Failure Mode and Effect Analysis (FMEA) for Improving the Efficiency of a Two Combustion Chamber Downdraft Gasification Stove

https://doi.org/10.47194/orics.v6i2.387

Authors

Keywords:

biomass stove, failure mode, FMEA, gasification, thermal efficiency

Abstract

The growing energy demand in areas lacking access to modern infrastructure drives the development of biomass-based thermal technologies, such as the dual-chamber downdraft gasification stove. This stove offers higher efficiency and lower emissions compared to direct combustion but still poses failure risks in various system components. This study aims to identify critical failure modes affecting the thermal efficiency of the stove through the Failure Mode and Effect Analysis (FMEA) approach. The analysis involved mapping the system's structure and functions, followed by evaluating failure modes using three parameters: Severity (S), Occurrence (O), and Detection (D) to obtain the Risk Priority Number (RPN). Results indicate the highest risk occurs in the combustion system (RPN 180), followed by the air control system (RPN 160). Key causes include suboptimal secondary air distribution and valve blockage. Other systems such as insulation, maintenance access, safety, and fabrication had lower RPNs but still require design and quality control improvements. Recommendations focus on improving airflow design, using high-temperature-resistant materials, and adopting precision fabrication procedures. Using the FMEA approach, the gasification stove can be enhanced in terms of reliability, efficiency, and user safety, making it more feasible as a small-scale renewable energy solution for communities.

References

Gupta, A., & Kumar, P. (2021). Risk assessment of biomass-based energy systems using FMEA and fuzzy logic: A case study of gasification plant. Renewable Energy, 179, 1605–1615. https://doi.org/10.1016/j.renene.2021.07.029

Li, M., & Tan, W. (2016). Thermal insulation materials for stove and oven safety. Journal of Materials Engineering and Performance, 25(9), 3780–3787. https://doi.org/10.1007/s11665-016-2174-4

Liu, S., Zhang, Y., Wang, R., & Li, M. (2022). A review of FMEA-based methods for reliability improvement in complex energy systems. Energy Reports, 8, 1523–1539. https://doi.org/10.1016/j.egyr.2022.06.034

Luo, Z., He, M., & Xu, Y. (2022). Influence of welding and manufacturing precision on stove efficiency. Journal of Manufacturing Processes, 76, 345–353. https://doi.org/10.1016/j.jmapro.2022.02.021

Singh, J., Kolar, A. K., & Mani, M. (2018). Design and development of a downdraft biomass gasifier for rural applications. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 40(6), 700–707. https://doi.org/10.1080/15567036.2018.1424063

Tayari, F., Aghaalikhani, M., & Ranjbar, F. (2021). Experimental investigation and performance analysis of a biomass gas stove: Efficiency and emission aspects. Renewable Energy, 172, 408–417. https://doi.org/10.1016/j.renene.2021.03.087

Wang, J., Zhao, Y., & Liu, Y. (2018). Design and control of biomass combustion air systems. Applied Thermal Engineering, 136, 240–248. https://doi.org/10.1016/j.applthermaleng.2018.03.050

Wang, Y., Zhang, H., & Wu, D. (2019). Integrated risk evaluation of biomass heating systems using improved FMEA and entropy-based methods. Journal of Cleaner Production, 231, 440–452. https://doi.org/10.1016/j.jclepro.2019.05.227

Zhang, H., Wang, X., & Li, C. (2020). Secondary air optimization in biomass gasifier stoves using CFD. Renewable Energy, 146, 2580–2592. https://doi.org/10.1016/j.renene.2019.08.112

Zhou, Y., Li, S., & Cao, Y. (2020). Effect of secondary air injection on the performance of a downdraft gasifier for household cooking. Energy Reports, 6, 294–301. https://doi.org/10.1016/j.egyr.2020.11.224

Published

2025-06-30

How to Cite

Suryaman, Zakaria, K., & Yuningsih, S. H. (2025). Failure Mode and Effect Analysis (FMEA) for Improving the Efficiency of a Two Combustion Chamber Downdraft Gasification Stove. Operations Research: International Conference Series, 6(2), 100–106. https://doi.org/10.47194/orics.v6i2.387