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Expert System for Control and Maintenance of Steam Package Boiler Drum and Feed Water Using Rule-Based Fuzzy Logic Techniques

Expert system as a branch in artificial intelligence have impact greatly in many fields of discipline experimentally with various applications. This paper presents research work for expert system for steam package boiler control and maintenance using rule-base fuzzy logic technologies. The system handles cause of boiler errors in terms of control and maintaining the level in boiler drum and feed water variables. The methodology used was quantitative and qualitative as the system validates the consistency, correctness, and its precision on the test value cases, with twenty-one (21) boiler domain practitioners on dynamic simulation. The boiler variables with less or higher test value worst-cases validates the system, indicating red on the boiler’s panel, while on test value best-cases, validates the system, indicating green on the boiler’s panel as end users entered the right values. The steam package boiler system prevents damaged and controls its alkalinity, scaling, chemical corrosion, forming, correct pH values and then conductivity which deals with the feed boiler water and monitored the level in the boiler drum using the industry process parameters, pressure, temperature, level, and flow. The system mean (µ) error on auto run mode was computed as 1.5. The system can be deployed in chemical plants, oil, and gas industry etc. where steam package boilers are needed for steam generation and to reduced need for draughting.

Expert System, Rule-Base System, Fuzzy Logic, Steam Package Boiler, Dynamic Simulation

Boye Aziboledia Frederick, Daniel Matthias, Onate Egerton Taylor. (2023). Expert System for Control and Maintenance of Steam Package Boiler Drum and Feed Water Using Rule-Based Fuzzy Logic Techniques. American Journal of Computer Science and Technology, 6(2), 80-95.

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Amit, K. J. (2012). An Approach towards Efficient Operation of Boilers. International Journal of Scientific & Engineering Research, 3 (6).
2. Adetokunbo et al, (2012), Software Engineering Methodologies: A Review of the Waterfall Model and Object-Oriented Approach, International Journal of Scientific & Engineering Research, 4 (7).
3. Anne Håkansson (2013), Portal of Research Methods and Methodologies for Research Projects and Degree Projects, WORLDCOMP'13 - The 2013 World Congress in Computer Science, Computer Engineering, and Applied Computing, 22-25 July 2013, FECS'13 - The 2013 International Conference on Frontiers in Education: Computer Science and Computer Engineering.
4. Anabik, S. & Ashok, S. D. (2012). Fuzzy Logic Approach for Boiler temperature and water level. International Journal of Scientific and Engineering Research, 3 (6).
5. Bretz, E. A. (1990), Expert System Enhance Decision Making Abilities of O&M Permission Electrical world, 39-48.
6. Celin S, Anne Frank Joe, Rajalakshmi G, Thaj Mary Delsy T, Jamuna Rani D (2016), Embedded Fuzzy Based Boiler Control, International Journal of Robotics and Automation (IJRA), 5 (2).
7. Emmanuel C. Ogu, Adekunle, Y. A. (2013), Basic Concepts of Expert System Shells and an Efficient Model for Knowledge Acquisition, International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064, Vol. 2 (4).
8. Edgar Amaya Simeón & Ricardo Ribeiro Gudwin, (2010), An Expert System for Fault Diagnostics in Condition Based Maintenance, ABCM Symposium Series in Mechatronics - Vol. 4 - pp. 304-313.
9. Tripathi, K. P. (2011), “A Review on Knowledge-based Expert System: Concept and Architecture,” Artif. Intell. Tech. - Nov. Approaches Pract. Appl., vol. 4, no. 4, pp. 19-23.
10. Jabbar H. K. & R. Z.; Khan (2015), “Survey on development of expert system in the areas of Medical, Education, Automobile and Agriculture,” Comput. Sustain. Glob. Dev. (INDIACom), 2015 2nd Int. Conf., vol., no., pp. 776-780, 11-13.
11. Krishan K. (2016), Fuzzy Logic Execution in Boiler Control, IJSRD - International Journal for Scientific Research & Development| Vol. 4, Issue 05, 2016 | ISSN (online): 2321-0613.
12. Konstantin E. Aronson, Boris E. Murmansky, Ilia B. Murmanskii & Yuri M. Brodov, (2020), An Expert System for Diagnostics and Estimation of Steam Turbine Components’ Condition, Int. J. of Energy Prod. & Mgmt., Vol. 5, No. 1 (2020) 70-81.
13. Mrudula, P. (2013). Expert System-A Review Article, International Journal of Engineering Sciences & Research Technology, 2 (6).
14. Simin, S. S., Fatemeh, M., Fatemeh, A., Marjan, T. & Afsaneh, A. (2013). Investigate the Effect of Expert Systems Application on Management Performance. Institute of Interdisciplinary Business Research. Interdisciplinary Journal of Contemporary Research in Business, 478 4 (1).
15. Chee T. et al., (2016), The Application of Expert System: A Review of Research and Applications, ARPN Journal of Engineering and Applied Sciences, ISSN 1819-6608, VOL. 11, NO. 4, February 2016.
16. Michael, A. B. B. (2016). Model Predictive Fuzzy Control of a Steam Boiler, Master’s degree in Automàtic and Robotics. Escola Tècnica Superior d’Enginyeria Industrial de Barcelona.
17. Muhammad, A., Suleman, A., Humza, W. & Nuka Nwiabu, and Ibrahim Adeyanju (2012), User Centered Approach to Situation Awareness, International Journal of Computer Applications, (0975-8887), Vol. 49-No17, July 2012.
18. Yangping Zhou, Xiang Fang and Xu Hong He (2011). “Use of an expert system in a personnel evaluation process”. Proceedings of IEEE International Conference Quality and Reliability, Beijing. 2011: 15-19.
19. Harald S and Georg H. (2015), Expert Systems – Smart Solutions for Power Plant, STEAG Energy Services GmbH, Essen, German, presented in Session 8 “Plant Optimization & Improvements I” on September 3rd, 2015, in Bangkok, Thailand.
20. Marco, A. A., Lopez, C., Floresa, H. & Eduardo, G. G. (2003). “An intelligent tutoring system for turbine start up training of electrical power plant operators”. Expert Systems with Applications, 24, 95-101.
21. Tavira-Mondragon, Jose M. N, Jimenez-Fraustro Fernando, Orozco-Martinez Roni, (2011), Power Plant Simulators and Their Application in an Operators Training Center.
22. Nabil, M., Ali, M. & Govardhan, A. (2012), Comparison study between Traditional and Object-Oriented Approaches to Develop all projects in Software Engineering, International Journal of Computer Science, and Information Technologies, 3 (1), 3022–3028.
23. Bryman, A., & Bell, E. (2011). Business Research Methods (3rd ed.). Oxford: Oxford University Press.
24. Kusumarasdyati R (2016), Qualitative and Quantitative Approaches to Action Research. Universitas Negeri Surabaya,, Pp 139-146.
25. Emerson Process Management Power and Water Solution Inc (2011), Emerson Process Management (online).
26. Fundamentals of Expert Systems Pdf (Online).
27. Installation, Operation, Maintenance Manual, Indorama Eleme Fertilizer and Chemical Limited, IEFCL TRAIN 2 Fertilizer Project (IEFCL2), DOC. NO: CXBF001-CPR-012.
28. Harry P. G., (Online), Running head: Expert Systems and Applications.