Computer-aided Design Tools Research Articles

Latin American Natural Product Database (LANaPDB): An Update.

Natural product (NP) databases are crucial tools in computer-aided drug design (CADD). Over the past decade, there has been a worldwide effort to assemble information regarding natural products (NPs) isolated and characterized in certain geographical regions. In 2023, it was published LANaPDB, and to our knowledge, this is the first attempt to gather and standardize all the NP databases of Latin America. Herein, we present and analyze in detail the contents of an updated version of LANaPDB, which includes 619 newly added compounds from Colombia, Costa Rica, and Mexico. The present version of LANaPDB has a total of 13 578 compounds, coming from ten databases of seven Latin American countries. A chemoinformatic characterization of LANaPDB was carried out, which includes the structural classification of the compounds, calculation of six physicochemical properties of pharmaceutical interest, and visualization of the chemical space by employing and comparing two different fingerprints (MACCS keys (166-bit) and Morgan2 (2048-bit)). Furthermore, additional analyses were made, and valuable information not included in the first version of LANaPDB was added, which includes structural diversity, molecular complexity, synthetic feasibility, commercial availability, and reported and predicted biological activity. In addition, the LANaPDB compounds were cross-referenced to two of the largest public chemical compound databases annotated with biological activity: ChEMBL and PubChem.

CAD Sensitization, an Easy Way to Integrate Artificial Intelligence in Shipbuilding

There are two main areas in which the Internet of Ships (IoS) can help: firstly, the production stage, in all its phases, from material bids to manufacture, and secondly, the operation of the ship. Intelligent ship management requires a lot of information, as does the shipbuilding process. In these two phases of the ship’s life cycle, IoS acts as a key to the keyhole. IoS tools include sensors, process information and real-time decision-making, fog computing, or delegated processes in the cloud. The key point to address this challenge is the design phase. Getting the design process right will help in both areas, reducing costs and making agile use of technology to achieve a highly efficient and optimal outcome. But this raises a lot of new questions that need to be addressed: At what stage should we start adding control sensors? Which sensors are best suited to our solution? Is there anything that offers more than simple identification? As we begin the process of answering all these questions, we realize that a Computer Aided Design (CAD) tool, as well as Artificial Intelligence (AI), mixed in a single tool, could significantly help in all these processes. AI combined with specialized CAD tools can enhance the sensitization phases in the shipbuilding process to improve results throughout the ship’s life cycle. This is the base of the framework developed in this paper.

Static IRdrop Analysis Using Open Source CAD Software

This paper investigates the open source static IRdrop analysis tool, PDNSim, which is part of the OpenROAD computer-aided design tool. The main approach used for static IRdrop analysis is discussed, namely the compilation of an equivalent circuit model used for further calculations. The results of static IRdrop analysis obtained using PDNSim are compared with the results obtained using modern commercial CAD tool and the error of the obtained analysis results is evaluated.

On the coupled effect of a MIS-based anode and AlGaN-polarized super-junction to reduce the local electric field for AlGaN/GaN Schottky barrier diodes

This work employs advanced physical models with the help of technology computer-aided design tools to systematically design and investigate AlGaN/GaN Schottky barrier diodes (SBDs), focusing on enhancing forward conduction and reverse blocking characteristics. A recessed metal/insulator/III-nitride (MIS) anode is demonstrated to manage electric field distribution. The incorporation of a 1 nm thick Al2O3 layer enables a reduced leakage current and a significant increase in breakdown voltage (BV). Subsequently, tailored field plates (FPs) further improve the BV of the MIS SBD to ∼1650 V but strong electric field magnitude will be found at the edge of the FP. Hence, a MIS SBD with a graded AlGaN barrier layer (MIS-GA SBD) is designed, featuring a gradient decrease in Al content along the [0001] direction. The generation of negative polarization charges within the barrier functions as a super-junction, significantly homogenizing the electric field. As a result, the MIS-GA SBD achieves a remarkable BV exceeding 3500 V, highlighting its strong potential for high-voltage power electronic applications.

Sketching Versus Digital Design Tools in Architectural Design

Sketching is a design tool that can be assumed to be ill-structured, does not offer exact solutions, is intuitive, and is open-ended in the initial stages of architectural design. Sketching creates an opportunity for architects to release their creativity and intuition, giving rise to spontaneous ideas and concepts in an organic and natural way. During the initial design phases, like in the conceptual stage of the design, designers receive aid from conventional sketching as their concepts and ideas can easily transform into tangible, real-world forms. With the development of digital design methods like CAD (computer-aided design) in pursuit of AI (artificial intelligence), it has been accepted that manual sketches are no longer the only method used in the design process, and the trend toward using new methods has begun. The diversity and evolution of tools used in architectural design, together with the integration of CAD, AI, and traditional sketching techniques, have contributed to the development of architectural design and facilitated enhanced collaboration, visualization, and efficiency across the design process. As a result, it has evolved to embrace the use of CAD, which was the first method adopted from these developments, as a basic skill in the field of architectural design education. This shift places a strong emphasis on the professional field of architectural design while also encouraging students to explore the innovative potential of CAD for design purposes. CAD presents architects with a robust platform that facilitates the creation of intricate designs and precise measurements during the initial stages of the design process. Following CAD, the development of AI-driven design tools motivates architecture students and designers to transform their concepts into concrete designs. Although it is known that each method mentioned has its own positive or negative aspects, it is not possible to say that any of them is used alone in architectural design processes. At this point, combining the design process with CAD and AI-supported design tools, as well as traditional manual sketching in architecture, helps develop a diverse and adaptable skill set in design. Integrating digital design tools into the architectural field emphasizes the enduring importance of traditional sketches, especially in terms of inspiration and conceptualization in architectural design, while also updating the design process. This document aims to explore the progression of employing diverse design tools, namely manual sketching, CAD, and AI-driven design tools, throughout the architectural design process. This paper undertakes a comparative analysis of using computational design tools instead of traditional sketching with pen and pencil, aiming to juxtapose their respective benefits and drawbacks. In conclusion, although it is not yet possible to assert the superiority of one method over the other, it is evident that traditional sketching continues to hold significant relevance and effectiveness in the design process despite its long-term use.

A generative-AI-based design methodology for car frontal forms design

With the advancement of artificial intelligence, big data, and cloud computing, numerous generative AI applications have surfaced. In contrast to conventional generative design and computer-aided design tools, these applications significantly enhance design productivity. However, there are currently few design methodologies based on generative AIs in the academic community to improve the efficiency of industrial designers and optimize the design process. This study introduces a creative and practical methodology for designing car frontal forms based on generative AIs. In this methodology, imagery adjectives describing car frontal forms are generated by sending valid prompts to the text-generative AI application GPT-4.0. Then input typical imagery adjectives into the image-generative AI Midjourney successively as prompts to generate many car frontal forms that align with the typical imagery adjectives, forming a reference form database. Subsequently, a base form is selected, and target imageries are defined. Simultaneously, forms from the reference form database, conforming to the target imageries, are chosen as the reference forms. The main form elements of the base and reference forms are then delineated using cubic Bézier curves. Finally, a form curve blending algorithm is applied to obtain a set of alternatives, and the image-generative AI application Vega AI is utilized to convert the alternatives into three-dimensional renderings. FAHP-based expert evaluation and consumer perceptual evaluation are employed to validate the alternatives. Results indicate that the alternatives effectively capture the imageries of the reference forms. The proposed generative-AI-based design methodology enhances the efficiency of industrial designers, thereby minimizing human and material costs in product development. Additionally, this study presents a design case using various generative AIs to inspire designers to re-examine the traditional design process.

Innovating Pharmaceuticals: The Rise of 3D printing in Drug Delivery.

Additionally known as three-dimensional (3D) printing, additive manufacturing has made major advancements possible in the fields of engineering, business, the arts, education, and medical. Thanks to recent developments, it is now possible to print three-dimensional to create complex, useful living tissues, biocompatible substances, cells, and supporting structures are combined. Regenerative medicine is utilizing 3D bioprinting. Additive manufacturing technology, or 3D printing, has been labelled the “next big thing” and is predicted to overtake cell phones in popularity. 3D printers use digital templates to produce actual, three-dimensional items. Adding layers to a print, commonly referred to as additive manufacturing, allows for the use of more than a hundred different materials, including nylon, metal, and plastic. Applications for 3D printing can be found in many different industries, such as industrial design, manufacturing, dental, automotive, aerospace, civil engineering, education, jewellery, footwear, and geographic information systems. It has shown to be a simple and affordable solution for a variety of use cases. Using computer-aided design tools and programming, three-dimensional printing is a sophisticated technique that adds material to a base surface to create three-dimensional things. Additive layer manufacturing, also referred to as 3D printing, is the technique of creating three-dimensional things by depositing or solidifying material one layer at a time. Using a computer-aided design module, pharmaceutical components are organized in a three-dimensional pattern. Afterwards, the constituents are converted into a machine-readable format resembling the surface of a three-dimensional dosage form. 3D printing has been used for jewelry, shoe-making, architecture, engineering & construction, the automotive industry as well as the aerospace field, dentistry and medicine, plus geographic information systems (GIS), civil engineering and education. After that stage of the process is completed, the surface transferred to the machine is then printed in different layers. Bioprinting is an interdisciplinary domain that integrates additive manufacturing with biology and material sciences to manufacture threedimensional structures representative of living organisms. The ability to create biological tissues and organs has attracted considerable attention in biomedical research owing to the rising demand for personalized medicine. This scenario propelled bioprinting forward which received much interest thus triggering comprehensive research efforts by various players such as companies, universities as well as research institutes. The goal of this book is to provide a thorough analysis of the complex and rapidly evolving field of bioprinting by critically analyzing and evaluating the existing scientific literature.

Integrating deep learning, MATLAB, and advanced CAD for predictive root cause analysis in PLC systems: A multi-tool approach to enhancing industrial automation and reliability

The integration of Deep Learning (DL), MATLAB, and Advanced Computer- Aided Design (CAD) in the root cause analysis of prognostic errors in Programmable Logic Controller (PLC) systems represents a significant advancement in industrial automation and reliability. This research explores the synergistic application of these technologies to diagnose, predict, and mitigate failures in PLC systems, which are critical for controlling automated processes in various industries. By employing DL algorithms, the study enhances predictive maintenance capabilities, allowing for early detection of anomalies and reducing downtime. MATLAB is utilized as the central platform for data processing, algorithm development, and simulation, providing a versatile environment for integrating DL models with real-time data from PLCs. Advanced CAD tools are employed to model and visualize the physical systems controlled by the PLCs, offering a comprehensive view that bridges the gap between digital analysis and physical implementation. The research methodology includes data collection from PLC systems, DL model training and validation, MATLAB-based simulations, and CAD modelling. The findings demonstrate improved accuracy in identifying the root causes of PLC prognostic errors, leading to more efficient maintenance strategies and enhanced system reliability. This paper concludes that the integration of DL, MATLAB, and CAD provides a powerful approach for advancing predictive maintenance in industrial settings, ultimately contributing to greater operational efficiency and cost savings.

OpenECAD: An efficient visual language model for editable 3D-CAD design

Computer-aided design (CAD) tools are utilized in the manufacturing industry for modeling everything from cups to spacecraft. These programs are complex to use and typically require years of training and experience to master. Structured and well-constrained 2D sketches and 3D constructions are crucial components of CAD modeling. A well-executed CAD model can be seamlessly integrated into the manufacturing process, thereby enhancing production efficiency. Deep generative models of 3D shapes and 3D object reconstruction models have garnered significant research interest. However, most of these models produce discrete forms of 3D objects that are not editable. Moreover, the few models based on CAD operations often have substantial input restrictions. In this work, we fine-tuned pre-trained models to create OpenECAD models (0.55B, 0.89B, 2.4B and 3.1B), leveraging the visual, logical, coding, and general capabilities of visual language models. OpenECAD models can process images of 3D designs as input and generate highly structured 2D sketches and 3D construction commands, ensuring that the designs are editable. These outputs can be directly used with existing CAD tools’ APIs to generate project files. To train our network, we created a series of OpenECAD datasets. These datasets are derived from existing public CAD datasets, adjusted and augmented to meet the specific requirements of vision language model (VLM) training. Additionally, we have introduced an approach that utilizes dependency relationships to define and generate sketches, further enriching the content and functionality of the datasets.

Software for Bioprinting.

The bioprinting of heterogeneous organs is a crucial issue. To reach the complexity of such organs, there is a need for highly specialized software that will meet all requirements such as accuracy, complexity, and others. The primary objective of this review is to consider various software tools that are used in bioprinting and to reveal their capabilities. The sub-objective was to consider different approaches for the model creation using these software tools. Related articles on this topic were analyzed. Software tools are classified based on control tools, general computer-aided design (CAD) tools, tools to convert medical data to CAD formats, and a few highly specialized research-project tools. Different geometry representations are considered, and their advantages and disadvantages are considered applicable to heterogeneous volume modeling and bioprinting. The primary factor for the analysis is suitability of the software for heterogeneous volume modeling and bioprinting or multimaterial three-dimensional printing due to the commonality of these technologies. A shortage of specialized suitable software tools is revealed. There is a need to develop a new application area such as computer science for bioprinting which can contribute significantly in future research work.

Large-Scale Solar Potential Analysis in a 3D CAD Framework as a Use Case of Urban Digital Twins

Solar radiation impacts diverse aspects of city life, such as harvesting energy with PV panels, passive heating of buildings in winter, cooling the loads of air-conditioning systems in summer, and the urban microclimate. Urban digital twins and 3D city models can support solar studies in the process of urban planning and provide valuable insights for data-driven decision support. This study examines the calculation of solar incident radiation at the city scale in Sofia using remote sensing data for the large shading context in a mountainous region and 3D building data. It aims to explore the methods of geometry optimisation, limitations, and performance issues of a 3D computer-aided design (CAD) tool dedicated to small-scale solar analysis and employed at the city scale. Two cases were considered at the city and district scales, respectively. The total face count of meshes for the simulations constituted approximately 2,000,000 faces. A total of 64,379 roofs for the whole city and 4796 buildings for one district were selected. All calculations were performed in one batch and visualised in a 3D web platform. The use of a 3D CAD environment establishes a seamless process of updating 3D models and simulations, while preprocessing in Geographic Information System (GIS) ensures working with large-scale datasets. The proposed method showed a moderate computation time for both cases and could be extended to include reflected radiation and dense photogrammetric meshes in the future.

Ligand Binding Affinity Prediction for Membrane Proteins with Alchemical Free Energy Calculation Methods.

Alchemical relative binding free energy (ΔΔG) calculations have shown high accuracy in predicting ligand binding affinity and have been used as important tools in computer-aided drug discovery and design. However, there has been limited research on the application of ΔΔG methods to membrane proteins despite the fact that these proteins represent a significant proportion of drug targets, play crucial roles in biological processes, and are implicated in numerous diseases. In this study, to predict the binding affinity of ligands to G protein-coupled receptors (GPCRs), we employed two ΔΔG calculation methods: thermodynamic integration (TI) with AMBER and the alchemical transfer method (AToM) with OpenMM. We calculated ΔΔG values for 53 transformations involving four class A GPCRs and evaluated the performance of AMBER-TI and AToM-OpenMM. In addition, we conducted tests using different numbers of windows and varying simulation times to achieve reliable ΔΔG results and to optimize resource utilization. Overall, both AMBER-TI and AToM-OpenMM show good agreement with the experimental data. Our results validate the applicability of AMBER-TI and AToM-OpenMM for optimization of lead compounds targeting membrane proteins.

Strengths and limitations of web servers for the modeling of TCRpMHC complexes

Cellular immunity relies on the ability of a T-cell receptor (TCR) to recognize a peptide (p) presented by a class I major histocompatibility complex (MHC) receptor on the surface of a cell. The TCR-peptide-MHC (TCRpMHC) interaction is a crucial step in activating T-cells, and the structural characteristics of these molecules play a significant role in determining the specificity and affinity of this interaction. Hence, obtaining 3D structures of TCRpMHC complexes offers valuable insights into various aspects of cellular immunity and can facilitate the development of T-cell-based immunotherapies. Here, we aimed to compare three popular web servers for modeling the structures of TCRpMHC complexes, namely ImmuneScape (IS), TCRpMHCmodels, and TCRmodel2, to examine their strengths and limitations. Each method employs a different modeling strategy, including docking, homology modeling, and deep learning. The accuracy of each method was evaluated by reproducing the 3D structures of a dataset of 87 TCRpMHC complexes with experimentally determined crystal structures available on the Protein Data Bank (PDB). All selected structures were limited to human MHC alleles, presenting a diverse set of peptide ligands. A detailed analysis of produced models was conducted using multiple metrics, including Root Mean Square Deviation (RMSD) and standardized assessments from CAPRI and DockQ. Special attention was given to the complementarity-determining region (CDR) loops of the TCRs and to the peptide ligands, which define most of the unique features and specificity of a given TCRpMHC interaction. Our study provides an optimistic view of the current state-of-the-art for TCRpMHC modeling but highlights some remaining challenges that must be addressed in order to support the future application of these tools for TCR engineering and computer-aided design of TCR-based immunotherapies.

Digitalising BIPV energy simulation: A cross tool investigation

The long-term viability of Building Integrated Photovoltaics (BIPV) as a renewable energy technology has garnered increased attention in recent discussions. However, there is currently a noticeable absence of simulation tools specific to BIPV applications that can cover the whole modelling chain. It remains unclear to what extent existing PV and BIM-based simulation tools can effectively address the complexities of BIPV projects. Therefore, this study aims to assess the process of existing simulation tools for BIPV energy simulation, three standalone PV tools (SAM, PV*SOL premium, and PVsyst), two Building Information Modelling (BIM)-based standalone PV tools (BIMsolar and Solarius PV), two plug-ins in BIM-based tools (INSIGHT for Revit, Ladybug Tools for Grasshopper/Rhinoceros 3D), and one Computer-Aided Design and Drafting (CADD) tool plugin (Skelion for Sketchup). Based on one existing building project with three different types of BIPV-installations, this study explored the capability of these eight tools in modelling/importing building geometry, selecting weather data, setting system layout and array, evaluating the solar resource, estimating energy losses, and assessing energy generation. The simulation results are compared with monitored energy yield data and presented with deviation analysis. Suggestions focus on pointing out the future development directions for BIPV digital simulation. This study offers insights and guidance for digitalising the BIPV performance simulation in the complex building design.

Muqarnas in Islamic Architecture: Development, Materials, and Techniques

Muqarnas was first created during the first millinium AD and became a defining feature of Islamic architecture during the second mellinium, specifically between the 11th and 16th centuries, both in religious and secular contexts. Although largely abandoned by the 17th century, the use of muqarnas decoration reached its peak during the above period. This study examines muqarnas, its three-dimensional architectural embellishment, as well as its development and influence on modern architecture. For this purpose, the descriptive analytical approach was employed. Architectural surveys were carried out at the local level, while textual analysis was done to analyze the historical development. The history of muqarnas was traced from Islamic religious buildings to modern architecture. It was found that digital technologies including Computer Aided Design (CAD) and computer numerical control (CNC) have influenced muqarnas pattern design and rebirth in the 20th and 21st centuries. Both ancient and modern muqarnas use isometries and symmetry, although their design procedures are different. Parametric design and CAD tools allow the current muqarnas to be dynamic and flexible, unlike the traditional ones. The current research underlines that regionally available materials and pattern availability affect the design of muqarnas. Early manifestations of muqarnas were used to fragment squinches, which ultimately led to the creation of an aesthetically pleasing formal mechanism and a system of three-dimensional decoration. In the middle period, muqarnas was also used as decorative carvings on structural member. At present, lightweight materials such as fiberglass and pre-fabricated muqarnas are preferred in contemporary architecture, although the details of muqarnas are still maintained for their aesthetic value. The geometry used to calculate muqarnas has remained the same since its development, regardless of the materials used. This research stimulates the design of new muqarnas patterns for aesthetic purposes and building performance optimization. Modern architecture uses muqarnas compositions and digital technologies to reflect the traditional cultural and historical patterns, creating a developing trend.

Contextual Knowledge Framework in CAD Education from the Perspectives of Practicing Engineers

The contemporary industry landscape requires engineering graduates to have expertise in utilizing advanced Computer-Aided Design (CAD) tools. However, prevailing practices reveal a lack of contextual knowledge among Mechanical Engineering undergraduates and fresh graduate engineers in effectively employing 3D CAD modelling software for optimal product design development. Consequently, this study was undertaken to address this issue, with a specific focus on the integration of contextual knowledge into 3D CAD modelling. The study aims to elucidate the fundamental elements of contextual knowledge regularly employed by practicing engineers in their daily design endeavours, specifically in 3D CAD modelling. A transcendental phenomenology approach was used, and four engineers from the engineering department of a shipbuilding company in Peninsular Malaysia were purposefully selected as respondents. The analysis yielded three recurring themes central to the application of contextual knowledge in visualizing and presenting models through 3D CAD modelling: Realization, Design Intention, and Normalization. These elements are pivotal in assisting engineers in contextualizing their design work during the modelling and presentation stages of the new product development process.

Conceptualization and development of a semi-automatic vegetable transplanter prototype for small landholdings

The process of seedling transplantation has significant importance within the realm of mechanical vegetable production in contemporary agriculture. A prototype of a two-row tractor-mounted semi-automatic vegetable seedling transplanter (SVT) was conceptualized and developed for small agricultural holdings. The functional behaviour of the prototype was examined with computer-aided design tools, and the various units of the prototype have been finalized. To develop the prototype, the feeding, metering, transplanting, drive train, and soil compacting/covering unit of the machine were developed and constructed using materials readily accessible locally. The machine has a set row-to-row spacing of 600 mm, and it may alter the plant-to-plant spacing when the machine's forward speed changes. The pace was customized to achieve the required 450 mm plant-to-plant spacing. A 12:1 speed reduction gearbox was used for the proper metering of seedlings. The effect of independent factors, namely tray cell type, feeding mechanism, soil covering/compacting wheel angle, and age of seedling, on the machine's actual field capacity (AFC) was examined. The prototype underwent preliminary field testing to assess the functional viability, and the functioning was satisfactory. The main effect of the feeding mechanism and soil covering/compacting wheel angle on AFC was statistically significant at 5 % for tomato and brinjal whereas their first-order interaction was found statistically significant on AFC for tomatoes. The findings demonstrate that this study's prototype can be marketed or used to further vegetable production studies.

An investigation into the thermal surface contact resistance, fin width and temperature on negative bias temperature instability during self-heating

This work investigates the impacts of the thermal surface contact resistance (SR), fin width and temperature on the negative bias temperature instability (NBTI) during self-heating based on 14 nm p-FinFET through technology computer-aided design (TCAD) tool. In order to promote the accuracy of simulation, the experimental data are used to calibrate the TCAD results. The simulation results reveal that as SR increases, the lattice temperature rises by 20.07 %, which leads to a 15.84 % decrease of the carrier mobility and finally a reduction of the saturation current by 5.07 %. Moreover, as WFin decreases from 8 nm to 2 nm, the device threshold voltage increases by 15.41 %, resulting in that the saturation current reduces by 19.06 %. Besides, with an increase of the ambient temperature from 300 K to 500 K, the lattice temperature and trapped charge rise by 60.48 % and 12.53 %, respectively, which eventually leads to an 18.13 % decrease of the saturation current.

Packing optimization of practical systems using a dynamic acceleration methodology

System design is a challenging and time-consuming task which often requires close collaboration between several multidisciplinary design teams to account for complex interactions between components and sub-systems. As such, there is a growing demand in industry to create better performing, efficient, and cost-effective development tools to assist in the system design process. Additionally, the ever-increasing complexity of systems today often necessitates a shift away from manual expertise and a movement towards computer-aided design tools. This work narrows the scope of the system design process by focusing on one critical design aspect: the packaging of system components. The algorithm presented in this paper was developed to optimize the packaging of system components with consideration of practical, system-level functionalities and constraints. Using a dynamic acceleration methodology, the algorithm packages components from an initial position to a final packed position inside of a constrained volume. The motion of components from initial to final positions is driven by several acceleration forces imposed on each component. These accelerations are based on physical interactions between components and their surrounding environment. Various system-level performance metrics such as center of mass alignment and rotational inertia reduction are also considered throughout optimization. Results of several numerical case studies are also presented to demonstrate the functionality and capability of the proposed packaging algorithm. These studies include packaging problems with known optimal solutions to verify the efficacy of the algorithm. Finally, the proposed algorithm was used in a more practical study for the packaging of an urban air mobility nacelle to demonstrate the algorithm’s prospective capabilities in solving real-world packaging problems.

Design, Simulation and Fabrication of an Ergonomic Handgrip for Public Transport in Bangladesh

Many individuals in Bangladesh prefer using private vehicles to avoid the discomfort of public transportation, causing significant congestion during rush hours. To ensure a pleasant journey in public transit, including safe and comfortable handgrips becomes crucial. This study adopts a comprehensive approach to alleviate the discomfort and hand fatigue experienced by public transport commuters in Bangladesh. Our research methodology thoroughly analyses existing handgrips with a diverse age group (11-50) and varied occupational backgrounds, ensuring inclusivity. Meticulously collected anthropometric data from previously published works incorporates the 95th percentiles to account for diverse hand sizes. Leveraging computer-aided design tools, we optimize the hand grip design based on ergonomic principles and hand anatomy. Our study fills a crucial gap by integrating locally derived anthropometric data. The resulting ergonomic hand grip, designed for the specific needs of Bangladeshi commuters, is poised for seamless integration into the public transport system, promising a substantial improvement in comfort and a more positive commuting experience.