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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
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.