Journal of Applied Engineering Design and Simulation

Improving Automotive Accessory Development: A Warranty-Based Analysis of Material Defects and Process Enhancement

2025-07-25T15:53:12+08:00

Automotive accessories play a crucial role in enhancing vehicle safety, aesthetics, and functionality; however, they account for a significant portion of recurring warranty claims at MNC Automotive. In 2022, analysis of warranty claims data revealed that 30% of total claims were attributed to a single accessory type, indicating systemic weaknesses in design validation, supplier performance, and quality assurance. To address these challenges, this study proposed an improved accessory part development process that emphasizes early supplier collaboration, comprehensive design validation, statistical validation methods (such as SPC, Regression Analysis and Confidence Intervals), and standardized manufacturing practices. The study integrated SPC (Control Charts) and regression analysis to validate defect trends and link supplier performance with defect rates, offering quantitative validation beyond qualitative tools like Pareto charts and Ishikawa diagrams. Confidence intervals were calculated to estimate defect reduction, providing a statistical basis for the improvement strategies. Furthermore, the study included a cost-saving analysis, indicating potential RM 1.5 million savings, which was estimated through a cost-benefit analysis that simulates the ROI from improved processes. Incorporating comparative benchmarking with historical data allows us to track the severity and progress of improvements in defect rates and warranty claims. Additionally, the study integrated a more detailed evaluation of supplier performance, where supplier audits and performance ratings were used to identify critical areas for improvement in quality control. The proposed part development process aligns with APQP, PPAP, and IATF 16949 frameworks, ensuring that the model conforms to globally recognized quality management standards. Key elements of these frameworks, such as early engagement, traceability, and continuous improvement cycles, were incorporated to address recurring quality issues, thereby improving product reliability, reducing defects, and strengthening supplier relationships. This study contributes to the broader field of automotive engineering by offering a data-driven approach to improving the manufacturing and supply chain processes, with implications for reducing long-term costs, enhancing product quality, and improving customer satisfaction. By addressing key weaknesses in supplier collaboration, design validation, and quality assurance, the proposed improvements are expected to lead to significant reductions in warranty claims, ultimately benefiting both manufacturers and consumers.

Planning Preventive Maintenance for Press Machine using Reliability Centered Maintenance (RCM) Method: A Case Study in a Plantation Company

2025-07-16T19:30:20+08:00

This research focuses on the organized preventive maintenance scheduling of screw press machine for palm oil processing machine in maintaining the company’s productivity and product quality. The minimization of failure risk and productivity enhancement was investigated by means of Reliability Centered Maintenance (RCM) methodology. The preventive maintenance plan was developed based on Failure Modes and Effects Analysis (FMEA) for critical components such as worm screws, bearings, lengthening shafts, and press cages in determining risk and crucial factor which affects productivity. Reliability data from January to December 2023 indicated the initial conditions of these components. Data for this study were collected over a 12-month period, from January to December 2023, to characterize the baseline operational conditions of the system components. Through the application of the proposed reliability-centered maintenance approach, it was determined that achieving a target reliability level of 70% requires a structured maintenance schedule. This includes reconditioning the worm screws every 22 days using SS 304 electrode wire, replacing bearings at 22-day intervals prior to reaching their estimated technical lifespan, inspecting bolts and nuts on the lengthening shaft every 17 days, and inspecting and cleaning the press cage every 18 days. Failure Modes and Effects Analysis (FMEA) confirmed that the implementation of this maintenance strategy significantly reduces the risk of screw press machine failures, mitigates unplanned production downtime, and enhances overall operational efficiency. These improvements contribute to meeting production targets effectively in the context of a competitive global manufacturing environment.

Dung Beetle Optimization Algorithm for Predicting Damage to 2D Truss Structures

2025-09-02T10:55:42+08:00

This study predicts the degree of damage in 2D truss members using the Dung Beetle Optimization algorithm (DBO) in conjunction with finite element analysis for searching natural frequencies. The difference in these natural frequencies between the finite element model and actual measurements is known as the objective function. A number of scenarios, from simple to complex, are proposed to assess the performance of this algorithm. The convergence results, which are based on MATLAB software, required only 25~30 iterations and were then displayed to validate the potential practical use of DBO. Moreover, this short study only focused on the application of DBO to predict damage of truss structures, without going into the comparison of advantages and disadvantages with other existing algorithms.

Design and Experimental Evaluation of a Tilt-Angle Propeller Test Rig for Vertical Thrust Characterisation of the TRQ-1 Quadcopter

2025-08-22T14:41:19+08:00

This study presents the design and experimental evaluation of a custom-built test rig that was specially developed for vertical thrust measurement of the TRQ-1 quadcopter prototype, The test rig was designed to replicate the TRQ-1's tilt mechanism. The custom-built test rig enables accurate and repeatable thrust measurements under varying tilt-angles. In this work, a series of experiments were conducted using an APC 10×5 propeller to quantify vertical thrust at 0°, +15°, and -15° tilt-angles across a range of rotational speeds starting from 1500 RPM up to a maximum of 5500 RPM. Validation against available manufacturer thrust data confirmed the rig's measurement accuracy, and deviations from manufacturer thrust data were generally within ±5%, with a maximum deviation of 7.12% at low RPM (2010) and minimum deviation of 1.33% at higher RPM (3060–5010). These values confirmed the accuracy of the rig within acceptable engineering tolerances. The results indicated that a +15° forward tilt configuration consistently reduces vertical thrust due to thrust vector redirection. Meanwhile, the -15° rearward tilt configuration yielded a modest increase in vertical thrust, especially at lower RPMs range. These findings are consistent with aerodynamic theory, which highlights the trade-off between thrust vectoring for manoeuvrability and vertical lift performance. The proposed test rig demonstrates reliable performance and provides a consistent tool to evaluate the aerodynamic behaviour of tilt-propeller quadcopter configurations.

Soliton For Optical Sensor : Numerical Studies

2025-09-02T12:35:33+08:00

Soliton for optical sensors is essentially a new way for overcoming a sensing sensitivity constraint. High sensitivity in terms of device accuracy is in demand nowadays, and it plays an important part in achieving improved performance. Due to this constraint, we observe that the largest sensing limitation originates from the input optical pulse that travels inside the waveguide, which governs pulse reduction before sensor testing. As a result, the development of optical soliton is required to circumvent this limitation. In the present work, we proposed design recommendations for soliton-based optical sensors by numerically investigating soliton production in a silicon channel waveguide. The effects of nonlinearity, dispersion, and waveguide geometry on soliton stability were examined. The findings indicate that adjusting the waveguide thickness to 300 nm guarantees single-mode operation at 1.55 µm, resulting in an anomalous dispersion regime with group velocity dispersion of –26.83 ps²·mm⁻¹ and a group index of 6.96. Stable solitary pulse propagation was made possible by the calculated soliton order of 0.84, which indicates operation near the basic soliton regime. At waveguide length of 8.7 mm, where dispersive and nonlinear effects are well balanced, maximum transmission took place, but soliton production required a minimum length of ~4.5 mm. At this length, the soliton retained its intensity and pulse waveform, indicating strong propagation conditions. These findings provide a mathematical framework for connecting soliton order, dispersion length, and nonlinear length to sensor performance. The findings show that maintaining pristine soliton output within a silicon waveguide is a straightforward strategy to improve the sensitivity as well as performance of next-generation optical sensors.

The Effect of Mold Curing on the Mechanical Integrity of Cold Mix Asphalt: A Laboratory Study from Marshall Stability Perspective

2025-09-09T12:31:19+08:00

Cold Mix Asphalt (CMA) is increasingly recognized for its environmental and economic advantages, yet its mechanical performance is still heavily reliant on the curing condition, an aspect often ignored in laboratory evaluations. A lack of standardized curing procedures during sample preparation has led to inconsistencies in performance assessments, making it difficult to compare results across studies or optimize mix designs effectively. This study presents a laboratory investigation in order to examine the impact of curing conditions on the mechanical integrity of CMA, with a particular focus on the mold curing process. CMA specimens were cured both inside and outside the Marshall mold to evaluate differences in mechanical performance as measured by the Marshall Stability test. It is found that specimens which underwent curing inside the mold have higher Marshall Stability value with 7.480kN as compared to 3.415kN for specimens that were cured outside of the mold. The results show a significant greater stability and durability for the specimens cured inside the mold due to enhanced cohesive development and the preservation of compaction. While this curing approach may not replicate actual field conditions, the findings are vital for improving laboratory protocols and ensuring accurate, reproducible evaluations of CMA formulations

Improving Workplace Safety: An Ergonomic Assessment and Engineering Control Approach

2025-09-12T20:22:06+08:00

Workplace injuries in machining departments, particularly back pain from manual handling, reduce productivity and increase manpower shortages. This study aimed to identify the root causes of these injuries and propose an engineering control solution through the Plan-Do-Check-Act (PDCA) cycle. Hazard Identification, Risk Assessment, and Risk Control (HIRARC), Ishikawa diagram analysis, and ergonomic assessment using the Rapid Entire Body Assessment (REBA) were applied to evaluate existing practices. The findings showed that lifting cutting tools from low storage racks produced a high REBA score of 9, indicating a high risk of musculoskeletal disorders. A new ergonomically designed storage rack concept was developed and evaluated using CATIA V5 software, with three alternatives compared through a Pugh Chart. Design B, which eliminated the need for trunk bending, was selected. Reassessment revealed that the REBA score decreased from 9 to 2, while the risk score for back pain was reduced from 12 to 3, achieving a 75% risk reduction. These improvements demonstrate a significant enhancement in workplace safety, reducing injury risks and improving productivity. The study highlights how ergonomic interventions integrated with the PDCA framework can provide practical solutions for minimising occupational hazards and ensuring sustainable productivity.

Performance Comparison of A and Dijkstra Algorithms with Bézier Curve in 2D Grid and OpenStreetMap Scenarios

2025-06-23T17:25:29+08:00

This paper presents a comparative study of the A* and Dijkstra algorithms for path planning in both 2D grid maps and real-world OpenStreetMap (OSM) environments. The evaluation focused on three key performance metrics: computational efficiency, path smoothness, and the number of turns. Both algorithms were tested under varying obstacle densities, and Bézier curve smoothing was applied to enhance path quality. In 2D grid maps, A* consistently generated smoother paths with fewer turns, especially in complex environments. Its heuristic-based search allowed it to expand fewer nodes, resulting in faster computation times compared to Dijkstra. On the other hand, Dijkstra's algorithm, though robust and optimal, exhibited longer runtimes and produced paths with more turns due to its exhaustive search approach. In the OSM-based scenarios, both algorithms yielded paths of identical length. However, A* significantly outperformed Dijkstra in terms of runtime across most test cases, further demonstrating its computational advantage. These findings validate A*’s practical advantage of real-time applications where both efficiency and path quality are crucial. While Dijkstra remains a reliable benchmark, A* offers a balanced trade-off between speed and path quality, making it more suitable for real-world path planning applications in both structured and unstructured environments.

A Modular Java-Based Framework for Deploying Deep Learning Time-Series Forecasting Models via ONNX

2025-09-08T18:22:35+08:00

Abstract

Numerical Predictions on the Wake Interference Flow in Two-dimensional Street Canyon based on Various RANS Turbulence Closure Models

2025-09-25T10:11:14+08:00

The precise numerical prediction of urban flow patterns is crucial for evaluating ventilation performance, pollution dispersion, and pedestrian comfort in densely built environments. Among these types of patterns, the wake interference flow poses a distinct modeling difficulty due to its complex vortex dynamics. This study performs a series of steady Reynolds-Averaged Navier-Stokes (RANS) simulations to evaluate the predictive efficiency of five turbulence closure models: standard k-ε (STD), renormalisation group k-ε (RNG), realizable k-ε (RLZ), shear-stress transport k-ω (SST), and Reynolds stress model (RSM) in a two-dimensional (2D) idealized street canyon with an aspect ratio of 3 within the wake interference flow regime. The predicted results are compared with wind tunnel experimental data using velocity profiles, statistical validation metrics, and streamlines visualization.The results demonstrate that the quantitative assessment utilizing the factor of two observations (FAC2) distinctly reveals a satisfactory predicted of streamwise velocity within the street canyon, topped by RNG (0.92) and followed by STD (0.91), RSM (0.90), SST (0.89), and RLZ (0.88). Nevertheless, all models inadequately predict the vertical velocity, as the FAC2 values fall below the threshold of 0.5. The qualitative assessment of the velocity streamlines indicates that the RNG and STD predictions closely resemble the flow pattern obtained from the experimental results that determine the main characteristics of the wake interference flow regime. Other models exhibited inadequate performance due to the observation of completely different flow patterns. Consequently, it can be concluded that while all models can estimate the streamwise velocity in the wake interference regime with good accuracy, substantial constraints persist in predicting the in-canyon vertical velocity. The observed limitations, together with the apparent variation between models in replicating secondary vortex formations, suggest several avenues for future investigations.