Computer-aided Engineering Analysis Research Articles

Development and evaluation of RFID-integrated endoscopic clips for laparoscopic surgery marking.

As advancements in surgical instruments and techniques continue to evolve, minimally invasive surgery has become increasingly preferred as a means of reducing patient pain and recovery time. However, one major challenge in performing minimally invasive surgery for early gastrointestinal cancer is accurately identifying the location of the lesion. This is particularly difficult when the lesion is confined to the lumen of the intestine and cannot be visually confirmed from the outside during surgery. In such cases, surgeons must rely on CT or endoscopic imaging to locate the lesion. However, if the lesion is difficult to identify with these images or if the surgeon has less experience, it can be challenging to determine its precise location. This can result in an excessive resection margin, deviating from the goal of minimally invasive surgery. To address this challenge, researchers have been studying the development of a marker for identifying the lesion using a radio-frequency identification (RFID) system. One proposed method for clinical application of this detection system is to attach an RFID tag to an endoscopic hemostatic clip and fix it to the intended position, providing a stable marker for the inner wall of the organ. This approach has the potential to improve the accuracy and effectiveness of minimally invasive surgery for early gastrointestinal cancer. In the development of a marker for identifying gastrointestinal lesions using a radio-frequency identification (RFID) system, the shape of the clip and suitable materials for attaching the RFID tag were determined through finite element method (FEM) analysis. A prototype of the clip was then fabricated and ex-vivo experiments were conducted using porcine intestine to evaluate the stability of the clip in relation to its position. To further evaluate the performance of the RFID-integrated clip in vivo, the clip was placed in the gastric wall of the stomach of anesthetized porcine using an endoscopic instrument. The clip was then detected using a RFID detector designed for laparoscopic approach. And later, the accuracy of detection was confirmed by incising the lesion. The design and fabrication of a clip with varying thicknesses using STS316 and STS304 stainless steel were accomplished using the results of finite element method analysis. The stability of the clip was evaluated through ex-vivo experiments, showing it to be a viable option. In-vivo experiments were performed on anesthetized porcine, in which the RFID-integrated clip was placed in the gastric wall and detected using a custom-made RFID detector. The resection margin, measured at about 30 mm from the detector position, was accomplished with low error. These findings indicate the feasibility and efficacy of using an RFID-integrated clip as a marker in minimally invasive surgery for the identification of gastrointestinal lesions. The study evaluated the feasibility of using stainless steel clips for lesion detection in endoscopic surgery using computer-aided engineering analysis and ex-vivo experimentation. Results showed that STS304 was suitable for use while STS316L was not. The ex-vivo experiments revealed that the clip holding force and tissue retention length varied depending on the location of attachment. In-vivo experiments confirmed the accuracy and usefulness of the RFID lesion detection system. However, challenges remain for its use in clinical field, such as ensuring the stability of the clip and the safe attachment of the RFID tag, which requires further research for commercialization.

3D printing of personalised stents using new advanced photopolymerizable resins and Ti-6Al-4V alloy

PurposeThe development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.Design/methodology/approachThe methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.FindingsA series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.Originality/valueThis study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.

Investigating tooth surface reconstruction principle of a gear rack and pinion system with variable transmission ratio pinion

Rack-and-pinion gear sets with variable transmission ratios have gradually become a standard core component in steering systems, as the harmony between portability and sensitivity in vehicle steering can be achieved with such applications. When the conventional meshing theory is adopted to calculate point clouds of variable-ratio tooth surfaces, drawbacks will occur with respect to unevenness in point cloud density, inaccessible tooth surface boundaries, and point cloud fusion at the interface between the working tooth surface and fillet. Thus, the generated point cloud of variable ratio tooth surfaces is inapplicable for computer-aided engineering (CAE) and plastic forming. In this study, the point cloud reconstruction of pinion tooth surfaces with variable transmission ratio was investigated. Meanwhile, based on the analysis of transient length in contact lines that occur during gear meshing, various criteria were proposed to determine the validity of the variable-ratio rack-and-pinion design in terms of whether continuous and reverse driving can be achieved. By adopting the proposed methods, the designed variable-ratio pinion tooth surfaces demonstrate point clouds with equidistant distributions and clear boundaries. CAE analysis results also indicate a good quality in gear meshing. The real-time gear meshing status of variable-ratio rack-and-pinion sets is characterized by the transient length of contact lines. The measured variation curves for the transmission ratios of a prototype demonstrate significant consistency with the theoretical curves, indicated by attaining transmission ratio errors within a reasonable range. The validity of the design methods proposed in this study has been verified by the aforementioned results.

STATIC STRENGTH ESTIMATE OF STRUCTURAL ELEMENTS OF IMPLANT SYSTEMS LIKO 4 × 10 OF VARIOUS DESIGNS

Introduction. The creation of effective, reliable, safe, technologically advanced and competitive products is the main task of medical device engineering. The most important requirement to modern medical devices is to guarantee patients’ safety during their lifetime. Today the use of modern computer-aided engineering analysis packages is the most effective calculation method for evaluating the strength and reliability of unique medical devices that can lead to serious consequences if their operation is disturbed. One of the most suitable and efficient systems for computer-aided engineering (CAE) system is the ANSYS software.The purpose of this study was the comparative assessment of the elastic and elastoplastic formation of 4x10 dental implants of different designs on the abutment-pin and screw-body interface, using the computer simulation of the stress-strain state.Materials and methods. Two kinds of dental implants were chosen for this study: a Liko-M 4 × 10 implant with the cylindrical body shape and a Liko-M DG 4 × 10 implant with a tapered body shape. The contact between the abutment and screw as well as the implant body and screw is frictional. The pre-tensioning of the screw from the initial tightening was 400 N. The load was applied to the cylindrical surface of the abutment at a percentage of its height.Results. Elastic and elasto-plastic calculations of the stress-strain state of Liko-M 4 × 10 and Liko-M DG 4 × 10 implants were performed. Besides the results of the main calculations of the stress-strain state of the implants Liko-M 4x10 and Liko-M DG 4 × 10, necessary to assess their static strength, we have also calculated the strength coefficients of implant bodies. Comparative analysis of the static strength of the Liko-M 4 × 10 and Liko-M DG 4 × 10 implants provides conclusions, which are significant for practical application of the implants.

Improve Product Design and Injection Molding for Electrical Outlet Cover Plastic with the Help of CAE Software

CAE (Computer-Aided Engineering) analysis is based on the sequence characteristics of the system, combining model reasoning to conduct analysis, the results have physical significance, is Know-Why but not the Know-How of traditional experience, thus it is possible to systematize and scientificize the injection molding parameter and design types for the order of state and product quality, achieving the goal of scientific injection molding (Scientific Molding). Due to the reliability of CAE results, it is possible to point out potential problems during injection molding and design, propose design modifications and possible solutions to obstacles and possible solutions, can avoid unsafed experience. CAE at the design stage can be performed on a computer for design modification options to conduct evaluation (Evaluate), evaluate (Verify) and optimize (Optimize), reducing time and cost mold testing, actual mold fixing, shortening actual trial and error cycle, shortening product development time and time-to-market, reducing waste, time and cost in stages. CAE can help injection molders predict and capture injection molding parameters for product quality impact, find out the processing direction (Processing Window) and optimize injection molding parameters. CAE can indicate the main factors affecting the quality of injection molding, thereby providing design modification parameters, injection molding parameters and quantitative criteria. In this article applied the CAE method to improve injection molding added the the best product. There are a lot of results: First of all, when making the mold, we will make the inserts to escape the air at the position of the cylinders. And the air outlet at the edge of the product so that the air at the edge can escape well; After improving the gate position, cooling water line, pressure protection, mold temperature, we see that the product has a change in warping, but it is not significant.

Improve Product Design and Injection Molding for Controler Plate Plastic with the Help of CAE Software

CAE (Computer-Aided Engineering) analysis is based on the sequence characteristics of the system, combining model reasoning to conduct analysis, the results have physical significance, is Know-Why but not the Know-How of traditional experience, thus it is possible to systematize and scientificize the injection molding parameter and design types for the order of state and product quality, achieving the goal of scientific injection molding (Scientific Molding). Due to the reliability of CAE results, it is possible to point out potential problems during injection molding and design, propose design modifications and possible solutions to obstacles and possible solutions, can avoid unsafed experience. CAE at the design stage can be performed on a computer for design modification options to conduct evaluation (Evaluate), evaluate (Verify) and optimize (Optimize), reducing time and cost mold testing, actual mold fixing, shortening actual trial and error cycle, shortening product development time and time-to-market, reducing waste, time and cost in stages. CAE can help injection molders predict and capture injection molding parameters for product quality impact, find out the processing direction (Processing Window) and optimize injection molding parameters. CAE can indicate the main factors affecting the quality of injection molding, thereby providing design modification parameters, injection molding parameters and quantitative criteria. In this article applied the CAE method to improve injection molding added the the best product. There are a lot of results: First of all, when making the mold, we will make the inserts to escape the air at the position of the cylinders. And the air outlet at the edge of the product so that the air at the edge can escape well; After improving the gate position, cooling water line, pressure protection, mold temperature, we see that the product has a change in warping, but it is not significant.

Development of a new HotBalloonTM ablation catheter equipped with a balloon surface temperature monitoring sensor for pulmonary vein isolation

The balloon surface temperature (BST) should be monitored to ensure the success of the ablation procedure using the HotBalloonTM ablation catheter (HBC) in clinical settings. Therefore, we sought to develop a new HBC equipped with a surface temperature monitoring sensor. The BST was evaluated using a pseudo-tissue model and a thermocouple to imitate catheter insertion into the pulmonary vein. Thermo-fluid analysis with computer-aided engineering (CAE) was performed to analyse the temperature distribution in the catheter and the balloon. The CAE analysis reproduced the results from a pseudo-tissue model experiment and demonstrated that some fluid zones inside the catheter shaft had a nearly identical temperature as the BST during the liquid suction period. The pseudo-tissue model experiment confirmed that the temperature was almost the same between the balloon surface and the position of 5 mm inside the catheter shaft from the proximal end of the balloon. A thermocouple placed at 5 mm or 25 mm from the proximal end of the balloon within the catheter shaft showed an equivalent temperature result. This 5–25-mm distance is acceptable to set the BST monitoring sensor inside the catheter shaft, since the sensor can help accurately estimate the BST.

Lightweight injection mold using additively manufactured Ti-6Al-4V lattice structures

Injection mold requires a large weight, significant cost of material, safety management, and installation of auxiliary facilities. In this study, we realized a lightweight injection mold consisting of lattice structures through the additive manufacturing (AM) technology for overcoming these limitations. A compression test was conducted to understand the intrinsic mechanical properties of lattice structures according to density. Moreover, the external force applied to a mold using computer-aided engineering (CAE) was confirmed. Based on the results of the compression test of the lattice structure and CAE analysis for the mold, a lightweight injection mold was designed and fabricated to facilitate design for additive manufacturing. Furthermore, the lightweight injection mold was assembled into the injection machine and the injection test was performed. The weight and amount of material of the mold were reduced by ~79%, and the injection molding of 400 shots was successful using polyvinyl chloride (PVC) without damaging the mold.

Evaluation of Discharging Surplus Soils for Relative Stirred Deep Mixing Methods by MPS-CAE Analysis

Most of the ground in Japan is soft, leading to great damage in the event of liquefaction. Various ground-improvement measures are being taken to suppress such damage. However, it is difficult to carry out ground-improvement work while checking the internal conditions of the ground during the construction. Therefore, a visible and measurable evaluation of the performance of the ground-improvement work was conducted in this study. The authors performed a simulation analysis of the relative stirred deep mixing method (RS-DMM), a kind of ground-improvement method, using a computer-aided engineering (CAE) analysis based on particle-based methods (PBMs). In the RS-DMM, the “displacement reduction type (DRT)” suppresses displacement during construction. Both the DRT and the normal type (NT) were simulated, and a visible and measurable evaluation was performed on the internal conditions during each construction, the quality of the improved body, and the displacement reduction performance. As an example of these results, it was possible to visually evaluate the discharge of surplus soil by the spiral rod attached to the stirring wing of the DRT. In addition, the authors succeeded in quantitatively showing that more surplus soil was discharged when the stirring wing of the DRT was used than when the stirring wing of the NT was used.

Influence of Disinfectants on Airport Conveyor Belts

The coronavirus disease has influenced almost all of our everyday activities. Traveling and transportation have been influenced significantly and there is no doubt that air transportation has been restricted and therefore reduced considerably. It is predicted that the change back to pre-pandemic conditions will take several years, and so it is a reasonable assumption that disinfectants will be used more frequently for a long time. The presented article initially deals with the possible impacts of the pandemic on aircraft infrastructure—namely, on the influence of disinfectants on the rubber materials used, for example, in conveyor belts. The proposed methodology is based on the Weibull analysis for conveyor belt lifetime prediction regarding the impact of disinfectants. The Weibull distribution is a continuous probability distribution that can be applied as a theoretical model for statistical data processing. It was named after Weibull, who suggested shape, scale, and location parameters that made the distribution meaningful and useful. Currently, this distribution is applied in many areas, such as biology, economics, and hydrology. In engineering applications, it can be used for reliability and survival analysis. It is used mainly in cases where failure time is dependent on the operating hours, cycles, or age of the component. In the reliability area, it can be used, for example, to predict the lifetime or failure time of a component. To show the consequences of material changes due to the use of disinfectants, this article also presents a CAE (Computer Aided Engineering) analysis that was used for the evaluation of other hyperelastic material characteristics. This research is based on the results of experimental measurements, during which the influence of the types of disinfectant commonly used for the elimination of the coronavirus disease on airport conveyor belt rubber segments was tested. From the performed analysis, it was found that the influence of disinfectants on the material characteristics, including material hardness, elasticity, and static and dynamic loading, could be significant. Therefore, the probability of mechanical damage to the rubber part of the conveyor belt becomes higher, and time intervals for the maintenance or repair of airport conveyor belts should be considered.

CAE Analysis and Auralization of Driveline Clunk NVH

<div class="section abstract"><div class="htmlview paragraph">Noise and vibration evaluation of driveline clunk can be challenging as it is the result of driver input conditions and is transient in nature. As with many noise and vibration challenges, the use of computer-aided engineering (CAE) simulation is useful as it allows for detailed study of the phenomenon and prediction of potential improvements. A hybrid approach of physical test-based measurements and CAE analysis can be used to leverage the advantages of CAE in a comprehensive evaluation including the total vehicle noise, vibration, and harshness (NVH) performance. In this paper we present work performed to facilitate engineering evaluations of driveline clunk using both measured test and CAE simulation data. We explain how we used measured test data to inform the CAE analysis, how the simulation approached modelling of the transient clunk event, and how the measured data was used to provide contextual sound for realistic evaluation of the CAE output as heard by the passengers. The ability to listen to the simulated clunk in the context of the remainder of the vehicle NVH provides a direct link to evaluation of correlation between CAE and test results, as well as judgement of subjective performance and gap-to-target levels.</div></div>

Automatic Finite Element Mesh Generation on 3D Surfaces Based on STEP

Computer Aided Engineering (CAE) have a vital value in die and mould manufacturing. For the purpose of enhancing the modelling ability of the existing CAE analysis system and improving the mesh generation quality and working efficiency, a system for automatic finite element mesh generation on 3D surfaces is designed and implemented. Applying the neutral mechanism for product information sharing provided by STEP, product model import and reconstruction process is first implemented. And then product model information extraction module is developed aims at preparing geometrical and topological information for finite element mesh generation. An improved strategy for automatic triangular mesh generation over 3D surface is adopted to realize the mesh generation of the system. Implemented results indicate that the presented system helps to improve the mesh quality and at the same time increase the process efficiency and reduce the time cost.

Thermal, Rheological, Mechanical, and Electrical Properties of Polypropylene/Multi-Walled Carbon Nanotube Nanocomposites.

In this paper, nanocomposites based on polypropylene (PP) filled with up to 5 wt.% of multi-walled carbon nanotubes (MWCNTs) were investigated for determining the material property data used in numerical simulation of manufacturing processes such as the injection molding and extrusion. PP/MWCNT nanocomposite pellets were characterized for rheological behavior, crystallinity, specific volume and thermal conductivity, while injection-molded samples were characterized for mechanical and electrical properties. The addition of MWCNTs does not significantly change the melting and crystallization behavior of the PP/MWCNT nanocomposites. The effect of MWCNTs on melt shear viscosity is more pronounced at low shear rates and MWCNT loadings of 1–5 wt.%. However, with the addition of up to 5 wt.% of MWCNTs, the PP/MWCNT nanocomposite still behaves like a non-Newtonian fluid. The specific volume of the PP/MWCNT nanocomposites decreases with increasing MWCNT loading, especially in the MWCNT range of 1–5 wt.%, indicating better dimensional stability. The thermal conductivity, depending on the pressure, MWCNT wt.% and temperature, did not exceed 0.35 W/m·K. The PP/MWCNT nanocomposite is electrical non-conductive up to 3 wt.%, whereas after the percolating path is created, the nanocomposite with 5 wt.% becomes semi-conductive with an electrical conductivity of 10−1 S/m. The tensile modulus, tensile strength and stress at break increase with increasing MWCNT loading, whereas the elongation at break significantly decreases with increasing MWCNT loading. The Cross and modified 2-domain Tait models are suitable for predicting the melt shear viscosity and specific volume as a function of MWCNTs, respectively. These results enable users to integrate the PP/MWCNT nanocomposites into computer aided engineering analysis.

A real‐time clamping force measurement eigenvalue for prediction, adjustment, and control of injection product quality

AbstractClamping force is a crucial parameter in injection molding. Improper clamping force setting can result in poor product quality and shorter machine lifespan. The objective of this study was to establish an eigenvalue‐injection clamping force peak value by real‐time clamping force measurement with strain gage sensor for prediction, adjustment, and control of injection product quality. In this study, computer‐aided engineering (CAE) structural analysis technique was used to analyze and verify the points of measurement of the sensor. Next, the molded product was conducted using the following injection molding parameters: V/P switchover point, clamping force, injection speed, melt temperature, mold temperature, packing pressure, and packing time. The relationship between injection clamping force peak value and product quality were examined. The results showed that CAE analysis could successfully predict and provide suitable points for sensor measurement. Comparison of analysis and experiment results revealed that injection clamping force peak value and part weight exhibited identical trends. Finally, the injection clamping force peak value not only could it successfully predict product quality, but also it would achieve the purpose of optimizing and stabilizing the clamping force and part weight.

Reconstruction of thermo-physical properties to improve material database for casting simulation

In this work, an advanced method is proposed for computational recovery of thermo-physical properties in a wide range from room temperature to values above the alloy melting point. This method allows us to improve material databases of CAE (Computer-Aided Engineering) programs for simulation of high-temperature technological processes. In most cases, computation of unsteady temperature fields is an important stage of CAE analysis in mechanical engineering. Moreover, various manufacturing technologies such as casting, welding, surface hardening, coating, heat treatment provide the desired material structure and its strength by controlling temperature field during solidification and subsequent cooling of a machine part. The problem of reliability in computer modeling arises from the fact that CAE programs usually are not equipped with comprehensive material databases. We have solved this problem especially for casting simulation and molding materials, which can differ in composition at different plants and therefore cannot be combined into a common database. To determine unknown thermo-physical properties, the temperature had been measured in several points of solidifying cylindrical sample initially, and the appropriate computer simulation of the test technology was performed. Then the difference between the calculated and experimental temperatures was minimized using the modified Levenberg-Marquardt optimization algorithm.

Correlation between estimated balloon contact by computer-aided engineering analysis and lesion area by hot balloon ablation.

Correlation between estimated balloon contact by computer-aided engineering analysis and lesion area by hot balloon ablation.

CAE Analysis for Disposable Mouth Mirror Based on Autodesk Moldflow Plastic Insight

This study is carried out to focus on computer aided engineering analysis on dental toolkit for disposable mouth mirror by using Autodesk Moldflow Insight (AMI) software. Disposable mouth mirror designs contain with a very small and precise features for it handles and fix angle between shank and working area (mirror). A 3D cad model of disposable mouth mirror has been construct and imported to the simulation software. The part has been analysed with thermoplastic material of Polypropylene (PP) as a part material for its light weight and durability. The simulation and analysis by moulding software package is used in order to determine the best range of operating parameter for injection moulding process in furtherance to get the low manufacturing defect. The process parameters that has been selected includes mould surface temperature, melt temperature, flow rate and cooling time during the injection moulding process. At the end, the best range of operating parameters has been proposed and simulates to study the product behaviour.

Finite element analysis of passenger car transverse stabilizer bar based on NX8.0

The parametric design and finite element analysis of the lateral stabilizer bar of the new energy bus were carried out by using NX8.0, and the structural strength and stiffness of the stabilizer bar were qualitatively analyzed. The simplified methods for different boundary conditions, solving types and finite element models are compared. All the processes are completed under the same software, which ensures the uniformity and editability of the data. Finally, the subject is introduced into the student s computer-aided engineering analysis training program, so that the students” comprehensive ability is improved.

Electric Vehicles Batteries: Requirements and Challenges

Jie Deng is a research engineer in the Department of Electrification Subsystems and Power Supply at Ford Motor Company. He has extensive experience in computer-aided engineering analysis (structural, fluid, and thermal), battery simulations, and material characterization. He got his PhD in Mechanical Engineering from Florida State University and has published over 30 papers. His current research mainly focuses on battery array design and multi-physics modeling and testing of battery behaviors under various abuse conditions. Chulheung Bae is a high-voltage battery systems group supervisor at Ford Motor Company, where his research activities focus on lithium ion battery system development and validation for automotive applications. Dr. Bae has over 22 years of experience in advanced battery materials and various energy storage devices, including Lithium Ion, NiZn, Lead-Acid and redox flow batteries, and ultra-Capacitors. Dr. Bae has a Doctorate in Chemical Engineering from University of Manchester in the UK. Adam Denlinger is manager of high-voltage systems research and development at Ford Motor Company. Adam’s team is responsible for delivering high-voltage battery system innovations—including packaging, durability, thermal, management and controls, and EMC—as well as human-centered technologies targeting an enhanced electrified vehicle ownership experience. The team also leads multiple collaborations in this field with industry, university, and national lab partners. Adam has worked with Ford for 22 years, with experience delivering powertrain technologies, including Ford’s first Ecoboost engine application, industry-first hydrogen internal combustion engine vehicle fleet, and multiple high-voltage battery systems for battery electric (BEV) and plug-in electric (PHEV) vehicles. Ted Miller is manager of electrification subsystems and power supply research. His team is responsible for Ford global electrification subsystem and power supply research, delivering battery system design innovations in advanced cell technology, packaging, thermal, EDS, EMC, charging, power conversion, and energy management and modeling. They provide subject matter expertise from raw materials to end-of-life recycling. The team also leads collaboration with university, industrial, and National Lab partners. Mr. Miller is chairman of the United States Advanced Battery Consortium and a member of the Idaho National Laboratory Strategic Advisory Committee and the University of Michigan Energy Institute External Advisory Board.

Integrating Taguchi method and artificial neural network to explore machine learning of computer aided engineering

ABSTRACTPlastic injection molding has been a very important technology in industries; however, problems that arise during molding cannot be understood or predicted by general linear rules; therefore, one needs to rely on experienced professionals to assess problems. Although computer aided engineering (CAE) technology has flourished in recent years, it is limited due to long analysis time and is not suitable for on-site real-time judgments. The Back Propagation Neural Network (BPNN) has excellent predictive ability for nonlinear problems, and can immediately provide accurate results after multiple sets of data trainings. In this study, CAE analysis data is used to train the BPNN, and the Taguchi orthogonal method is used to optimize the hyperparameters in the neural networks to construct a neural network that can predict CAE analysis results. The results of this study show that the prediction of the maximum injection pressure and the maximum cooling time is pretty good. However, there is still a big gap related to warpage prediction. Therefore, this study adds more training data on warpage, and conducts secondary training for the neural network. The results show improved predictions.