Abstract: Hand gesture is one of the typical methods used in
sign language for non-verbal communication. It is most commonly
used by people who have hearing or speech problems to
communicate among themselves or with normal people. Various sign
language systems have been developed by manufacturers around the
globe but they are neither flexible nor cost-effective for the end
users. This paper presents a system prototype that is able to
automatically recognize sign language to help normal people to
communicate more effectively with the hearing or speech impaired
people. The Sign to Voice system prototype, S2V, was developed
using Feed Forward Neural Network for two-sequence signs
detection. Different sets of universal hand gestures were captured
from video camera and utilized to train the neural network for
classification purpose. The experimental results have shown that
neural network has achieved satisfactory result for sign-to-voice
translation.
Abstract: Inconel 718, a nickel based super-alloy is an
extensively used alloy, accounting for about 50% by weight of
materials used in an aerospace engine, mainly in the gas turbine
compartment. This is owing to their outstanding strength and
oxidation resistance at elevated temperatures in excess of 5500 C.
Machining is a requisite operation in the aircraft industries for the
manufacture of the components especially for gas turbines. This
paper is concerned with optimization of the surface roughness when
turning Inconel 718 with cermet inserts. Optimization of turning
operation is very useful to reduce cost and time for machining. The
approach is based on Response Surface Method (RSM). In this work,
second-order quadratic models are developed for surface roughness,
considering the cutting speed, feed rate and depth of cut as the cutting
parameters, using central composite design. The developed models
are used to determine the optimum machining parameters. These
optimized machining parameters are validated experimentally, and it
is observed that the response values are in reasonable agreement with
the predicted values.
Abstract: The effect of artificial pozzolan (waste brick) on the
physico-chemical properties of cement manufactured was
investigated. The waste brick is generated by the manufacture of
bricks. It was used in the proportions of 0%, 5%, 10%, 15% and 20%
by mass of cement to study its effect on the physico-chemical
properties of cement incorporating artificial pozzolan. The physicochemical
properties of cement at anhydrous state and the hydrated
state (chemical composition, specific weight, fineness, consistency of
the cement paste and setting times) were studied. The experimental
results obtained show that the quantity of pozzolanic admixture
(waste brick) of cement manufactured is the principal parameter who
influences on the variation of the physico-chemical properties of the
cement tested.
Abstract: Due to the fast development of technology, the
competition of technological products is turbulent; therefore, it is
important to understand the market trend, consumers- demand and
preferences. As the smartphones are prevalent, the main purpose of
this paper is to utilize Analytic Hierarchy Process (AHP) to analyze
consumer-s purchase evaluation factors of smartphones. Through the
AHP expert questionnaire, the smartphones- main functions are
classified as “user interface", “mobile commerce functions",
“hardware and software specifications", “entertainment functions" and
“appearance and design", five aspects to analyze the weights. Then
four evaluation criteria are evaluated under each aspect to rank the
weights. Based on an analysis of data shows that consumers consider
when purchase factors are “hardware and software specifications",
“user interface", “appearance and design", “mobile commerce
functions" and “entertainment functions" in sequence. The “hardware
and software specifications" aspect obtains the weight of 33.18%; it is
the most important factor that consumers are taken into account. In
addition, the most important evaluation criteria are central processing
unit, operating system, touch screen, and battery function in sequence.
The results of the study can be adopted as reference data for mobile
phone manufacturers in the future on the design and marketing
strategy to satisfy the voice of customer.
Abstract: Today, the central role of industrial robots in automation in general and in material handling in particular is crystal clear. Based on the current status of Photovoltaics and by focusing on lightweight material handling, PV industry has turned into a potential candidate for introducing a fresh “pick and place" robot technology. Thus, to examine the industry needs in this regard, firstly the best suited applications for such robotic automation,and then the essential prerequisites in PV industry should be identified. The objective of this paper is to present holistic views on the industry trends, general automation status and existing challenges facing lightweight robotic material handling in PV Silicon Wafer and Thin Film technologies. The results of this study show that currently no uniform pick and place solution prevails among PV Silicon Wafer manufacturers and the industry calls for a new robot solution to satisfy its needs in new directions.
Abstract: Westudy a dual-channel supply chain under
decentralized setting in which manufacturer sells to retailer and to
customers directly usingan online channel. A customer chooses the
purchase-channel based on price and service quality. Also, to buy
product from the retail store, the customer incurs a transportation cost
influenced by the fluctuating gasoline cost. Both companies are under
the revenue sharing contract. In this contract the retailer share a
portion of the revenue to the manufacturer while the manufacturer
will charge the lower wholesales price. The numerical result shows
that the effects of gasoline costs, the revenue sharing ratio and the
wholesale price play an important role in determining optimal prices.
The result shows that when the gasoline price fluctuatesthe optimal
on-line priceis relatively stable while the optimal retail price moves
in the opposite direction of the gasoline prices.
Abstract: It can be said that the business sector is faced with a range of challenges–a rapidly changing business environment, an increase and diversification of customers- demands and the consequent need for quick response–for having in place flexible management and production info systems. As a matter of fact, many manufacturers have adopted production info management systems such as MES and ERP. Nevertheless, managers are having difficulties obtaining ever-changing production process information in real time, or responding quickly to any change in production related needs on the basis of such information. This is because they rely on poor production info systems which are not capable of providing real-time factory settings. If the manufacturer doesn-t have a capacity for collecting or digitalizing the 4 Ms (Man, Machine, Material, Method), which are resources for production, on a real time basis, it might to difficult to effectively maintain the information on production process. In this regard, this paper will introduce some new alternatives to the existing methods of collecting the 4 Ms in real time, which are currently comprise the production field.
Abstract: this article proposed a methodology for computer
numerical control (CNC) machine scoring. The case study company
is a manufacturer of hard disk drive parts in Thailand. In this
company, sample of parts manufactured from CNC machine are
usually taken randomly for quality inspection. These inspection data
were used to make a decision to shut down the machine if it has
tendency to produce parts that are out of specification. Large amount
of data are produced in this process and data mining could be very
useful technique in analyzing them. In this research, data mining
techniques were used to construct a machine scoring model called
'machine priority assessment model (MPAM)'. This model helps to
ensure that the machine with higher risk of producing defective parts
be inspected before those with lower risk. If the defective prone
machine is identified sooner, defective part and rework could be
reduced hence improving the overall productivity. The results
showed that the proposed method can be successfully implemented
and approximately 351,000 baht of opportunity cost could have
saved in the case study company.
Abstract: Product Lead Time (PLT) is the period of time from
receiving a customer's order to delivering the final product. PLT is an
indicator of the manufacturing controllability, efficiency and
performance. Due to the explosion in the rate of technological
innovations and the rapid changes in the nature of manufacturing
processes, manufacturing firms can bring the new products to market
quicker only if they can reduce their PLT and speed up the rate at
which they can design, plan, control, and manufacture. Although
there is a substantial body of research on manufacturing relating to
cost and quality issues, there is no much specific research conducted
in relation to the formulation of PLT, despite its significance and
importance. This paper analyzes and formulates PLT which can be
used as a guideline for achieving the shorter PLT. Further more this
paper identifies the causes of delay and factors that contributes to the
increased product lead-time.
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: 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: 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 focuses on developing an integrated
reliable and sophisticated model for ultra large wind turbines And to
study the performance and analysis of vector control on large wind
turbines. With the advance of power electronics technology, direct
driven multi-pole radial flux PMSG (Permanent Magnet Synchronous
Generator) has proven to be a good choice for wind turbines
manufacturers. To study the wind energy conversion systems, it is
important to develop a wind turbine simulator that is able to produce
realistic and validated conditions that occur in real ultra MW wind
turbines. Three different packages are used to simulate this model,
namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind
simulator developed by National Renewable Energy Laboratory
(NREL). The wind turbine mechanical parts are modeled by FAST
(Fatigue, Aerodynamics, Structures and Turbulence) code which is
also developed by NREL. Simulink is used to model the PMSG, full
scale back to back IGBT converters, and the grid.
Abstract: Tensile armour wires provide a flexible pipe's
resistance to longitudinal stresses. Flexible pipe manufacturers need
to know the effect of defects such as scratches and cracks, with
dimensions less than 0.2mm which is the limit of the current nondestructive
detection technology, on the fracture stress and fracture
strain of the wire for quality assurance purposes. Recent research
involving the determination of the fracture strength of cracked wires
employed laboratory testing and classical fracture mechanics
approach using non-standardised fracture mechanics specimens
because standard test specimens could not be manufactured from the
wires owing to their sizes. In this work, the effect of miniature
cracks on the fracture properties of tensile armour wires was
investigated using laboratory and finite element tensile testing
simulations with the phenomenological shear fracture model. The
investigation revealed that the presence of cracks shallower than
0.2mm is worse on the fracture strain of the wire.
Abstract: Due to the high percentage of induction motors in industrial market, there exist a large opportunity for energy savings. Replacement of working induction motors with more efficient ones can be an important resource for energy savings. A calculation of energy savings and payback periods, as a result of such a replacement, based on nameplate motor efficiency or manufacture-s data can lead to large errors [1]. Efficiency of induction motors (IMs) can be extracted using some procedures that use the no-load test results. In the cases that we must estimate the efficiency on-line, some of these procedures can-t be efficient. In some cases the efficiency estimates using the rating values of the motor, but these procedures can have errors due to the different working condition of the motor. In this paper the efficiency of an IM estimated by using the genetic algorithm. The results are compared with the measured values of the torque and power. The results show smaller errors for this procedure compared with the conventional classical procedures, hence the cost of the equipments is reduced and on-line estimation of the efficiency can be made.
Abstract: In this paper we present discretization and decomposition methods for a multi-component transport model of a chemical vapor deposition (CVD) process. CVD processes are used to manufacture deposition layers or bulk materials. In our transport model we simulate the deposition of thin layers. The microscopic model is based on the heavy particles, which are derived by approximately solving a linearized multicomponent Boltzmann equation. For the drift-process of the particles we propose diffusionreaction equations as well as for the effects of heat conduction. We concentrate on solving the diffusion-reaction equation with analytical and numerical methods. For the chemical processes, modelled with reaction equations, we propose decomposition methods and decouple the multi-component models to simpler systems of differential equations. In the numerical experiments we present the computational results of our proposed models.
Abstract: Malaysian corporations going global increased
many folds. The shift from domestic to international operations
requires increased expatriation to achieve global business goals.
Therefore, this study aims to identify the determinants for success
in expatriation of Malaysian international corporations. There are
certain attributes necessary for a global employee to succeed in
international assignment. Self-administered questionnaires were
sent to 327 respondents with a response rate of 35.2 percent. The
results indicated that most Malaysian manufacturers are involved
in expatriation. For a global employee to succeed in an
international assignment, the ability to work in international teams
was identified and ranked as the most important factor in
determining the effectiveness of expatriation followed by language
proficiency, adaptability to the international assignment and
expatriate sensitivity to cultural elements. The results support
previous research with regard to the importance of an effective
expatriation selection process in order for a company-s
international expansion strategy to succeed.
Abstract: The inherent complexity in nowadays- business
environments is forcing organizations to be attentive to the dynamics
in several fronts. Therefore, the management of technological
innovation is continually faced with uncertainty about the future.
These issues lead to a need for a systemic perspective, able to analyze
the consequences of interactions between different factors. The field
of technology foresight has proposed methods and tools to deal with
this broader perspective. In an attempt to provide a method to analyze
the complex interactions between events in several areas, departing
from the identification of the most strategic competencies, this paper
presents a methodology based on the Delphi method and Quality
Function Deployment. This methodology is applied in a sheet metal
processing equipment manufacturer, as a case study.
Abstract: Since the 1990s the American furniture industry faces a transition period. Manufacturers, one of its most important actors made its entrance into the retail industry. This shift has had deep consequences not only for the American furniture industry as a whole, but also for other international furniture industries, especially the Chinese. The present work aims to analyze this actor based on the distinction provided by the Global Commodity Chain Theory. It stresses its characteristics, structure, operational way and importance for both the U.S. and the Chinese furniture industries.
Abstract: Electronics Products that achieve high levels of integrated communications, computing and entertainment, multimedia features in small, stylish and robust new form factors are winning in the market place. Due to the high costs that an industry may undergo and how a high yield is directly proportional to high profits, IC (Integrated Circuit) manufacturers struggle to maximize yield, but today-s customers demand miniaturization, low costs, high performance and excellent reliability making the yield maximization a never ending research of an enhanced assembly process. With factors such as minimum tolerances, tighter parameter variations a systematic approach is needed in order to predict the assembly process. In order to evaluate the quality of upcoming circuits, yield models are used which not only predict manufacturing costs but also provide vital information in order to ease the process of correction when the yields fall below expectations. For an IC manufacturer to obtain higher assembly yields all factors such as boards, placement, components, the material from which the components are made of and processes must be taken into consideration. Effective placement yield depends heavily on machine accuracy and the vision of the system which needs the ability to recognize the features on the board and component to place the device accurately on the pads and bumps of the PCB. There are currently two methods for accurate positioning, using the edge of the package and using solder ball locations also called footprints. The only assumption that a yield model makes is that all boards and devices are completely functional. This paper will focus on the Monte Carlo method which consists in a class of computational algorithms (information processed algorithms) which depends on repeated random samplings in order to compute the results. This method utilized in order to recreate the simulation of placement and assembly processes within a production line.