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2018 Institute of industrial and systems Engineers Annual Conference and Expo, IISE 2018

作者： Beller, Cassiano Souza Muncinelli, Gianfranco De Lima, Edson Pinheiro Deschamps, Fernando Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Federal University of Technology - Parana Curitiba Brazil Department of Mechanical Engineering Federal University of Parana Curitiba Brazil

Industry 4.0 has recently become an ubiquitous topic of study both by academics and practitioners. Beyond the technology application domain, one major issue that most organizations have to face when structuring their efforts towards Industry 4.0 is the identification of viable opportunities for the deployment of Industry 4.0-related technologies. Proof of concept projects are usually developed to address this, as they are an exploratory means to quickly assess the application of a given technology to a specific context. If results are positive, these projects may grow into larger projects that will be used to deploy the considered technologies in a wider scale. This work aims to propose a framework that helps facilitate the assessment of proof of concept projects and their transition into wider scale projects. This framework is based both in the existing literature on Industry 4.0 technologies and in case studies of proof of concept projects that were used to assess such technologies. The framework is composed of three main components: the technologies being evaluated, the design objectives that they meet and the outcomes that are expected. The relationships among these components is also considered, and a process that mediates their use is proposed. © 2018 Institute of industrial Engineers (IIE). All rights reserved.

关键词： Project management

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Use of PROMETHEE Method for Decision Making in Bus Fleet Maintenance Proposal of Framework

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Procedia Manufacturing 2019年 39卷 1913-1920页

作者： Alexandre Milkiewicz Sanches Eduardo de Freitas Rocha Loures Edson Pinheiro de Lima Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Curitiba 80215-901 Brazil Federal institute of Paraná (IFPR) Curitiba 82530-200 Brazil Federal University of Technology – Parana (UTFPR) Pato Branco 85503-390 Brazil

In the business environment, decision making is a differential when the team responsible for it does it right. This implies some assumptions, such as knowledge of the activity, internal and external variables that impact the company’s business, as well as the quality of the workforce. Thus, when the maintenance issue is addressed, be it in industrial or service companies, the expected results will be translated by the satisfaction indexes of its users. This work aims to propose a framework with the elements that lead to the proper decision making in maintenance for bus companies. For this, the multicriteria decision-making method chosen was PROMETHEE. The PROMETHEE method has the flexibility to treat data both qualitatively and quantitatively, offering different scenarios to managers on the best decision to make. It is known that companies seek to minimize their maintenance costs and maximize the quality of service provided.

关键词： Maintenance costs decision making multicriteria method

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A Proposal for the Support of Demand Required from Production Through the Alignment of Production Planning and Control Strategies and Maintenance Planning and Control: An Analytical Approach

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Procedia Manufacturing 2019年 39卷 868-876页

作者： Alexandre Milkiewicz Sanches Lourival José de Souza Sergio E. Gouvea da Costa Edson Pinheiro de Lima Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba 80215-901 Brazil Federal institute of Parana (IFPR) Curitiba 82530-200 Brazil Federal University of Technology – Parana (UTFPR) Pato Branco 85503-390 Brazil

Operation and maintenance are important administrative and operational functions of the production, as they can guarantee the required demand. Together, they have the responsibilities of doing right (quality advantage), fast (speed advantage), timely (reliability advantage), quick setup (flexibility advantage) and affordability. In addition, they are close to several important activities such as: safety, environment, productivity, marketing, quality, reliability and accounting systems. With this new vision, changes and opportunities are being presented to these sectors of operation and maintenance. In the new paradigm, the maintenance and operation teams are motivated to strategically guarantee the full operation of the production system and not only to preserve the equipment. And, thus, to develop an efficient strategy, providing the sustainability and the increase of the assets of the company, reaching the goals of the planning and control of the production established by the company. The main objective of this work is to analyze a proposal to meet the required production demand through the alignment of production control planning strategies and maintenance planning and control. The analysis of the research points to some significant contributions, for example, to the areas of strategy and logistics of organizations that work mainly in environments with a high level of competitiveness. Through a case study, the analysis pointed to the positive impact of alignment on parameters such as: sustainability of the competitive strategy, productivity, costs, reliability and availability of physical assets, and flexibilization of the productive organizational system.

关键词： Maintenance management production management competitive strategy production strategy competitive priorities

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An Efficient Decision-Making Approach for the Planning of Diagnostic Services in a Segmented Healthcare System

An Efficient Decision-Making Approach for the Planning of Di...

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作者： Mendoza-Gómez, Rodolfo Ríos-Mercado, Roger Z. Valenzuela-Ocaña, Karla B. Tecnológico de Monterrey Campus Toluca School of Engineering and Architecture Av. Eduardo Monroy Cárdenas 2000 San Antonio Buenavista Toluca 50110 Mexico Graduate Program in Systems Engineering AP 111-F Cd. Universitaria San Nicolás de los Garza NL 66455 Mexico Tecnológico de Monterrey Campus Toluca Department of Industrial Engineering Av. Eduardo Monroy Cárdenas 2000 San Antonio Buenavista Toluca 50110 Mexico

In this paper, we address a decision-making problem related to the requirement of costly equipment by medical diagnostic services in a segmented public healthcare system comprising several institutions and private providers. The problem is motivated by a real-world case of the Mexican healthcare system. The aim of this study is to determine which hospitals can provide the service, their capacity levels, the allocation of demand in each institution, and the referral of patients to other institutions or private providers while minimizing annual investment costs and operating costs required to satisfy demand. A mixed-integer linear programming model that takes into account different characteristics such as patient acuity levels, types of equipment, and demand variation through time is introduced. The model was empirically assessed to evaluate its impact on the decision-making process. A sensitivity analysis to evaluate solution behavior for variations of critical parameters was performed. The results showed that some values could generate a significant effect on the total costs for the service coverage and in the efficiency of the service, whereas overall results indicated the usefulness of the model. While this model is valuable to aid this decision-making problem, it is limited to medium-size instances of up to 90 facilities. To solve the problems with larger instances, a two-phase heuristic algorithm is proposed. In the first phase, the method uses a greedy construction mechanism, and in the second phase, it attempts to improve the solution. Empirical evidence on large instances shows that good solutions with low computing times are reached in comparison with the exact method. © 2019 World Scientific Publishing Company.

关键词： Operating costs

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A WebLab Control Experiment using the Ball and Beam System and Multiobjective Optimization

A WebLab Control Experiment using the Ball and Beam System a...

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Experiment@ International Conference (exp.at)

作者： Ricardo Massao Kagami Guinther Kovalski da Costa Luciano Antônio Mendes Roberto Zanetti Freire Industrial and Systems Engineering Graduate Program – PPGEPS Pontifícia Universidade Católica do Paraná – PUCPR Curitiba Brazil Department of Control and Automation Engineering Pontifícia Universidade Católica do Paraná - PUCPR Curitiba Brazil

By associating active learning methodologies and digital media as a form to improve educational quality, the diversity of experimentations in engineering education has been motivating researches in many areas with possibilities of increasing both students' knowledge and skills. Control engineering is an area where educational laboratories are usually costly, thus the use of virtual laboratories for remote experimentation became an interesting approach. In this work, it is presented a remote experimentation procedure for the ball and beam system, which is a nonlinear and unstable open loop process. Considering the advanced control topic, multiobjective optimization was introduced in the experiment in order to tune Proportional-Integral-Derivative (PID) controllers. Through the description of the system model, the multiobjective optimization technique, and the experiment configuration, students can simulate and test their controllers remotely in a real plant.

关键词： Laboratories Mathematical model PD control Optimization Process control PI control

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ELSA-Py - Open-Source Extension for Communication and Data Management in Interactive Remote Experimentation Under Ilab Shared Architecture

ELSA-Py - Open-Source Extension for Communication and Data M...

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APCA International Conference on Automatic Control and Soft Computing (CONTROLO)

作者： Thiago Schaedler Uhlmann Pedro Henrique Dos Santos Sbais Luciano Antonio Mendes Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

Paper depicts an architecture expansion for communication and data management that can be used in Remote Experimentation and Game-Based Learning. This architecture is compliant with iLab Shared Architecture and is based upon open source software and hardware, in particular low cost platforms such as the Raspberry Pi 3. It consists of three main entities: user-side interface, experiment-side (lab) application and, interconnecting both, the cloud server enhanced with the messaging intermediator. Architecture takes into account typical requirements for educational institutions, such as open-source technologies, remote systems usage management (service brokerage) and security. In trial implementations, three single-user, remotely operated experiments have been enabled using ELSA-Py, in which students will be able to practice concepts of lean production (LyMIE), object position control (Windball) and image calibration (TabRecon). The integration has been tested and the performance of ELSA-Py architecture as a tool do deploy educational remotely operated systems is discussed.

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Design approach for additive manufacturing in spare part supply chains

arXiv

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arXiv 2020年

作者： de Brito, Filipe Marinho da Cruz Júnior, Gélson Frazzon, Enzo Morosini Basto, João Pedro Tavares Vieira Alcalá, Symone Gomes Soares School of Electrical Mechanical and Computer Engineering Federal University of Goiás GoiâniaGoiás74605-010 Brazil INESC P&D Brasil São Paulo11055-300 Brazil Graduate Program in Production Engineering Department of Production Engineering and Systems Federal University of Santa Catarina Florianópolis88040-900 Brazil Department of Industrial Engineering and Management Faculty of Engineering University of Porto Porto4200-465 Portugal INESC TEC - Technology Faculty of Engineering University of Porto Porto4200-465 Portugal Production Engineering Faculty of Sciences and Technology Federal University of Goiás Aparecida de Goiânia Goiás74968-755 Brazil

In the current industrial revolution, additive manufacturing (AM) embodies a promising technology that can enhance the effectiveness, adaptability, and competitiveness of supply chains (SCs). Moreover, it facilitates the development of distributed SCs, thereby enhancing product availability, inventory levels, and lead time. However, the wide adoption of AM in industrial SCs creates various challenges, leading to new difficulties for SC design. In this context, this paper proposes a new design approach to AM SCs using optimization methods. More specifically, the proposed approach, comprising the pmedian and mixed-integer linear programming models, considers the decision of deploying productive resources (3D printers) in specific locations of generic spare part SCs. The approach was evaluated in a real-world use case of an elevator maintenance service provider. The obtained results demonstrated the promising capabilities of the proposed design approach in managing the challenges arising from the forthcoming widespread use of 3D printers in manufacturing SCs. © 2020, CC-BY-NC-ND.

关键词： 3D printers

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Numerical analysis of general-vibration-based method for structural health monitoring

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AIP Conference Proceedings 2020年第1期2227卷

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita 1Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 2Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 3Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 4Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

For damage detection, this research article discusses an easy-to-compute damage index derived from the governing dynamic of the structure that has potential practical application in Structural Health Monitoring (SHM). The research uses simplified structural models to explore the sensitivity of the index to damages, to compare the index performance with a traditional but popular damage detection method, and to understand the local/global predictive capability of the index. The research uses two simple models, namely, single- and two-degree-of-freedom systems. The results suggest that the damage index is local, that can only monitor damages occurring near the points of measurements, but it is sensitive to damages, unlike the natural frequency, which is global but less sensitive.

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The accuracy of the F statistic for structural health monitoring

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AIP Conference Proceedings 2020年第1期2227卷

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita 1Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 2Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 3Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 4Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Understanding the reliability of engineering methods is crucial for its adoption and deployment. This research focuses on the reliability of the Power Spectral Density (PSD) method via the use of the F statistic for damage detection. To the author best knowledge, the method is rather classic but its realibility has not been discussed in the context of a large data size. Priory, the research anticipates that the accuracy is a function of the damage level. In this study, we evaluate 3500 cases with five levels of structural integrity, namely, healthy condition and damaged conditions with 1%, 5%, 10%, and 20% damage levels. The dataset is established via a numerical analysis of a seven degree-of-freedom system loaded with a concentrated dynamic force with random magnitude. A spring on the system is reduced in its stiffness to simulate damages. Our significant findings are the following: it is challenging for the PSD-based method to differentiate the healthy condition from the damaged conditions when the damage level is small. However, the reliability is high at 95% probability when the structural integrity has dropped by five percent.

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Multi-objective Support Vector Machines Ensemble Generation for Water Quality Monitoring

Multi-objective Support Vector Machines Ensemble Generation ...

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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 Parana (PUCPR) Curitiba Brazil

Real-world classification problems generally deal with imbalanced data, where one class represents the majority of the data set. The present work deals with event detection on a drinking-water quality time series, where the presence of a quality event is the minority class. In order to solve such problems, supervised learning algorithms are recommended. Researchers have also used multi-objective optimization (MOO) in order to generate diverse models to build ensembles of classifiers. Although MOO has been used for ensemble member generation, there is a lack on it's application for member selection, which is usually done by selecting a specific subset from the resulting models, or by using meta-algorithms, such as boosting. The proposed work comprises the application of MOO design in the whole process of ensemble generation. To do so, one multi-objective problem (MOP) is defined for the creation of a set of non-dominated solutions with Pareto-optimal support vector machines (SVM). After that, a second MOP is defined for the selection of such SVMs as members of an ensemble. Such methodology is compared to other member selection methods, such as: the single best classifier, an ensemble composed of the full set of non-dominated solutions, and the selection of a specific subset from the Pareto front. Results show that the proposed method is suitable for the creation of ensembles, achieving the highest classification scores.

关键词： Support vector machines Optimization Mood Training Event detection Kernel Supervised learning

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