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IISE Annual Conference and Expo 2021

作者： Santos, Reginaldo Carreiro de Lima, Edson Pinheiro da Costa, Sérgio Eduardo Gouvêa Deschamps, Fernando Industrial and Systems Engineering Graduate Program Pontifícia Universidade Católica do Paraná PR Curitiba Brazil

ISBN: (纸本)9781713838470

The technological paradigm shift is supporting the digital transformation of manufacturing, characterized by emerging industry 4.0 technologies, and the inherent complexity in selecting appropriate technologies. This increasing complexity of technologies, the multiple and conflicting decision criteria, and the abundance of technology alternatives demand a structured process for managers to select technologies to be acquired and implemented. This work derived from the observation of a real problem in a recognized world class automaker company. The identified problem consists in a lack of a consolidated process (procedure) to support managers and specialists in selecting industry 4.0 technologies. This paper aims at extending theory concerning technology management and selection, by proposing a research agenda regarding the solution for the defined problem. A systematic literature review (SLR) is performed to support it, comprising the analysis and synthesis of a review portfolio. The construction of a structured procedure for industry 4.0 technology selection would serve two purposes: (i) to identify the most suitable technology to solve a specific problem, (ii) to support the creation of a technology roadmap to ground a long-term investment plan. The procedure should be able to deal with both purposes to support firms in a digital transformation journey, enabling an objective, rational and traceable decision-making process. © 2021 IISE Annual Conference and Expo 2021. All rights reserved.

关键词： Industry 4.0

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CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BASED ON ARTIFICIAL NEURAL NETWORKS AND TREE DECISION MODELS 15

CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BAS...

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15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on Computer Science and Information systems, MCCSIS 2022

作者： Yazdanpanah, Hamed Silva, Augusto C.M. Guedes, Murilo Morales, Hugo M.P. dos Coelho, Leandro S. Moro, Fernando G. Department of Research Robô Laura PR Curitiba Brazil Department of Computer Science University of São Paulo SP São Paulo Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana PR Curitiba Brazil Electrical Engineering Graduate Program Federal University of Parana PR Curitiba Brazil

ISBN: (纸本)9789898704405

Early recognition of clinical deterioration (CD) has vital importance in patients’ survival from exacerbation or death. Electronic health records (EHRs) data have been widely employed in Early Warning Scores (EWS) to measure CD risk in hospitalized patients. Recently, EHRs data have been utilized in Machine Learning (ML) models to predict mortality and CD. The ML models have shown superior performance in CD prediction compared to EWS. Since EHRs data are structured and tabular, conventional ML models are generally applied to them, and less effort is put into evaluating the artificial neural network’s performance on EHRs data. Thus, in this article, an extremely boosted neural network (XBNet) is used to predict CD, and its performance is compared to eXtreme Gradient Boosting (XGBoost) and random forest (RF) models. For this purpose, 103,105 samples from thirteen Brazilian hospitals are used to generate the models. Moreover, the principal component analysis (PCA) is employed to verify whether it can improve the adopted models’ performance. The performance of ML models and Modified Early Warning Score (MEWS), an EWS candidate, are evaluated in CD prediction regarding the accuracy, precision, recall, F1-score, and geometric mean (G-mean) metrics in a 10-fold cross-validation approach. According to the experiments, the XGBoost model obtained the best results in predicting CD among Brazilian hospitals’ data. © 2022 15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on Computer Science and Information systems, MCCSIS 2022. All rights reserved.

关键词： Neural networks

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Portfolio Selection and Comparative Portfolio Analysis of Transportation Services, Hotel and Leisure, and Education Subsectors Against Service Sector in the Philippine Market Using Mean-variance Model

Portfolio Selection and Comparative Portfolio Analysis of Tr...

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2024 IEEE International Conference on industrial engineering and engineering Management, IEEM 2024

作者： Cruz, E.L. Young, M.N. Chuahay, T.N. Prasetyo, Y. Persada, S. Nadilfatin, R. Contreras, M. School of Industrial Engineering and Engineering Management Mapua University Manila Philippines School of Graduate Studies Mapua University Manila Philippines Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350386097

This paper presents a framework for portfolio selection in the transportation services, hotel and leisure, and education subsectors of the Philippine market using the mean-variance model. Using the service sector and the broader market as benchmarks, this study spans 7,670 test days from January 1, 1993, to December 31, 2022, identifying optimal risk-return factors (RRFs) of 0.4 for transportation, 0.2 for hotel and leisure, and 0.3 for education. Furthermore, the higher percentage allocations the investors are recommended to invest in are International Container Terminal Services, Inc., Waterfront Philippines, Incorporated, and Far Eastern University, Incorporated. Paired t-test results, with p-values below 0.01 and 0.05, indicate these subsectors can outperform the service sector. The study also conducted a comparative analysis with 30-year historical data to crisis periods like the Global Financial Crisis (GFC) and the COVID-19 pandemic, exhibiting distinct performance trends and emphasizing the need for tailored strategies during economic disruptions. The findings of this research may provide an alternative portfolio selection model for investors seeking to optimize their investment portfolios. © 2024 IEEE.

关键词： Leisure

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Mean Variance Portfolio Selection Utilizing Services Subsector’s (Media, Telecommunications, and Information Technology) 30-Year Philippine Stock Exchange Trading Data

Mean Variance Portfolio Selection Utilizing Services Subsect...

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2024 IEEE International Conference on industrial engineering and engineering Management, IEEM 2024

作者： Salazar, E.D. Young, M.N. Chuahay, T.N. Pratseyo, Y. Persada, S. Nadilfatin, R. Contreras, Myra F. School of Industrial Engineering and Engineering Management Mapúa University Intramuros Philippines School of Graduate Studies Mapúa University Intramuros Philippines Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institur Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350386097

The Philippine Stock Exchange (PSE), established in 1927, has significantly evolved, especially since the 1980s with major reforms and technological advancements. This paper analyzes the performance of portfolios in the Media, Telecommunications, and Information Technology sectors listed on the PSE over a 30-year span. Using mean-variance analysis, it evaluates portfolio optimization by balancing risk and return. Drawing on data from 1993 to 2022, the study examines portfolios across various risk-return frontiers (RRFs) and compares the service sector's performance. The results highlight varying portfolio metrics across RRFs, with some showing outperformance and higher RRFs leading to diminishing returns. The study also identifies key companies with significant stock allocations, providing strategic insights for portfolio construction. These findings offer investors guidance on optimizing portfolio strategies within the PSE for better decision-making and investment outcomes. © 2024 IEEE.

关键词： mean-variance theory Philippine stock exchange portfolio selection service sector

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Multi-Objective Grey Wolf Optimizer for the Identification Process of a real MIMO System

Multi-Objective Grey Wolf Optimizer for the Identification P...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Allan Christian Krainski Ferrari Gideon Villar Leandro Leandro dos Santos Coelho Eletrical Engineering Department Federal University of Paraná UFPR Curitiba Brazil Electrical Engineering Graduate Program (PPGEE) Federal University of Paraná (UFPR) and Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR)

This article implements the multi-objective grey wolf optimizer (MOGWO) in the identification process of a multivariable system. For a sequence of 100 runs, MOGWO approach had compared and analyzed with the grey wolf optimizer (GWO), the single-objective version. In the computational simulation, the determination coefficient values and mean square error had used to analyze the quality of the models obtained. In the results, MOGWO showed superior to GWO to the differences between the order of magnitude of the system outputs. The implementation shows that MOGWO and other multi-objective metaheuristics can be an alternative method to solve problems of identification processes of multivariable systems.

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A preliminary discussion of digital transformation and semantic interoperability to support the information exchange in the business process 28

A preliminary discussion of digital transformation and seman...

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28th ISTE International Conference on Transdisciplinary engineering, TE 2021

作者： Nakano, Lucas Yoshio Bertoldi, Pedro Henrique Szejka, Anderson Luis Canciglieri Junior, Osiris Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Automation and Control Engineering Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9781643682082

The development of interoperability is more and more an essential task for all kinds of organizations. It needs to be measured, verified, and continuously improved. With the advent of the Internet of Things, Industry 4.0, Digital Transformation, as well as all technologies it brings, such as big data, cloud computing, and mobile applications, this subject become quite ordinary and necessary, not only in a manufacturing scenario but also in a business process. As crucial benefits, it can bring possible gains for developers and users, also reduce the efforts to communicate multiple and different platforms. Like all new implementations, there are significant challenges that have to be overcome to allow satisfactory results. In this paper, after a systematic literature review to better understand the technologies and this new situation, we conduct a study involving a case in a business process, presenting some actions that can be executed and technologies that can be implemented to reach a well interoperable environment. For instance, to analyze the interoperability maturity level and to adopt ontologies as an alternative to integrate heterogeneous systems. Finally, in the last part of the paper, we give conclusions and perspectives for futures works. © 2021 The authors and IOS Press.

关键词： Interoperability

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A Security-Constrained Hydrothermal Unit Commitment Model in the Day-Ahead Electricity Market

SSRN

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SSRN 2022年

作者： Lezama-Lope, Uriel I. Ríos-Mercado, Roger Z. Ceciliano-Meza, José Luis Graduate Program in Systems Engineering Mexico Tecnológico de Monterrey Department of Industrial Engineering Mexico

In 2015, the Ministry of Energy created a wholesale electricity market in Mexico. As a result, the country shifted from a vertically integrated regulation to a competitive market framework. In this context, the day-ahead market is essential to plan better the generation and sales of energy. This paper evaluates a hydro-thermal security-constrained unit commitment model and its solution method. The objective function determines the maximum economic surplus of the participants in the market. The problem is modeled as a mixed-integer non-linear programming incorporating real-world constraints from the particular problem and a hydropower generator function non-linear features. A decomposition approach that solves a master problem and a series of subproblems is developed. Furthermore, a new component has been added to deal with the non-linear features of the hydropower generator function using a first-order Taylor's approximation. Simulation results are presented starting by solving a representative case of the electricity market in Mexico, demonstrating its use. Moreover, to evaluate the performance, multiple instances are created from publicly available information on the day-ahead market in Mexico. The model can be helpful in markets with sizable hydropower sources to obtain a more accurate and timely system operation scheduling. © 2022, The Authors. All rights reserved.

关键词： Power markets

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Current Panorama, Practice Gaps, and Recommendations to Accelerate the Transition to a Circular Bioeconomy in Latin America and the Caribbean

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Circular Economy and Sustainability 2022年第1期2卷 281-312页

作者： Salvador, Rodrigo Pereira, Reinalda Blanco Sales, Gabriel Fernandes de Oliveira, Vanessa Campana Vergani Halog, Anthony De Francisco, Antonio C. Sustainable Production Systems Laboratory (LESP) Graduate Program in Industrial Engineering (PPGEP) Universidade Tecnológica Federal Do Paraná (UTFPR) Ponta Grossa Brazil School of Earth and Environmental Sciences The University of Queensland St Lucia 4072 QLD Australia

The rampant use of resources and the increasing risk of scarcity have been contributing to greater awareness regarding the need for maintaining resources in use for longer and the shift to renewable alternatives, in which perspective the concept of a circular bioeconomy (CBE) has been permeating the most diverse sectors. Therefore, the study’s aims were manifold: identify (i) existing practices and initiatives, (ii) barriers and potential opportunities and (iii) existing gaps for advancing a circular bioeconomy in Latin America and the Caribbean (LAC) and (iv) provide recommendations aiming at the development of a circular bioeconomy (CBE) in the region. To that end, a systematic review of the existing academic literature was done, and reports from relevant non-peer reviewed sources were also consulted. CBE practices in LAC are concentrated in only a few of the countries in the region and very much revolve around recovering value from by-products and waste streams. There are a range of economic, technological, environmental, and social barriers. Opportunities for a CBE are mainly related to the use of waste as raw material (found abundantly in the countries being investigated) and the use of new techniques/technologies. The gaps between the current state and a successful CBE are related to policy, scaling-up, collaborations, and establishing efficient business models. Recommendations for a successful CBE in the region include greater engagement of public actors, investing and developing the local economy, establishing biorefineries and industrial parks, and finding new technological routes for bioresources. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Bioeconomy Circular bioeconomy Circular business Circular economy Latin America Policy

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Association of the Factors Affecting Risk Score in HIRADC Form of a Thermal Power Plant 24

Association of the Factors Affecting Risk Score in HIRADC Fo...

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6th International Conference on Management Science and industrial engineering, MSIE 2024

作者： Uayan, Christian Jay A. Prasetyo, Yogi Tri Novendah, Ierenne Ayuwati, Irene Dyah Cahigas, Maela Madel L. Nadlifatin, Reny School of Industrial and Engineering Management Mapúa University 658 Muralla St. Intramuros Manila1002 Philippines School of Graduate Studies Mapúa University 658 Muralla St. Intramuros Manila1002 Philippines International Bachelor Program in Engineering Yuan Ze University 135 Yuan-Tung Road Chung-Li32003 Taiwan Department of Industrial Engineering and Management Yuan Ze University 135 Yuan-Tung Road Chung-Li32003 Taiwan University of Surabaya Surabaya60284 Indonesia School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia

ISBN: (纸本)9798400717130

In devising an effective Hazard Identification, Risk Assessment and Determining Controls plan of a company, it is crucial to understand the factors that relate with the Inherent and Residual Risks to prioritize the implementation of controls. In this study, the Process Area, Activity, Hazard Category, Inherent Risk Score and Residual Risk Score are brought into Chi-Squared Test to identify which factors are closely associated with Inherent and Residual Risk Scores. Moreover, the factors and range of scores were assessed into categorical level through Phi coefficient analysis. Chi-Squared Test dictates that there is a close relationship between Process Area and the Inherent Risk Score while Activity is closely associated with the Residual Risk Score. Results suggest that the thermal power plant is putting more effort into activities that involve high-level risks especially those that directly affect the environment. © 2024 ACM.

关键词： Thermoelectric power plants

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Deep Learning-Based Residual Useful Lifetime Prediction for Assets With Uncertain Failure Modes

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Journal of Computing and Information Science in engineering 2025年第4期25卷 041002页

作者： Su, Yuqi Fang, Xiaolei Operations Research Graduate Program North Carolina State University 915 Partners Way Raleigh NC 27607 Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University 915 Partners Way Raleigh NC 27607

industrial prognostics focuses on utilizing degradation signals to forecast and continually update the residual useful life of complex engineering systems. However, existing prognostic models for systems with multiple failure modes face several challenges in real-world applications, including overlapping degradation signals from multiple components, the presence of unlabeled historical data, and the similarity of signals across different failure modes. To tackle these issues, this research introduces two prognostic models that integrate the mixture (log)-location-scale distribution with deep learning. This integration facilitates the modeling of overlapping degradation signals, eliminates the need for explicit failure mode identification, and utilizes deep learning to capture complex nonlinear relationships between degradation signals and residual useful lifetimes. Numerical studies validate the superior performance of these proposed models compared to existing methods.

关键词： Failure mechanisms mixture (log)-location-scale distribution Failure Weibull distribution multiple failure modes Signals Service life (Equipment) prognostics data analytics Deep learning machine learning for engineering applications engineering systems and industry applications industrial Internet of things big data and analytics

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