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All Journal International Journal of Mechanical Engineering Technologies and Applications (MECHTA) Makara Journal of Technology
Badmus, Ismaila
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Multicriteria Analysis of Vehicle Exhausts Emission using Fuzzy Analytic Hierarchy Oke, Sunday Ayoola; Abdul, Ibraheem Adedotun; Badmus, Ismaila; Rajan, John; Jose, Swaminathan; Yekinni, Adekunle Adetayo; Olaiya, Kabiru Alani; Adeniran, Mofoluwaso Kehinde; Benrajesh, Pandiaraj
Makara Journal of Technology Vol. 30, No. 1
Publisher : UI Scholars Hub

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Abstract

This study employs the fuzzy analytic hierarchy process (FAHP) to identify the critical factors and their degree of relevance to the vehicle emission process. Its innovation lies in the potential to blend ambiguity and uncertainty with the established AHP. FAHP transforms information into a defuzzification state through signal-to-noise ratios, normalization, and pairwise comparison. The principal parameters considered are revenue, sold packing units, CAGR, packing materials, consumption, and CO2 emissions (A, B, C, D, E, and F, respectively). From the normalized defuzzified weight result, consumption (Parameter E) is the best (normalized weight, 0.8685917), while CO2 emissions (Parameter F) was the worst (normalized weight, 0.050454358). Considering the weights and ranks of the data, run order 4 ranked first with values of 0.2414, 0.0903, 0.1864, 0.1448, 0.2867, 0.0412, and 0.99078 for parameters A, B, C, D, E, and F, respectively. This work is useful for logistics managers who wish to control vehicle emissions. Manufacturers could reduce vehicle emissions by improving the combustion process designs through the data for the ranking of these prioritized parameters.
A Sensitivity Analysis Scheme on Biodiesel Production Parameters from Waste Coconut Oil-Based Biofuel Oke, Sunday Ayoola; Aigbogun, Patrick Itua; Abdul, Ibraheem Adedotun; Badmus, Ismaila; Rajan, John; Jose, Swaminathan; Aderibigbe, Samuel Bolaji
International Journal of Mechanical Engineering Technologies and Applications Vol. 7 No. 2 (2026): July - December 2026
Publisher : Mechanical Engineering Department, Engineering Faculty, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/MECHTA.2026.007.02.10

Abstract

This study conducts a sensitivity analysis on the biofuel production parameters of waste coconut oil-based biodiesel, building on literature experimental data and DEMATEL methodical results, involving criteria such as Sr, Sc, (Sr – Sc), and (Sr + Sc) and the direct relation matrix (X), which was expanded to full fractional design analysis. To evaluate sensitivity, three alternative scenarios, 1, 2, and 3, each containing 25 options and levels 1 to 4, were considered. The blend process operational parameters, including blend ratio of fuel, engine speed, and load, were varied in turn with others held constant while the outcomes of Sr, Sc (Sr – Sc), and (Sr + Sc) were observed. The most important criteria are engine speed and load (36% each in all options) for alternative 1. The highest degree of influence occurs at option 20 (for engine speed) and option 15 (for load) with a corresponding value of 10.09. By value rating, blend ratio is the most important criterion (highest value of 24 at option 25) and no parametric interaction. The trend of influence increases for the blend ratio of fuel, from -1.6 to 1.33. The combined effect of engine speed and load dominates the causal group with 68% (i.e., options 1 to 4, 6 to 9, and 16 to 20), indicating that engine speed and load jointly influence the blend ratio of fuel (effect group). This paper introduces a sensitivity analysis as an approach to enhancing the stability, robustness, and reliability of blending parameters for coconut oil-based biodiesel.
Co-Authors Abdul, Ibraheem Adedotun Adeniran, Mofoluwaso Kehinde Aderibigbe, Samuel Bolaji Aigbogun, Patrick Itua Benrajesh, Pandiaraj Jose, Swaminathan Oke, Sunday Ayoola Olaiya, Kabiru Alani Rajan, John Yekinni, Adekunle Adetayo