Abstract: The systematic evaluation of manufacturing
technologies with regard to the potential for product designing
constitutes a major challenge. Until now, conventional evaluation
methods primarily consider the costs of manufacturing technologies.
Thus, the potential of manufacturing technologies for achieving
additional product design features is not completely captured. To
compensate this deficit, final evaluations of new technologies are
mainly intuitive in practice. Therefore, an additional evaluation
dimension is needed which takes the potential of manufacturing
technologies for specific realizable product designs into account. In
this paper, we present the approach of an evaluation method for
selecting manufacturing technologies with regard to their potential
for product designing. This research is done within the Fraunhofer
innovation cluster »AdaM« (Adaptive Manufacturing) which targets
the development of resource efficient and adaptive manufacturing
technology processes for complex turbomachinery components.
Abstract: This article presents a new vibration diagnostic
method designed to (PM) machines with permanent magnets. Those
devices are commonly used in small wind and water systems or
vehicles drives. The author’s method is very innovative and unique.
Specific structural properties of PM machines are used in this method
- electromotive force (EMF) generated due to vibrations. There was
analysed number of publications which describe vibration diagnostic
methods and tests of electrical PM machines and there was no
method found to determine the technical condition of such machine
basing on their own signals. In this article will be discussed: the
method genesis, the similarity of machines with permanent magnet to
vibration sensor and simulation and laboratory tests results. The
method of determination the technical condition of electrical machine
with permanent magnets basing on its own signals is the subject of
patent application and it is the main thesis of author’s doctoral
dissertation.
Abstract: OEE has been used in many industries as measure of
performance. However due to limitations of original OEE, it has been
modified by various researchers. OEE for mining application is
special version of classic equation, carries these limitation over. In
this paper it has been aimed to modify the OEE for mining
application by introducing the weights to the elements of it and
termed as Mine Production index (MPi). As a special application of
new index MPishovel has been developed by authors. This can be used
for evaluating the shovel effectiveness. Based on analysis, utilization
followed by performance and availability were ranked in this order.
To check the applicability of this index, a case study was done on
four electrical and one hydraulic shovel in a Swedish mine. The
results shows that MPishovel can evaluate production effectiveness of
shovels and can determine effectiveness values in optimistic view
compared to OEE. MPi with calculation not only give the
effectiveness but also can predict which elements should be focused
for improving the productivity.
Abstract: The paper presents combined automatic speech
recognition (ASR) of English and machine translation (MT) for
English and Croatian and Croatian-English language pairs in the
domain of business correspondence. The first part presents results of
training the ASR commercial system on English data sets, enriched
by error analysis. The second part presents results of machine
translation performed by free online tool for English and Croatian
and Croatian-English language pairs. Human evaluation in terms of
usability is conducted and internal consistency calculated by
Cronbach's alpha coefficient, enriched by error analysis. Automatic
evaluation is performed by WER (Word Error Rate) and PER
(Position-independent word Error Rate) metrics, followed by
investigation of Pearson’s correlation with human evaluation.
Abstract: The use of permanent magnets (PM) is increasing in
permanent magnet synchronous machines (PMSM) to fulfill the
requirements of high efficiency machines in modern industry. PMSM
are widely used in industrial applications, wind power plants and the
automotive industry. Since PMSM are used in different
environmental conditions, the long-term effect of NdFeB-based
magnets at high temperatures and their corrosion behavior have to be
studied due to the irreversible loss of magnetic properties.
In this paper, the effect of magnetic properties due to corrosion
and increasing temperature in a climatic chamber has been presented.
The magnetic moment and magnetic field of the magnets were
studied experimentally.
Abstract: This paper presents the performance state analysis of
Self-Excited Induction Generator (SEIG) using Artificial Bee Colony
(ABC) optimization technique. The total admittance of the induction
machine is minimized to calculate the frequency and magnetizing
reactance corresponding to any rotor speed, load impedance and
excitation capacitance. The performance of SEIG is calculated using
the optimized parameter found. The results obtained by ABC
algorithm are compared with results from numerical method. The
results obtained coincide with the numerical method results. This
technique proves to be efficient in solving nonlinear constrained
optimization problems and analyzing the performance of SEIG.
Abstract: Web search engines are designed to retrieve and
extract the information in the web databases and to return dynamic
web pages. The Semantic Web is an extension of the current web in
which it includes semantic content in web pages. The main goal of
semantic web is to promote the quality of the current web by
changing its contents into machine understandable form. Therefore,
the milestone of semantic web is to have semantic level information
in the web. Nowadays, people use different keyword- based search
engines to find the relevant information they need from the web.
But many of the words are polysemous. When these words are
used to query a search engine, it displays the Search Result Records
(SRRs) with different meanings. The SRRs with similar meanings are
grouped together based on Word Sense Disambiguation (WSD). In
addition to that semantic annotation is also performed to improve the
efficiency of search result records. Semantic Annotation is the
process of adding the semantic metadata to web resources. Thus the
grouped SRRs are annotated and generate a summary which
describes the information in SRRs. But the automatic semantic
annotation is a significant challenge in the semantic web. Here
ontology and knowledge based representation are used to annotate
the web pages.
Abstract: This paper presents the voltage problem location
classification using performance of Least Squares Support Vector
Machine (LS-SVM) and Learning Vector Quantization (LVQ) in
electrical power system for proper voltage problem location
implemented by IEEE 39 bus New- England. The data was collected
from the time domain simulation by using Power System Analysis
Toolbox (PSAT). Outputs from simulation data such as voltage, phase
angle, real power and reactive power were taken as input to estimate
voltage stability at particular buses based on Power Transfer Stability
Index (PTSI).The simulation data was carried out on the IEEE 39 bus
test system by considering load bus increased on the system. To verify
of the proposed LS-SVM its performance was compared to Learning
Vector Quantization (LVQ). The results showed that LS-SVM is faster
and better as compared to LVQ. The results also demonstrated that the
LS-SVM was estimated by 0% misclassification whereas LVQ had
7.69% misclassification.
Abstract: Consumer-to-Consumer (C2C) E-commerce has been
growing at a very high speed in recent years. Since identical or
nearly-same kinds of products compete one another by relying on
keyword search in C2C E-commerce, some sellers describe their
products with spam keywords that are popular but are not related to
their products. Though such products get more chances to be retrieved
and selected by consumers than those without spam keywords,
the spam keywords mislead the consumers and waste their time.
This problem has been reported in many commercial services like
ebay and taobao, but there have been little research to solve this
problem. As a solution to this problem, this paper proposes a method
to classify whether keywords of a product are spam or not. The
proposed method assumes that a keyword for a given product is
more reliable if the keyword is observed commonly in specifications
of products which are the same or the same kind as the given
product. This is because that a hierarchical category of a product
in general determined precisely by a seller of the product and so is
the specification of the product. Since higher layers of the hierarchical
category represent more general kinds of products, a reliable degree
is differently determined according to the layers. Hence, reliable
degrees from different layers of a hierarchical category become
features for keywords and they are used together with features only
from specifications for classification of the keywords. Support Vector
Machines are adopted as a basic classifier using the features, since
it is powerful, and widely used in many classification tasks. In
the experiments, the proposed method is evaluated with a golden
standard dataset from Yi-han-wang, a Chinese C2C E-commerce,
and is compared with a baseline method that does not consider
the hierarchical category. The experimental results show that the
proposed method outperforms the baseline in F1-measure, which
proves that spam keywords are effectively identified by a hierarchical
category in C2C E-commerce.
Abstract: ‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.
Abstract: Recently GPS data is used in a lot of studies to
automatically reconstruct travel patterns for trip survey. The aim is to
minimize the use of questionnaire surveys and travel diaries so as to
reduce their negative effects. In this paper data acquired from GPS and
accelerometer embedded in smart phones is utilized to predict the
mode of transportation used by the phone carrier. For prediction,
Support Vector Machine (SVM) and Adaptive boosting (AdaBoost)
are employed. Moreover a unique method to improve the prediction
results from these algorithms is also proposed. Results suggest that the
prediction accuracy of AdaBoost after improvement is relatively better
than the rest.
Abstract: Flow forming is widely used in many industries, especially in defence technology industries. Pressure vessels requirements are high precision, light weight, seamless and optimum strength. For large pressure vessels, flow forming by 3 rollers machine were used. In case of long range rocket motor case flow forming and welding of pressure vessels have been used for manufacturing. Due to complication of welding process, researchers had developed 4 meters length pressure vessels without weldment by 4 rollers flow forming machine. Design and preparation of preform work pieces are performed. The optimization of flow forming parameter such as feed rate, spindle speed and depth of cut will be discussed. The experimental result shown relation of flow forming parameters to quality of flow formed tube and prototype pressure vessels have been made.
Abstract: This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.
Abstract: The paper gives basic information on application of
rotation bending for manufacturing ship hull parts from steel plates
and on MGPS machines, employed for this purpose.
Abstract: Analysis of EEG brainwave provides information on mental or emotional states. One of the particular states that can have various applications in human machine interface (HMI) is concentration. 8-channel EEG signals were measured and analyzed. The concentration index was compared during resting and concentrating periods. Among eight channels, locations the frontal lobe (Fp1 and Fp2) showed a clear increase of the concentration index during concentration regardless of subjects. The rest six channels produced conflicting observations depending on subjects. At this time, it is not clear whether individual difference or how to concentrate made these results for the rest six channels. Nevertheless, it is expected that Fp1 and Fp2 are promising locations for extracting control signal for HMI applications.
Abstract: In this paper, for detection of inclined eccentricity in an induction motor, time–frequency analysis of the stator startup current is carried out. For this purpose, the discrete wavelet transform is used. Data are obtained from simulations, using winding function approach. The results show the validity of the approach for detecting the fault and discriminating with respect to other faults.
Abstract: In this study, Electrical Discharge Machining (EDM) is used to modify the surface of high carbon steel En31 with the help of tool electrode (Copper-Chromium-Nickel) manufactured by powder metallurgy (PM) process. The effect of EDM on surface roughness during surface alloying is studied. Taguchi’s Design of experiment (DOE) and L18 orthogonal array is used to find the best level of input parameters in order to achieve high surface finish. Six input parameters are considered and their percentage contribution towards surface roughness is investigated by analysis of variances (ANOVA). Experimental results show that an hard alloyed surface (1.21% carbon, 2.14% chromium and 1.38% nickel) with surface roughness of 3.19µm can be generated using EDM with PM tool. Additionally, techniques like Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS) are used to analyze the machined surface and EDMed layer composition, respectively. The increase in machined surface micro-hardness (101%) may be related to the formation of carbides containing chromium.
Abstract: Time base maintenance (TBM) is conventionally applied by the power utilities to maintain circuit breakers (CBs), transformers, bus bars and cables, which may result in under maintenance or over maintenance. As information and communication technology (ICT) industry develops, the maintenance policies of many power utilities have gradually changed from TBM to condition base maintenance (CBM) to improve system operating efficiency, operation cost and power supply reliability. This paper discusses the feasibility of using intelligent electronic devices (IEDs) to construct a CB CBM management platform. CBs in power substations can be monitored using IEDs with additional logic configuration and wire connections. The CB monitoring data can be sent through intranet to a control center and be analyzed and integrated by the Elipse Power Studio software. Finally, a human-machine interface (HMI) of supervisory control and data acquisition (SCADA) system can be designed to construct a CBM management platform to provide maintenance decision information for the maintenance personnel, management personnel and CB manufacturers.
Abstract: This paper is concerned with minimization of mean
tardiness and flow time in a real single machine production
scheduling problem. Two variants of genetic algorithm as metaheuristic
are combined with hyper-heuristic approach are proposed to
solve this problem. These methods are used to solve instances
generated with real world data from a company. Encouraging results
are reported.
Abstract: Cloud virtualization technologies are becoming more
and more prevalent, cloud users usually encounter the problem of how
to access to the virtualized remote desktops easily over the web
without requiring the installation of special clients. To resolve this
issue, we took advantage of the HTML5 technology and developed
web-based remote desktop. It permits users to access the terminal
which running in our cloud platform from anywhere. We implemented
a sketch of web interface following the cloud computing concept that
seeks to enable collaboration and communication among users for
high performance computing. Given the development of remote
desktop virtualization, it allows to shift the user’s desktop from the
traditional PC environment to the cloud platform, which is stored on a
remote virtual machine rather than locally. This proposed effort has
the potential to positively provide an efficient, resilience and elastic
environment for online cloud service. This is also made possible by the
low administrative costs as well as relatively inexpensive end-user
terminals and reduced energy expenses.