Last Updated： Aggregation Period:Oct 15, 2025～Nov 11, 2025
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16～23 item / All 23 items
![[Video] Semiconductor Process & Device Simulator "NovaTCAD"](https://image.mono.ipros.com/public/product/image/109/2000358506/IPROS654598304808202301.JPG?w=280&h=280)
Crosslight's TCAD integrates 2D/3D process simulators and device simulators. Free trial available!
■ A video demonstrating the automatic processing of simulations using NovaTCAD is currently available on the YouTube link below! ■ If you would like a trial version, please use the "Trial Version Application Form." (For details about the product, please refer to the product introduction materials.)
Avoid risks before equipment introduction! A simulation that realizes early equipment startup.
"MR" is a facility introduction simulation that allows for the verification of the "layout" and "workability" of the installation site by overlaying 3D data onto the real world. Layout issues, such as those involving other equipment, can be checked using "HoloLens." It enables pre-simulation from the perspective of the workers, facilitating the creation of a smooth working environment. 【Features】 ■ Ability to verify the "layout" and "workability" of the installation site ■ Layout issues can be checked using "HoloLens" ■ Pre-simulation from the perspective of the workers can be conducted ■ Realization of a smooth working environment ■ Risk avoidance before equipment installation *For more details, please refer to the PDF document or feel free to contact us.
Achieve a reduction in design and development costs! Capable of handling large-scale analysis with high-efficiency parallel computing.
"Moldex3D" is a resin flow analysis software that simulates the manufacturing process of resin injection molding in 3D (three dimensions). By verifying product design and molding conditions in advance and implementing countermeasures for defects, it reduces development man-hours and mold prototyping costs. Additionally, even beginners in resin flow analysis can apply high-end mesh and set conditions like experienced users, allowing for high-precision analysis preparation to be completed in a short time. 【Features (partial)】 ■ Easy and comfortable operation ■ High accuracy and reproducibility ■ Excellent expandability *For more details, please refer to the PDF materials or feel free to contact us.
The blades used for calculations can be created using the "Generic Blade" feature of CAESES.
One of the advantages of CAESES is its optimization design through an automation system connected to CFD software. This article introduces the blade shape optimization of marine propellers using OpenFOAM and CAESES, which is currently in use. In CAESES, in addition to methods for designing parametric 2D and 3D models, it is also possible to connect with various external software. *For more details, you can view the related links. For further information, please download the PDF or feel free to contact us.*
![[Simulator Utilization Case] Reduction of On-Site Adjustment Work Hours for Unique Equipment](https://image.mono.ipros.com/public/product/image/eb8/2000732222/IPROS79059104910479614137.png?w=280&h=280)
Introduction of case studies on the use of PLC and robot collaboration simulators *Case study collection available.
We would like to introduce a case study of utilizing PLC and robot collaboration using our emulation technology. <Case Study> ■Company: Domestic Manufacturer ■Challenge: We want to confirm the behavior of our unique equipment at the system level in advance. ■Implementation: - Confirmed the behavior of unique equipment combined with cylinders and tools. - Reproduced the equipment using 3D CAD shapes. - Passed axis values to the software side to understand interferences, etc. ■Results: → Contributed to a quick startup as intuitive motion programming was possible. → Since feedback was also possible through software UI operations, it could be used for teaching as well. Currently, we are offering a collection of case studies titled "Case Studies on the Use of PLC and Robot Collaboration Simulators," which includes solutions to challenges faced by the above-mentioned company. If you are interested or considering a simulator, please feel free to download it. *For more details, please download the materials or contact us through our website.
FIMMWAVE is software that allows for easy mode analysis of complex waveguide and fiber structures using a waveguide mode solver.
A large number of complementary solvers ・FIMMWAVE contains a variety of robust and computationally efficient solvers optimised for such structures. ・FIMMWAVE combines:methods based on semi-analytic techniques, which allow to tackle efficiently problems with strong variations in refractive index, thin layers, etc. ・numerical methods such as finite elements (FEM) or finite differences (FDM), providing robust solutions to arbitrary problems.
Visualization solutions for the use of engineering software
OpenLM is a solution for managing the operation of expensive engineering software. It primarily receives information from management servers of software that mainly adopt a floating license model and achieves "visibility of software operation" by providing unified reporting. Expensive applications such as 3D CAD are increasing in variety, making it difficult to grasp the number of users, and it is said that without managing operational performance, efficient and effective use cannot be achieved. By implementing OpenLM, it is possible not only to achieve "cost reduction" but also to maximize the use of existing licenses and improve corporate productivity.
Case studies on inorganic solids and polymers! Designing new compounds in a cost-effective and time-efficient manner.
High-quality physics-based simulations and machine learning approaches accelerate the research of new materials and shorten the time to market. Through the workflow, it is possible to automatically create hundreds of predictive models using representative machine learning techniques (Partial Least Squares Regression (PLS), Multiple Linear Regression (MLR), Principal Component Regression (PCR), Kernel PLS) combined with descriptors and fingerprints, and select models with high predictive performance (AutoQSAR). For datasets with thousands of data points, similar to AutoQSAR, the workflow allows for the automatic creation of predictive models using deep learning (DeepAutoQSAR, DeepChem/AutoQSAR). To represent the properties of a wide range of materials (polymers, molecules, solids), effective descriptors customized for each system can be utilized.
