Systems Engineering: Emerging Technologies Changing the Big Picture
Systems engineering is crucial because it provides a structured approach to designing, managing, and integrating complex systems.
In an increasingly interconnected and technology-driven world, systems engineering is essential for ensuring that complex systems function efficiently, reliably, and safely.
The discipline allows engineers to consider the big picture, not just isolated components, and helps optimize the entire system across its lifecycle—from concept and design to deployment and maintenance. It’s a holistic approach that supports decision-making, reduces risk, and ensures that all aspects of a system, including people, processes, and technology, work together seamlessly.
Here are the three top reasons that systems engineering is important today and will continue to be in the future:
It’s important for current systems engineers and anyone considering a systems engineering related field to be cognizant of emerging technologies and the impact they have.
For example, AI and ML have, in some ways, changed everything. AI can automate aspects of systems design, such as optimization, predictive maintenance, and real-time system monitoring. ML algorithms can help systems engineers predict system behaviors and identify potential failures before they occur. They also assist in processing large datasets to uncover insights that inform decision-making.
Then there’s the influence of digital twins on systems engineering. Digital twins are virtual models of physical systems that can be used to simulate, monitor, and analyze system performance in real time. They allow systems engineers to test different scenarios, predict outcomes, and optimize system performance in a virtual environment before implementation in the real world.
This will greatly enhance design, testing, and maintenance of complex systems.
Additionally, the Internet of Things (IoT), cloud/edge computing, autonomous systems, blockchain, advanced simulation and modeling tools and quantum computing also factor into the new era of technological challenges for systems engineers.
IoT connects physical devices to digital systems, enabling continuous data collection and real-time monitoring. Systems engineers will leverage this vast amount of data for better decision-making, optimization, and troubleshooting. It will play a significant role in sectors like manufacturing, smart cities, and healthcare.
Cloud computing allows for the storage and processing of large amounts of data in a distributed manner, while edge computing moves computation closer to where data is generated (e.g., on-site at a factory or in a vehicle). These technologies will enable systems engineers to create and manage systems that are more scalable, flexible, and efficient.
The rise of autonomous systems, such as self-driving cars, drones, and robots, will significantly impact systems engineering. Engineers will need to integrate autonomous systems with existing infrastructure, develop new methodologies for safety and verification, and deal with the challenges of machine-human interaction and reliability.
While blockchain is often associated with cryptocurrencies, its ability to offer secure, transparent, and immutable data transactions can be valuable for systems engineering. It could enhance supply chain management, improve cybersecurity, and create decentralized systems that are more resilient and verifiable.
Advances in computational power and simulation tools (e.g., virtual reality and augmented reality) will allow systems engineers to model systems in ways that were previously impossible. These technologies will support better design choices, training, and decision-making by providing a more immersive and accurate representation of complex systems.
Many experts in this field believe that the technology that will have the greatest impact on systems engineering long term is quantum computing.
Though still in its infancy, quantum computing could revolutionize systems engineering by solving problems that are currently intractable for classical computers. It could enhance optimization problems, data analysis, and simulation of complex systems in fields such as materials science, cryptography, and logistics.
Bottom Line: Systems engineering will continue to play a critical role in managing the increasing complexity of modern systems. As new technologies like AI, digital twins, IoT, and quantum computing emerge, systems engineers will need to adapt their approaches to incorporate these tools effectively.
These advancements will enable engineers to optimize performance, reduce risks, and deliver more innovative and efficient systems.
Tonex offers nearly 400 systems engineering courses in more than four dozen categories. Topics cover everything from Space Engineering and Defense Technology to Smart Cities, Automotive Engineering and Advanced Systems Engineering Certification.
Our systems engineering training courses are designed to apply systems engineering processes and methods. This approach teaches participants how to align practical system thinking and systems engineering knowledge and skills with process improvement, project management and program management.
Systems engineering training courses include discussions projects, case studies, formal presentation and workshops covering key aspects of systems engineering on a single system and system of systems (SoS) through a development lifecycle.
For more information, questions, comments, contact us.