Online Multi-Channel Forging Tonnage Monitoring and Fault Pattern Discrimination Using Principal Curve

2004 ◽  
Author(s):  
Jihyun Kim ◽  
Qiang Huang ◽  
Jianjun Shi ◽  
Tzyy-Shuh Chang
Keyword(s):  
Process Monitoring ◽  
Process Condition ◽  
Pattern Discrimination ◽  
Process Conditions ◽  
Late Response ◽  
Principal Curve ◽  
Whole Process ◽  
Online Process Monitoring ◽  
Real Time Information ◽  
Forging Press

Due to late response to process condition changes, forging processes are normally exposed to large number of defective products. To achieve online process monitoring, multi-channel tonnage signals are often collected from the forging press. The tonnage signals contain significant amount of real time information regarding the product and the process conditions. In this paper, a methodology is developed to detect profile changes of multi-channel tonnage signals for forging process monitoring and to classify fault patterns. The changes include global or local profile deviations, which correspond to deviations of a whole process cycle or process segment(s) within a cycle respectively. Principal curve method is used to conduct feature extraction and discrimination of tonnage signals. The developed methodology is demonstrated with industry data from a crankshaft forging processes.

Online Multichannel Forging Tonnage Monitoring and Fault Pattern Discrimination Using Principal Curve

2005 ◽  
Vol 128 (4) ◽  
pp. 944-950 ◽  
Author(s):  
Jihyun Kim ◽  
Qiang Huang ◽  
Jianjun Shi ◽  
Tzyy-Shuh Chang
Keyword(s):  
Process Monitoring ◽  
Process Condition ◽  
Pattern Discrimination ◽  
Process Conditions ◽  
Late Response ◽  
Principal Curve ◽  
Whole Process ◽  
Online Process Monitoring ◽  
Real Time Information ◽  
Forging Press

Due to the late response to process condition changes, forging processes are normally exposed to a large number of defective products. To achieve online process monitoring, multichannel tonnage signals are often collected from the forging press. The tonnage signals contain significant amount of real time information regarding the product and the process conditions. In this paper, a methodology is developed to detect profile changes of multichannel tonnage signals for forging process monitoring and to classify fault patterns. The changes include global or local profile deviations, which correspond to deviations of a whole process cycle or process segment(s) within a cycle, respectively. The principal curve method is used to conduct feature extraction and discrimination of tonnage signals. The developed methodology is demonstrated with industry data from a crankshaft forging processes.

scholarly journals Indicative Marker Microbiome Structures Deduced from the Taxonomic Inventory of 67 Full-Scale Anaerobic Digesters of 49 Agricultural Biogas Plants

2021 ◽  
Vol 9 (7) ◽  
pp. 1457
Author(s):  
Julia Hassa ◽  
Johanna Klang ◽  
Dirk Benndorf ◽  
Marcel Pohl ◽  
Benedikt Hülsemann ◽  
...  
Keyword(s):  
Stable Process ◽  
Process Condition ◽  
Full Scale ◽  
Process Models ◽  
Process Efficiency ◽  
Process Conditions ◽  
Rrna Gene ◽  
General Process ◽  
Specific Distribution ◽  
Biogas Plants

There are almost 9500 biogas plants in Germany, which are predominantly operated with energy crops and residues from livestock husbandry over the last two decades. In the future, biogas plants must be enabled to use a much broader range of input materials in a flexible and demand-oriented manner. Hence, the microbial communities will be exposed to frequently varying process conditions, while an overall stable process must be ensured. To accompany this transition, there is the need to better understand how biogas microbiomes respond to management measures and how these responses affect the process efficiency. Therefore, 67 microbiomes originating from 49 agricultural, full-scale biogas plants were taxonomically investigated by 16S rRNA gene amplicon sequencing. These microbiomes were separated into three distinct clusters and one group of outliers, which are characterized by a specific distribution of 253 indicative taxa and their relative abundances. These indicative taxa seem to be adapted to specific process conditions which result from a different biogas plant operation. Based on these results, it seems to be possible to deduce/assess the general process condition of a biogas digester based solely on the microbiome structure, in particular on the distribution of specific indicative taxa, and without knowing the corresponding operational and chemical process parameters. Perspectively, this could allow the development of detection systems and advanced process models considering the microbial diversity.

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.

Heat Transfer and Crystallization Modeling during Compression Molding of Thermoplastic Composite Parts

2015 ◽  
Vol 651-653 ◽  
pp. 1507-1512 ◽  
Author(s):  
Jalal Faraj ◽  
Baptiste Pignon ◽  
Jean Luc Bailleul ◽  
Nicolas Boyard ◽  
Didier Delaunay ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Physical Properties ◽  
Volume Fraction ◽  
Thermoplastic Composite ◽  
Large Temperature ◽  
Process Conditions ◽  
Thermoplastic Resin ◽  
Whole Process ◽  
Low Viscosity ◽  
Thermo Physical Properties

We present in this paper, the coupling of heat transfer to the crystallization of composite in a closed mold. The composite is based on thermoplastic resin (low viscosity PA 66) with glass fiber (50% volume fraction). In order to realize this coupling, an accurate characterizationof thermo physical properties in process conditions, especially in the molten and solid state is needed. In addition, theidentification of the parameters of crystallization kinetics is required. Therefore, we present the methods that were used to study the thermo physical properties as the thermal conductivity, heat capacity and the specific volume. Moreover, the kinetic of crystallization was estimated over a large temperature range by using Flash DSC and classical DSC. In order to validate the measurements, the whole process was modeled by finite elements. The model includes the resolution of the strong coupling between the heat transfer and crystallization. Finally, the experimental and numerical results were compared.

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.

Effect of carburizing and annealing processes in improving the Ni/WC–Co adhesion strength

2017 ◽  
Vol 232 (3) ◽  
pp. 338-348 ◽  
Author(s):  
AW Hassan ◽  
MY Noordin ◽  
S Izman ◽  
K Denni
Keyword(s):  
Heat Treatment ◽  
Adhesion Strength ◽  
Positive Impact ◽  
Process Condition ◽  
Scratch Test ◽  
Process Conditions ◽  
X Ray ◽  
Treatment Processes ◽  
Before And After ◽  
Field Emission Electron Microscopy

Heat treatment processes have a positive impact in improving the adhesion strength of different interlayer/substrate materials. However, information regarding the effect of these processes in enhancing the adhesion strength of an electroplated nickel interlayer on tungsten carbide substrate for diamond deposition is lacking. In this study, the effect of carburizing and annealing process conditions in enhancing the adhesion strength of the electroplated nickel interlayer was investigated. The heat treatment processes were designed and modeled by the design of experiments technique. The heat-treated specimens were characterized by the field-emission electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction techniques. The adhesion of the interlayer before and after the heat treatment was assessed by the scratch test. The results show that the adhesion of the electroplated nickel interlayer was remarkably improved by both processes. The mathematical models for predicting the adhesion strength of the carburized and annealed nickel interlayer within the specified ranges were developed. The maximum adhesion strength of 30 N was obtained from the nickel interlayer annealed at the highest process condition of temperature and time.

Ultrasonic Nondestructive Testing for In-Line Monitoring of Wire-Arc Additive Manufacturing (WAAM)

2020 ◽  
Author(s):  
Md Shahjahan Hossain ◽  
Hossein Taheri ◽  
Niraj Pudasaini ◽  
Alexander Reichenbach ◽  
Bishal Silwal
Keyword(s):  
Quality Assurance ◽  
Additive Manufacturing ◽  
Nondestructive Testing ◽  
Large Scale ◽  
Gas Flow ◽  
Complex Structure ◽  
Process Condition ◽  
Process Conditions ◽  
Ultrasonic Signals ◽  
Wire Arc Additive Manufacturing

Abstract The applications for metal additive manufacturing (AM) are expanding. Powder-bed, powder-fed, and wire-fed AM are the different kinds of AM technologies based on the feeding material. Wire-Arc AM (WAAM) is a wire-fed technique that has the potential to fabricate large-scale three-dimensional objects. In WAAM, a metallic wire is continuously fed to the deposition location and is melted by an arc-welding power source. As the applications for WAAM expands, the quality assurance of the parts becomes a major concern. Nondestructive testing (NDT) of AM parts is necessary for quality assurance and inspection of these materials. The conventional method of inspection is to perform testing on the finished parts. There are several limitations encountered when using conventional methods of NDT for as-built AM parts due to surface conditions and complex structure. In-situ process monitoring based on the ultrasound technology is proposed for WAAM material inspection during the manufacturing process. Ultrasonic inline monitoring techniques have the advantages of providing valuable information about the process and parts quality. Ultrasonic technique was used to detect the process condition deviations from the normal. A fixture developed by the authors holds an ultrasonic sensor under the build platform and aligned with the center of the base plate. Ultrasonic signals were measured for different process conditions by varying the current and gas flow rate. Features (indicators) from the radio frequency (RF) signal were used to evaluate the difference in signal clusters to identify and classify different build conditions. Results show that the indicator values of the ultrasonic signals in the region of interest (ROI) changes with different process conditions and can be used to classify them.

Process Monitoring during Normal Operations at Canadian Nuclear Power Plants

2000 ◽  
Vol 44 (22) ◽  
pp. 811-814 ◽  
Author(s):  
Eric Davey
Keyword(s):  
Process Monitoring ◽  
Observational Studies ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Process Conditions ◽  
Control Room ◽  
Monitoring Process ◽  
Underlying Basis ◽  
Generic Strategy

This paper summarizes the findings from several observational studies to characterize the basis for a process monitoring strategy used by operators in ‘normal’ operations at CANDU nuclear power plants. These studies were undertaken in support of projects to develop improved control room displays and information systems to better support operators in both normal and abnormal operating situations. With the assistance of operators from several plants, an underlying basis for process monitoring was defined and a ‘generic’ strategy for monitoring process conditions in ‘normal’ operations has been established.

Automated Monitoring of Manufacturing Processes, Part 1: Monitoring Methods

1995 ◽  
Vol 117 (2) ◽  
pp. 121-132 ◽  
Author(s):  
R. Du ◽  
M. A. Elbestawi ◽  
S. M. Wu
Keyword(s):  
Spectral Analysis ◽  
System Modeling ◽  
Process Condition ◽  
Process Conditions ◽  
Manufacturing Processes ◽  
Monitoring Methods ◽  
Time Frequency ◽  
Automated Monitoring ◽  
Two Phases ◽  
Analysis System

This paper presents a systematic study of various monitoring methods suitable for automated monitoring of manufacturing processes. In general, monitoring is composed of two phases: learning and classification. In the learning phase, the key issue is to establish the relationship between monitoring indices (selected signature features) and the process conditions. Based on this relationship and the current sensor signals, the process condition is then estimated in the classification phase. The monitoring methods discussed in this paper include pattern recognition, fuzzy systems, decision trees, expert systems and neural networks. A brief review of signal processing techniques commonly used in monitoring, such as statistical analysis, spectral analysis, system modeling, bi-spectral analysis and time-frequency distribution, is also included.

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