Abstract: This paper deals with the problem of thermal and
mechanical shocks, which rising during operation, mostly at
interrupted cut. Here will be solved their impact on the cutting edge
tool life, the impact of coating technology on resistance to shocks
and experimental determination of tool life in heating flame.
Resistance of removable cutting edges against thermal and
mechanical shock is an important indicator of quality as well as its
abrasion resistance. Breach of the edge or its crumble may occur due
to cyclic loading. We can observe it not only during the interrupted
cutting (milling, turning areas abandoned hole or slot), but also in
continuous cutting. This is due to the volatility of cutting force on
cutting. Frequency of the volatility in this case depends on the type
of rising chips (chip size element). For difficult-to-machine materials
such as austenitic steel particularly happened at higher cutting speeds
for the localization of plastic deformation in the shear plane and for
the inception of separate elements substantially continuous chips.
This leads to variations of cutting forces substantially greater than for
other types of steel.
Abstract: A study of the H-beam's nanosize structure phase
states after thermomechanical strengthening was carried out by TEM.
The following processes were analyzed. 1. The dispersing of the
cementite plates by cutting them by moving dislocations. 2. The
dissolution of cementite plates and repeated precipitation of the
cementite particles on the dislocations, the boundaries, subgrains and
grains. 3. The decay of solid solution of carbon in the α-iron after
"self-tempering" of martensite. 4. The final transformation of the
retained austenite in beinite with α-iron particles and cementite
formation. 5. The implementation of the diffusion mechanism of γ ⇒
α transformation.
Abstract: Packing problems arise in a wide variety of application
areas. The basic problem is that of determining an efficient arrangement
of different objects in a region without any overlap and
with minimal wasted gap between shapes. This paper presents a
novel population based approach for optimizing arrangement of irregular
shapes. In this approach, each shape is coded as an agent and
the agents' reproductions and grouping policies results in arrangements
of the objects in positions with least wasted area between
them. The approach is implemented in an application for cutting
sheets and test results on several problems from literature are presented.
Abstract: In this paper, a set of experimental data has been used to assess the influence of abrasive water jet (AWJ) process parameters in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. The effects of these input parameters are studied on depth of cut (h); one of most important characteristics of AWJ. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the AWJ process parameters. The objective is to determine a suitable set of process parameters that can produce a desired depth of cut, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.
Abstract: In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature. Various researchers and practitioners have tried to identify and implement strategies in supply chains which can bring competitiveness in the supply chains i.e. supply chain competitiveness. The purpose of this paper is to suggest select strategies for supply chain competitiveness in the Indian manufacturing sector using an integrated approach of literature review and exploratory interviews with eminent professionals from the supply chain area in various industries, academia and research. The aim of the paper is to highlight the important area of competitiveness in the supply chain and to suggest recommendations to the industry and managers of manufacturing sector.
Abstract: Shape optimization of the airfoil with high aspect ratio
of long endurance unmanned aerial vehicle (UAV) is performed by the
multi-objective optimization technology coupled with computational
fluid dynamics (CFD). For predicting the aerodynamic characteristics
around the airfoil the high-fidelity Navier-Stokes solver is employed
and SMOGA (Simple Multi-Objective Genetic Algorithm), which is
developed by authors, is used for solving the multi-objective
optimization problem. To obtain the optimal solutions of the design
variable (i.e., sectional airfoil profile, wing taper ratio and sweep) for
high performance of UAVs, both the lift and lift-to-drag ratio are
maximized whereas the pitching moment should be minimized,
simultaneously. It is found that the lift force and lift-to-drag ratio are
linearly dependent and a unique and dominant solution are existed.
However, a trade-off phenomenon is observed between the lift-to-drag
ratio and pitching moment. As the result of optimization, sixty-five
(65) non-dominated Pareto individuals at the cutting edge of design
spaces that is decided by airfoil shapes can be obtained.
Abstract: An effort to find out the smaller size of cuttings for propagation of Morus alba was made in experimental area Department of Forestry, Range Management and Wildlife, University of Agriculture, Faisalabad, Pakistan. Different size of cuttings i.e. 2", 4", 6" and 8" were planted in polythene tubes of 3.5"x7". The effort was also made to compare the performance of cuttings in open air and in polythene low tunnel. Root length, number of root branches, root diameter and root fresh and dry weight were found maximum in two inches cuttings while minimum in four inches cuttings. Root growth was found maximum in open air as compared to under polythene sheet.
Abstract: Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.
Abstract: Metal cutting is a severe plastic deformation process
involving large strains, high strain rates, and high temperatures.
Conventional analysis of the chip formation process is based on bulk
material deformation disregarding the inhomogeneous nature of the
material microstructure. A series of orthogonal cutting tests of AISI
1045 and 1144 steel were conducted which yielded similar process
characteristics and chip formations. With similar shear angles and cut
chip thicknesses, shear strains for both chips were found to range
from 2.0 up to 2.8. The manganese-sulfide (MnS) precipitate in the
1144 steel has a very distinct and uniform shape which allows for
comparison before and after chip formation. From close observations
of MnS precipitates in the cut chips it is shown that the conventional
approach underestimates plastic strains in metal cutting.
Experimental findings revealed local shear strains around a value of
6. These findings and their implications are presented and discussed.
Abstract: This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.
Abstract: This paper presents how the real-time chatter
prevention can be realized by feedback of acoustic cutting signal, and
the efficacy of the proposed adaptive spindle speed tuning algorithm is
verified by intensive experimental simulations. A pair of
microphones, perpendicular to each other, is used to acquire the
acoustic cutting signal resulting from milling chatter. A real-time
feedback control loop is constructed for spindle speed compensation
so that the milling process can be ensured to be within the stability
zone of stability lobe diagram. Acoustic Chatter Signal Index (ACSI)
and Spindle Speed Compensation Strategy (SSCS) are proposed to
quantify the acoustic signal and actively tune the spindle speed
respectively. By converting the acoustic feedback signal into ACSI,
an appropriate Spindle Speed Compensation Rate (SSCR) can be
determined by SSCS based on real-time chatter level or ACSI.
Accordingly, the compensation command, referred to as Added-On
Voltage (AOV), is applied to increase/decrease the spindle motor
speed. By inspection on the precision and quality of the workpiece
surface after milling, the efficacy of the real-time chatter prevention
strategy via acoustic signal feedback is further assured.
Abstract: Australia, while being a large and eager consumer of
innovative and cutting edge Information and Communication
Technologies (ICT), continues to struggle to remain a leader in
Technological Innovation. This paper has two main contributions to
address certain aspects of this complex issue. The first being the
current findings of an ongoing research project on Information and
Innovation Management in the Australian Information and
Communication Technologies (ICT) sector. The major issues being
considered by the project include: investigation of the possible
inherent entrepreneurial nature of ICT; how to foster ICT innovation;
and examination of the inherent difficulties currently found within
the ICT industry of Australia in regards to supporting the
development of innovative and creative ideas. The second major
contribution is details of the I.-C.A.N. (Innovation by Collaborative
Anonymous Networking) software application information
management tool created and evolving in our research group. I-CAN,
besides having a positive reinforcement acronym, is aimed at
facilitating productive collaborative innovation in an Australian
workplace. Such a work environment is frequently subjected to
cultural influences such as the 'tall poppy syndrome' and 'negative'
or 'unconstructive' peer-pressure. There influences are frequently
seen as inhibitors to employee participation, entrepreneurship and
innovation.
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. In this paper, an experimental study on the
influence of the wear of the cutting tool (systematic dispersions) is
explored. This study was carried out on three stages .The first stage
allows machining without elimination of dispersions (random,
systematic) so the tolerances of manufacture according to total
dispersions. In the second stage, the results of the first stage are
filtered in such way to obtain the tolerances according to random
dispersions. Finally, from the two previous stages, the systematic
dispersions are generated. The objective of this study is to model
by the least squares method the error of manufacture based on
systematic dispersion. Finally, an approach of optimization of the
manufacturing tolerances was developed for machining on a CNC
machine tool
Abstract: This paper presents design and characterization of a
microaccelerometer designated for integration into cataract surgical
probe to detect hardness of different eye tissues during cataract
surgery. Soft posterior lens capsule of eye can be easily damaged in
comparison with hard opaque lens since the surgeon can not see
directly behind cutting needle during the surgery. Presence of
microsensor helps the surgeon to avoid rupturing posterior lens
capsule which if occurs leads to severe complications such as
glaucoma, infection, or even blindness. The microsensor having
overall dimensions of 480 μm x 395 μm is able to deliver significant
capacitance variations during encountered vibration situations which
makes it capable to distinguish between different types of tissue.
Integration of electronic components on chip ensures high level of
reliability and noise immunity while minimizes space and power
requirements. Physical characteristics and results on performance
testing, proves integration of microsensor as an effective tool to aid
the surgeon during this procedure.
Abstract: This paper presents a solution for ceramic cutting tools availability in interrupted machining. Experiments were performed on a special fixture – the interrupted cut simulator. This fixture was constructed at our Department of Machining and Assembly within the scope of a project by the Czech Science Foundation. The goals of the tests were to contribute to the wider usage of these cutting materials in machining, especially in interrupted machining. Through the centuries, producers of ceramic cutting tools have taken big steps forward. Namely, increasing durability in maintaining high levels of strength and hardness lends an advantage. Some producers of these materials advise cutting inserts for interrupted machining at the present time [1, 2].
Abstract: This paper presents the theoretical background and
the real implementation of an automated computer system to
introduce machine vision in flower, fruit and vegetable processing
for recollection, cutting, packaging, classification, or fumigation
tasks. The considerations and implementation issues presented in this
work can be applied to a wide range of varieties of flowers, fruits and
vegetables, although some of them are especially relevant due to the
great amount of units that are manipulated and processed each year
over the world. The computer vision algorithms developed in this
work are shown in detail, and can be easily extended to other
applications. A special attention is given to the electromagnetic
compatibility in order to avoid noisy images. Furthermore, real
experimentation has been carried out in order to validate the
developed application. In particular, the tests show that the method
has good robustness and high success percentage in the object
characterization.
Abstract: Greenhouse gases (GHG) emissions impose major
threat to global warming potential (GWP). Unfortunately
manufacturing sector is one of the major sources that contribute
towards the rapid increase in greenhouse gases (GHG) emissions. In
manufacturing sector electric power consumption is the major driver
that influences CO2 emission. Titanium alloys are widely utilized in
aerospace, automotive and petrochemical sectors because of their
high strength to weight ratio and corrosion resistance. Titanium
alloys are termed as difficult to cut materials because of their poor
machinability rating. The present study analyzes energy consumption
during cutting with reference to material removal rate (MRR).
Surface roughness was also measured in order to optimize energy
consumption.
Abstract: In metal cutting industries, mathematical/statistical
models are typically used to predict tool replacement time. These
off-line methods usually result in less than optimum replacement
time thereby either wasting resources or causing quality problems.
The few online real-time methods proposed use indirect measurement
techniques and are prone to similar errors. Our idea is based on
identifying the optimal replacement time using an electronic nose to
detect the airborne compounds released when the tool wear reaches
to a chemical substrate doped into tool material during the
fabrication. The study investigates the feasibility of the idea, possible
doping materials and methods along with data stream mining
techniques for detection and monitoring different phases of tool
wear.
Abstract: Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.
Abstract: A judicious choice of insert material, tool geometry and
cutting conditions can make hard turning produce better surfaces than
grinding. In the present study, an attempt has been made to
investigate the effect of cutting tool materials on cutting forces (feed
force, thrust force and cutting force) in finish hard turning of AISI
D2 cold work tool steel. In conclusion of the results obtained with a
constant depth of cut and feed rate, it is important to note that cutting
force is directly affected by cutting tool material.