Smarter Motion Control for Smart Manufacturing

Motion control is one of my favorite disciplines. I remember the summer I spent at my university lab working on controllers for unstable systems. My tools were incredibly advanced for that time, but motion control has come a long way since, thankfully.

Factories around the world are being pressed to do more with less. Ongoing supply chain disruptions, on-shoring and near-shoring, and environmental impact concerns are pushing manufacturers to be increasingly agile and resilient.

To get there, factories need smarter motion control. Figure 1 illustrates why this is the case: motion control is central to many manufacturing processes. The underlying motion control systems must meet these same criteria for the factory to be efficient, responsive, and robust.

Figure 1 : Smart factories involve a wide variety of motion control applications. (Image source: Analog Devices)

In this blog, I’ll highlight how to achieve these goals with high-precision motion control and machine health monitoring. I will explain how these techniques are critical elements of the digital transformation trend leading to truly intelligent factories.

High-precision motion control

The path to smarter motion control begins with higher precision current and position measurements, which creates opportunities to minimize waste while maximizing responsiveness and throughput. The precision of any control system depends on its sensors.

While there are many options in the case of position sensing, magnetic sensors are particularly attractive because they offer high resolution at a lower cost than optical encoders. They are more robust in applications subject to dust and vibration, and their contactless nature minimizes wear and tear.

However, magnetic sensors can be susceptible to external magnetic fields' interference and surrounding materials' influence. Their accuracy can also be affected by temperature fluctuations, so calibration may be necessary to maintain their accuracy, which can reduce their advantages in terms of cost and reliability. Plus, many magnetic sensors only perform well in close range, which limits their applications.

One way to balance these considerations is with anisotropic magnetoresistance (AMR) sensors. Unlike Hall effect, giant magnetoresistance (GMR), and tunnel magnetoresistance (TMR) sensors, AMR sensors exhibit robustness in magnetically harsh environments and maintain accuracy with wide air-gap tolerances. The need for calibration and maintenance is considerably reduced because AMR sensors don’t experience degradation and angular error under these conditions.

A good example is the ADA4571 family of angle sensors from Analog Devices. These sensors, equipped with integrated signal conditioners, facilitate higher absolute accuracy position sensing for motor drive and servo applications. The ADA4571 features built-in calibration engines that keep errors to <0.5° over a wide range of temperatures (Figure 2).

Figure 2 : Shown is the typical error of the ADA4571 sensors for VDD = 5.5 (left), which can be improved by enabling the built-in gain control (GC) function (right). (Image source: Analog Devices)

Machine health monitoring

While performance is essential in the intelligent factory, so are efficiency and resilience. By monitoring motor vibration and shock, machine health sensors (such as vibration sensors) in factories can reduce unplanned downtime, extending the asset’s useable lifetime while reducing maintenance costs. While there are many sensor options, microelectromechanical systems (MEMS) accelerometers strike an appealing balance of capabilities, offering high bandwidth and low noise at a fraction of piezoelectric systems' price and power consumption (Figure 3).

Figure 3 : The sensors available for machine health monitoring have cost, performance, and power tradeoffs. (Image source: Analog Devices)

A good MEMS example is the ADXL1001/ADXL1002 family of sensors. Focusing on the ADXL1002, noteworthy features include noise of just 25 micro g per root Hertz (μg/√Hz) in the ±50 g range, and resilience to external shocks up to 10,000 g. A linear frequency response from DC to 11 kilohertz (kHz) makes the parts suitable for slowly rotating equipment, while low power consumption facilitates wireless sensing designs. For applications that require measurement along three axes, the ADXL371 can be a suitable choice.

Real-time connectivity for digital transformation

The real power of the sensing solutions discussed so far comes from their ability to unlock deep insights into factory operations. Once data such as voltages, currents, positions, and temperatures are collected from various motion-control systems, automated systems can analyze this data to optimize real-time manufacturing flows.

As illustrated in Figure 4, deterministic data collection currently involves a variety of fieldbus protocols like EtherCAT and PROFINET. However, the industry is rapidly adopting Time-Sensitive Networking (TSN) as a standard for next-generation networks. This trend is fundamental to the emergence of converged information technology/operational technology (IT/OT) infrastructure, which brings together enterprise and factory floor systems on a single network.

Figure 4 : The manufacturing sector is transitioning from standalone fieldbus networks to converged IT/OT infrastructure based on TSN over Gigabit Ethernet (GbE). (Image source: Analog Devices)

These networks require sub-millisecond network cycle times to ensure determinism and up to gigabit bandwidth to accommodate new high-speed traffic sources such as video feeds from vision systems. Modern motion control systems need Ethernet physical layers (PHYs) like the ADIN1200/1300 family to meet these requirements. These robust, low-power and low-latency PHYs support GbE in industrial environments. They can operate in ambient temperatures up to 105°C, have been extensively tested for electromagnetic compatibility (EMC), and offer rugged features like brownout protection.

Conclusion

In the evolving landscape of smart manufacturing, intelligent motion control is a pivotal element, driving factories toward greater agility and resilience. Central to this optimization is the precision and efficiency of motion control systems. With newly expanded sensor options, engineers have opportunities to improve everything from position tracking to machine health monitoring. By feeding this progressively vast and precise data into increasingly capable factory networks, the promise of digital transformation is quickly becoming a reality. As we embrace this digital era, the exciting fusion of intelligent motion control and advanced networking promises a future of truly smart manufacturing.