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All Journal Indonesian Journal of Industrial Engineering & Management International Journal of Industrial Engineering and Engineering Management
Adedeji, Kasali Aderinmoye
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Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

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Optimizing the Parameters of Carbon Fiber Reinforced Plastic Composite Drilling Process Using Signal-to-noise Ratio-based Grey Wolf Optimization Algorithm Taiwo, Emmanuel Oluwatobi; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
International Journal of Industrial Engineering and Engineering Management Vol. 6 No. 1 (2024)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v6i1.7691

Abstract

This study aims to develop an optimization scheme that contributes to the production of carbon fiber-reinforced plastics using the grey wolf optimization approach. Different from other optimization schemes such as the Taguchi method, which takes some time to compute and use, this grey wolf optimization approach introduced a fast convergence scheme to reduce computation time thereby making its implementation in the factory very interesting. Data used for the analysis was obtained from a doctoral thesis via an experimental approach. Four responses were considered in this work, namely the torque, delamination at entry and exit, eccentricity and thrust force. A spreadsheet was used to implement the computational procedure of the grey wolf optimization algorithm. In using the wolves, at the initial level, the starting point was a zero where hunting had not begun and the prey had just entered the park, which is within the territory of the grey wolves. With this in mind, real life is mimicked and such data gathered would aid precise decision-making. The results revealed the feasibility of the approach and convergence was obtained at the tenth iteration with the best fitness value at 9020785071. It is expected that the findings from this work will be useful as a method for planning in production planning and policy development for the carbon fiber-reinforced plastic industry. This study is a noteworthy contribution to the production development of CFRPs where the grey wolf algorithm is used to analyze the problem. In addition, evidence of the responses determining the quality of drilled products is provided.
Optimization of MQL-Turning Process Parameters to Produce Environmentally-Benign AISI 4340 Alloy with Nano-Lubricants using Cuckoo Search Algorithm Ozule, Chukwuka Prosper; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye; Nwankiti, Ugochukwu Sixtus
IJIEM - Indonesian Journal of Industrial Engineering and Management Vol 5, No 2: June 2024
Publisher : Program Pascasarjana Magister Teknik Industri Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijiem.v5i2.22728

Abstract

The current research consists of a machining process involving AISI steel where the input parameters are the cutting depth, feed rate and cutting speed while the responses include the cutting force, surface roughness and tool wear. Usually, heat is generated during the turning process and various machining processes, and to reduce it, coolants are considered. In this work, CuO and Al2O3 were used as nano lubricants (MQL). Data obtained from the machining process were inserted into Minitab 18 software where quadratic objective functions were formulated as related to each output concerning the input parameters. Objective functions were optimized with the aid of C++ programming code. The cuckoo search algorithm was used for the optimization process of the work. This work clearly shows a reduction of the output parameters that is, cutting force from 243N to 127.20N, surface roughness from 0.66µm to 0.368µm and tool wear from 0.069mm to 0.0046mm using CuO as the nano lubricant. While using Al2O3, cutting force was lowered from 363N to 197.63N, surface roughness from 1.98µm to 0.148µm and tool wear from 0.219mm to 0.063mm. This clearly shows that using CuO helps to obtain a better cutting force coupled with elongation of the tool life but Al2O3 best gives a better surface finish.
Integration of Fuzzy 0/1 Knapsack Dynamic Programming and PROMETHEE Method for Vehicle Exhaust Emission Parametric Optimization and Selection in the Packing Industry Agada, Alexander Iwodi; Rajan, John; Jose, Swaminathan; Oke, Sunday Ayoola; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
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.v6i2.7689

Abstract

Packaging industries fabricate and transport products in wrapped, sealed, and cushioned containers and boxes on roads, often through fossil-fuelled vehicles that emit carbons. Thus, decarbonization and net zero emission drive are compelling for these vehicles. This paper proposes a robust green logistics interaction model for monitoring and reducing exhaust pipe emissions in an uncertain environment. It uses a hybrid method known as fuzzy-0/1-KDP-PROMETHEE (Fuzzy-0/1 Knapsack dynamic programming-Preference Ranking Organization Method for Enrichment Evaluation) approach to concurrently reduce uncertainty, optimize the capacity of the knapsack and establish the preferred option among the parameters of green logistic. Both PROMETHEE I and II were introduced and tested using logistics data from an Indian environment based on secondary data. The method works by first reducing the effect of uncertainty on the model outcomes. This was achieved by establishing the output space as the fuzzy state, creating fuzzy rules, and mapping degrees to rules. Then, the degrees are used to maximize, ensuring that the weighted sum is not greater than the capacity of the Knapsack. The outcome is then regarded as the element of the green logistics exhaust emission process. The results obtained from the analysis, using the replacement of fuzzy expert (triangular) with fuzzy extent (trapezoidal), fuzzy geometric mean (triangular), and fuzzy geometric mean (trapezoidal) reveal that the fuzzy-0/1-KDP-PROMETHEE method adequately represents the score obtained using the data set from the exhaust emissions.
An Application of Data Envelopment Analysis in the Selection of the Best Response for the Drilling of Carbon Fiber-reinforced Plastic Composites Adedeji, Wasiu Oyediran; Odusoro, Salome Ifeoluwa; Adedeji, Kasali Aderinmoye; Rajan, John; Oke, Sunday Ayoola; Oyetunji, Elkanah Olaosebikan; Nwankiti, Ugochukwu Sixtus
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.5792

Abstract

In the drilling operation, defects such as delamination at exit and entry are very disturbing responses that impact the efficiency of the drilling process. Without control, an exponential growth in the amount of drilled components with defect quantities may result. Thus, the process engineer has input in attaining the desired production levels for components in the drilling process. Consequently, this article deploys a novel method of data envelopment analysis to evaluate the relative efficiency of the drilling process in reducing the defects possible in the producing components from the CFRP composites. The high-speed steel drill bits were utilized to process the CFPs, while the responses considered are the entry and exit determination, thrust force, and torque, among others. Literature experimental data in twenty-seven experimental counts were summarized into fewer groups and processed through the data envelopment analysis method. The results show that capturing the CFRP composite responses is feasible, providing an opportunity for enhanced efficiency and a situation where undesirable defects in the CFRP composite production process may be eradicated. The article’s uniqueness and primary value are in being the foremost article in offering an updated vast representation of the comparative efficiency of CFRP composite parameters within the literature for the composite area. The work adds value to the CFRP composite literature by envisaging and understanding the comparative efficiency for the parameters, identifying and separating the best from the worst decision-making unit. It also reveals how the parameters are linked by their relative placements. The article's novelty is that using data envelopment to compare the efficiency in reducing drilling defects such as entry and exit determination, among others. The method’s utility is to provide information for cost-effective drilling operations during the planning and control phases of the operation.
Vehicle Exhausts Emission Pattern Decisions for Logistic Services and Packing Industries with Orthogonal Array-Based Rough Set Theory Agada, Alexander Iwodi; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 2 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i2.7740

Abstract

Precise monitoring of vehicle emissions in green logistics, focusing on the contributions of vehicles from packing industries, is crucial for many issues. It helps to understand the total emissions and gain insights into the mechanism of vehicle-associated environmental concerns. Notwithstanding, a key issue when monitoring vehicle emissions is the effective discrimination problem for different patterns generated from the parameters. Data from the packing industry are available from distribution networks but its pattern cannot be discriminated. Given this background, this article presents a new method of the orthogonal array-based rough set to discern patterns of the parametric behaviors to monitor emissions from vehicle exhausts in the packing industry. The proposed method is based on an Indian logistics network and delivery system data, which was obtained from previous work in the literature. By setting controls on the parameters of the packing industry which includes revenue obtained, packing units sold, growth rate, carbon-dioxide equivalent, materials utilized, and quantity consumed, the method was able to discern the patterns of the parametric behavior. The orthogonal arrays, which are developed, form factors (parameters) and levels to ascertain a balanced and uniform analysis of the various groups of options. Indiscernibility and approximation concepts of fuzzy sets are then applied to arrive at the outcome. Unlike previous studies, this study eliminates the need for tracking data, assumptions, and external information to establish the set membership. However, it utilizes the available information within the data. The rough set analysis indicates that there are no discernable patterns or rules that distinguish between "Yes" and "No" decisions. The method of rough set illustrated in this work shows the feasibility of the approach in the Indian packing industry. The method is useful for the logistics manager and government agencies responsible for the control of vehicle-generated greenhouse emissions.
Application of Data Envelopment Analysis for Performance Efficiency Evaluation of Oil Palm Empty Bunch Fruit Composites in The Aerospace Industry Udoibe, Ndifreke John; Oke, Sunday Ayoola; Ayanladun, Chris Abiodun; Rajan, John; Jose, Swaminathan; Adeyemi, Olusola Michael; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 2 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i2.7741

Abstract

In this study, we propose the data envelopment analysis method as a scheme to determine the technical efficiency of a set of parametric inputs of the water absorption process when developing the oil palm particulate composite treated with an alkali solution. Although alkali-treated oil palm bunch composites have been analyzed previously for water absorption, a single parameter such as water absorption rate prevails in analyses. Unfortunately, multiple inputs and multiple outputs have been ignored and the efficiency evaluation of such composites has been missing in the literature. To address this gap, the present study exploits the linear programming theory and formulated models for each decision-making unit and solves that formulation for optimum value determination for inputs of the composites. This study investigates the technical efficiency of the water absorption in the oil palm empty fruit bunch composite development process. Overall, judging the performance of the parameters regarding the frequency of attaining 100% efficiency, analysis was performed on the average performance of all parameters in all sixteen scenarios. In this regard, the efficiency of particulate loading was 36.1%, for composite weight plus mold, it was 96.3% and for initial weight, the average efficiency score was 67.8%. It is suggestive that composite weight plus mold with an average efficiency of 96.3% is the best parameter while particulate loading with 36.1% is the worst parameter. Thus result is consistent with the result based on each scenario. From the perspective of DMUs, DMU11 with a score of 78.4% is the best ranking unit while DMU14 is the work ranking unit with an efficiency score of 60.9%. Besides, the average efficiency score for all the DMUs is 66.7%. The work is important to composite development engineers and for policy decision-making.
Co-Authors Adedeji, Wasiu Oyediran Adeyemi, Olusola Michael Agada, Alexander Iwodi Ayanladun, Chris Abiodun Benrajesh, Pandiaraj Jose, Swaminathan Nwankiti, Ugochukwu Sixtus Odusoro, Salome Ifeoluwa Oke, Sunday Ayoola Oyetunji, Elkanah Olaosebikan Ozule, Chukwuka Prosper Rajan, John Taiwo, Emmanuel Oluwatobi Udoibe, Ndifreke John