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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Luiz Marcio Spinosa Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba Parana Brazil

This paper introduces an approach to deal with IMS (Intelligent Manufacturing System) models, in order to help the development of Decision Support systems, Simulators and Performance Evaluators. The complexity of such systems is growing continuously requiring knowledge and information exchange between different manufacturing functions with more and more efficiency. This paper explores some potentialities of soft computing approaches and intelligent agent-oriented design including artificial neural networks, fuzzy systems, and evolutionary computation. The rationale is in order to support decision making processes performed by the autonomous and co-operative units of an IMS.

关键词： Computational modeling Manufacturing Object oriented modeling Artificial intelligence Artificial neural networks Evolutionary computation Fuzzy logic

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Opposition-based shuffled PSO with passive congregation applied to FM matching synthesis

Opposition-based shuffled PSO with passive congregation appl...

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IEEE Congress on Evolutionary Computation

作者： Munoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincon, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424478347

Synthesis of musical instruments or human voice is a time consuming process which requires theoretical and experimental knowledge about the synthesis engine. Commonly, performers need to deal with synthesizer interfaces and a process of trial and error for creating musical sounds similar to a target sound. This drawback can be overcome by adjusting automatically the synthesizer parameters using optimization algorithms. In this paper a hybrid particle swarm optimization (PSO) algorithm is proposed to solve the frequency modulation (FM) matching synthesis problem. The proposed algorithm takes advantage of a shuffle process for exchanging information between particles and applies the selective passive congregation and the opposition-based learning approaches to preserve swarm diversity. Both approaches for injecting diversity are based on simple operators, preserving the easy implementation philosophy of the particle swarm optimization. The proposed hybrid particle swarm optimization algorithm was validated for a three-nested FM synthesizer, which represents a 6-dimensional multimodal optimization problem with strong epistasis. Simulation results revealed that the proposed algorithm presented promising results in terms of quality of solutions. © 2011 IEEE.

关键词： Global optimization

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Multi-objective PID Controller Tuning for an industrial Gasifier

Multi-objective PID Controller Tuning for an Industrial Gasi...

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Congress on Evolutionary Computation

作者： Victor Henrique Alves Ribeiro Gilberto Reynoso- Meza Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil

Control of industrial plants is an important engineering field of study, where the optimization of such processes can lead to better product quality and higher profit. The present work deals with the optimization of an industrial gasifier, proposed as a benchmark challenge by ALSTOM Power Technologies in 2002. Researchers from around the globe proposed different methods for optimizing such system, using linear and nonlinear system identification techniques, different controller schemes, such as proportional-integral-derivative and model predictive controllers, and search methods for controller tuning. The authors care for the study of a methodology that can generalize the controller optimization process of real industrial systems, where linear system identification can lead to simpler systems, which are used to design more robust controllers. The proposed work deals with linear system identification and multiobjective optimization for the gasifier's controller design. To do so, the authors divide the problem in two steps, the linear system identification, where step functions are fed to the gasifier in order to detect the output response of the system, and the design of a proportional-integral-derivative controller, where spherical pruned multi-objective differential evolution algorithm is used in order to optimize the controller gains. The proposed method, unfortunately, does not provide an optimal controller, which can be explained by the complexity of the benchmark system. With such results, the authors believe a better multi-objective problem definition is necessary. Also, it is concluded that such benchmark presents a real challenge for future controller design methndologies.

关键词： Optimization Process control Benchmark testing Tuning PD control Genetic algorithms

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A genetic algorithm based method to support the geometric prosthesis modelling in skull repairing

A genetic algorithm based method to support the geometric pr...

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2013 International Conference on Biomedical engineering and Environmental engineering (ICBEEE 2013)

作者： Marcelo Rudek Osiris Canciglieri Junior Thiago Greboge Anderson Luis Szejka Industrial and Systems Engineering Post-Graduate Program PPGEPSPontifical Catholic University of ParanaPUCPR

This paper addresses the problem of the geometric modeling of prosthesis to correct defects in skull bone by computational approach viewpoint. The missing area in a defective skull can be virtually filled by a criterion based on the curvature of the skull shape. The basic argument is that in a computed tomography, the 2D skull border in slice image is similar to a rounded form. This research is proposing a method to find adjusted ellipses on its curvature by Ellipse Adjustment Algorithm(EAA) technique. If the ellipse is correctly adjusted in each computed tomography slice, the resulting arcs that fill the missing area can be built in 3D in order to complete an unknown region in the bone. The problem is that there are many possible solutions and the selection of the best ellipse that fits the contour shape is performed by a Genetic Algorithm(GA). The piece of bone that was missed in skull can be built as a synthetic image to fill a hole at defect position in the skull. With the ellipse parameters it is possible to generate profiles with its set of points in order to build the 3D model using a CAD system. The case study shows the use of the method applied to non-symmetric defects and presents the obtained results.

关键词： Prosthesis modelling tomography images genetic algorithm

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Comparison between two FPGA implementations of the particle swarm optimization algorithm for high-performance embedded applications

Comparison between two FPGA implementations of the particle ...

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424464388

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. There are several embedded applications which requires to solve online optimization problems with a high performance. However, the PSO suffers on large execution times, and this fact becomes evident when using Reduced Instruction Set Computer (RISC) microprocessors in which the operational frequencies are low in comparison with the high operational frequencies of traditional personal computers (PCs). This paper compares two hardware implementations of the parallel PSO algorithm using an efficient floating-point arithmetic which perform computations with large dynamic range and high precision. The full-parallel and the partially-parallel PSO architectures allow the parallel capabilities of the PSO to be exploited in order to decrease the running time. Three well-known benchmark test functions have been used to validate the hardware architectures and a comparison in terms of cost in logic area, quality of the solution and performance is reported. In addition, a comparison of the execution time between the hardware and two C-code software implementations, based on a Intel Core Duo at 1.6GHz and a embedded Microblaze microprocessor at 50MHz, are presented. © 2010 IEEE.

关键词： Global optimization

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Current Issues in the Flexibilization of Smart Product-Service systems and their Impacts in Industry 4.0

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Procedia Manufacturing 2020年 51卷 1153-1157页

作者： Athon F.C.S. de Moura Leite Matheus B. Canciglieri Yee Mey Goh Radmehr P. Monfared Eduardo de F. Rocha Loures Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba – Paraná Brazil School of Mechanical Electrical and Manufacturing Engineering Loughborough University Loughborough – Leicestershire United Kingdom

In Industry 4.0, trends on Servitisation are intertwined with increased use of “smart technologies”, bringing light to Smart Product-Service systems. Currently, Smart-PSSs need to cope with dynamic customer’s needs, which generates system requirements in a higher frequency, resulting in reconfiguration of such system. This research aims to study current issues regarding the reconfiguration of Smart-PSSs, focusing on flexibilization. An exploration of issues is done by a qualitative literature review, with results structured in a schema. This schema approaches issues which are not yet solved or addressed in literature, showing that systemic solutions are necessary to solve explored issues. A discussion of current limitations and trends in research is presented, bridging studied material and pointing out current Industry 4.0 technologies that might cope with the issues if approached systemically. The paper points to further research regarding a expansions on the literature review and next steps on solving current issues.

关键词： Smart Product-Service System Semantic Interoperability Industry 4.0 Flexible Smart Product-Service System

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A pyrex nanochannel device fabricated by AFM nanolithography

A pyrex nanochannel device fabricated by AFM nanolithography

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7th IEEE International Conference on Nano/Micro Engineered and Molecular systems, NEMS 2012

作者： Hibbert, Orain Busch, Taylor Tung, Steve Micoelectronics-Photonics Graduate Program University of Arkansas Fayetteville AR 72701 United States Department of Mechanical Engineering University of Arkansas Fayetteville AR 72701 United States

ISBN: (纸本)9781467311243

A Pyrex nanochannel device was fabricated using AFM nanolithography in conjunction with MEMS-based microfabrication. The fabrication process began with the patterning of microchannels on a Pyrex substrate using photolithography and wet etching. AFM nanolithography was then performed to realize a nanochannel between the micro reservoirs. A diamond-coated AFM probe with a relatively large force constant served as the cutting tool. A detailed study was conducted to determine the relationship between the AFM input parameters and the resultant nanochannel dimensions. A linear trend was obtained between the AFM scratch force and the nanochannel depth. A similar trend was also observed between the number of repeated scratches and the channel depth. Minimal material pileup on the nanochannel sidewall was observed during the scratch process. Flow patency in the capped-off nanochannel was demonstrated through fluorescence microscopy. © 2012 IEEE.

关键词： Atomic force microscopy

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Improved quantum-inspired evolutionary algorithm with diversity information applied to economic dispatch problem with prohibited operating zones

Improved quantum-inspired evolutionary algorithm with divers...

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作者： Neto, Júlio Xavier Vianna De Andrade Bernert, Diego Luis Dos Santos Coelho, Leandro Pontifical Catholic University of Parana PUCPR Undergraduate Program at Mechatronics Engineering Imaculada Conceição 1155 Zip code 80215-901 Curitiba Parana Brazil Pontifical Catholic University of Parana PUCPR Industrial and Systems Engineering Graduate Program LAS/PPGEPS Imaculada Conceição 1155 80215-901 Curitiba Parana Brazil

The objective of the economic dispatch problem (EDP) of electric power generation, whose characteristics are complex and highly nonlinear, is to schedule the committed generating unit outputs so as to meet the required load demand at minimum operating cost while satisfying all unit and system equality and inequality constraints. Recently, as an alternative to the conventional mathematical approaches, modern meta-heuristic optimization techniques have been given much attention by many researchers due to their ability to find an almost global optimal solution in EDPs. Research on merging evolutionary computation and quantum computation has been started since late 1990. Inspired on the quantum computation, this paper presented an improved quantum-inspired evolutionary algorithm (IQEA) based on diversity information of population. A classical quantum-inspired evolutionary algorithm (QEA) and the IQEA were implemented and validated for a benchmark of EDP with 15 thermal generators with prohibited operating zones. From the results for the benchmark problem, it is observed that the proposed IQEA approach provides promising results when compared to various methods available in the literature. © 2010 Elsevier Ltd. All rights reserved.

关键词： Optimization

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Accelerating the artificial bee colony algorithm by hardware parallel implementations

Accelerating the artificial bee colony algorithm by hardware...

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2012 IEEE 3rd Latin American Symposium on Circuits and systems, LASCAS 2012

作者： Muñoz, Daniel M. Llanos, Carlos H. Coelho, Leandro Dos S. Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781467312080

Artificial bee colony (ABC) is an optimization algorithm inspired on the intelligent behavior of honey bee swarms. It is suitable to be applied when mathematical techniques are impractical or provide suboptimal solutions. As a population-based algorithm, the ABC suffers on large execution times specifically for embedded optimization problems with computational limitations. For that we propose a hardware parallel architecture of the opposition-based ABC algorithm (HPOABC) that facilitates the implementation in Field programmable Gate Arrays (FPGAs). Numerical simulations using four well-known benchmark problems demonstrate that the opposition-based approach allows the algorithm to improve its functionality, preserving the swarm diversity. Additionally, synthesis results point outs that the HPOABC architecture is effectively mapped in hardware and is suitable for embedded applications. © 2012 IEEE.

关键词： Global optimization

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Investigation of a geometrical base parameter affecting on bending quality in a thin sheet metal 1st

Investigation of a geometrical base parameter affecting on b...

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1st International Conference on engineering Innovation, ICEI 2016

作者： Blattler, Aran Kamonrattanapisud, Maitri Intarakumthornchai, Thanasan Aue-U-lan, Yingyot program Sirindhorn International Thai-German Graduate School of Engineering King Mongkut's University of Technology North Bangkok Thailand Department of Industrial Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Thailand

ISBN: (纸本)9783038356912

A geometrical base parameter is investigated to determine the effect on a bending quality of a thin sheet metal for a roll forming process. This parameter is usually used as a criterion for the quality control of incoming materials for the bending process. This study was conducted by using a FEM simulation. The determination of the geometrical base parameter was considered as an appropriate and unique characteristic for each type of materials. To find this geometrical base parameter, the dimensions of the workpiece must be measured while loading. The sensitivity of the bend allowance of a sheet metal was dependent on this geometrical base parameter. The high geometrical base parameter was led to indicate the elongation and the strength of the material. The principles of the geometrical base parameter are dependent on several factors, such as the bending angle, bending radius, material thickness, bend allowance, bending types and mechanical properties of materials. The outcomes of this study could provide the information used to enhance the bend quality of the sheet metal. © 2017 Trans Tech Publications.

关键词： Sheet metal

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