The Future of Machines: Self-Aware Control Systems

Publish Date: Apr 27, 2012 | 17 Ratings | 4.00 out of 5 | Print | Submit your review


Machine builders have made advances in developing technology that can complete repetitive tasks with great speed. See how you can integrate the next generation of machines into your control systems.

When examining machine-industry trends, you often encounter new controller technologies that increase the performance and throughput of high-end machines, motor technologies, or energy-efficient algorithms, or you learn about tools that help lower the cost of machine design. Over the last few decades, machine builders have made considerable advances in developing machines that can complete repetitive tasks with ever-increasing speed. There are other trends and technologies, however, that might have an even more significant influence on the next generation of machines and the way those machines are integrated in your work process.

After spending decades optimizing machinery equipment speed, the industry is running into new limiting boundaries. High speeds and operating machines running at maximum load are increasing the wear and tear of mechanical components and tools. This increases the importance of maintenance and systems that ensure uptime. Additionally, many tasks in the industry are not purely repetitive. Solutions to application problems such as picking randomly shaped parts out of a bin are far from realization. Last, but not least, several manufacturing processes still involve a significant amount of work by humans. The machine industry needs to address safety concerns that arise when humans work alongside machines and robotic systems.

The availability of data and information about the environment, processes, and machine parameters is crucial to addressing these new machine industry challenges. Therefore. sensors and measurement technology that can acquire this information are playing a significant role for the next generation of machines. The sensor market was very static for decades, but the last few years have brought substantial innovation. Sensor technology advancements have been adopted into many electronic devices, from smart phones to home automation systems, and prices have dropped to all-time lows.

You can use sensors to create systems that are aware of their environment, perform real-time process monitoring, and know every detail about their mechanical component health. However, sensors alone are worth no more than the control systems of the past. The key to solving new challenges is creating control systems that can integrate sensor data, gather information in real time, and use information from multiple sensors within high-speed control loops. High-performance embedded systems with industrial-grade ruggedness, such as NI CompactRIO programmable automation controllers (PACs), provide direct sensor connectivity through modular I/O devices. You can use the reconfigurable field-programmable gate array (FPGA) to preprocess sensor data even before the information is transferred to the real-time processor, which executes custom control or monitoring tasks programmed in the NI LabVIEW graphical development environment.

So how will sensor and measurement technology change the future of machines? 

First, by integrating advanced measurement and sensor technology into  mechanical systems and machines, you can implement machine condition monitoring applications. Condition-based maintenance systems help decrease unscheduled outages and optimize machine performance while reducing maintenance and repair costs. Additionally, you can use measurement and sensor technology to increase machinery and equipment safety and provide the control system with information about system health at any time during operation. You can add machine condition monitoring tasks through embedded subsystems that are connected to the control system via network technologies or that are integrated into the control system as another task.

Figure 1. CompactRIO PACs offer connectivity to hundreds of sensors and actuators, such as in this application from Oregon State University.

Next, with a more seamless integration of sensor information in the controller you can create self-healing or adaptive machines and systems that can adjust, for example, to the changing characteristics of mechanical components. By enabling the control system to identify these changing conditions caused by mechanical component wear and tear, you can implement routines that gather data during a startup process or during the machine’s operation and use adaptive control algorithms, which improve machine operation.

Finally, by integrating advanced sensors you can develop dynamic machines that adapt to changing environmental parameters and monitor process parameters to ensure near-perfect manufacturing results. With additional knowledge about the process, the machine can detect imperfections or changes in the raw material, adjusting for vibrations that might appear within a machined part or dealing with tasks that are different for each of the processed parts or iterations of the process. Good examples are medical machines and devices, such as cell-sorting systems or DNA sequencers that must process unpredictable structures such as naturally growing cells. These systems need to heavily adapt their process based on information they gather from imaging sensors, camera systems, or other advanced sensor systems.

Figure 2. You can use high-performance NI Smart Camera systems to create vision-guided robotics applications, such as this one from Vetraco.

The increased adoption of measurement and sensor technology for control applications will also revolutionize the robotics machine industry. If you look closely at the well-orchestrated movement of a line of welding robots, you see that they simply perform the same predefined movements again and again. You need advanced sensor technology to adapt industrial robotics systems (which have been used in industry for decades) to perform more advanced applications, such as picking parts from a bin or handling delicate parts and goods. You can use tactile sensors, light detection and ranging (LIDARs), and camera systems to give robots the ability to detect the presence and location of objects and humans, or control the amount of force and pressure applied to parts and goods. This opens up new application areas for robotics.

Sensors have always been part of high-end machines. With new technologies, decreasing prices, and high-performance control systems with the capability to incorporate and process information from multiple sensors, you can create the next generation of machines and devices that are fully aware of their environment and monitor all machine and process parameters so that they can adapt to changing conditions.

Please visit the following links for more machine design resources:

Control and Monitoring for Industrial Machinery

Machine Design Tutorials and Case Studies


Christian Fritz

Christian Fritz is the product manager for advanced machine control and robotics at National Instruments. He focuses on industrial and embedded control systems and helps machine builders and roboticists improve their design process. Christian has a degree in electrical engineering from the University of Applied Sciences in Munich/Germany.

Back to Top

Bookmark & Share


Rate this document

Answered Your Question?
Yes No