Envisioning the Future of Software-Defined Factories
BY: Benjamin Saltsman, Director, Data Analytics, Simulation and IoT
For over a decade, the automotive sector has been making gradual progress toward the modernization of traditional manufacturing practices. Today, these efforts are accelerating rapidly alongside unprecedented advancements in technology defined by increasingly intelligent, data-driven processes. New standards for productivity and efficiency on the factory floor are being established.
The automotive industry is entering a new era where many factory operations are driven less by manual tasks, which can at times be cost-prohibitive, time-consuming and error-prone. Instead, we are seeing the rise of factory automation powered by both intelligent hardware and smart manufacturing software. This new generation of software-defined factories will consist of a wide and constantly expanding range of features and technologies.
One major component of this transformation is the integration of intelligent software into existing factory machinery and advanced robotics. Manufacturing facilities will significantly reduce reliance on the manual performance of essential yet tedious tasks, such as the assembly of individual parts and entire vehicles. Automation will complement human workers, making factory work safer and more efficient, minimizing operational downtime while improving accuracy and precision. This leads to a significant increase in productivity for all stakeholders.
Another significant advancement is the use of digital twins. Almost every physical object on the factory floor, from machinery to material handling equipment, will have a virtual replica. These digital twins leverage connectivity to PLCs, IoT devices and IT/OT systems, providing manufacturers with enhanced visibility into all systems and their performance. This allows for near real-time identification and mitigation of inefficiencies across the production floor.
The integration of AI and machine-learning technologies further enhances these components. AI improves the precision of automated manufacturing processes and the accuracy of data within digital twins. It also analyzes and generates actionable insights on how to improve a factory’s overall operations. This enables a more agile approach to factory safety, production efficiency, material waste reduction, and space utilization.
Overall, the fusion of intelligent software and physical processes represents a significant step forward in the modernization of automotive manufacturing. This technological revolution is actively redefining and shaping the future of the mobility sector.
As we move forward, the continued implementation and development of AI-powered automation and digital twins will help reduce operational inefficiencies and foster better collaboration across teams. This could boost productivity and unlock new opportunities for creativity and innovation.
What are the near- and long-term benefits you see as a result of the software-defined factory?
Card Verification officer at National Identification Authority
1wInsightful
Design Verification Engineer | Experienced in FPGA integration | Skilled in VHDL, Verilog, Altium design, C, C++
4wWhile many are rightly highlighting the benefits of software-defined factories—like efficiency, scalability, and cost savings—we must also consider the long-term impact on the job market. As automation and intelligent machines reduce the need for manual labor, traditional factory jobs may gradually disappear. Though new roles will emerge in AI, automation, hardware design, and verification, even software development is being reshaped by AI. Additionally, the rise of digital twins will demand more sophisticated software capable of overseeing, maintaining, and optimizing these virtual replicas of manufacturing systems. The key will be adaptability—those who upskill in these future-facing domains will stay relevant in this rapidly evolving landscape.
OPERATIONS & INDUSTRIAL & PLANT DIRECTOR / MANAGING ( Manufacturing / Production / Process & Product Engineering / Quality / Supply Chain / Maintenance / P&L / Capex / Opex / Lean Manufacturing / Black Belt Six Sigma).
1moThank you, Ben Saltsman, for sharing such a compelling vision of the future of manufacturing. I completely agree that the integration of intelligent software, AI, and digital twins is not only transforming the way we produce, but also creating a safer, more efficient, and more collaborative environment on the factory floor. As someone currently engaged in the operational side of the industry, I truly believe this shift represents a great opportunity to make a real difference — by embracing innovation, reducing inefficiencies, and fostering continuous improvement. I'm excited to be part of this transformation and to contribute toward building the software-defined factories of tomorrow.
Tecnico automotriz y Estudio en la Universidad Autónoma de Santo Domingo
1moGracias por compartir
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1moData-driven processes collect numbers in real-time, it’s like when you’re driving your car, and then you see that there is a school zone ahead and a sign which says limit speed at 25km/hr, in that moment you check that the odometer says you’re driving at 50, so you down shift to 25 in that very moment, the adjustments are carried out at the exact moment they are required to be done, you don’t have to wait for by-hour reports to do that. You can ensure manufactured parts’ specifications are met by monitoring dimensionals, so corrections are done in real-time leaving no time for defective parts. Even though a certification station is already fixed at the exit of either some processes or some machines, and some machines also have already installed in them a sort of data-driven system, I think complex data-driven systems have the potential to increase productivity, effectiveness, additionally to others KPI. You can also assure ideal inventories by feeding the system with real-time on-hand data. In conclusion, since all of the factory's KPIs are quantifiable, they can be traced in real-time per use of data-driven system, thus the decision-making processes would be more productive as effective.