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Comprehensive experimental evaluation of a systematic approach for cost effective and rapid design of condition monitoring systems using Taguchi's method

A. Al-Habaibeh, F. Zorriassatine, N. Gindy
<span title="">2002</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ng6t2zmulzbwtbhvek7oabouze" style="color: black;">Journal of Materials Processing Technology</a> </i> &nbsp;
The experiments investigate two new types of cutting tools each with three distinct conditions which are processed by four different and independent neural network paradigms -two supervised and two unsupervised  ...  This paper provides an extensive experimental and analytical evaluation of a previously presented approach to the systematic design of condition monitoring systems for machining operations [1].  ...  A Brief Description of the ASPS Approach and Taguchi's Method -The ASPS Approach The ASPS approach helps to design a condition monitoring system for a machine tool or a process using an automated simple  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s0924-0136(02)00267-4">doi:10.1016/s0924-0136(02)00267-4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/r6ghfia2nfaxregcuhablrtfg4">fatcat:r6ghfia2nfaxregcuhablrtfg4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170922234213/http://irep.ntu.ac.uk/id/eprint/11962/1/196338_353%20Al%20habaibeh%20Postprint.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e6/68/e6689df04fc478c89fddda194093ac1c97e1281f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s0924-0136(02)00267-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

An optimised back propagation neural network approach and simulated annealing algorithm towards optimisation of EDM process parameters

Masoud Azadi Moghaddam, Farhad Kolahan
<span title="">2015</span> <i title="Inderscience Publishers"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/acq3l5j6zjad5mtoekdbyrgdkm" style="color: black;">International Journal of Manufacturing Research</a> </i> &nbsp;
Experimental results indicate that the proposed optimisation procedure is quite efficient in modelling and optimisation of EDM process parameters.  ...  Next, the developed model is embedded into SA algorithm to determine the best set of process parameters values for an optimal set of outputs.  ...  First, the experimental data are gathered based on L 36 Taguchi design matrix. Then, the process is modelled using an optimised back propagation neural network (OBPNN).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1504/ijmr.2015.071616">doi:10.1504/ijmr.2015.071616</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qtoqe7xcozbadndmbo7dypbzky">fatcat:qtoqe7xcozbadndmbo7dypbzky</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170705191835/https://profdoc.um.ac.ir/articles/a/1050503.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b1/09/b109ccf5f135d3a0b82fe4523f90a8a7f4b9873a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1504/ijmr.2015.071616"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Neural Image Processing of the Wear of Cutting Tools Coated with Thin Films

M.J. Jackson, G.M. Robinson, L.J. Hyde, R. Rhodes
<span title="2006-04-01">2006</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4e66gdmhsngujmmwlxdbbox5mq" style="color: black;">Journal of materials engineering and performance (Print)</a> </i> &nbsp;
The experiments were designed using Taguchi's design of experiments (DoE) and suitable L18 orthogonal array (OA) was selected for the chosen parameters: cutting speed, feed rate, depth of cut, material  ...  From the obtained results, it is obvious that the neural network models can be successfully used for predicting the output responses without performing the experiments.  ...  Design of experiments using the Taguchi approach: 16 steps to product and process improvement, John Wiley & Sons, Inc., USA. [20] Senthilkumar, N., Tamizharasan, T. (2012).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1361/105994906x95922">doi:10.1361/105994906x95922</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/76gc24bucfh7dnwkiuxsv7hnkm">fatcat:76gc24bucfh7dnwkiuxsv7hnkm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721095509/http://apem-journal.org/Archives/2013/Abstract-APEM8-4_231-241.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9b/3f/9b3fefb171b34629b03108ea1bfda450bfe935d6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1361/105994906x95922"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Taguchi-Based and Intelligent Optimisation of a Multi-Response Process Using Historical Data

Tatjana Šibalija, Vidosav Majstorović, Mirko Soković
<span title="2011-04-15">2011</span> <i title="Faculty of Mechanical Engineering"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hljgvntzybck3oodncdnbsrfaa" style="color: black;">Strojniski vestnik</a> </i> &nbsp;
Optimisation of manufacturing processes is typically performed by utilising mathematical process models or designed experiments.  ...  The paper presents an approach to optimisation of manufacturing processes with multiple potentially correlated responses, using historical process data.  ...  INTRODUCTION Process optimisation is typically performed by analysing the process responses obtained from designed experiments, carried out on the actual manufacturing process.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5545/sv-jme.2010.061">doi:10.5545/sv-jme.2010.061</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7jtyw4dugncxtmh377aj2ys5xe">fatcat:7jtyw4dugncxtmh377aj2ys5xe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808132255/http://en.sv-jme.eu/data/upload/2011/04/08_2010_061_Sibalija_04.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c2/46/c246512ba1d3902991fde6114206c2b192099312.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5545/sv-jme.2010.061"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

AN APPLICATION OF ANN FOR MODELING AND OPTIMISATION OF PROCESS PARAMETERS OF MANUFACTURING PROCESS: A REVIEW

Nitin Kumar Rathi, Nisha Rathi
<span title="2020-05-10">2020</span> <i title="IJEAST"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/namhphsg6rdvtofp27o3scimoy" style="color: black;">International Journal of Engineering Applied Sciences and Technology</a> </i> &nbsp;
With the perspective of demand of readily adaptable manufacturing technologies, Artificial Neural Networks is an influential tool.  ...  Optimization of process parameters of the manufacturing processes. Previously the choice of suitable process parameters was a hard and tedious task.  ...  In this survey, complete information on applications of ANN and machine learning methods for modeling of different manufacturing process and their process parameters optimisation is concisely presented  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33564/ijeast.2020.v04i12.017">doi:10.33564/ijeast.2020.v04i12.017</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/d5e6zel4ozeevewkrgsczneqye">fatcat:d5e6zel4ozeevewkrgsczneqye</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200709152518/https://www.ijeast.com/papers/127-134,Tesma412,IJEAST.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5d/fb/5dfb8e25e17f5ba1b00a86081ecebd0da10b2e21.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33564/ijeast.2020.v04i12.017"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Quality Improvement Using Taguchi's Model: – A Casy Study from Serbia

Vidosav D. Majstorovic, Tatjana Sibalija
<span title="2014-01-13">2014</span> <i title="Riga Technical University"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tanchmf42fhlzplj4oizdzeide" style="color: black;">Materials Science and Applied Chemistry</a> </i> &nbsp;
The developed Taguchi's model for the multiobjective process design could incorporate customers' specifications for several characteristics and could be used to optimise various types of manufacturing  ...  The model is given in a form of an hybrid intelligent system for the process design (optimisation, modelling and/or simulation), providing the possibility for learning features (learning from the experimental  ...  INTRODUCTION The approach of Taguchi's robust design has been successfully used in many single-response process design problems.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7250/eb.2013.011">doi:10.7250/eb.2013.011</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mby45pnm7vd77jud77otebpsry">fatcat:mby45pnm7vd77jud77otebpsry</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170921214704/https://eb-journals.rtu.lv/article/download/eb.2013.011/296" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/23/73/2373b77fb7f92a24f46ffad836c2042d8c9f39ba.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7250/eb.2013.011"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Modelling of Material Removal in Abrasive Belt Grinding Process: A Regression Approach

Pandiyan, Caesarendra, Glowacz, Tjahjowidodo
<span title="2020-01-05">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nzoj5rayr5hutlurimhzyjlory" style="color: black;">Symmetry</a> </i> &nbsp;
regression (SVR) and random forests (RF) have been applied to the experimental data determined using the Taguchi design of experiments (DoE).  ...  This article explores the effects of parameters such as cutting speed, force, polymer wheel hardness, feed, and grit size in the abrasive belt grinding process to model material removal.  ...  Taguchi Design of Experiments (DoE) and Data Collection The experiments were performed based on Taguchi's L27 orthogonal array (five-factor, threelevel) model.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/sym12010099">doi:10.3390/sym12010099</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x3roq62kpbavdnkvmo3hehgsty">fatcat:x3roq62kpbavdnkvmo3hehgsty</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200107023215/https://res.mdpi.com/d_attachment/symmetry/symmetry-12-00099/article_deploy/symmetry-12-00099-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/eb/a1/eba179d4aa395ef90e6c62225e70d1142a00fa40.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/sym12010099"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Minimising Defect Formation in Sand Casting of Sheet Lead: A DoE Approach

Prabhakar, Papanikolaou, Salonitis, Jolly
<span title="2020-02-13">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/54rwmy3lgfe7fbkfa7e74fa6fi" style="color: black;">Metals</a> </i> &nbsp;
Finally, an optimal set of process parameters leading to the minimisation of surface defects was identified.  ...  Sand casting of lead sheet is a traditional manufacturing process used up to the present due to the special features of sand cast sheet such as their attractive sheen.  ...  Experiments were subsequently conducted using different combinations of the process parameters as per the Taguchi's orthogonal array and the parameters were optimised for minimal casting defects.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/met10020252">doi:10.3390/met10020252</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ei7u7cztpbfhxlieoo5tqxabva">fatcat:ei7u7cztpbfhxlieoo5tqxabva</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200509014726/https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/15138/Minimising_defect_formation_in_sand_casting_of_sheet_lead-2020.pdf;jsessionid=700CC7ABC96416BF9212D904136A5939?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/29/56/29565ecfa00bde1b4df9243f877d599cecd7c855.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/met10020252"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Optimization of different welding processes using statistical and numerical approaches – A reference guide

K.Y. Benyounis, A.G. Olabi
<span title="">2008</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ukd76hjdabbnpmiehiy62cmzju" style="color: black;">Advances in Engineering Software</a> </i> &nbsp;
Nowadays, application of Design of Experiment (DoE), Evolutionary algorithms and computational network are widely used to develop a mathematical relationship between the welding process input parameters  ...  Generally, all welding processes are used with the aim of obtaining a welded joint with the desired weld-bead parameters, excellent mechanical properties with minimum distortion.  ...  [25] have explained some concepts related to neural networks and how they can be used to model weld bead geometry, in terms of equipment parameters, in order to evaluate the accuracy of neural networks  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.advengsoft.2007.03.012">doi:10.1016/j.advengsoft.2007.03.012</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oy7vtclayvhmhpiuqesuqp7lju">fatcat:oy7vtclayvhmhpiuqesuqp7lju</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20171109053128/https://core.ac.uk/download/pdf/11311286.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0f/a2/0fa24b5b63677ae352d6c6fcf6f7689bf9ad44cc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.advengsoft.2007.03.012"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Intelligent approach based on FEM simulations and soft computing techniques for filling system design optimisation in sand casting processes

Ahmed Ktari, Mohamed El Mansori
<span title="2021-03-24">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/uvqilzacoje2vogjcpf5ygyabi" style="color: black;">The International Journal of Advanced Manufacturing Technology</a> </i> &nbsp;
FEM simulations and soft computing techniques for filling system design optimisation in sand casting processes -The Abstract This paper reports an intelligent approach for modeling and optimisation of  ...  filling system design (FSD) in the case of sand casting process of aluminium alloy.  ...  Since several training algorithms are used in neural network applications, it is difficult to predict the best one in terms of accuracy for a given problem.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00170-021-06876-z">doi:10.1007/s00170-021-06876-z</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/awcpfis7nzezpcdtcfwlyimjia">fatcat:awcpfis7nzezpcdtcfwlyimjia</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716090448/https://sam.ensam.eu/bitstream/handle/10985/20136/MSMP_IJAMT_2021_KTARI.pdf;jsessionid=B44912BC88535D44AD526A94F9C06EBD?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/75/c4/75c4eb4ca68daf1bddf05700ad8f17b3e258d6d9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00170-021-06876-z"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Hybrid Approach to Design Optimisation: Preserve Accuracy, Reduce Dimensionality

Mariusz Kamola
<span title="2007-03-01">2007</span> <i title="Walter de Gruyter GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gtmb6i7f4nafrasuvcrl3t5ahe" style="color: black;">International Journal of Applied Mathematics and Computer Science</a> </i> &nbsp;
The proposed methodology is intended to be used by those not having much knowledge of the system or modelling technology, but having the basic practice in optimisation.  ...  Special attention is paid to cases where simulation failures (regardless of their nature) form big obstacles in the course of the optimisation process.  ...  The applicability and benefits of an approach outlined in conclusion 2 is best visible in case ofpower plant model.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2478/v10006-007-0006-3">doi:10.2478/v10006-007-0006-3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gz2t75ot5zcotdqr3dx6kcjkai">fatcat:gz2t75ot5zcotdqr3dx6kcjkai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808053855/http://staff.elka.pw.edu.pl/~mkamola/Kamola07a.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ef/46/ef466096455d0a42d949626b7cea094d6f2bffe1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2478/v10006-007-0006-3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Simulation-based selection of optimum pressure die-casting process parameters using neural nets and genetic algorithms

A. Krimpenis, P.G. Benardos, G.-C. Vosniakos, A. Koukouvitaki
<span title="2005-02-09">2005</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/uvqilzacoje2vogjcpf5ygyabi" style="color: black;">The International Journal of Advanced Manufacturing Technology</a> </i> &nbsp;
Furthermore, they can be employed in the fitness function of a Genetic Algorithm that can optimise the process, i.e. yield the combination of input parameters that achieves the best output parameter values  ...  Systematic knowledge accumulation regarding the manufacturing process is essential in order to obtain optimal process conditions.  ...  Simulation runs provide training examples for constructing neural network metamodels that can act as surrogate simulation models and can easily be used in optimising process parameter values through embedding  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00170-004-2218-0">doi:10.1007/s00170-004-2218-0</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gejrio5msbel7gdd7aywj2wnsm">fatcat:gejrio5msbel7gdd7aywj2wnsm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200323041732/https://www.researchgate.net/profile/George-Christopher_Vosniakos/publication/225984331_Simulation-based_selection_of_optimum_pressure_die-casting_process_parameters_using_neural_nets_and_genetic_algorithms/links/0c96053c662ad450e3000000.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1a/67/1a67f6b08b9f632d20d24a0575d582845daa6641.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00170-004-2218-0"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Investigation of surface roughness and material removal rate for UD-GFRP composite using Taguchi grey relational analysis

Surinder Kumar, Meenu
<span title="2017-06-30">2017</span> <i title="Universiti Malaysia Pahang Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ni2re55ssjh3pdzxem3hzcflzi" style="color: black;">International Journal of Automotive and Mechanical Engineering</a> </i> &nbsp;
Taguchi approach was used for the experiment. The parameters studied were tool rake angle, speed, depth of cut, feed, tool nose radius, and cutting environment.  ...  The grey relational analysis was used to optimise the parameters affecting the response.  ...  The authors are also thankful to the Maharashtra Engineering Industry, India (P) Limited, Satara Maharashtra for supplying the UD-GFRP rods used in this work.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15282/ijame.14.2.2017.14.0343">doi:10.15282/ijame.14.2.2017.14.0343</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2dzdxysrbvgi5jnqal2wkxc2lq">fatcat:2dzdxysrbvgi5jnqal2wkxc2lq</a> </span>
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A modified principal component analysis-based utility theory approach for optimization of correlated responses of EDM process

R Chakravorty, SK Gauri, S Chakraborty
<span title="2012-12-13">2012</span> <i title="African Journals Online (AJOL)"> International Journal of Engineering, Science and Technology </i> &nbsp;
The reported experimental data on EDM processes in literature are analyzed using the modified PCA-based UT approach and PCA-based PQLR method.  ...  So, ideally, use of principal component analysis (PCA)-based approaches that take into account the possible correlations between the responses are suitable for optimization of EDM process.  ...  Acknowledgement: The authors would like to thank the referees for their valuable comments and suggestions which have substantially improved the content and presentation of this paper.  ... 
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Optimization of Machining Parameters in WEDM of AISI D3 Steel Using Taguchi Technique

Brajesh Kumar Lodhi, Sanjay Agarwal
<span title="">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pg7ahjk7dvd2tinhv7p6przfy4" style="color: black;">Procedia CIRP</a> </i> &nbsp;
To validate the study, confirmation experiment has been carried out at optimum set of parameters and predicted results have been found to be in good agreement with experimental findings.  ...  An orthogonal array, the signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) were employed to the study the surface roughness in the WEDM of AISI D3 Steel.  ...  Mathematical and Artificial Neural Network models has been developed relating the machining performance and process parameters. Bhangoria et al.  ... 
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