 × 5 m. A relative error (imprecision) of ±25% and a 10% bias are added to the data spaced at 5 × 5 m (short-term geological data) in different scenarios. To combine these different types of data, two methodologies are investigated: cokriging and ordinary kriging. Both types of data are used to estimate blocks with the two methodologies. The grade tonnage curves and swath plots are used to compare the results against the true block grade distribution. In addition, the block misclassification is evaluated. The results show that standardized ordinary cokriging is a better methodology for imprecise and biased data and produces estimates closer to the true grade block distribution, reducing block misclassification.

Study on the Measuring and Positioning of the Rim Valve Hole Based on Machine Vision

2014 ◽  
Vol 711 ◽  
pp. 333-337 ◽  
Author(s):  
Fang Wang ◽  
Chao Kun Ma ◽  
Shan Qiang Dai ◽  
Chang Chun Li
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Measurement Method ◽  
Ccd Camera ◽  
Servo Motor ◽  
Processing Characteristic ◽  
Linear Ccd ◽  
Hole Position ◽  
And Control

The author has designed a visual workbench to realize that the rim can rotate with the workbench. Meanwhile, the linear CCD camera records the rim’s circumference. The paper has explored the measurement method of getting the rim valve hole position using machine vision. The system can calculate the position of rim-hole and control the servo motor by image processing, characteristic recognizing and measuring to locate the position of wheel-hole automatically. And the paper has verified the accuracy of the method by experiments.

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