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All Journal International Journal of Mechanical Engineering Technologies and Applications (MECHTA) Indonesian Journal of Industrial Engineering & Management International Journal of Industrial Engineering and Engineering Management Makara Journal of Technology
Jose, Swaminathan
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Improving Thermal Friction Drilling Performance of AISI 304 Stainless Steel Using the Harris Hawk Optimization Method Ogunmola, Bayo Yemisi; Alozie, Nehemiah Sabinus; Adeyinka, Oluwo; Nwankiti , Ugochukwu Sixtus; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan
International Journal of Industrial Engineering and Engineering Management Vol. 6 No. 2 (2024)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v6i2.7743

Abstract

Presently, in friction drilling optimization schemes, quick convergence of solutions and simplicity of methods are still challenging. These issues are drawbacks in obtaining the maximum potential benefits from the optimization process. Therefore, this paper applies a new optimization method, Harris Hawk optimization to the thermal drilling process of AISI 304 stainless steel. The algorithm minimizes the axial force, determination error, radial force, and radial error and maximizes the bushing length as the major output of the process. The proposed approach was tested with experimental data obtained from the literature. The obtained results indicate that the optimal production is feasible. An example is given here of the results of the input parameters for the minimum axial force, which is as follows: After 500 iterations, the optimal axial force yields a tool cylindrical region diameter of 5.78593 mm, a friction angle of 60 degrees, a friction contact area ratio of 57.7082, workpiece thickness of 3 mm, feed rate of 140 mm/min and rotational speed of 3002.85 rpm, which can be applied. The results assist engineers in implementing optimal conditions for the drilling process. The outcome of this study strengthens decisions to establish thresholds of values that are less or more than expected thereby providing a basis for comparison, reward, and reprimand for workers. Thus the drilling process can be optimized.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar

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 NEW DEVELOPMENT OF AN X–R CONTROL CHART OPTIMIZED WITH TAGUCHI, TAGUCHI-PARETO AND TAGUCHI-ABC METHODS FOR MAINTENANCE RELIABILITY OPTIMIZATION Oluwo, Adeyinka; Alozie, Nehemiah Sabinus; Ogunmola, Bayo Yemisi; Raji, Akinwale Olusegun; Rajan, John; Jose, Swaminathan; Oke, Sunday Ayoola; Aderibigbe, Samuel Bolaji
International Journal of Mechanical Engineering Technologies and Applications Vol. 7 No. 1 (2026): January - June 2026
Publisher : Mechanical Engineering Department, Engineering Faculty, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/MECHTA.2026.007.01.11

Abstract

This paper aims to develop a variable control chart-based (R chart and X bar) method to determine the stability and predictability of the maintenance reliability parameters in a grain-based food processing plant in Nigeria. The R chart and X bar charts were developed using the changes in the range and average of reliability parameters over the maintenance period. The previous study, which is extended here, evaluates reliability parameters for 35 weeks to capture the plant's frequency of failure, MTTR, MTTF, and downtime. These are transformed into the Weibull probability density function, cumulative density function, reliability, and hazard rate and measured from the viewpoint of orthogonal array generation and analysis. This paper found that the variable control chart–based method provides an expression for the stability and prediction of the maintenance reliability parameters using Taguchi-based methods. The proposed approach would be valuable for maintenance managers to understand the behavior of their system parameters in attaining sustainable practices in the grain-based food industry. This study analyses the interactions of the maintenance reliability parameters in the grain-based food industries, which is new in the food equipment maintenance domain of practice. The originality and novelty of this approach will aid in establishing controls while ensuring that maintenance costs are minimized.
Hybrid Non-Dominated Sorted Genetic Algorithm II with Random Forest Algorithm Oriented Polynomial Regression Model for the Photovoltaic Thermal System Oke, Sunday Ayoola; Adeyemi, Samuel Adeolu; Shokoya, Nurudeen Olatunde; Rajan, John; Jose, Swaminathan; Aderibigbe, Samuel Bolaji; Oluwo, Adeyinka; Ogunmola, Bayo Yemisi; Alozie, Nehemiah Sabinus
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.2026.007.02.2

Abstract

A hybrid non-dominated sorted genetic algorithm II with a random forest. The polynomial regression (HNSGAII-RFPR) method for the photovoltaic thermal system (PTS) optimization problem is proposed. This new method uses polynomial regression to generate an objective function, which at first contains essential and non-essential terms of the parameters for the PTS. The random forest algorithm was used on the regression model to identify the important terms of the parameters by deploying the mean squared error metric, which showed the difference between prediction and experimental values. The parameters used in the process are collector angle, number of collector tubes, volume-area proportion, mass flow rate, collector azimuth, and collector plate material, while the outputs are the electrical and thermal efficiencies. Results showed that the electrical efficiency exhibited acceptable terms, with the mean squared error of 0.09, while the thermal efficiency results were not acceptable with a mean squared error of roughly 130. However, the proposed algorithm performed satisfactorily regarding accuracy. Moreover, experiments with the training and testing data, which are 14/18 and 4/18, respectively, were obtained from the experiment of Kuo et al. The simulation experiments highlight that the use of the HNSGAA II-RFPR schema can produce interesting results for the photovoltaic thermal system. The simulations ensure a good balance between solution convergence and its diversity. The implementation of the tests demonstrated that the proposed method competes with another evolutionary algorithm tested.
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 Adeboye, Busayo Adedeji, Kasali Aderinmoye Adedeji, Wasiu Oyediran Adekoya, Abdulganiyu Adegboyega Adeniran, Mofoluwaso Kehinde Aderibigbe, Samuel Bolaji Adeyemi, Olusola Michael Adeyemi, Samuel Adeolu Adeyinka, Oluwo Agada, Alexander Iwodi Aigbogun, Patrick Itua Alozie, Nehemiah Sabinus Ayanladun, Chris Abiodun Badmus, Ismaila Benrajesh, Pandiaraj Emorinken, Samuel Olayinka Francis, Osita Prince Ibitoye, Ayomide Sunday Nwankiti , Ugochukwu Sixtus Nwankiti, Ugochukwu Sixtus Odudare, Samson Oluwaseun Ogunmola, Bayo Yemisi Oke, Sunday Ayoola Okwo, Jeremiah Ugo Olaiya, Kabiru Alani Olowu, Joseph Kolawole Oluwo, Adeyinka Onitiri, Modupe Adeoye Oyekeye, Manasseh Olusegun Oyelami, Seun Oyetunji, Elkanah Olaosebikan Ozule, Chukwuka Prosper Rajan, John Raji, Akinwale Olusegun Shokoya, Nurudeen Olatunde Taiwo, Emmanuel Oluwatobi Udoibe, Ndifreke John Umoh, Akwaeno Uduak Yekinni, Adekunle Adetayo