Fabrication of Air Engine

Authors

  • Dr. R. Senthil Kumar, A.Sathiskumar, Manikandan B, Manohar S D J, Tamilarasan B Muthayammal Engineering College, Rasipuram, Namakkal, Tamil Nadu, India Author

DOI:

https://doi.org/10.15662/IJEETR.2026.0802462

Keywords:

Air Engine, Compressed Air Technology, Pneumatic System, Thermodynamics, Mechanical Fabrication, Energy Conversion, Chain Drive Mechanism

Abstract

An air engine is a pneumatic device that converts the energy of compressed air into useful mechanical work without combustion. It operates on the principle of expansion of compressed air, making it an environmentally friendly alternative to traditional engines. The fabrication of an air engine involves systematic design, material selection, machining, assembly, and testing processes based on concepts from Mechanical Engineering and Thermodynamics.

 

The fabrication process begins with the design phase, where detailed drawings and dimensions of components such as the cylinder, piston, crankshaft, connecting rod, air inlet and exhaust valves, and frame are prepared. Proper design ensures efficient air flow, minimal leakage, and smooth motion transfer. Materials like mild steel, aluminum, and cast iron are selected depending on strength, weight, cost, and machinability.

 

Manufacturing of individual components is carried out using conventional machining processes such as turning, milling, drilling, shaping, and grinding. The cylinder is finished with high precision to reduce friction and air leakage, while the piston is designed to fit accurately within the cylinder. The crankshaft and connecting rod are fabricated to withstand dynamic loads and ensure effective conversion of reciprocating motion into rotary motion.

 

Assembly is a critical stage where all components are fitted together with proper alignment. Bearings, seals, and gaskets are used to reduce friction and prevent air leakage. The compressed air supply system is connected through control valves that regulate the entry and exit of air inside the cylinder. When compressed air enters the cylinder, it pushes the piston, creating reciprocating motion. This motion is transmitted to the crankshaft, producing rotary output.

 

After assembly, the air engine is tested for performance, efficiency, and leakage. Adjustments are made to improve sealing, alignment, and air flow. Lubrication is provided to reduce wear and enhance durability. The overall system is evaluated based on speed, torque, and operational smoothness.

 

The fabricated air engine demonstrates the practical application of pneumatic systems and energy conversion principles. It offers advantages such as low pollution, simple construction, low maintenance, and safe operation. However, limitations such as lower efficiency compared to internal combustion engines and dependency on compressed air supply exist.

 

This project highlights the potential of air engines in small-scale applications and as a sustainable alternative for future energy systems.

References

1. Gorla, R., and Reddy, S., 2005, Probabilistic HeatTransfer and Structural Analysis of Turbine Blade,IJTJE, Vol. 22, pp 1- 11.

2. S.S.Verma, “AIR POWERED VEHICLES”,The Open Fuels & Energy Science Journal, 2008, Volume 1, pp.54-56

3. Rose Robert, William J. Vincent, 2004, Fuel CellVehicle World Survey 2003-Break throughTechnologies Institute, February’ 2004, Washington,D.C.

4. B R Singh and O Singh, “DEVELOPMENT OF A VANED-TYPE NOVEL AIR TURBINE”, JMES993 © IMechE 2008, Proc. IMechE Vol. 222 Part C: J. Mechanical Engineering Science, pp. 2419-2426

5. Singh B.R. and Singh O., 2010, CRITICAL EFFECT OFROTOR VANES WITH DIFFERENT INJECTION ANGLES ONPERFORMANCE OF A VANED TYPE NOVEL AIR TURBINE,International Journal of Engineering andTechnology, Chennai, India, IJET-ISSN: 0975-4024,Vol. 2 Number 2(28), 2010, pp. 118-123.

6. S. S. Verma, Latest Developments of a Compressed Air Vehicle: A Status Report, Volume 13 Issue 1 Version 1.0 Year 2013.

7. Mistry Manish K, Dr.Pravin P.Rathod, Prof. Sorathiya Arvind S, Study and development of compressed air engine single cylinder: a review study, IJAET/Vol.III/ Issue I/January-March, 2012

8. Abhishek Lal, Design and Dynamic Analysis of Single Stroke Compressed Air Engine, Vol.3, No.2, 2013.

9. Thanigaivelan, R., Senthilkumar, R., Arunachalam, R. M., & Natarajan, N. (2017). Impact of the shape of electrode-tool on radical overcut of micro-hole in electrochemical micromachining. Surface Engineering and Applied Electrochemistry, 53(5), 486–492.

10. Senthil Kumar, R., & Suresh, P. (2019). Experimental study on electrical discharge machining of Inconel using RSM and NSGA optimization technique. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41.

11. Kumar, S., & Paramasivam, S. (2020). Study on tool steel machining with ZNC EDM by RSM, GREY and NSGA. Journal of Materials Research and Technology, 9(3), 3885–3896.

12. Senthil Kumar, I. R., & Suresh, P. (2019). Investigation over the surface integrity of tungsten carbide using ZNC-EDM. International Journal of Management Technology and Engineering, 9(1).

13. Senthilkumar, R., Tamizharasan, K., Sowndharya, T., & Kirthikajain, M. (2017). Fabrication and analysis of regenerative braking system. Journal for Research, 3(02).

14. Ashokan, A., Murugesan, S., Muthaiyan, R., Arumugam, S., Saravanan, P., et al. (2025). Numerically analyzing heat transmission in blood using a cardioplegia concentric tube heat exchanger during open cardiac surgery. International Journal of Environmental Sciences, 11(18s).

15. Raman, M., Saravanan, P., Muthusamy, S., & Subramaniam, S. (2022). Studies on diesel engine exhaust gas for retrieving the waste heat through Triple Tube Heat Exchanger (TTHE) through different tubes. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44(2), 4149-4164.

16. Perumal saravanan and Mohan raman., 2020 Experimental And Numerical Analysis Of Diesel Engine Exhaust Heat Recovery Using Triple Tube Heat Exchanger, Thermal Science, 2020:24; 525-531.

17. Kumar, K.S., Perumal, S., Mohan, R. and Kalidoss, K., 2016. Numerical Analysis of Triple Concentric tube Heat Exchanger using Dimpled Tube Geometry. Asian Journal of Research in Social Sciences and Humanities, 6(8), pp.2078-2088.nhancing The Heat Transfer: A Review., Imperial Journal of Interdisciplinary Research, Volume 3, Issue 9, ISSN 2454-1362. 682-688.

18. C.Nagarajan and M.Madheswaran - ‘Stability Analysis of Series Parallel Resonant Converter with Fuzzy Logic Controller Using State Space Techniques’- Taylor &Francis, Electric Power Components and Systems, Vol.39 (8), pp.780-793, May 2011. DOI: 10.1080/15325008.2010.541746

19. C.Nagarajan and M.Madheswaran - ‘Experimental verification and stability state space analysis of CLL-T Series Parallel Resonant Converter’ - Journal of Electrical Engineering, Vol.63 (6), pp.365-372, Dec.2012. DOI: 10.2478/v10187-012-0054-2

20. C.Nagarajan and M.Madheswaran - ‘Performance Analysis of LCL-T Resonant Converter with Fuzzy/PID Using State Space Analysis’- Springer, Electrical Engineering, Vol.93 (3), pp.167-178, September 2011. DOI 10.1007/s00202-011-0203-9

21. Anand, L., Maurya, M., Seetha, J., Nagaraju, D., Ravuri, A., &Vidhya, R. G. (2023, July). An intelligent approach to segment the liver cancer using Machine Learning Method. In 2023 4th international conference on electronics and sustainable communication systems (ICESC) (pp. 1488-1493). IEEE.

22. Rajendran, S., Sundarapandi, A. M. S., Krishnamurthy, A., &Thanarajan, T. (2022). An intelligent face recognition technology for iot-based smart city application using condition-cnn with foraging learning pso model. International Journal of Pattern Recognition and Artificial Intelligence, 36(14), 2256018.

23. Murugeshwari, B., &Sujatha, R. (2014). Preservation of Privacy for Multiparty Computation System with Homomorphic Encryption. International Journal of Emerging Technology and Advanced Engineering, 4(3), 530-535.

24. Sugumar, R. (2025). Unified AI Framework for Predictive Data Engineering and Real Time Prescription and Billing Systems. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 8(5), 17261.

25. Samrat, B., Thomas, P. K., Kumar, S., Benila, A., Bhardwaj, R., &Vigenesh, M. (2024, December). Industrial informatics in optimizing software-defined vehicles for logistics. In 2024 IEEE 2nd International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP) (pp. 1-9). IEEE.

26. Soundappan, S. J. (2024). AI-driven customer intelligence in enterprise lakehouse systems Sentiment Mining Governance-Aware Analytics and Real-Time Data Synchronization. International Journal of Advanced Engineering Science and Information Technology.

27. Rajasekar, M. (2024). AI-Powered Cyber-Secure Federated Learning on AWS for Next-Generation Digital Banking Analytics. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 7(3).

28. Deivendran, P., Babu, P. S., Malathi, G., Anbazhagan, K., & Kumar, R. S. (2023). Emotion Recognition for Challenged People Facial Appearance in Social using Neural Network. arXiv preprint arXiv:2305.06842.

29. Sugumar, R., &Murugeshwari, B. (2016). An Efficient MChord based Authentication for Vehicular Ad-Hoc Networks.

30. Pandey, V. K., Mishra, S., Rengarajan, A., Savita, &Roomi, M. M. (2024, March). Enhancing Weather Forecasting with Machine Learning Techniques. In International Conference on Renewable Power (pp. 147-156). Singapore: Springer Nature Singapore.

31. Mathew, A., & Alex, H. (2025). Federated Learning for Secure Genomic Research: Privacy-Preserving AI Solutions for Precision Medicine. Science and Technology: Developments and Applications Vol. 9, 36-43.

32. Selvi, G. V., Anbarasan, A. B., Murthy, B. A., &Prabavathy, S. (2023). An Application Oriented Integrated Unequal Clustering Algorithm for Wireless Sensor Network. In Underwater Vehicle Control and Communication Systems Based on Machine Learning Techniques (pp. 140-154). CRC Press.

33. Soundappan, S. J. (2025). Next Generation AI Enabled Holistic Cognitive Platform for Secure Cloud Network Intelligence Enterprise Systems and Digital Trust Optimization. International Journal of Computer Technology and Electronics Communication, 8(5), 11534-11542.

34. Rajasekar, M. (2024). Real-Time Predictive DevOps Intelligence for Risk-Aware Digital Business Processes in Cloud and SAP Ecosystems. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 7(4), 10713-10718.

35. Jagadeesh, S., & Sugumar, R. (2017). A comparative study on artificial bee colony with modified ABC algorithm. European Journal of Applied Sciences, 9(5), 243–248.

36. Murugeshwari, B., Sarukesi, K., &Jayakumar, C. (2010, March). An efficient method for knowledge hiding through database extension. In 2010 International Conference on Recent Trends in Information, Telecommunication and Computing (pp. 342-344). IEEE.

37. Reddy, K. V. V. K., &Vimal, V. R. (2024, July). A novel approach on improved segmentation and classification of remote sensing images using AlexNet compared over linear discriminant analysis with improved accuracy. In 2024 Second International Conference on Advances in Information Technology (ICAIT) (Vol. 1, pp. 1-6). IEEE.

38. Gowthami, D., &Vigenesh, M. (2024). Distributed and Lightweight Intrusion Detection for IoT: A Lightweight Pyramidal U-Net With Tri-Level Dual Inception-Based Framework. In The Convergence of Self-Sustaining Systems With AI and IoT (pp. 154-173). IGI Global Scientific Publishing.

39. Anand, P. V., &Anand, L. (2023, December). An Enhanced Breast Cancer Diagnosis using RESNET50. In 2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) (pp. 1-5). IEEE.

40. Mathew, A. (2022). Leveraging Big Data Analytics to Power AI and ML (Machine Learning) Automation. Educational Research (IJMCER), 4(5), 131-134.

41. Dhinakaran, D. (2022). Joe Prathap P. M, Selvaraj D, Arul Kumar D and Murugeshwari B," Mining Privacy-Preserving Association Rules based on Parallel Processing in Cloud Computing,". International Journal of Engineering Trends and Technology, 70(3), 284-294.

42. Poornima, G., &Anand, L. (2024, April). Effective Machine Learning Methods for the Detection of Pulmonary Carcinoma. In 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) (pp. 1-7). IEEE.

43. Rengarajan, A., Jayakumar, C., & Sugumar, R. (2012). Optimization Of Recent Attacks Using Internet Protocol. National Journal of System and Information Technology, 5(1), 8.

44. Mathew, A., &Romasco, L. (2024). Forensic Investigation of Artificial Intelligence Systems. Research Updates in Mathematics and Computer Science Vol. 4, 154-164.

45. Vekariya, V., Kumar, S., &Rengarajan, A. (2024). A distinctive and smart agricultural knowledge-based framework using ontology. In Sustainability in Digital Transformation Era: Driving Innovative & Growth (pp. 207-213). CRC Press.

46. Soundappan, S. J. (2020). Big data analytics in healthcare: Applications for pandemic forecasting. International Journal of Advanced Research in Computer Science & Technology, 3.

47. Sugumar, R. (2024). AI-Augmented Quality Engineering for Performance Optimization and Test Orchestration in Distributed Systems. International Journal of Science, Research and Technology, 7(5), 12835-12846.

48. Soundappan, S. J., & Sugumar, R. (2016). Optimal knowledge extraction technique based on hybridisation of improved artificial bee colony algorithm and cuckoo search algorithm. International Journal of Business Intelligence and Data Mining, 11(4), 338–356.

49. Mathew, A. (2025). Ahead of the breach: Predictive threat intelligence in aviation inspired by Scattered Spider attacks. Multidisciplinary International Journal of Research and Development (MIJRD), 4(6), 54–58.

50. Soundappan, S. J. (2021). DataOps: Orchestrating Reliable ML Data Pipelines. International Journal of Research and Applied Innovations, 4(4), 5533-5537.

51. Garg, V. K., Soundappan, S. J., &Kaur, E. M. (2020). Enhancement in intrusion detection system for WLAN using genetic algorithms. South Asian Research Journal of Engineering and Technology, 2(6), 62–64.

52. Anand, L., Tyagi, R., & Mehta, V. (2024, January). Food recognition using deep learning for recipe and restaurant recommendation. In Proceedings of Eighth International Conference on Information System Design and Intelligent Applications (pp. 269-279). Singapore: Springer Nature Singapore.

53. Kumar, A., &Anand, L. (2025). A Novel EEG-Based Deep Learning Framework for Enhancing Communication in Locked-In Syndrome Using P300 Speller and Attention Mechanisms. KSII Transactions on Internet and Information Systems (TIIS), 19(11), 3841-3855.

54. Soundappan, S. J. (2022). AI-Based Fault Detection and Isolation for Reliability in Modern Power Systems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7106-7110.

55. Chandra, S., Rengarajan, A., Sahoo, G. S., & Sharma⁴, S. (2024, October). Identifying Neuronal Damage and Plasticity by Analyzing Changes in Diffusion Tensor. In Proceedings of the 5th International Conference on Data Science, Machine Learning and Applications; Volume 2: ICDSMLA 2023, 15–16 December, Hyderabad, India (Vol. 2, p. 433). Springer Nature.

Downloads

Published

2026-03-28

How to Cite

Fabrication of Air Engine. (2026). International Journal of Engineering & Extended Technologies Research (IJEETR), 8(2), 4560-4575. https://doi.org/10.15662/IJEETR.2026.0802462