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All Journal International Journal of Industrial Engineering and Engineering Management International Journal of Applied Sciences and Smart Technologies
Swaminathan Jose
School of Mechanical Engineering, Vellore Institute of Technology, Vellore, India
Industrial & Manufacturing Engineering

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Using the Six Sigma DMAIC Approach to Improve Maintenance Practices of Ground-Service Mechanical Equipment within a Sub-Saharan African Airport Olanrewaju Samson Omisakin; Sunday Ayoola Oke; Adeyinka Oluwo; John Rajan; Swaminathan Jose
International Journal of Applied Sciences and Smart Technologies Vol. 8 No. 1 (2026): Volume 08, Issue 1, June 2026
Publisher : Faculty of Science and Technology, Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/4etrde73

Abstract

Despite its ambitions for the most effective and world-class standard attainment, the ground-service equipment literature for airports is limited in engagements with the question of how to ascertain the effectiveness of maintenance services for critical ground-service equipment, to improve company goodwill and passenger comfort. By borrowing ideas from the process improvement literature, the DMAIC approach was instituted in a sub-Saharan African airport to capture the five critical ground-services mechanical equipment of package air-conditioner, escalator, travelator, baggage handling equipment and elevator. The methodology deployed to solve the problem is technical action research conducted in a large international airport. The DMAIC improvement framework was designed, installed and regularly managed for outcomes in discussions with the maintenance ground-service team from the delegated department. The cause and effect analysis was deployed to establish the frontline reasons for the equipment failures. The results revealed that 80% of the studied ground-service equipment exhibits the Cp/Cpk values above 1.33. Consequently, the maintenance procedure adopted to maintain the equipment is capable of maintaining a large majority of the equipment studied. However, there is scope to improve the performance of the escalator, whose value of the Cp/Cpk ratio falls below the 1.33 benchmark. A DMAIC framework appropriate to analyse the maintenance efficiency of ground-service mechanical equipment in airports is contributed for the first time to the airport setting.
A Sub-Saharan African Airport Mechanical Equipment Failure Assessment Using Joint FMECA-GRA Method Based On Technical Process Efficiency Olanrewaju Samson Omisakin; Sunday Ayoola Oke; Adeyinka Oluwo; John Rajan; Swaminathan Jose
International Journal of Applied Sciences and Smart Technologies Vol. 8 No. 1 (2026): Volume 08, Issue 1, June 2026
Publisher : Faculty of Science and Technology, Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/x3kf5y87

Abstract

This article establishes how airport ground equipment fails in operations to enhance failure prediction, reduce maintenance and costs. Airports are essential to enhance the economy of a developing country and these failures affect the efficiency of the airport system. Consequently, this paper deals with utilising the risk priority number of equipment failures to create ranks for selected airport ground equipment and study the performance of these equipment using the grey relational analysis. Three methods were established to evaluate the failures of five selected major equipment (elevators, travellator, escalator, baggage handling equipment and air-conditioners): the risk priority number (RPN), RPN with same weights and RPN with different weights for the risk factors. All the methods approved elevator 8, travellator 6, escalator 11, baggage handler 3 and air conditioner 9 as the best, indicating reduced risk factors from the equipment. The worst equipment approved by all the methods are elevator 2, baggage handler 6 and air-conditioner 7. However, while the RPN, and RPN (with an equal weight of risk factors) approve travellator 3 and escalator 9 as the worst equipment, a divergent choice of travellator 1 and escalator 5 is mapped RPN method with different weights for the risk factors as the worst equipment. This work contributes to the airport maintenance literature by applying three models to evaluate the failure of ground equipment in airports to identify equipment that should be given the utmost priority and those that warrant the least attention of the airport maintenance management.
Coating Adherence Optimization for 67Ni18Cr5Si4B Alloy Powder by High-Velocity Oxygen Fuel Spray Based on the Grey Wolf Algorithm Method Anthony Ozimu Adekola; Bayo Yemisi Ogunmola; Modupe Adeoye Onitiri; Nehemiah Sabinus Alozie; Adeyinka Oluwo; John Rajan; Swaminathan Jose; Sunday Ayoola Oke
International Journal of Industrial Engineering and Engineering Management Vol. 7 No. 2 (2025)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v7i2.7874

Abstract

Adhesion engineers increasingly use coatings in industrial equipment on gas turbine blades and vanes because of the benefits of protection against thermal stresses, oxidation, and hot corrosion. However, the coating process has suffered sub-optimal value determination, posing a serious threat to the economics of coating. While the prevailing approach of introducing the Taguchi method appears effective in resolving this issue, it sacrifices convergence speed and multiple optimization solutions. Thus, the grey wolf algorithm is proposed to optimize the coating of 67Ni18Cr5Si4B alloy powder process parameters, including powder feed rate, spray velocity, and spray distance. The high-velocity oxygen fuel spray was used, and the objectives were good microhardness, adhesion strength, and porosity. The optimal value to obtain the best coating for each of the responses was given as 85MPa for the adhesion strength, 0.684909% porosity, and 583.04HV microhardness. The present study offers important insights into the optimization thresholds to help the components development process. The quantitative form of this work is new. Fast convergence solutions offered by metaheuristics such as the grey wolf optimization algorithm are rarely found in the literature.
Novel NGT-DEMATEL Method for Interrelationship Management of Safety Conformity in a Bottling Process Plant Shedrach Aliakwe Martins; Sunday Ayoola Oke; Adeyemi Adebayo Ogundare; Joseph Ifeolu Orisaleye; Samuel Bolaji Aderibigbe; John Rajan; Swaminathan Jose; Abdulfatai Folawuyo Ahmed
International Journal of Industrial Engineering and Engineering Management Vol. 8 No. 1 (2026)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v8i1.11526

Abstract

The NGT (nominal group technique) is a structured brainstorming decision-making method with the ability to reach a quick consensus and incorporate all voices in safety management. The DEMATEL method is used to establish safety measure influential parameters, their interdependence, and their impacts on each other. This article presents the NGT-DEMATEL method based on the NGT and DEMATEL methods and uses real-time bottling process data to test the proposed method. The results reveal that for segments 1 to 5, the casual groups, having positive (Sr – Sc) values, are sorters (0.3523), rescuers (0.6271), sugar handles (0.4332), haulage drivers (1.0958), and haulage truck mates (0.2442) for segment 1; sighters (0.2981), washer operators (0.7459), and technical operators (utilities) (0.3761) for segment 2; sugar lifters (2.8805) and ETP technicians (1.1935) for segment 3; forklift technician (1.6203) for segment 4; kitchen (0.0399) for segment 5. However, the effect groups are forklift drivers (-0.8338), chip neck removers (-1.5044) and extra bottle removers (-0.4143) for segment 1; filler operators (-0.3078), palletizers/depalletizers (-0.0421), chip neck removers (-0.9615), packers/unpackers (-0.1086) for segment 2; syrup mixers (-2.5812), laboratory technicians (-1.4505) and water technicians (-0.0423) for segment 3; welders (-1.1380) and battery changers/technicians (-0.4823) for segment 4; security (-2.4973), and contractor 2 (safety boot suppliers) (-1.0840) for segment 5. The most important criteria in segments 1 to 5 are forklift drivers, sighters, syrup mixers, welders, and security. The principal novelty of this article is that it introduces a procedure to concurrently incorporate consensus and the voices of workers while establishing the interrelationships of the various workers using the NGT-DEMATEL method. This is the first article to develop and use NGT-DEMATEL for safety conformity in the bottling process plant.
Combined Application of CRITIC and Back Propagation Neural Network Prediction Method for Vehicle Emission Parametric Evaluation in Logistic Networks and Distribution Systems Sunday Ayoola Oke; Alexander Iwodi Agada; Bayo Yemisi Ogunmola; Henry Ogbemudia Omoregbee; Modupe Adeoye Onitiri; Nehemiah Sabinus Alozie; John Rajan; Swaminathan Jose; Pandiaraj Benrajesh
International Journal of Industrial Engineering and Engineering Management Vol. 8 No. 1 (2026)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v8i1.9607

Abstract

Logistic network and distribution services in the packing industry generate vast amounts of vehicle emissions, which are difficult to control due to the lack of scientific guidance. This paper predicts the emissions from vehicles engaged in logistic networks. The CRITIC (Criteria Importance Through Inter-criteria Correlation) method is integrated with the backpropagation neural network (BPNN) to analyze the input parameters of the emissions process from vehicles plying roads in the packing industry. The packing industry transports goods in packages and delivers them to customers in a road network. The application of the integrated CRITIC-BPNN method is demonstrated by using the dataset of a packing industry in India, obtained from the literature. The results revealed how the packing industry can translate its environmental control strategy into a parametric framework, yielding diverse outputs to assist in selecting optimal decisions. The proposed method exhibits unique characteristics. (1) It emerges as the first decision-making tool for objective criteria-based vehicle emission process control and could serve as a tool for logistics planning. (2) It employs integrated ideas of multi-criteria analysis and neural networks. (3) Objective and optimal emission analysis decisions are advanced through an analysis of multi-criteria tools. By employing the CRITIC method, the conflicting objectives of the emission process are successfully tackled and synchronized objectively to arrive at robust weights used in the back propagation neural network method for the final prediction. Moreover, the neural network method uses intelligence to gather data and translate it into usable forms to predict vehicle emissions.
Co-Authors Abdulfatai Folawuyo Ahmed Adeyemi Adebayo Ogundare Adeyinka Oluwo Adeyinka Oluwo Alexander Iwodi Agada Anthony Ozimu Adekola Bayo Yemisi Ogunmola Henry Ogbemudia Omoregbee John Rajan John Rajan Joseph Ifeolu Orisaleye Modupe Adeoye Onitiri Nehemiah Sabinus Alozie Olanrewaju Samson Omisakin Pandiaraj Benrajesh Samuel Bolaji Aderibigbe Shedrach Aliakwe Martins Sunday Ayoola Oke Sunday Ayoola Oke