Abstract: Manufacturing tolerancing is intended to determine
the intermediate geometrical and dimensional states of the part during
its manufacturing process. These manufacturing dimensions also
serve to satisfy not only the functional requirements given in the
definition drawing, but also the manufacturing constraints, for
example geometrical defects of the machine, vibration and the wear
of the cutting tool. The choice of positioning has an important influence on the cost
and quality of manufacture. To avoid this problem, a two-step
approach has been developed. The first step is dedicated to the
determination of the optimum position. As for the second step, a
study was carried out for the tightening effect on the tolerance
interval.
Abstract: In this paper, we propose two algorithms to optimally
solve makespan and total completion time scheduling problems with
learning effect and job dependent delivery times in a single machine
environment. The delivery time is the extra time to eliminate adverse
effect between the main processing and delivery to the customer. In
this paper, we introduce the job dependent delivery times for some
single machine scheduling problems with position dependent learning
effect, which are makespan are total completion. The results with
respect to two algorithms proposed for solving of the each problem
are compared with LINGO solutions for 50-jobs, 100-jobs and 150-
jobs problems. The proposed algorithms can find the same results in
shorter time.
Abstract: The growth in the demand of electrical energy is
leading to load on the Power system which increases the occurrence
of frequent oscillations in the system. The reason for the oscillations
is due to the lack of damping torque which is required to dominate
the disturbances of Power system. By using FACT devices, such as
Unified Power Flow Controller (UPFC) can control power flow,
reduce sub-synchronous resonances and increase transient stability.
Hence, UPFC is used to damp the oscillations occurred in Power
system. This research focuses on adapting the neuro fuzzy controller
for the UPFC design by connecting the infinite bus (SMIB - Single
machine Infinite Bus) to a linearized model of synchronous machine
(Heffron-Phillips) in the power system. This model gains the
capability to improve the transient stability and to damp the
oscillations of the system.
Abstract: In this article, the radial displacement error correction
capability of a high precision spindle grinding caused by unbalance
force was investigated. The spindle shaft is considered as a flexible
rotor mounted on two sets of angular contact ball bearing. Finite
element methods (FEM) have been adopted for obtaining the
equation of motion of the spindle. In this paper, firstly, natural
frequencies, critical frequencies, and amplitude of the unbalance
response caused by residual unbalance are determined in order to
investigate the spindle behaviors. Furthermore, an optimization
design algorithm is employed to minimize radial displacement of the
spindle which considers dimension of the spindle shaft, the dynamic
characteristics of the bearings, critical frequencies and amplitude of
the unbalance response, and computes optimum spindle diameters
and stiffness and damping of the bearings. Numerical simulation
results show that by optimizing the spindle diameters, and stiffness
and damping in the bearings, radial displacement of the spindle can
be reduced. A spindle about 4 μm radial displacement error can be
compensated with 2 μm accuracy. This certainly can improve the
accuracy of the product of machining.
Abstract: The subject of this paper is to review, comparative
analysis and simulation of selected components of power electronic
systems (PES), consistent with the concept of a more electric aircraft
(MEA). Comparative analysis and simulation in software
environment MATLAB / Simulink were carried out on the base of a
group of representatives of civil aircraft (B-787, A-380) and military
(F-22 Raptor, F-35) in the context of multi-pulse converters used in
them (6- and 12-pulse, and 18- and 24-pulse), which are key
components of high-tech electronics on-board power systems of
autonomous power systems (ASE) of modern aircraft (airplanes of
the future).
Abstract: This paper evaluates the accrual based scheduling for
cloud in single and multi-resource system. Numerous organizations
benefit from Cloud computing by hosting their applications. The
cloud model provides needed access to computing with potentially
unlimited resources. Scheduling is tasks and resources mapping to a
certain optimal goal principle. Scheduling, schedules tasks to virtual
machines in accordance with adaptable time, in sequence under
transaction logic constraints. A good scheduling algorithm improves
CPU use, turnaround time, and throughput. In this paper, three realtime
cloud services scheduling algorithm for single resources and
multiple resources are investigated. Experimental results show
Resource matching algorithm performance to be superior for both
single and multi-resource scheduling when compared to benefit first
scheduling, Migration, Checkpoint algorithms.
Abstract: Polylactic acid (PLA) is the most commercially
available bio-based and biodegradable plastic at present. PLA has
been used in plastic related industries including single-used
containers, disposable and environmentally friendly packaging owing
to its renewability, compostability, biodegradability, and safety.
Although PLA demonstrates reasonably good optical, physical,
mechanical and barrier properties comparable to the existing
petroleum-based plastics, its brittleness and mold shrinkage as well as
its price are the points to be concerned for the production of rigid and
semi-rigid packaging. Blending PLA with other bio-based polymers
including thermoplastic starch (TPS) is an alternative not only to
achieve a complete bio-based plastic, but also to reduce the
brittleness, shrinkage during molding and production cost of the
PLA-based products. TPS is a material produced mainly from starch
which is cheap, renewable, biodegradable, compostable, and nontoxic.
It is commonly prepared by a plasticization of starch under
applying heat and shear force. Although glycerol has been reported as
one of the most plasticizers used for preparing TPS, its migration
caused the surface stickiness of the TPS products. In some cases,
mixed plasticizers or natural fibers have been applied to impede the
retrogradation of starch or reduce the migration of glycerol. The
introduction of fibers into TPS-based materials could reinforce the
polymer matrix as well. Therefore, the objective of the present
research is to study the effect of starch type (i.e. native starch and
phosphate starch), plasticizer type (i.e. glycerol and xylitol with a
weight ratio of glycerol to xylitol of 100:0, 75:25, 50:50, 25:75 and
0:100) and fiber content (i.e. in the range of 1-25 %wt) on properties
of PLA/TPS blend and composite. PLA/TPS blends and composites
were prepared using a twin-screw extruder and then converted into
dumbbell-shaped specimens using an injection molding machine. The
PLA/TPS blends prepared by using phosphate starch showed higher
tensile strength and stiffness than the blends prepared by using native
one. In contrast, the blends from native starch exhibited higher
extensibility and heat distortion temperature (HDT) than those from
the modified starch. Increasing xylitol content resulted in enhanced
tensile strength, stiffness and water resistance, but decreased
extensibility and HDT of the PLA/TPS blend. Tensile properties and
hydrophobicity of the blend could be improved by incorporating
silane treated-jute fibers.
Abstract: Rapid prototyping is a new group of manufacturing
processes, which allows fabrication of physical of any complexity
using a layer by layer deposition technique directly from a computer
system. The rapid prototyping process greatly reduces the time and
cost necessary to bring a new product to market. The prototypes
made by these systems are used in a range of industrial application
including design evaluation, verification, testing, and as patterns for
casting processes. These processes employ a variety of materials and
mechanisms to build up the layers to build the part. The present work
was to build a FDM prototyping machine that could control the X-Y
motion and material deposition, to generate two-dimensional and
three-dimensional complex shapes. This study focused on the
deposition of wax material. This work was to find out the properties
of the wax materials used in this work in order to enable better
control of the FDM process. This study will look at the integration of
a computer controlled electro-mechanical system with the traditional
FDM additive prototyping process. The characteristics of the wax
were also analysed in order to optimise the model production process.
These included wax phase change temperature, wax viscosity and
wax droplet shape during processing.
Abstract: The aim of the performed work is to establish the 2D
and 3D model of direct unsteady task of sample heat treatment by
moving source employing computer model on the basis of finite
element method. Complex boundary condition on heat loaded sample
surface is the essential feature of the task. Computer model describes
heat treatment of the sample during heat source movement over the
sample surface. It is started from 2D task of sample cross section as a
basic model. Possibilities of extension from 2D to 3D task are
discussed. The effect of the addition of third model dimension on
temperature distribution in the sample is showed. Comparison of
various model parameters on the sample temperatures is observed.
Influence of heat source motion on the depth of material heat
treatment is shown for several velocities of the movement. Presented
computer model is prepared for the utilization in laser treatment of
machine parts.
Abstract: Automated Teller Machines (ATMs) can be
considered among one of the most important service facilities in the
banking industry. The investment in ATMs and the impact on the
banking industry is growing steadily in every part of the world. The
banks take into consideration many factors like safety, convenience,
visibility, and cost in order to determine the optimum locations of
ATMs. Today, ATMs are not only available in bank branches but
also at retail locations. Another important factor is the cash
management in ATMs. A cash demand model for every ATM is
needed in order to have an efficient cash management system. This
forecasting model is based on historical cash demand data which is
highly related to the ATMs location. So, the location and the cash
management problem should be considered together. This paper
provides a general review on studies, efforts and development in
ATMs location and cash management problem.
Abstract: Cloud Computing refers to applications delivered as
services over the internet, and the datacenters that provide those
services with hardware and systems software. These were earlier
referred to as Software as a Service (SaaS). Scheduling is justified by
job components (called tasks), lack of information. In fact, in a large
fraction of jobs from machine learning, bio-computing, and image
processing domains, it is possible to estimate the maximum time
required for a task in the job. This study focuses on Trust based
scheduling to improve cloud security by modifying Heterogeneous
Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT
(Trust Reputation HEFT) which is then compared to Dynamic Load
Scheduling.
Abstract: The knitted fabric suffers a deformation in its
dimensions due to stretching and tension factors, transverse and
longitudinal respectively, during the process in rectilinear knitting
machines so it performs a dry relaxation shrinkage procedure and
thermal action of prefixed to obtain stable conditions in the knitting.
This paper presents a dry relaxation shrinkage prediction of Bordeaux
fiber using a feed forward neural network and linear regression
models. Six operational alternatives of shrinkage were predicted. A
comparison of the results was performed finding neural network
models with higher levels of explanation of the variability and
prediction. The presence of different reposes is included. The models
were obtained through a neural toolbox of Matlab and Minitab
software with real data in a knitting company of Southern
Guanajuato. The results allow predicting dry relaxation shrinkage of
each alternative operation.
Abstract: In this paper, we present a comparative study of three
methods of 2D face recognition system such as: Iso-Geodesic Curves
(IGC), Geodesic Distance (GD) and Geodesic-Intensity Histogram
(GIH). These approaches are based on computing of geodesic
distance between points of facial surface and between facial curves.
In this study we represented the image at gray level as a 2D surface in
a 3D space, with the third coordinate proportional to the intensity
values of pixels. In the classifying step, we use: Neural Networks
(NN), K-Nearest Neighbor (KNN) and Support Vector Machines
(SVM). The images used in our experiments are from two wellknown
databases of face images ORL and YaleB. ORL data base was
used to evaluate the performance of methods under conditions where
the pose and sample size are varied, and the database YaleB was used
to examine the performance of the systems when the facial
expressions and lighting are varied.
Abstract: Due to the fast and flawless technological innovation
there is a tremendous amount of data dumping all over the world in
every domain such as Pattern Recognition, Machine Learning, Spatial
Data Mining, Image Analysis, Fraudulent Analysis, World Wide
Web etc., This issue turns to be more essential for developing several
tools for data mining functionalities. The major aim of this paper is to
analyze various tools which are used to build a resourceful analytical
or descriptive model for handling large amount of information more
efficiently and user friendly. In this survey the diverse tools are
illustrated with their extensive technical paradigm, outstanding
graphical interface and inbuilt multipath algorithms in which it is
very useful for handling significant amount of data more indeed.
Abstract: Lots of motors have been being used in industry.
Therefore many researchers have studied about the failure diagnosis of
motors. In this paper, the effect of measuring environment for
diagnosis of gear fault connected to a motor shaft is studied. The fault
diagnosis is executed through the comparison of normal gear and
abnormal gear. The measured FFT data are compared with the normal
data and analyzed for q-axis current, noise and vibration. For bad and
good environment, the diagnosis results are compared. From these, it
is shown that the bad measuring environment may not be able to detect
exactly the motor gear fault. Therefore it is emphasized that the
measuring environment should be carefully prepared.
Abstract: This paper presents a speed estimation scheme based
on second-order sliding-mode Super Twisting Algorithm (STA) and
Model Reference Adaptive System (MRAS) estimation theory for
Sensorless control of multiphase induction machine. A stator current
observer is designed based on the STA, which is utilized to take the
place of the reference voltage model of the standard MRAS
algorithm. The observer is insensitive to the variation of rotor
resistance and magnetizing inductance when the states arrive at the
sliding mode. Derivatives of rotor flux are obtained and designed as
the state of MRAS, thus eliminating the integration. Compared with
the first-order sliding-mode speed estimator, the proposed scheme
makes full use of the auxiliary sliding-mode surface, thus alleviating
the chattering behavior without increasing the complexity. Simulation
results show the robustness and effectiveness of the proposed
scheme.
Abstract: Chatter vibrations and process instabilities are the
most important factors limiting the productivity of the milling
process. Chatter can leads to damage of the tool, the part or the
machine tool. Therefore, the estimation and prediction of the process
stability is very important. The process stability depends on the
spindle speed, the depth of cut and the width of cut. In milling, the
process conditions are defined in the NC-program. While the spindle
speed is directly coded in the NC-program, the depth and width of cut
are unknown. This paper presents a new simulation based approach
for the prediction of the depth and width of cut of a milling process.
The prediction is based on a material removal simulation with an
analytically represented tool shape and a multi-dexel approach for the
workpiece. The new calculation method allows the direct estimation
of the depth and width of cut, which are the influencing parameters of
the process stability, instead of the removed volume as existing
approaches do. The knowledge can be used to predict the stability of
new, unknown parts. Moreover with an additional vibration sensor,
the stability lobe diagram of a milling process can be estimated and
improved based on the estimated depth and width of cut.
Abstract: This research studies the joint production,
maintenance and subcontracting control policy for an unreliable
deteriorating manufacturing system. Production activities are
controlled by a derivation of the Hedging Point Policy, and given that
the system is subject to deterioration, it reduces progressively its
capacity to satisfy product demand. Multiple deterioration effects are
considered, reflected mainly in the quality of the parts produced and
the reliability of the machine. Subcontracting is available as support
to satisfy product demand; also, overhaul maintenance can be
conducted to reduce the effects of deterioration. The main objective
of the research is to determine simultaneously the production,
maintenance and subcontracting rate, which minimize the total,
incurred cost. A stochastic dynamic programming model is
developed and solved through a simulation-based approach
composed of statistical analysis and optimization with the response
surface methodology. The obtained results highlight the strong
interactions between production, deterioration and quality, which
justify the development of an integrated model. A numerical example
and a sensitivity analysis are presented to validate our results.
Abstract: This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.
Abstract: Biomass treatment through densification is very suitable and helpful technology before its effective energy recovery. Densification process of biomass is significantly influenced by various technological and material variables, which are ultimately reflected on the final solid biofuels quality. The paper deals with the experimental research of the relationship between technological and material variables during densification of fast-growing trees, roundly fast-growing willows. The main goal of presented experimental research is to determine the relationship between compression pressure and raw material particle size from a final briquettes density point of view. Experimental research was realized by single-axis densification. The impact of particle size with interaction of compression pressure and stabilization time on the quality properties of briquettes was determined. These variables interaction affects the final solid biofuels (briquettes) quality. From briquettes production point of view and from densification machines constructions point of view is very important to know about mutual interaction of these variables on final briquettes quality. The experimental findings presented here are showing the importance of mentioned variables during the densification process.