Industrial application of knowledge-based engineering in commercial CAD / CAE systems

Pokojski, Jerzy; Szustakiewicz, Karol; Woźnicki, Ł.; Oleksiński, Konrad; Pruszyński, Jarosław

doi:10.1016/j.jii.2021.100255

Cited by 10 publications

(5 citation statements)

References 37 publications

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“…This research is also strengthened by research stating that the learning process with multimedia is important by utilizing technology. Students are given direct reinforcement by being projected by everyday life to increase their understanding of concepts [36][37]. One of the objectives of learning science is understanding the concept that can be achieved.…”

Section: Discussionmentioning

confidence: 99%

Enhancement of Students’ Learning Outcomes through Interactive Multimedia

Hadi¹,

Yuksafa²,

Yarmi³

et al. 2022

Int. J. Interact. Mob. Technol.

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Purpose of this study was to determine the effect of using animated video media on student learning outcomes in Solar System science subjects and to determine the improvement in student learning outcomes in class VI SDN Padurenan Jaya.The research design used is a quantitative technique using a quasi-experimental method in the form of Non-Equivalent Control Group Design. The variables in this study are, the independent variable is the use of animation media, while the dependent variable is student learning outcomes. The subjects of this study were students of class VI A and VI B at SDN Padurenan Jaya, totaling 52 students. The sample was determined by purposive sampling, namely, 28 students as the experimental group (VI A) and 26 students as the control group (VI B). Data collection techniques in this study used multiple choice tests in the form of pretest and posttest. Testing the requirements of the hypothesis using normality test (using chi squared analysis technique) and homogeneity test. The validity of the test items was carried out by expert judgment and testing instruments. The reliability of the instrument was test calculated by the Kuder-Richardson formula (KR-20) obtained r = 0.893 which means the reliability of the instrument is very high. The data analysis technique used was a separate group t-test (independent sample test). The t-test was used to determine differences in the level of student learning outcomes.Based on the results of the study, the average score for the pretest control class was 46.54 and the average posttest was 64.04; while in the experimental class the average value of the pretest was 48.39 and the average value of the posttest was 74.82. The increase in learning outcomes for the control class was 17.50 and the experimental class was 26.43. Analysis using all results posttest and tested by t-test with the acquisition of t count > t table (4.775 > 2.021), indicating that Ho is rejected and Ha is accepted, from these results it can be concluded that student learning outcomes using animated video media are greater than the results. Student learning using conventional methods (lectures or blackboards).

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Section: Discussionmentioning

confidence: 99%

Enhancement of Students’ Learning Outcomes through Interactive Multimedia

Hadi¹,

Yuksafa²,

Yarmi³

et al. 2022

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

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“…Studies [23], [59], [76], [77] provide a neutral, feedback-controlled file-based CAD -CAE integration platform that optimizes geometric design variables based on feedback from CAE analyses. Studies [24], [64], [77] [78] support a CAD to CAE digital framework that is focused on CAE to optimize a 5-DOF robot joint's design.…”

Section: Cad/cae-centricmentioning

confidence: 99%

A Review of Generative Models for 3D Vehicle Wheel Generation and Synthesis

Akande,

Alabi,

Oyinloye

2024

J. Comput. Theor. Appl.

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Integrating deep learning methodologies is pivotal in shaping the continuous evolution of computer-aided design (CAD) and computer-aided engineering (CAE) systems. This review explores the integration of deep learning in CAD and CAE, particularly focusing on generative models for simulating 3D vehicle wheels. It highlights the challenges of traditional CAD/CAE, such as manual design and simulation limitations, and proposes deep learning, especially generative models, as a solution. The study aims to automate and enhance 3D vehicle wheel design, improve CAE simulations, predict mechanical characteristics, and optimize performance metrics. It employs deep learning architectures like variational autoencoders (VAEs), convolutional neural networks (CNNs), and generative adversarial networks (GANs) to learn from diverse 3D wheel designs and generate optimized solutions. The anticipated outcomes include more efficient design processes, improved simulation accuracy, and adaptable design solutions, facilitating the integration of deep learning models into existing CAD/CAE systems. This integration is expected to transform design and engineering practices by offering insights into the potential of these technologies.

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“…Similarly, Silva et al (2012) highlighted the properties of OO modelling, namely encapsulation, abstraction, inheritance and polymorphism applied to a KBS for sensor fault modelling, detection and mitigation. Pokojski et al (2021) proposed to divide the development object-oriented systems into three main layers: the knowledge acquisition layer, the knowledge management layer (whose basic task is to analyse and transform the knowledge collected in a first layer into a formal model of knowledge), and the layer generating the formal model of the product/process, modelled using the knowledge defined in the two previous layers (the basic structure of the model is generated in the form of appropriate classes and relations between them). The concept approach emphasized the importance of acquiring engineering knowledge before it is modelled and implemented in a programming code.…”

Section: Related Workmentioning

confidence: 99%

A knowledge‐based system for electric motors compliance verification in a multinational‐level company

Haselein

Silva

2022

Expert Systems

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Electric motors are highly customizable products that have to meticulously comply with the client's needs, commercial and legal requirements of each market. In this context, the configure‐to‐order (CTO) approach allows the user to define the product configuration at the time of the order and the supplier to develop a product that meets the customer's needs. This paper presents an object‐oriented knowledge‐based system (OOKBS) that integrates rule‐ and case‐based reasoning to verify the compliance of a variant‐rich and complex product—electric motors—in a multinational‐level company. The system adopts a modular structure to evaluate distinct compliance aspects, such as technical constraints and commercial requirements, and to improve the compliance assessment based on the designs of motors previously sold. The work targeted a product line with significant market share in North America, and is the result of a collaboration among the following teams: product compliance, international sales, engineering systems, and product engineering. In total, the system development involved nine experts from these areas. This study has the originality of presenting a product configuration system (PCS) that integrates rule‐based and case‐based approaches to verify the compliance of a modular product. The results indicate a reduction of 73% of internal technical queries within the prototype scope. Moreover, the system usability tests highlight the completeness of outcomes, quick access to information, and easy integration of automatic product compliance verification into the company's design flow. Furthermore, we discussed how the system was effectively implemented in a design routine based on both concurrent engineering and CTO scenarios.

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Industrial application of knowledge-based engineering in commercial CAD / CAE systems

Cited by 10 publications

References 37 publications

Enhancement of Students’ Learning Outcomes through Interactive Multimedia

Enhancement of Students’ Learning Outcomes through Interactive Multimedia

A Review of Generative Models for 3D Vehicle Wheel Generation and Synthesis

A knowledge‐based system for electric motors compliance verification in a multinational‐level company

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