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Knowledge-Data Driven for Cyber-Physical Production systems in the Aerospace Industry: Current Issues and Emergent Technologies

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IFAC-PapersOnLine 2024年第19期58卷 1162-1167页

作者： Murillo Skrzek Anderson L. Szejka Fernando Mas Maria Jose Escalona Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil University of Seville (US) Seville Spain CT Engineering Group Spain

The aerospace manufacturing industry exhibits significant complexity in all its tasks. For instance, the aircraft’s main body comprises several components with multiple dimensions, geometries, and materials. This kind of manufacturing system is specialised in creating aerospace parts characterised by advanced technology, limited production quantities, and a high degree of customisation. The aerospace products and the corresponding manufacturing systems have extensive life cycles spanning decades and are repurposed to accommodate product variations. Any disturbance during the project progression has the potential to result in escalated expenses and time investments, leaving economic and environmental drivers. In this way, Cyber-Physical Production systems (CPPS) are emerging to reduce misinterpretation and mistakes across all stages of the manufacturing process. Therefore, the main aim of this paper is to discuss the current issues and emergent technologies across the literature review to address the following Research Issue 1 (RI1): What are the current issues and emergent technologies in CPPS and KDD for the Aerospace Industry? Research Issue 2 (RI2): What is the gap in CPPS and KDD for the aerospace industry? This initial literature review is concentrated on the Knowledge data-driven (KDD) to aid in developing CPPS for Aerospace Sheet Metal (ASM) parts manufacturing and examining the use of CPPS in the aerospace sector. Finally, this research contributes to the research community with an initial overview of research trends in the domain of KDD for CPPS in the aerospace industry and finds the main research gaps in this area.

关键词： Knowledge data-driven Cyber-Physical Production System Aerospace Industry Content Analysis

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Hardware particle swarm optimization based on the attractive-repulsive scheme for embedded applications

Hardware particle swarm optimization based on the attractive...

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2010 International Conference on Reconfigurable Computing and FPGAs, ReConFig 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 DF 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 DF Brazil

ISBN: (纸本)9780769543147

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from premature convergence and high elapsed time when solving multimodal and large scale engineering problems. This problem becomes an evident drawback for embedded applications in which the microcontrollers often operates at low computational capacity. This paper proposes a hardware implementation of a parallel self-adaptive PSO algorithm based on an attractive-repulsive scheme and using the efficient floating-point arithmetic which performs computations with large dynamic range and high precision. The parallel capabilities of the PSO are exploited by implementing parallel particles directly in hardware in order to decrease the running time. In addition, the attractive-repulsive technique avoids the premature convergence problem by self-adapting the swarm behavior according to its diversity. Synthesis and simulation results for benchmark test problems were performed, demonstrating the correctness of the proposed architectures. Finally, an elapsed time comparison between the hardware and software implementations shows the suitableness of the proposed architecture for embedded applications. © 2010 IEEE.

关键词： Global optimization

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A Study of the Sensitivity of the Fuel Consumption to Driving Strategy by Micro Simulation

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Procedia Computer Science 2019年 157卷 375-381页

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information Systems Information Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Global warming due to excessive emission greenhouse gases is a significant issue faced by humanity, and collectively, cars and trucks contribute about 20% to the entire global-warming gases. For a reason, recently, many attempts have been endured to reduce the emission and to increase fuel efficiency, including vehicle platooning, better driving strategy, and increasing engine efficiency. This study intends to provide a more detail assessment regarding the effects of the driving strategy to fuel consumption. For the purpose, the vehicle dynamics are quantified by employing the car-following model based on the optimal velocity model. The fuel consumption is estimated from the regression model of Ahn 18 . The result suggests that the braking distance strongly affects fuel consumption.

关键词： Optimal Velocity Model Micro Simulation Car-Following Model Fuel Efficiency

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A normative differential evolution approach for estimation of heat transfer coefficient during freezing treatment by inverse analysis

A normative differential evolution approach for estimation o...

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IEEE Congress on Evolutionary Computation

作者： Mariani, Viviana Cocco Klein, Carlos Eduardo Luvizotto, Luiz Guilherme Justi Dos Santos Coelho, Leandro Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paran Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil

ISBN: (纸本)9781424478347

Among the existing meta-heuristic optimization algorithms, a well-known branch is the differential evolution (DE). DE is a powerful population-based algorithm of evolutionary computation field designed for solving global optimization problems which only has a few control parameters. With an eye to improve the performance of DE, in this paper, a DE approach combined with a cultural algorithm technique based on normative knowledge (NDE) is investigated to estimate the heat transfer coefficient during freezing treatment by inverse analysis. Numerical results for inverse heat transfer problem demonstrate the applicability and efficiency of the NDE algorithm. In this application, NDE approach outperforms a classical DE approach in terms of quality of solution. © 2011 IEEE.

关键词： Inverse problems

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Cauchy particle swarm optimization with dynamic adaptation applied to inverse heat transfer problem

Cauchy particle swarm optimization with dynamic adaptation a...

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2010 IEEE International Conference on systems, Man and Cybernetics, SMC 2010

作者： Mariani, Viviana Cocco Neckel, Vagner Jorge Grebogi, Rafael Bartnik Dos Santos Coelho, Leandro Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil

ISBN: (纸本)9781424465880

The particle swarm optimization (PSO) algorithm is a member of the wide category of swarm intelligence methods for solving global optimization problems. Its basic idea is the simulation of simplified animal social behaviors such as fish schooling and bird flocking. PSO algorithms are attracting attentions in recent years, due to their ability of keeping good balance between convergence and diversity maintenance. Several attempts have been made to improve the performance of the original PSO algorithm. In this paper, a modified version of the original PSO based on Cauchy distribution and dynamic adaptation of inertia factor, named modified PSO (MPSO), is proposed. to estimate the unknown variables of an inverse heat transfer problem. To validate the optimization performance of the proposed MPSO, an inverse heat transfer problem is illustrated and the algorithm has to estimate its unknown variables. The results testify that the MPSO can perform well in an inverse heat transfer problem. ©2010 IEEE.

关键词： Heat transfer

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Controller tuning with multi-objective optimization: benchmark definitions for SISO linear systems: A PI controller case ⁎

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IFAC-PapersOnLine 2024年第7期58卷 126-131页

作者： Gilberto Reynoso-Meza Ricardo Massao Kagami Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Control Systems Optimization Laboratory (LOSC) Pontifícia Universidade Católica do Paraná (PUCPR)

Multi-objective optimization techniques are practical techniques for controller tuning purposes. A wide variety of papers use such an approach or propose new algorithms to approximate the Pareto front. Nevertheless, despite the expressive volume of works dealing with it, there is no standard benchmark testbed that could be used as a baseline comparison among different techniques. This work addresses such a gap, with a first step proposing a linear-SISO testbed with guidelines and rules and providing a basic example for a PI controller. Such a benchmark is expected to promote further research on the topic.

关键词： Multi-objective optimization Parametric optimization Evolutionary Algorithms

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Developing a sustainable operations maturity model (SOMM) 22

Developing a sustainable operations maturity model (SOMM)

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22nd International Conference on Production Research, ICPR 2013

作者： Machado, C.G. Pinheiro De Lima, E. Gouvea Da Costa, S.E. Cestari, J.M.A.P. Kluska, R.A. Hundzinski, L.N. Industrial and Systems Engineering Graduate Program Pontifical Catholic Univeristy of Paraná-PUCPR R. Imaculada Conceição 1155 Curitiba Paraná Brazil Federal University of Technology-Paraná Av. Sete de Setembro 3165 Curitiba Paraná Brazil

The concepts associated with sustainability have been gradually incorporated into business models in recent years. Particularly in the field of Operations Management (OM), the adoption of new performance indicators and the revision of operations strategy content and process frameworks are changing the way companies manage their operations regarding sustainability, creating the right conditions for new operations management model development. Such models were created in order to assess the impact and to characterize the progress of new initiatives in sustainability in the economic, environmental and social spheres (Triple Bottom Line-TBL). This paper, based on academic literature and professional models, proposes a framework for verifying the level of maturity of sustainable operations. Its distinguishing aspect contemplates the integrated approach over TBL along five proposed maturity levels, followed by descriptions of context, structure, processes, value chain and functional recommendations on implementation. The main objective of the Sustainable Operations Maturity Model (SOMM) is to be applied as a managerial tool to support organizations when evaluating the integration of sustainability into their strategies, and especially to provide guidelines for the evolution of sustainable operation processes.

关键词： Sustainable development

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A case study on statistical characterization and optimization of coercivity in cobalt ferrite nanoparticles

A case study on statistical characterization and optimizatio...

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作者： Cedeño-Mattei, Y. Sánchez-Peña, M.L. Lara-Rodríguez, Y. Perales-Pérez, Ó. Cabrera-Ríos, M. Engineering Science and Materials Department University of Puerto Rico at Mayagüez Mayagüez Puerto Rico Industrial Engineering Department University of Puerto Rico Mayagüez Mayagüez 00681-9000 Puerto Rico Graduate Program in Systems Engineering University of Nuevo León Nuevo León Mexico

Characterization and optimization of material properties during synthesis and processing are frequent problems in materials science and engineering. In the present paper, the use of design of experiments (DOE) to characterize and improve coercivity in cobalt ferrite nanoparticles is described. The sequence of experiments was planned to capitalize on previous experimental runs available. Emphasis is placed on the rationale for choosing the additional runs. The results reveal that the choice of an adequate initial experimental design can save effort and resources in arriving at useful conclusions upon which subsequent experimental runs can be planned, capitalizing on the initial experimental structure. A region with attractive solutions in terms of coercivity, including a local maximum, was identified through the experimental sequences described in this case study. © 2011 Authors.

关键词： Design of experiments

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A chaotic firefly algorithm applied to reliability-redundancy optimization

A chaotic firefly algorithm applied to reliability-redundanc...

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IEEE Congress on Evolutionary Computation

作者： Dos Santos Coelho, Leandro De Andrade Bernert, Diego Luis Mariani, Viviana Cocco Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paran Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paran Imaculada Conceição 1155 80215-901 Curitiba Paran Brazil

ISBN: (纸本)9781424478347

The reliability-redundancy allocation problem can be approached as a mixed-integer programming problem. It has been solved by using optimization techniques such as dynamic programming, integer programming, and mixed-integer nonlinear programming. On the other hand, a broad class of meta-heuristics has been developed for reliability-redundancy optimization. Recently, a new meta-heuristics called firefly algorithm (FA) algorithm has emerged. The FA is a stochastic metaheuristic approach based on the idealized behavior of the flashing characteristics of fireflies. In FA, the flashing light can be formulated in such a way that it is associated with the objective function to be optimized, which makes it possible to formulate the firefly algorithm. This paper introduces a modified FA approach combined with chaotic sequences (FAC) applied to reliability-redundancy optimization. In this context, an example of mixed integer programming in reliability-redundancy design of an overspeed protection system for a gas turbine is evaluated. In this application domain, FAC was found to outperform the previously best-known solutions available. © 2011 IEEE.

关键词： Integer programming

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A Harmony search algorithm combined with differential operator applied to reliability-redundancy optimization

A Harmony search algorithm combined with differential operat...

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2009 IEEE International Conference on systems, Man and Cybernetics, SMC 2009

作者： Dos Santos Coelho, Leandro De Andrade Bernert, Diego Luis Mariani, Viviana Cocco Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil

ISBN: (纸本)9781424427949

The reliability-redundancy allocation problem can be approached as a mixed-integer programming problem. It has been solved by using optimization techniques such as dynamic programming, integer programming, and mixed-integer nonlinear programming. On the other hand, a broad class of meta-heuristics has been developed for reliability-redundancy optimization. Recently, a new meta-heuristics called harmony search (HS) algorithm has emerged. HS was conceptualized using an analogy with music improvisation process where music players improvise the pitches of their instruments to obtain better harmony. This paper introduces a modified HS approach combined with an operator of differential evolution - a paradigm of evolutionary computation - to solve optimization problems in reliability engineering. In this context, an example of mixed integer programming in reliability-redundancy design of an over-speed protection system for a gas turbine is evaluated. In this application domain, HS was found to outperform the previously best-known solutions available. ©2009 IEEE.

关键词： Integer programming

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