scholarly journals Powder Spread Process Monitoring in Polymer Laser Sintering and its Influences on Part Properties

JOM ◽  
2021 ◽  
Author(s):  
Sven Helge Klippstein ◽  
Florian Heiny ◽  
Nagaraju Pashikanti ◽  
Monika Gessler ◽  
Hans-Joachim Schmid
Keyword(s):  
Neural Network ◽  
Process Monitoring ◽  
Laser Sintering ◽  
Powder Bed ◽  
Online Process Monitoring ◽  
Manufacturing Technologies ◽  
High Level ◽  
The Impact ◽  
Very High ◽  
Online Process

AbstractConfidence in additive manufacturing technologies is directly related to the predictability of part properties, which is influenced by several factors. To gain confidence, online process monitoring with dedicated and reliable feedback is desirable for every process. In this project, a powder bed monitoring system was developed as a retrofit solution for the EOS P3 laser sintering machines. A high-resolution camera records each layer, which is analyzed by a Region-Based Convolutional Neural Network (Mask R-CNN). Over 2500 images were annotated and classified to train the network in detecting defects in the powder bed at a very high level. Each defect is checked for intersection with exposure areas. To distinguish between acceptable imperfections and critical defects that lead to part rejection, the impact of these imperfections on part properties is investigated.

scholarly journals Application of Near-Infrared Spectroscopy Analysis Technology to Total Nucleosides Quality Control in the Fermented Cordyceps Powder Production Process

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Tiannv Shi ◽  
Yongmei Guan ◽  
Lihua Chen ◽  
Shiyu Huang ◽  
Weifeng Zhu ◽  
...  
Keyword(s):  
Quality Control ◽  
Infrared Spectroscopy ◽  
Production Process ◽  
Process Monitoring ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Powder Preparation ◽  
Spectroscopy Analysis ◽  
Online Process Monitoring ◽  
Online Process

Product quality control is a prerequisite for ensuring safety, effectiveness, and stability. However, because of the different strain species and fermentation processes, there was a significant difference in quality. As a result, they should be clearly distinguished in clinical use. Among them, the fermentation process is critical to achieving consistent product quality. This study aims to introduce near-infrared spectroscopy analysis technology into the production process of fermented Cordyceps powder, including strain culture, strain passage, strain fermentation, strain filtration, strain drying, strain pulverizing, and strain mixing. First, high performance liquid chromatography (HPLC) was used to measure the total nucleosides content in the production process of 30 batches of fermented Cordyceps powder, including uracil, uridine, adenine, guanosine, adenosine, and the process stability and interbatch consistency were analyzed with traditional Chinese medicine (TCM) fingerprinting, followed by the near-infrared spectroscopy (NIRS) combined with partial least squares regression (PLSR) to establish a quantitative analysis model of total nucleosides for online process monitoring of fermented Cordyceps powder preparation products. The model parameters indicate that the established model with good robustness and high measurement precision. It further clarifies that the model can be used for online process monitoring of fermented Cordyceps powder preparation products.

scholarly journals Online process monitoring of a batch distillation by medium field NMR spectroscopy

2021 ◽  
Author(s):  
Anne Friebel ◽  
Erik von Harbou ◽  
Kerstin Münnemann ◽  
Hans Hasse
Keyword(s):  
Process Monitoring ◽  
Binary Systems ◽  
Spectroscopic Analysis ◽  
Ternary Systems ◽  
Ethyl Formate ◽  
Batch Distillation ◽  
Non Invasive ◽  
Robust Measurements ◽  
Online Process Monitoring ◽  
Online Process

Medium field NMR spectrometers are attractive for online process monitoring. Therefore, in the present work, a single-stage laboratory batch distillation still was coupled online with a medium field NMR spectrometer. This enables quantitative non-invasive measurements without calibration. The technique was used for studying isobaric and isothermal residue curves in two ternary systems: (dimethyl sulfoxide + acetonitrile + ethyl formate) and (ethyl acetate + acetone + diethyl ether) and boiling curves and high-boiling azeotropes in two binary systems: (acetic acid + pyridine) and (methanol + diethylamine). The results of the online NMR spectroscopic analysis were compared to results from offline analysis as well as to results from thermodynamic modeling using NRTL parameters that were parametrized with literature data. The new method for online process monitoring gives reliable results and is well-suited for fast and robust measurements of residue curves.

scholarly journals A feature fusion deep-projection convolution neural network for vehicle detection in aerial images

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250782
Author(s):  
Bin Wang ◽  
Bin Xu
Keyword(s):  
Neural Network ◽  
Feature Fusion ◽  
Rapid Development ◽  
Vehicle Detection ◽  
Convolution Neural Network ◽  
Aerial Images ◽  
Semantic Features ◽  
General Object ◽  
High Level ◽  
The Impact

With the rapid development of Unmanned Aerial Vehicles, vehicle detection in aerial images plays an important role in different applications. Comparing with general object detection problems, vehicle detection in aerial images is still a challenging research topic since it is plagued by various unique factors, e.g. different camera angle, small vehicle size and complex background. In this paper, a Feature Fusion Deep-Projection Convolution Neural Network is proposed to enhance the ability to detect small vehicles in aerial images. The backbone of the proposed framework utilizes a novel residual block named stepwise res-block to explore high-level semantic features as well as conserve low-level detail features at the same time. A specially designed feature fusion module is adopted in the proposed framework to further balance the features obtained from different levels of the backbone. A deep-projection deconvolution module is used to minimize the impact of the information contamination introduced by down-sampling/up-sampling processes. The proposed framework has been evaluated by UCAS-AOD, VEDAI, and DOTA datasets. According to the evaluation results, the proposed framework outperforms other state-of-the-art vehicle detection algorithms for aerial images.

scholarly journals ANALISIS RISIKO KEKERINGAN DI KABUPATEN BANTUL PROVINSI D.I. YOGYAKARTA

2021 ◽  
Vol 18 (2) ◽  
pp. 143
Author(s):  
Annisa Mu'awanah Sukmawati ◽  
Puji Utomo
Keyword(s):  
Risk Analysis ◽  
Rural Areas ◽  
Hazard Analysis ◽  
Drought Risk ◽  
Drought Event ◽  
Quantitative Research Methods ◽  
Risk Areas ◽  
High Level ◽  
The Impact ◽  
Very High

Bantul Regency is a district in Yogyakarta Province which has geographic, geological, hydrological, and demographic characteristics that are likely to cause drought. Drought event in Bantul Regency may have significant impacts on various aspects in line with the characteristics of drought impacts which are complex and cross-sectoral. This study addresses to analyze the level of risk of drought with observation units in 75 villages in the Bantul Regency. The risk analysis was carried out by comparing the time period of the 10 years, i.e. 2008 and 2018 to observe the shift of risk areas of drought in Bantul Regency. The research was conducted using quantitative research methods with quantitative descriptive and mapping analysis. The analysis steps are drought hazard analysis, vulnerability analysis, and drought risk analysis. The analysis shows that during the last 10 years, Kabupaten Bantul has been experiencing an increasing number of villages classified as high risk of drought, both in urban and rural areas. In 2008 there were 15 villages (20%) and increased to 21 villages (28%) in 2018 that were classified as very very high level. Meanwhile, in 2008 there were 30 villages (40%) in 2008 and increased to 32 villages (42.7%) in 2018 that were classified as very high level. It caused by the increasing probability of drought as well as vulnerability. The analysis results can be used as input for stakeholders to take mitigation and anticipation actions to reduce the impact of drought based on the spatial characteristics of the risk areas.

scholarly journals Modeling the Impact of High Temperature on Mortality in Pakistan

2021 ◽  
Vol 14 (1) ◽  
pp. 332
Author(s):  
Mushtaq Ahmad Khan Barakzai ◽  
S.M. Aqil Burney
Keyword(s):  
High Temperature ◽  
Geographical Location ◽  
Maximum Temperature ◽  
Climate Data ◽  
Medium Temperature ◽  
Average Rainfall ◽  
Medium Level ◽  
High Level ◽  
The Impact ◽  
Very High

The objective of this paper is to model and study the impact of high temperature on mortality in Pakistan. For this purpose, we have used mortality and climate data consisting of maximum temperature, variation in monthly temperature, average rainfall, humidity, dewpoint, as well as average air pressure in the country over the period from 2000 to 2019. We have used the Generalized Linear Model with Quasi-Poisson link function to model the number of deaths in the country and to assess the impact of maximum temperature on mortality. We have found that the maximum temperature in the country has a significant impact on mortality. The number of deaths in Pakistan increases as the maximum temperature increases. We found that, as the maximum temperature increase beyond 30 °C, mortality increases significantly. Our results indicate that mortality increases by 27% when the maximum temperature in the country increases from medium category to a very high level. Similarly, the number of deaths in the country increases by 11% when the temperature increases from medium temperature to high level. Furthermore, our study found that when the maximum temperature in the country decreases from a medium level to a low level, the number of deaths in the country decreases by 23%. This study does not consider the impact of other factors on mortality, such as age, medical conditions, gender, geographical location, as well as variability of temperature across the country.

scholarly journals Online process monitoring of a batch distillation by medium field NMR spectroscopy

2020 ◽  
Vol 219 ◽  
pp. 115561 ◽  
Author(s):  
Anne Friebel ◽  
Erik von Harbou ◽  
Kerstin Münnemann ◽  
Hans Hasse
Keyword(s):  
Nmr Spectroscopy ◽  
Process Monitoring ◽  
Batch Distillation ◽  
Online Process Monitoring ◽  
Online Process
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