Journal of Engineering & Technological Advances

REVIEW OF STRUCTURE AND APPLICATION IN THREE-AXIS CNC MACHINING: ERRORS, TOOL PATH STRATEGIES, AND EFFICIENCY IMPROVEMENTS

Walisijiang Tayier — 2024-07-29

The increasing demands for rapid production have significantly boosted the use of CNC systems in industries. Over the past decade, efforts have concentrated on improving the time efficiency and accuracy of CNC machines. This paper reviews research on CNC machine structures, highlighting common errors such as geometric inaccuracies. It examines advanced tool path generation strategies, including traditional methods and next-generation algorithms like genetic algorithms and the simplex search method. The review assesses these strategies' impacts on machining efficiency and accuracy, comparing current and historical approaches. The objective is to present a comprehensive overview of advancements in CNC machining, contributing to the development of more efficient, precise, and reliable manufacturing technologies.

TRENDS IN AUTISM SPECTRUM DISORDER PREDICTION USING MACHINE LEARNING: A REVIEW

Fakhitah Ridzuan — 2024-07-29

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that significantly affects social, linguistic, and cognitive skills. Early diagnosis is crucial for improving long-term outcomes, yet traditional diagnostic methods are time-consuming and expensive. This review aims to explore the potential of machine learning techniques in enhancing the accuracy and efficiency of ASD prediction and diagnosis. By examining ten studies, the review evaluates the various machine learning (ML) algorithms used, pre-processing techniques employed, and datasets analysed. Key findings indicate that pre-processing techniques such as handling missing values, normalization, and feature selection are vital for improving model accuracy. Support Vector Machine and Logistic Regression consistently demonstrated high accuracy in predicting ASD across various datasets. The conclusion underscores the importance of pre-processing in developing reliable machine learning models for ASD prediction and highlights the need for future research to address challenges related to data accessibility, model interpretability, and validation across diverse populations. The responsible integration of ML technologies into clinical practice could revolutionize early diagnosis and intervention strategies for ASD.

ENHANCING CNC PRECISION: A REVIEW OF GEOMETRIC ERRORS AND SIMULATION METHODS IN THREE-AXIS CNC SYSTEMS

Walisijiang Tayier — 2024-07-29

The rapid expansion in industrial production has markedly increased the deployment of computer numerical control (CNC) systems. Recent efforts have concentrated on optimizing these machines for time-efficient cutting tool operations. The accuracy of CNC systems is heavily dependent on their geometric configurations, but geometric errors such as alignment deviations, backlash, and thermal deformation can compromise structural integrity and operational precision. This review focuses on the role of simulation in three-axis CNC machining, particularly through techniques like finite element analysis (FEA), to predict and mitigate these errors. By examining various CNC machine components, the review highlights how simulation methodologies can address geometric inaccuracies. Key findings indicate that integrating advanced simulation tools with CNC systems effectively reduces geometric errors, enhances machining accuracy, and improves overall system performance. This integration leads to more reliable and precise machining operations, thereby advancing the efficiency and effectiveness of CNC systems in high-precision manufacturing environments.

BIOMECHANICAL RESPONSE COMPARISON OF NIGERIAN CHILD ANTHROPOMETRIC TEST DEVICE (ATD) AND HYBRID III DUMMY

Ibrahim Rafukka — 2024-07-29

Anthropometric Test Devices (ATD) or crash dummies are used to simulate the response of human beings in crash tests of vehicles. There is concern about the difference in anthropometry of people from various locations of the world and current crash test dummies used in safety certification of vehicles. Three-year-old (3YO) Hybrid III dummy may not represent Nigeria children because they were produced using United States child anthropometry. The aim of this work is to investigate how the size of 3YO Nigeria child dummy affects crash injury outcomes in Finite Element (FE) crash analysis. FE dummy model that is scaled to Nigeria child anthropometry was used to simulate a sled test and the injury parameters such as head accelerations, chest acceleration and resultant upper neck moment and force were evaluated and compared with experimental results of with the view to ascertain how good can represent Nigerian child in crash test. The results show that is different from in head acceleration and chest acceleration by 29% and 6% respectively. Nigerian child resultant upper neck moment and force were 10% and 23% respectively lower than . Difference in the injury outcomes means that model cannot represent three-year-old Nigerian child in certification. Hence crash dummy of Nigerian child anthropometry is necessary in certifying vehicle safety performance for cars used in Nigeria.

ASSESSING THE RAPID DRAWDOWN RISKS ON SLOPE STABILITY

Priyadatchini Karunakaran — 2024-07-29

This study investigates the slope failure that occurred at a 152.18-acre residential development in Kulim. The unreinforced slope was reported to be deemed stable before its failure in the mid-April 2023. Continuous pumping activity for nearby basement construction had been underway for several weeks prior to the failure. To confirm the causality of drawdown effect, the groundwater level was monitored using two piezometer standpipes. The fieldwork investigation confirmed a significant difference in groundwater levels caused by the dewatering activities. By developing a numerical model using Slope/W software, slope stability analysis was performed to assess the slope performance before and after the failure, analysing the impact of dewatering. The findings revealed a significant reduction in the factor of safety (FOS) from 1.348 to 1.080, not adhering to the Jabatan Kerja Raya (JKR)’s slope specifications of a minimum FOS of 1.3 for unreinforced soil. The findings also confirmed the detrimental effect of rapid drawdown on the strength of the slope. To mitigate the slope failure, gabion walls were proposed as cost-effective alternatives. This remedial measure increased the FOS to 1.612, meeting JKR specifications of a minimum FOS of 1.5 for reinforced soil. The findings highlight the importance of educating on groundwater management to enhance safety and mitigate similar risks in future projects.

ENHANCING THE PERFORMANCE OF SOLAR TOWER POWER PLANTS USING AN AUXILIARY HEAT SOURCE

Dr Mohammad Hossein Yazdi — 2024-07-29

The solar tower power plant represents a cutting-edge solar thermal system designed to harness clean solar energy for electricity generation. Due to its abundant availability and cost-effectiveness, this technology has garnered significant interest recently. Solar power, as one of the most promising renewable energy sources, offers a sustainable alternative to fossil fuels, contributing to a reduction in greenhouse gas emissions and dependence on non-renewable energy resources. However, a major challenge lies in the plant's low efficiency and its inability to generate electricity during nighttime, cloudy weather, or rainfall. To tackle this challenge, our approach involves designing a solar tower power plant that integrates an external heat source to complement solar energy and ensure uninterrupted electricity production. This integration not only enhances the reliability of the power supply but also maximizes the utilization of renewable energy resources. The collector, a crucial component of the solar tower power plant, accounts for a significant portion of both construction costs and energy loss. Improving the collector's performance is therefore essential for enhancing the overall efficiency and economic viability of the plant. In this project, a novel collector design is proposed that not only heats the air under the collector through solar radiation but also utilizes an auxiliary heat source to further raise the air temperature. This increase in temperature accelerates air flow, which in turn enhances turbine rotation and consequently boosts electricity generation.

PREDICTIVE ANALYTICS FOR PATIENT MANAGEMENT SYSTEM USING IOT

SHIJITHA R — 2024-07-29

Lack of health care or inaccessibility of doctors and caregivers is a major concern. Patient health care puts tremendous pressure on hospital management in urban areas. Therefore, the development of IOT (Internet of Things) based patient monitoring systems allows doctors to obtain patient data from remote locations. The Internet of Things is an evolving technology that takes healthcare to the next level by providing affordable, reliable, and convenient devices that can be carried or embedded with patients. There is a growing interest in wearable sensors and medical devices. Therefore, wearable monitoring systems will take patient monitoring to a new level. The IOT allows various devices to be connected over the Internet. Data is collected using sensors and sent to the cloud via IOT channels, where both patients and doctors can access the data (real-time and historical) through a variety of devices. Any deviations from the norm will send alerts to both doctors and patients. This helps healthcare providers monitor a large number of patients at the same time.

METHOD OF UNDETERMINED COEFFICIENTS IN SOLVING THIRD-ORDER LINEAR DIFFERENTIAL EQUATIONS: A COMPREHENSIVE ANALYSIS

Noel Victor Aprecio — 2024-07-29

Higher-order linear differential equations have great significance theoretically and practically. This paper solves a third-order linear differential equation with constant coefficients by method of undetermined coefficients. Its strengths and limitations were analysed. Analysis suggests that the method of undetermined coefficients requires that the inhomogeneous term be algebraic, exponential, or sinusoidal functions only. Additionally, if the inhomogeneous term is a solution of the differential equation itself, may yield a linear combination of . In such case, the prediction for will be modified by multiplying the variable however many times necessary.