Driving Industry Advancements: Detroit Engineered Products’ Role in Computer-Aided Engineering Evolution.

CXOToday has engaged in an exclusive interview with Radha Krishnan, President and Founder, Detroit Engineered Products (DEP)


  1. Please explain the progress of computer-aided engineering technology and their impact on industry trends.

Computer-aided engineering (CAE) technology has advanced significantly, enabling engineers to simulate and optimize complex systems with unprecedented accuracy. CAE simulations help engineers identify potential design flaws, optimize performance, and ensure regulatory compliance. These capabilities are evolving rapidly and changing across industries. CAE has transformed industry trends by speeding up product development cycles, cutting costs, and improving safety standards. Additionally, it has facilitated the adoption of innovative design concepts and materials, leading to the development of more efficient and sustainable products. Furthermore, CAE has made engineering more accessible by providing tools to smaller companies and startups, fostering competition and innovation. Overall, CAE’s progress has transformed industries by enhancing efficiency, promoting innovation, and driving the evolution of engineering practices towards more sophisticated and sustainable solutions.


  1. What are the key strategies used by Detroit Engineered Products (DEP) to remain at the forefront of innovation in the competitive landscape?

We at Detroit Engineered Products (DEP) employ various strategies to maintain our innovative edge in this competitive landscape. Firstly, we invest in research and development (R&D) to explore new technologies, products, and markets. Embracing new technologies is paramount. Secondly, we form strategic partnerships and collaborations with other companies to gain access to complementary expertise and resources, as well as a global reach. Thirdly, we stay customer-centric by actively listening to customer feedback and anticipating their evolving needs, which helps us develop innovative solutions. And most importantly, fostering a culture of innovation within the organization is crucial. We encourage our employees to think creatively and take calculated risks.


  1. The concept of digital twins has spread across industries, providing prospects for virtual prototyping, predictive maintenance, and performance optimization. How does your organization use digital twin technology to improve engineering processes and provide value to clients?

Digital twin technology allows companies like ours to provide greater value to clients. By using digital twins, we can improve efficiency, cut costs, and deliver higher quality solutions to clients, ultimately ensuring better performance and longevity of their engineered systems. Creating virtual replicas of physical assets or systems enables us to conduct virtual prototyping, which allows for iterative design improvements before physical production. Real-time monitoring and analysis of digital twins make predictive maintenance more accurate, reducing downtime and extending equipment lifespan. Performance optimization is achieved by simulating various scenarios and identifying optimal configurations or operational strategies. In addition, digital twins enable remote diagnostics and troubleshooting, allowing for rapid response to issues and minimizing on-site interventions.


  1. The combination of artificial intelligence (AI) and machine learning (ML) technologies is transforming several sectors. How do you see these technologies transforming computer-aided engineering processes in the near future?

AI and ML are poised to revolutionize computer-aided engineering (CAE) processes in the near future by enhancing efficiency, accuracy, and innovation. These technologies enable CAE tools to analyze vast datasets and complex models, providing deeper insights and predictive capabilities. AI-powered algorithms can automate tedious tasks like mesh generation, parameter optimization, and simulation setup, reducing human error and speeding up the design iteration process. ML algorithms can also learn from past simulations to improve performance and provide more accurate predictions, leading to better decision-making throughout the product development lifecycle. Moreover, AI-driven design optimization can explore a broader design space, uncovering unconventional solutions that humans might overlook. Ultimately, the integration of AI and ML in CAE processes promises to streamline workflows, accelerate innovation, and deliver more robust and optimized engineering solutions.


  1. Your vision for the future of computer-aided engineering and how Detroit Engineered Products (DEP) plans to drive industry-wide advancements.

The future of computer-aided engineering (CAE) looks promising with seamless integration, real-time feedback, and sustainability-driven design. I see CAE evolving to provide comprehensive, multi-disciplinary simulations, speeding up product development and promoting eco-friendly designs. To advance the industry, Detroit Engineered Products (DEP) will invest in nurturing partnerships and talent development to effectively utilize emerging technologies. Collaboration among academia, research institutions, and industry players is crucial for Detroit Engineered Products (DEP) to push the boundaries of CAE. Open standards and interoperability between CAE tools will drive innovation and simplify data exchange across the engineering ecosystem. Through these efforts, Detroit Engineered Products (DEP) can lead the CAE industry towards unprecedented efficiency, innovation, and sustainability.