Abstract: The manufacture of large-scale precision aerospace
components using CNC requires a highly effective maintenance
strategy to ensure that the required accuracy can be achieved over
many hours of production. This paper reviews a strategy for a
maintenance management system based on Failure Mode Avoidance,
which uses advanced techniques and technologies to underpin a
predictive maintenance strategy. It is shown how condition
monitoring (CM) is important to predict potential failures in high
precision machining facilities and achieve intelligent and integrated
maintenance management. There are two distinct ways in which CM
can be applied. One is to monitor key process parameters and
observe trends which may indicate a gradual deterioration of
accuracy in the product. The other is the use of CM techniques to
monitor high status machine parameters enables trends to be
observed which can be corrected before machine failure and
downtime occurs.
It is concluded that the key to developing a flexible and intelligent
maintenance framework in any precision manufacturing operation is
the ability to evaluate reliably and routinely machine tool condition
using condition monitoring techniques within a framework of Failure
Mode Avoidance.
Abstract: The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters.
Abstract: The scale, complexity and worldwide geographical
spread of the LHC computing and data analysis problems are
unprecedented in scientific research. The complexity of processing
and accessing this data is increased substantially by the size and
global span of the major experiments, combined with the limited
wide area network bandwidth available. We present the latest
generation of the MONARC (MOdels of Networked Analysis at
Regional Centers) simulation framework, as a design and modeling
tool for large scale distributed systems applied to HEP experiments.
We present simulation experiments designed to evaluate the
capabilities of the current real-world distributed infrastructure to
support existing physics analysis processes and the means by which
the experiments bands together to meet the technical challenges
posed by the storage, access and computing requirements of LHC
data analysis within the CMS experiment.
Abstract: Education supported by mobile computers has been widely done for some time. Teachers have attempted to use mobile computers and to find concrete subjects for student-s fieldwork training in college education. The purpose of this research is to develop software for Personal Digital Assistant (PDA) to conduct fieldwork in our campus, and to report a fieldwork class using PDAs in the curriculum of the Department of Regional Environment Studies.
Abstract: Some quality control tools use non metric subjective information coming from experts, who qualify the intensity of relations existing inside processes, but without quantifying them. In this paper we have developed a quality control analytic tool, measuring the impact or strength of the relationship between process operations and product characteristics. The tool includes two models: a qualitative model, allowing relationships description and analysis; and a formal quantitative model, by means of which relationship quantification is achieved. In the first one, concepts from the Graphs Theory were applied to identify those process elements which can be sources of variation, that is, those quality characteristics or operations that have some sort of prelacy over the others and that should become control items. Also the most dependent elements can be identified, that is those elements receiving the effects of elements identified as variation sources. If controls are focused in those dependent elements, efficiency of control is compromised by the fact that we are controlling effects, not causes. The second model applied adapts the multivariate statistical technique of Covariance Structural Analysis. This approach allowed us to quantify the relationships. The computer package LISREL was used to obtain statistics and to validate the model.
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: Optical 3D measurement of objects is meaningful in
numerous industrial applications. In various cases shape acquisition
of weak textured objects is essential. Examples are repetition parts
made of plastic or ceramic such as housing parts or ceramic bottles as
well as agricultural products like tubers. These parts are often
conveyed in a wobbling way during the automated optical inspection.
Thus, conventional 3D shape acquisition methods like laser scanning
might fail. In this paper, a novel approach for acquiring 3D shape of
weak textured and moving objects is presented. To facilitate such
measurements an active stereo vision system with structured light is
proposed. The system consists of multiple camera pairs and auxiliary
laser pattern generators. It performs the shape acquisition within one
shot and is beneficial for rapid inspection tasks. An experimental
setup including hardware and software has been developed and
implemented.
Abstract: Wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When fewer base stations (BSs) may be available for location purposes or the measurements with large errors in non-line-of-sight (NLOS) environments, it is necessary to integrate all available heterogeneous measurements to achieve high location accuracy. This paper illustrates a hybrid proposed schemes that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to give a location estimate of the MS. The proposed schemes mitigate the NLOS effect simply by the weighted sum of the intersections between three TOA circles and the AOA line without requiring a priori information about the NLOS error. Simulation results show that the proposed methods can achieve better accuracy when compare with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).
Abstract: The elimimation of mefenamic acid has been carried
out by photolysis, ozonation, adsorption onto activated carbon (AC)
and combinations of the previous single systems (O3+AC and
O3+UV). The results obtained indicate that mefenamic acid is not
photo-reactive, showing a relatively low quantum yield of the order
of 6 x 10-4 mol Einstein-1. Application of ozone to mefenamic
aqueous solutions instantaneously eliminates the pharmaceutical,
achieving simultaneously a 40% of mineralization. Addition of AC to
the ozonation process does not enhance the process, moreover,
mineralization is completely inhibited if compared to results obtained
by single ozonation. The combination of ozone and UV radiation led
to the best results in terms of mineralization (60% after 120 min).
Abstract: To minimize power losses, it is important to
determine the location and size of local generators to be placed in
unbalanced power distribution systems. On account of some inherent
features of unbalanced distribution systems, such as radial structure,
large number of nodes, a wide range of X/R ratios, the conventional
techniques developed for the transmission systems generally fail on
the determination of optimum size and location of distributed
generators (DGs). This paper presents a simple method for
investigating the problem of contemporaneously choosing best
location and size of DG in three-phase unbalanced radial distribution
system (URDS) for power loss minimization and to improve the
voltage profile of the system. Best location of the DG is determined
by using voltage index analysis and size of DG is computed by
variational technique algorithm according to available standard size
of DGs. This paper presents the results of simulations for 25-bus and
IEEE 37- bus Unbalanced Radial Distribution system.
Abstract: A novel direction-of-arrival (DOA) estimation technique, which uses a conventional multiple signal classification (MUSIC) algorithm with periodic signals, is applied to a single RF-port parasitic array antenna for direction finding. Simulation results show that the proposed method gives high resolution (1 degree) DOA estimation in an uncorrelated signal environment. The novelty lies in that the MUSIC algorithm is applied to a simplified antenna configuration. Only one RF port and one analogue-to-digital converter (ADC) are used in this antenna, which features low DC power consumption, low cost, and ease of fabrication. Modifications to the conventional MUSIC algorithm do not bring much additional complexity. The proposed technique is also free from the negative influence by the mutual coupling between elements. Therefore, the technique has great potential to be implemented into the existing wireless mobile communications systems, especially at the power consumption limited mobile terminals, to provide additional position location (PL) services.
Abstract: Academia-industry relationship is not like that of
technology donator-acceptor, but is of interactive and collaborative
nature, acknowledging and ensuring mutual respect for each other-s
role and contributions with an eye to attaining the true purpose of
such relationships, namely, bringing about research-outcome
synergy. Indeed, academia-industry interactions are a system that
requires active and collaborative participations of all the
stakeholders.
This paper examines various issues associated with academic
institutions and industry collaboration with special attention to the
nature of resources and potentialities of stakeholders in the context of
knowledge management. This paper also explores the barriers of
academia-industry interaction. It identifies potential areas where
industry-s participation with academia would be most effective for
synergism. Lastly, this paper proposes an integrated model of several
new collaborative approaches that are possible, mainly in the Indian
scenario to strengthen academia-industry interface.
Abstract: The successful implementation of Service-Oriented Architecture (SOA) is not confined to Information Technology systems and required changes of the whole enterprise. In order to adapt IT and business, the enterprise requires adequate and measurable methods. The adoption of SOA creates new problem with regard to measuring and analysis the performance. In fact the enterprise should investigate to what extent the development of services will increase the value of business. It is required for every business to measure the extent of SOA adaptation with the goals of enterprise. Moreover, precise performance metrics and their combination with the advanced evaluation methodologies as a solution should be defined. The aim of this paper is to present a systematic methodology for designing a measurement system at the technical and business levels, so that: (1) it will determine measurement metrics precisely (2) the results will be analysed by mapping identified metrics to the measurement tools.
Abstract: Shape memory alloy (SMA) actuators have found a
wide range of applications due to their unique properties such as high
force, small size, lightweight and silent operation. This paper presents
the development of compact (SMA) actuator and cooling system in
one unit. This actuator is developed for multi-fingered hand. It
consists of nickel-titanium (Nitinol) SMA wires in compact forming.
The new arrangement insulates SMA wires from the human body by
housing it in a heat sink and uses a thermoelectric device for rejecting
heat to improve the actuator performance. The study uses
optimization methods for selecting the SMA wires geometrical
parameters and the material of a heat sink. The experimental work
implements the actuator prototype and measures its response.
Abstract: This study is concerned with the investigation of the
suitability of several empirical and semi-empirical drying models
available in the literature to define drying behavior of viscose yarn
bobbins. For this purpose, firstly, experimental drying behaviour of
viscose bobbins was determined on an experimental dryer setup
which was designed and manufactured based on hot-air bobbin
dryers used in textile industry. Afterwards, drying models considered
were fitted to the experimentally obtained moisture ratios. Drying
parameters were drying temperature and bobbin diameter. The fit
was performed by selecting the values for constants in the models in
such a way that these values make the sum of the squared differences
between the experimental and the model results for moisture ratio
minimum. Suitability of fitting was specified as comparing the
correlation coefficient, standard error and mean square deviation.
The results show that the most appropriate model in describing the
drying curves of viscose bobbins is the Page model.
Abstract: This paper observed the interhemispheric conjugate
auroral activity occurred on 21 September 2009. The GPS derived
ionospheric total electron content (TEC) during a weak substorm
interval recorded at interhemispheric conjugate points at Husafell in
Iceland and Syowa in Antarctica is investigated to look at their
signatures on the auroral features. Selection of all-sky camera (ASC)
images and keogram at Tjörnes and Syowa during the interval
00:47:54 – 00:50:14 UT on 21 September 2009 found that the auroral
activity had exerted their influence on the GPS TEC as a
consequence of varying interplanetary magnetic field (IMF) By
polarity.
Abstract: Spare parts inventory management is one of the major
areas of inventory research. Analysis of recent literature showed that
an approach integrating spare parts classification, demand
forecasting, and stock control policies is essential; however, adapting
this integrated approach is limited. This work presents an integrated
framework for spare part inventory management and an Excel based
application developed for the implementation of the proposed
framework. A multi-criteria analysis has been used for spare
classification. Forecasting of spare parts- intermittent demand has
been incorporated into the application using three different
forecasting models; namely, normal distribution, exponential
smoothing, and Croston method. The application is also capable of
running with different inventory control policies. To illustrate the
performance of the proposed framework and the developed
application; the framework is applied to different items at a service
organization. The results achieved are presented and possible areas
for future work are highlighted.
Abstract: A new, rapidly convergent, numerical procedure for
internal loading distribution computation in statically loaded, singlerow,
angular-contact ball bearings, subjected to a known combined
radial and thrust load, which must be applied so that to avoid tilting
between inner and outer rings, is used to find the load distribution
differences between a loaded unfitted bearing at room temperature,
and the same loaded bearing with interference fits that might
experience radial temperature gradients between inner and outer
rings. For each step of the procedure it is required the iterative
solution of Z + 2 simultaneous nonlinear equations – where Z is the
number of the balls – to yield exact solution for axial and radial
deflections, and contact angles.
Abstract: The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.
Abstract: Support vector regression (SVR) has been regarded
as a state-of-the-art method for approximation and regression. The
importance of kernel function, which is so-called admissible support
vector kernel (SV kernel) in SVR, has motivated many studies
on its composition. The Gaussian kernel (RBF) is regarded as a
“best" choice of SV kernel used by non-expert in SVR, whereas
there is no evidence, except for its superior performance on some
practical applications, to prove the statement. Its well-known that
reproducing kernel (R.K) is also a SV kernel which possesses many
important properties, e.g. positive definiteness, reproducing property
and composing complex R.K by simpler ones. However, there are a
limited number of R.Ks with explicit forms and consequently few
quantitative comparison studies in practice. In this paper, two R.Ks,
i.e. SV kernels, composed by the sum and product of a translation
invariant kernel in a Sobolev space are proposed. An exploratory
study on the performance of SVR based general R.K is presented
through a systematic comparison to that of RBF using multiple
criteria and synthetic problems. The results show that the R.K is
an equivalent or even better SV kernel than RBF for the problems
with more input variables (more than 5, especially more than 10) and
higher nonlinearity.