Journal of Engineering Research and Applied Science

Hybrid Manufacturing: The Integration of Subtractive and Additive Processes

2026-08-21T18:55:21+03:00

Hybrid Manufacturing (HM), which integrates Additive Manufacturing (AM) and Subtractive Manufacturing (SM) within a unified platform, has emerged as a pivotal advancement in contemporary production technologies. The resulting synergy enhances manufacturing flexibility, supports mass customization, and improves material utilization, while also reducing lead times and tooling requirements. This article presents a comprehensive review of HM systems, highlighting their operational principles, enabling technologies, and implementation strategies. Key system architectures such as the integration of Directed Energy Deposition (DED) or Laser Metal Deposition (LMD) with Computer Numerical Control (CNC) machining are discussed in detail. Case studies from aerospace, medical, and automotive industries were examined to demonstrate practical applications and performance outcomes. Additionally, the article explored critical challenges including thermal management, toolpath integration, interfacial bonding, and process monitoring. Emphasis was placed on the role of advanced simulation tools, in-situ sensing, and AI-driven optimization in overcoming these challenges and advancing HM capabilities. The paper concluded with a discussion of emerging trends and future research directions, underscoring HM’s role as a cornerstone in the evolution toward intelligent, sustainable, and digitally integrated production systems.

Design and Development of a Model Smart Home Automation System for Electronics Control

2026-08-21T18:55:21+03:00

This work presents the design and development of a model smart home automation system using the Internet of Things (IoT) for convenient electronics control. Conventional wired systems can be costly to retrofit, prompting the exploration of alternative solutions. This IoT-based system allows users to control home appliances remotely and through voice commands. The system utilizes a NodeMCU board, relays, and sensors to enable functionalities like remote monitoring and control, voice activation, sensor integration, automation scenarios, and security and safety. The developed system demonstrates the feasibility of convenience, efficiency, and safety for users using an IoT approach.

Energy and Surface Quality Analysis of AA6063 Alloy During Sulfuric Acid Anodizing at Different Bath Temperatures

2026-08-21T20:04:19+03:00

This study investigates the influence of anodizing bath temperature on coating properties, microstructure evolution, and cooling energy demand during sulfuric acid anodizing of AA6063 aluminum alloy. Experimental studies were carried out using 20 wt.% sulfuric acid electrolyte at a constant current density of 15 A/dm² and anodizing duration of 30 minutes. Coating thickness, Vickers microhardness, and scanning electron microscopy (SEM) analyses were performed to evaluate the coating quality. In addition, a thermodynamic cooling load model was developed to estimate the energy consumption of the anodizing bath cooling system. Results indicate that bath temperature significantly affects oxide layer morphology, pore structure, and mechanical properties. It has been observed that the coating thickness increases as the anodizing bath temperature increases. Microhardness values ranged from 459 HV to 534 HV, depending on process temperature. SEM observations revealed homogeneous pore distribution at 19–20°C, while dissolution effects became dominant at 22°C. Energy analysis showed that increasing bath temperature from 18 °C to 20 °C reduces cooling energy demand by approximately 17%. The combined analysis suggests that the optimal operating window for AA6063 sulfuric acid anodizing is between 19 °C and 20°C, providing a balance between coating quality and energy efficiency.

Cost Effective Hybridge Models for Allocating Industrial Machine Maintenance Budget in a Dynamic Economy

2026-08-21T18:55:21+03:00

In today's fast-paced and competitive business landscape, understanding the cost of failure has become increasingly crucial. The cost of failure refers to the financial and non financial consequences that arise from unsuccessful projects, initiatives, or processes. It encompasses not only the direct monetary losses but also the indirect impacts on reputation, customer satisfaction, and employee morale. Prevention is better than cure. Avoiding cost of failure occurrence is better than proffering solution after its ill effect. This is purely medicine after death. This study found this as gap in literature that needs the attention of economic researcher. Hence the development cost effective models capable of allotting available budget optimally for its effective usage. By this, failed projects that often results in wasted resources, such as time, labor, and materials as well as failed projects that demoralize employees, leading to decreased productivity and increased turnover rates will be under control from onset. Cost effectiveness models are analytical tools that help businesses compare the costs and benefits of different alternatives and make informed decisions. This study identified the required strategic decisions, with their attributes and their models adopted from literature for the required logics to these models. The computer algorithms was developed as well as the software model using a JAVA scripts for its implementation for decision making. Performance index of each machine were: Winnowing machine (WM is 0.324) ; Milling Machine (MM is 0.327); While that of Liquor Press Machine ( LPM was 0.349). The company available maintenance budget (AB) for the three machines in 2025 was Eighteen Million, Six hundred and forty five Thousands (18,645,000) Naira. Using the performance index of each machine to predict what should be allocated to each of this machine in 2025 maintenance activities ; Winnowing Machine Allocation Budget (AB_wm), 6,040,980 Naira; Milling Machine Allocation Budget (AB_mm), 6,096,915 Naira. While that of Liquor Press Machine Allocation Budget (AB_lpm), 6,507,105 Naira. This model is very simple and easy to use. It will find its application in small , medium and large scale industries.

Electromechanical Evaluation and Performance Metrics of Next Generation EV Motors: A Comparative Study on Traction Technologies

2026-08-21T18:55:21+03:00

Driven by the compulsory global imperative to curb carbon emissions and address the dwindling reserves of fossil fuels, the automotive world is currently navigating a major transition toward electrified propulsion. In this new era, the real-world performance of a New Energy Vehicle (NEV) is no longer just about the battery; it is defined by the complex electromechanical interplay between energy storage and the specific behaviour of its traction motor. Through a comprehensive review of contemporary literature, this research offers an in-depth electromechanical assessment and a side-by-side comparison of the core motor topologies dominating today’s market: AC Induction Motors (ACIM), Permanent Magnet Synchronous Motors (PMSM), Brushed and Brushless DC (BLDC) units, Switched Reluctance Motors (SRM), and the emerging Axial Flux architectures. Rather than just listing features, this study interrogates each design through the lens of critical metrics, including power-to-weight ratios, thermal endurance, and the hard realities of manufacturing costs. While PMSMs remain the industry's "gold standard" for high-end efficiency, our analysis uncovers a strategic move toward magnet-free alternatives, specifically SRMs and ACIMs, as manufacturers seek to escape the volatile supply chains of rare-earth elements. Moving beyond the physical hardware, this study investigates how advanced control architectures, namely Field-Oriented Control (FOC) and Model Predictive Control (MPC), serve as the cognitive center of the powertrain to enhance transient performance and optimize energy recuperation. By merging structural insights with operational realities, this work provides a practical roadmap for identifying the right traction solutions to meet the diverse demands of future e-mobility.

Statistical Methods in Optimizing Industrial Systems

2026-08-21T18:55:21+03:00

Optimizing industrial energy systems is vital for achieving sustainability goals, reducing costs, and improving operational performance. This paper examines the integration of advanced statistical methods, such as regression analysis, time-series forecasting, Monte Carlo simulations, and machine learning, into industrial energy management. These approaches enable predictive maintenance, accurate energy demand forecasting, and efficient resource allocation, while machine learning models in particular enhance reliability by predicting failures, minimizing downtime, and extending asset life. Statistical techniques also strengthen risk assessment and process control under uncertainty, supporting proactive energy management. Despite these advantages, challenges such as data quality, model scalability, and system complexity remain. Addressing these requires advances in data integration, algorithm interpretability, and interdisciplinary collaboration. By synthesizing statistical approaches with emerging technologies like artificial intelligence and the Internet of Things, this paper underscores the transformative role of statistically informed optimization in building resilient, cost-effective, and sustainable industrial energy systems.

Annual Running Cost as Dominant Feature for Industrial Machines Available Annual Running Cost Budget Allocation

2026-08-21T18:55:21+03:00

The annual running cost of a machine, which includes expenses like depreciation, repairs, maintenance, fuel, and operator wages, significantly impacts profitability, operational efficiency, and decision-making. Increased running costs can reduce profits, strain budgets, and potentially lead to decreased equipment utilization. Conversely, managing and reducing these costs can improve efficiency and competitiveness. This study found annual running cost as strong decision strategy for machine vendors’ selection pre procurement. A low purchase cost and good engineering factors machine may pay heavily for these when running the machine. Hence the need for its consideration after vendor might have passed both the machine low cost and the engineering features requirements. In other to proffers solutions to this, this study identified the attributes to this strategic decision, modeled it (mathematics logics and is algorithm development) and developed a software decision tool using python programming language for its application. Three machines were used as case studies in selected Cocoa processing Industry (Winnowing Machine (W/M), Cocoa Milling Machine (M/M) and Cocoa Liquor press(L/P) for extracting butter from the liquor . Concerning Winnowing Machine (W/M), the line with diamond shape points, was observed that the machine annual operating cost kept increasing gradually as the machine kept aging. This was as a result of frequent increase in repair and maintenance cost. The increase was pronounced well after the third year of purchase (2010) And in most cases the machine was over flogged. The Milling machine with square points shaped (M/M) was found sharp MAOC value It was observed the machine has a long time down time in 2013 due to costly damaged of critical component , the same issue was about to occur in 2015 but the experienced of 2013 helped to rectify the problem at infancy. The liquor press with pyramid shape points (L/P) really performed excellently well but dropped little at year 2015 , here it was observed that the machine was underutilized the cocoa crushing rate for the year was less compared with the initial targets of the company. Using the running cost fund available (N12,370,000:000) budgeted for the three factory machines, that of the winnowing machine (WM) was N4,557,815.874 which is the highest, followed by that of Milling Machine (MM) N 3,927,734.660 and that of the liquor press (LP) was N3,901,550.731 the list, based on available financial running cost capability of the company of Twelve Million ,three hundred and seventy ( N12,370,000) Naira only. This model will be found usable in allocating available running cost allocation to several machine in small, medium and large-scale industries.

Effect of CuO Nanoparticle Size and Concentration on Thermal Enhancement in Shell-and-Tube Heat Exchangers

2026-08-21T18:55:21+03:00

In this study, a custom-designed shell-and-tube heat exchanger (STHE) system was developed and initially modeled via simulation under nanoparticle-free conditions to establish baseline heat transfer parameters. Flow regimes were identified through Reynolds number calculations at different flow rates, and the corresponding convective heat transfer coefficients (hi, ho), overall heat transfer coefficient (U), and heat duty (Q) values were determined. Following simulation calibration, experimental investigations were conducted using CuO–water nanofluids with two distinct particle sizes (38 nm and 20 µm) and three concentrations (0.25%, 0.5%, and 0.75%). The impact of these parameters on the thermal performance of the STHE was evaluated under varying inlet temperature conditions. Experimental results revealed that cold fluid outlet temperatures increased significantly with the addition of nanoparticles, while hot fluid outlet temperatures decreased, indicating enhanced heat absorption. For 38 nm particles, the cold-side enhancement (ΔT) ranged from 1.0 °C to 2.2 °C, corresponding to approximately 5–12% improvement relative to the baseline. In contrast, 20 µm particles exhibited ΔT values of 1.5–2.7 °C, equating to a 6–14% increase depending on concentration and inlet temperature. The most pronounced enhancements were observed at 0.5% and 0.75% concentrations, particularly at higher temperature gradients, demonstrating that both particle size and concentration play critical roles in nanofluid-mediated heat transfer enhancement.

Characterization of Oil from Trunk Fish (Moryrus Rume)

2026-08-21T18:55:21+03:00

Fish is an important source of food that provide high protein content and essential amino acids to the body. Fish oil produced internationally (marine fish) are expensive to procure and occasionally unavailable. However, expression of oil from freshwater fish species will provide cheap, abundant and readily available product. This study therefore, aimed at the expression of fish oil from Mormyrus rume. A total of 10kg of Mormyrus rume was procured from Kainji Lake Basin, New Bussa Niger State. The fish were divided into three samples 1, 2 and 3 respectively. Sample 1 was pre-heated for a period of 10 minutes, at maximum temperature of 90⁰C, sample 2 for 15 minutes at a maximum temperature of 100⁰C and sample 3 for 20 minutes at maximum of 100⁰C. After pre-heating, samples were immediately transferred to laboratory for oil expression using a continues mechanical extruder. The characterization of the expressed fish oil was measured using the specific gravity, saponification value and free fatty acid value. Results showed that the fish oil from samples 1, 2, and 3 had specific gravity of 0.910, 0.907 and 0.909 respectively, the saponification value of 122.110mg/KOH/g, 124.582mg/KOH/g and 123.102mg/KOH/g respectively while the free fatty acid value was found to be 1.286% for sample 1, 1.342% for sample 2, and sample 3, 1.401. It is observed that the fish oil values ware within the acceptable standard value which are suitable for application in pharmaceutical and food industries. Therefore, Moryrus rume has the potential of producing fish oil for industrial and domestic use.

Theoretical Study to Design Efficient Dye-Sensitized Solar Cell (DSSC): A DFT/TDDFT Approach

2026-08-21T18:55:21+03:00

The electronic, optical, and photovoltaic parameters of 2,2′-biquinoline-4,4′-dicarboxylic acid (2BA) were investigated using the B3LYP and M06-2X hybrid functionals of density functional theory (DFT) with the basis set 6-311++G (d, p). The frontier molecular orbital (FMO) energies, absorption wavelengths, and electronic characteristics (total energy and energy range) of the 2BA were calculated using the B3LYP and M06-2X levels of time-dependent DFT (TD-DFT) with the 6-311++G (d, p) basis set. The TD-DFT method, employing the integral equation formalism-polarized continuum model (IEF-PCM), was utilized to investigate electronic transitions within the solvent environment (ethanol and methanol). When calculations performed using two different methods were compared with experimental values, the results closest to the experimental values were obtained using the TD-DFT/B3LYP method in ethanol. Photovoltaic parameters such as light harvesting efficiency (LHE), open-circuit voltage (V_oc), driving force for electron injection (ΔG_inj), and driving force for dye regeneration (ΔG_reg) were similarly calculated and analyzed. LHE calculations showed that the DFT/M06-2X method calculated better values than the TD-DFT/B3LYP method.

Experimental Investigation of the Pressure Drop of the Liquid Refrigerant in the Copper Tube Used in Air Conditioning Condensers

2026-08-21T18:55:21+03:00

Air-conditioning systems used in vehicles are required to deliver higher performance than those used in residential or stationary building applications due to their dynamic operating environments, stringent thermal comfort requirements, and the limited space available for system installation. Pressure drop in the tubes used in condensers and evaporators of automotive Heating, Ventilation, and Air Conditioning (HVAC) systems significantly affects compressor sizing and overall system performance. In HVAC applications, minimizing pressure drop while maintaining a high heat transfer coefficient is essential for improving energy efficiency and reducing compressor power consumption. This study presents an experimental investigation of the pressure drop characteristics of liquid refrigerants R-134a and R-1234yf flowing through a smooth circular copper tube. The variations in pressure drop were analyzed as a function of refrigerant mass flux and Reynolds number. In addition, friction factors were determined from the experimental data and compared with the widely used Blasius correlation. The resulting coefficients were evaluated against those predicted by the Blasius equation. The results indicate that the frictional pressure drop increases with increasing refrigerant mass flux for both refrigerants. The findings contribute to a better understanding of refrigerant flow behavior in compact heat exchanger tubes and provide valuable data for the design and optimization of high-performance automotive HVAC systems.

Enhanced Intelligent Crowd Control and Hazard Prevention System for Religious Places Using IoT

2026-08-21T18:55:21+03:00

Managing large crowds in religious places is a significant challenge due to the increased risk of overcrowding, stampedes, and unexpected hazards such as fire and gas leaks. Existing crowd management approaches are mostly manual and lack real time monitoring and quick response capabilities. This paper proposes an enhanced intelligent crowd control and hazard prevention system using Internet of Things technology to improve safety and management efficiency. The proposed system integrates sensors, cameras, and microcontrollers to continuously monitor crowd density and environmental conditions. The collected data is transmitted to a centralized platform for analysis to detect abnormal crowd behavior and potential hazards. When critical situations are identified, the system generates alerts for authorities and activates warning mechanisms to guide the crowd and reduce congestion. The system also supports remote monitoring, enabling faster decision-making and effective emergency response.

Optimization of Operational Design Parameters of Superheated Steam Micro Power Plant

2026-08-21T18:55:21+03:00

High cost of maintaining power plants has hindered the sustenance of small scale businesses; hence, there is the need to optimize plant’s operational parameters to enhance energy delivery efficiency for domestic and SMEs consumption. This study applied strategies of reduction of heat losses through optimal design for micro power plant operational parameters. For the 5-10 kW plant at PKS fuel feeding rates of 0.000703 kg/s and 0.000352 kg/s, temperatures (pressures) of 220^oC (0.38 MPa), and 235^oC (0.35MPa), optimal steam mass flow rate of 0.00357 kg/s and 0.00178 kg/s were respectively established. For safety and economy of operation, running at the lowest possible temperatures (pressures) of 235 ^oC (0.35 MPa) would be sufficient in both plants (5-10 kW) for generating optimum steam flow velocities (14.87 m/s, 7.43 m/s). This outcome outperformed the known micro power plants by at least 12%.

Process-Level Noise and Vibration Hazard Characterization for Engineering Control Prioritization in a Bottled Water Manufacturing Facility

2026-08-21T18:55:22+03:00

Machine-generated noise and vibration vary considerably across manufacturing processes, yet engineering interventions are frequently implemented without quantitative process-level prioritization. This study characterized workstation vibroacoustic conditions in a semi-automated bottled water manufacturing facility to identify production units requiring priority engineering control. Field measurements of machine generated noise and mechanical vibration were carried out using calibrated sound level and vibration meters, in the polyethylene terephthalate (PET) Blow, Water Treatment and Bottling/Packaging sections during ambient, idle and production operating conditions. Descriptive statistics, coefficients of variation, one-way analysis of variance (ANOVA), Games–Howell post hoc comparisons, and an Engineering Control Priority Index (ECPI) were applied to determine differences between production units and to rank intervention priorities. During production, the Water Treatment and Bottling/Packaging sections had higher mean noise levels (92.83 and 92.32 dB(A)) and vibration accelerations (7.15 and 7.29 m/s²) than the PET Blow section. Significant differences were found for both noise (p < 0.001, η² = 0.723) and vibration (p < 0.001, η² = 0.765). ECPI analysis identified the Water Treatment and Bottling/Packaging sections as the highest priorities for engineering intervention. The proposed framework provides a practical basis for engineering control prioritization and maintenance planning in manufacturing environments.

IOT-Based Intelligent Beehive Monitoring System using Acoustic and Environmental Analytics

2026-08-21T18:55:22+03:00

In the article, an IoT-based intelligent beehive monitoring system is developed by integrating acoustic signal processing with environmental monitoring for non-invasive, continuous monitoring of the health and behavior of the beehive population. An ESP32 microcontroller is used to collect the acoustic signal from the beehive and environmental parameters such as microclimate, send the signals to the cloud server for feature extraction, and perform the required signal processing for feature extraction, such as FFT, MFCC, etc., and send the results to the cloud server for monitoring the beehive population and send alerts in case of any issues such as swarming, queen loss, disease-related stress, etc., in the beehive population. The results obtained by testing the proposed system in experimental beehives indicate that the proposed system is capable of monitoring the beehive population by identifying the acoustic signals and microclimate changes that occur in the beehive population before the actual issues arise, thereby reducing the need for invasive monitoring of the beehive population.

Land Use Conflicts Between Residential and Industry Sectors on One Side and Utility-scale Photovoltaics on Another – a Missing Concept Gaining Importance.

2026-08-21T18:55:22+03:00

The purpose of this research note is to draw the attention of the researchers to the potential land use conflict that emerges during the energy transition. Namely, the competition between utility-scale photovoltaics (USPV) on one side and residential and industrial development on the other. This issue is an overlooked problem, even though other types of land use conflict have been raised in recent literature. The reason why this issue is unaddressed is probably because the described problem is not yet evident. However, population growth and industrialisation processes, together with increasing electricity demand, in particular the demand for renewable energy, are the main drivers of potential land use conflicts. The role of this paper is to shed light on the missing concept of land use conflict in the age of energy transition.