MCADCafe Industry Predictions for 2025 – CoreTechnologie

By David A. Selliman, Sales Director, SME at CoreTechnologie

David A. Selliman

CoreTechnologie Predictions for 2025 – Interoperability

In the face of rapid technological advancements, automation and innovation are redefining the engineering landscape. CoreTechnologie 2025 predictions emphasize the critical role of cutting-edge tools and methodologies in driving efficiency, accuracy, and scalability. Interoperability, allowing different software systems to exchange data seamlessly, has long been a challenge in CAD due to proprietary formats. From CADx, CAEx, and CAMx; the ecosystem will be refined to leverage time-to-market with the integration of ISO standards while validating 3D models before their use in downstream applications.  However, the push for open standards and cloud-based collaboration tools is reshaping the industry. It is anticipated that CADx will achieve unprecedented levels of integration, enabling engineers to work more efficiently across diverse systems without traditional compatibility barriers.

CoreTechnologie predicts that advancements in automation, persistent identifiers, and streamlined digital threads bridge interoperability gaps and enhance 3D data for better communication in the industry.   In addition, using the Geometric Validation Properties developed within the ISO consortium will ensure the 3D model has the required information for the target application or user.  Furthermore, scripting languages can automate the engineering chore, such as reducing the CADx file size for protection of IP, plant layout, and form function and fit.

How is all this going to be done? It can be done by bringing resources from around the globe into one room and having a conversation that becomes a mathematical equation of complexity. Moreover, in an argumentative tone, the best approaches are uncovered based on the experience and intelligence in the room. Ideas are formed by the best resources who exhibit passion, dedication, and hard work. Artificial Intelligence (AI) will aid in the evolution of the technology, however, AI will never replace the human element of an interactive face-to-face knowledge-sharing conversation.

Automation: CAD (Computer-Aided Design):
Automation in CAD revolutionizes design workflows through parametric modeling, script-based automation, and macros that streamline repetitive tasks. Generative design introduces AI-driven innovation, enabling engineers to create optimized solutions rapidly. Standardized and repeatable processes ensure consistency and efficiency across projects by leveraging scripting languages like Python and VBA. Recording macros and developing custom add-ons further tailor workflows to specific requirements, enhancing precision and adaptability. These advancements, combined with robust API integration and cloud-based collaboration, drive cost-effective, error-reduced, and scalable design solutions.

CAE (Computer-Aided Engineering):
CAE automation focuses on reducing the time and complexity of simulations and analyses. Techniques like automated meshing, batch processing, and machine learning integration streamline the design of experiments (what-if analyses). The future of CAE lies in hyper-automation, where Multiphysics simulations unify thermal, structural, and fluid dynamics analyses into cohesive workflows. These tools and advances in hardware enable the processing of massive datasets in minutes. Seamless integration across domains ensures consistent validation of 3D data, making simulation-based decision-making faster and more reliable.

Table 1 – PID Process ISO 10303

CAM (Computer-Aided Manufacturing):
CAM automation maximizes manufacturing efficiency and precision through innovations like toolpath optimization, CNC programming automation, and digital twins. By integrating IoT-enabled smart factories, automated feedback loops dynamically adjust manufacturing parameters in real time. Semantic representation of 3D models replaces the need for manual CNC coding, achieving unprecedented scalability and accuracy. With the transition to digital threads in Technical Data Packages (TDP), CAM facilitates seamless integration of manufacturing data across platforms, ensuring compatibility and interoperability in complex production environments.

Technology: Persistent Identifiers (PIDs), particularly Universally Unique Identifiers (UUIDs), refer to a type of identifier used to uniquely and consistently identify a resource or entity over time, even if the location or metadata of the resource changes. The UUID plays a pivotal role in automating the digital thread of Model-Based.
Enterprises (MBEs). Companies are looking for a method to shorten the time to market by utilizing technology to identify persistent IDs for downstream applications. Organizations achieve unparalleled traceability by assigning PIDs to engineering requirements and CAD objects, ensuring data consistency and integrity across design, manufacturing, and inspection workflows.

Standards such as ISO 10303 (STEP) and the Quality Information Framework (QIF) are instrumental in embedding UUIDs into their frameworks. These frameworks provide robust models to uniquely identify features, measurements, and requirements throughout a product’s lifecycle. The AP242 Edition 4 UUID report highlights groundbreaking progress in incorporating UUIDs into CAD and digital thread workflows.
Looking ahead, future research will expand UUID applications into areas including semantic PMI and functional equivalent evaluations, further solidifying the digital thread and enhancing harmonization.

Automating 3D CAD Model Reduction for AR/VR and Plant Layout

Table 2 Simplification Case Study

Manual simplification is time-intensive and costly, diverting engineers from core tasks. Automating this process ensures efficiency and quality. In manufacturing, augmented reality (AR) and virtual reality (VR) transform plant layout.  We have found that the 3D model can exceed the three (3) Gig file size.  Reducing this file for configuration and plant layout is needed to move to the digital twin.  Market Ready Geometry (MRG): AR/VR enables interactive product visualization and configuration, boosting customer engagement and closing sales faster.  Allowing for exclusion and including a list for removing data while keeping part of the assembly, like connecting points in tack, is essential.

Additionally, modeling will become indispensable when digital twins become more mainstream. A digital twin mimics the robotic line in the virtual world and shows engineers where to adjust modeling profiles and operating parameters.

To define the requirements and the use case, CoreTechnologie has observed customers developing multiple scripts for different purposes—heavier models for internal use and lighter models for external use.

Table 3 Sample File Size Reduction

Reusing 3D models across an enterprise leads to shorter ramp-up times, fewer errors, less waste, and faster time-to-resolution. Although these models drive the visualizations for various applications, their large size and complexity often hinder direct use in software tools. Automating model reduction alleviates this issue, allowing engineers to focus on design and innovation and allowing designers to focus on design and innovation rather than the engineering chore. Reduces time and cost associated with manual simplification. Enhances AR/VR, training, and layout processes for improved efficiency and customer satisfaction.

Conference and Collaboration: PDES, Inc. – Connecting the Digital Enterprise board members recently approved taking responsibility for a significant role in the GPDIS – Global Product Data Interoperability Summit conference. PDES, Inc. highlights a vision for enhancing digital enterprise interoperability through innovative partnerships and cutting-edge standards. Organizations that share goals and objectives must have a common ground for success in communication and a well-defined process. I believe this venue will allow further strength in the industry to build upon the ISO standards.

Initiatives like the MBx-IF forum and expanded collaboration with LOTAR and PDES, Inc. are driving the adoption of model-based systems engineering and advancing technology integration. These predictions reflect an unwavering dedication to empowering industries with sustainable, interoperable solutions for the future of digital manufacturing.

About CoreTechnologie: CT is committed to supporting your organization’s goals and looks forward to collaborating further. CT emphasizes a customer-centric approach, tailoring interoperability solutions to ensure seamless B-Rep and feature-based translations that meet the most demanding technology transfer requirements. With a proven track record, CT provides localized support and industry-leading expertise to address complex challenges.  Automating with CT 3D_Evolution.   3D_Evolution automates model reduction, cutting file sizes by over 90% while maintaining quality. For more information, contact CoreTechnologie at info@us.coretechnologie.com or visit www.coretechnologie.com.

About PDES: PDES, Inc. is the premier collaborative organization for developing and testing the ISO 10303 standards, as well as a major player in integrating related standards. Since 1988, the not-for-profit has facilitated developing and integrating manufacturing and design standards across domains. Its members are OEMs, software vendors, and academics focusing on ISO 10303 for design, manufacturing, CNC, and product lifecycle.  Next Steps

About Author:

David A. Selliman – Executive for CoreTechnologie for North America since September 2007. David is a Subject Matter Expert with more than 15 years of global leadership experience in automotive, general machinery, and aerospace markets, focusing on CAD, CAE, and CAM.

David currently serves on the Board Of Directors for PDES (a consortium focused on Model-Based Engineering and Long Term Data Retention). David previously served in various key executive positions at Mechanical Dynamics and MSC Software, focusing on the automotive sector. David continues to focus on industry-leading implementations of CAD interoperability solutions within PLM applications. Selliman earned his Bachelor’s degree in Business Administration from Davenport University with continued education in CAD, CAE, and CAM engineering.

Tags: 3D model reduction, AR/VR in manufacturing, CAD automation, CAE simulations, CAM manufacturing, CoreTechnologie predictions, digital thread, digital twin technology, global product data interoperability., hyper-automation, Interoperability, IoT in factories, ISO standards, manufacturing efficiency, Model-Based Enterprises (MBEs), persistent identifiers, semantic PMI, UUIDs

Category: Predictions

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