Desenvolvimento de um Data Logger para acompanhamento de variáveis de processo

Authors

  • Cristiano Sbabo Universidade de Caxias do Sul (UCS)
  • Ivandro Cecconello

Abstract

Data loggers comerciais possuem um custo elevado comparados a modelos Open Source. O objetivo do trabalho é criar um protótipo de coletor de dados de baixo custo, que possa coletar e registrar variáveis de processo, como temperatura, umidade e sinais de máquina. O coletor foi desenvolvido com a utilização da placa de prototipagem rápida Arduino, principal componente do sistema. O data logger pode ser conectado a uma máquina para coleta e seus dados são transmitidos ao display remoto que pode ser ligado a um PC para registro dos mesmos. Como resultado, dados registrados podem ser analisados através de planilha eletrônica. A utilização de display remoto traz ao protótipo uma novidade, visto que os coletores comerciais não possuem essa opção. Diante dos resultados, foi possível criar um coletor de dados robusto, de baixo custo e grande flexibilidade de programação para uso na coleta de diversos sinais analógicos e digitais.

 

http://dx.doi.org/10.18226/23185279.v8iss2p57

Author Biography

Cristiano Sbabo, Universidade de Caxias do Sul (UCS)

Engenharia Industria, Coleta de dados

References

S. Wang et al., “Implementing smart factory of industrie 4.0: an outlook”, International Journal of Distributed Sensor Networks, vol. 12, no. 1, pp. 3159805, 2016.

M. Aazam, S. Zeadally and K. A. Harras, “Deploying Fog Computing in Industrial Internet of Things and Industry 4.0”, IEEE Transactions on Industrial Informatics, vol.14, no.10, pp. 4674-4682, 2018.

L. Dalenogare et al.,” The expected contribution of Industry 4.0 technologies for industrial performance”, International Journal of Production Economics, vol. 204, pp.383-394, 2018.

P. Jonsson, M. Lesshammar,”Evaluation and improvement of manufacturing performance measurement systems ‐ the role of OEE”, International Journal of Operations & Production Management, vol.19, no.1, pp. 55–78, 1999.

B. S. de Ugarte, A. Artiba and R. Pellerin,” Manufacturing execution system–a literature review”, Production planning and control, vol. 20, no. 6, pp. 525-539, 2009.

M. Engelhardt and L.J. Bain, “On the Mean Time between Failures for Repairable Systems”, IEEE Transactions on Reliability, vol. 35, no.4, pp. 419–422, 1986.

R. Mukaro and X. Carelse,” A microcontroller-based data acquisition system for solar radiation and environmental monitoring”. IEEE Transactions on Instrumentation and Measurement, vol.48, no. 6, pp. 1232–1238, 1999.

L. Pocero et al.,“Open Source IoT Meter Devices for Smart and Energy Efficient School Buildings”, HardwareX, vol.1, pp. 54-67, 2017.

R. A. Delgado et al., “Design and Implementation of Manufacturing Execution System with open hardware”, Direccion y Organizacion, vol. 48, pp. 41-45, 2012.

S. Wang et al., “Towards smart factory for Industry 4.0: A self-organized multi-agent system with big data based feedback and coordination”, Computer Networks, vol.101, pp.158–168, 2016.

R. Y. Zhong et al.,” Intelligent Manufacturing in the Context of Industry 4.0: A Review”, Engineering, vol. 3, no. 5, pp. 616–630, 2017.

M. Rüβmann et al., “Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries”. Boston Consulting Group, vol. 9, 2015. [online]. Available:

https://www.bcg.com/ptbr/publications/2015/engineered_products_project_business_industry_4_future_productivity_growth_manufacturing_industries.aspx. [Accessed:10-Jan-2020].

S. Erol et al., “Tangible Industry 4.0: A Scenario-Based Approach to Learning for the Future of Production,” Procedia CIRP, vol. 54, pp. 13-18, 2016.

D. Christmann et al., “Vertical Integration and Adaptive Services in Networked Production Environments”, Innovations In Enterprise Information Systems Management And Engineering, pp. 147–162, 2016.

R. Besutti, V. Machado and I. Cecconello,” Development of an open source-based manufacturing execution system (MES): industry 4.0 enabling technology for small and medium-sized enterprises”, Scientia Cum Industria, vol. 7, no.2, pp. 1-11, 2019.

M. P. Lara et al., “Vertical and horizontal integration systems in Industry 4.0”. Wireless Networks, 2018.

T. Camargo et al., “Thermal comfort monitoring in aviaries by a real-time data acquisition system”. Revista Brasileira de Engenharia Agrícola e Ambiental, vol.23, no. 9, pp. 694-701, 2019.

F. Segura, V. Bartolucci and J. M. Andújar,” Hardware/Software Data Acquisition System for Real Time Cell Temperature Monitoring in Air-Cooled Polymer Electrolyte Fuel Cells”, Sensors, vol. 17, no.7, pp. 1600, 2017.

A. L. Vargas, M. Fuentes and M.Vivar, ” IoT application for real-time monitoring of Solar Home Systems based on ArduinoTM with 3G connectivity”, IEEE Sensors Journal, vol.1, no.1, pp.1-13, 201Catálogo FieldLogger, “Fieldlogger, Registro e Aquisição de Dados”, 2020.[online].Available: https://www.novus.com.br/downloads/Arquivos/cat%C3%A1logo%20fieldlogger.pdf. [Accessed:14-Feb-2020].

M. Rodriguez et al., “Wireless sensor network for data-center environmental monitoring”, Fifth International Conference on Sensing Technology, pp.533-537, 2011.

D. Dobrilovic et al., “Testing Zigbee RF module applicability for usage in temperature monitoring systems”, 22nd Telecommunications Forum Telfor (TELFOR), pp. 415-418, 2014.

P. Su et al.,” Decentralized fault tolerance mechanism for intelligent IoT/M2M middleware”, IEEE World Forum on Internet of Things (WF-IoT), pp.45-50, 2014.

R. Sidqi et al., “Arduino Based Weather Monitoring Telemetry System Using NRF24L01+”, IOP Conference Series: Materials Science and Engineering, vol. 336, pp.12024, 2018.

Y. Wang and Z. Chi, “System of Wireless Temperature and Humidity Monitoring Based on Arduino Uno Platform”, Sixth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC), pp. 770-773, 2016.

V. T. Jamdar, S. B. Deosarkar and S. V. Khobragade, “An Effective Arduino Based Communication Module for Railway Transportation System”, Second International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 749-752, 2018.

R. Escobar and C. A. Herrera, “Low-cost USB interface for operant research using Arduino and Visual Basic”, Journal of the Experimental Analysis of Behavior, vol.103, no. 2, pp. 427–435, 2015.

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Published

04/29/2020

How to Cite

Sbabo, C., & Cecconello, I. (2020). Desenvolvimento de um Data Logger para acompanhamento de variáveis de processo. Scientia Cum Industria, 8(2), 57–64. Retrieved from https://sou.ucs.br/etc/revistas/index.php/scientiacumindustria/article/view/8334

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Section

INDÚSTRIA 4.0 \ Lean