In modern industrial automation and intelligent measurement systems, ultrasonic sensors, characterized by non-contact measurement, high environmental robustness, and high reliability, are widely employed in distance measurement, liquid level monitoring, target detection, obstacle avoidance control, material detection, double-sheet detection, as well as web guiding and roll diameter control. In contrast to photoelectric sensors that rely on light reflection, ultrasonic sensors perform detection using ultrasonic waves, enabling stable and reliable operation even in demanding environments with dust, moisture, smoke, or variations in target color.
In recent years, with the continuous optimization of piezoelectric transducer materials, digital signal processing, and temperature compensation algorithms, the resolution and accuracy of ultrasonic sensors have been significantly improved. From industrial control to robotic navigation, and from liquid level measurement to intelligent transportation, ultrasonic sensors have become indispensable key components in the implementation of high-performance, interference-resistant measurement systems.
1. What Is an Ultrasonic Sensor?
An ultrasonic sensor is an electronic, transducer‑based measuring instrument that uses ultrasonic sound waves (mechanical vibrations with frequencies above 20 kHz) to detect the presence of an object and/or determine its distance in a non‑contact manner. It typically integrates one or more ultrasonic transducers together with drive, reception, timing, and signal‑processing electronics into a single housing, and outputs a standardized electrical signal (switching, analog, or digital) that represents the detected target or measured distance.
An ultrasonic sensor is an electronic, transducer‑based measuring instrument that uses ultrasonic sound waves (mechanical vibrations with frequencies above 20 kHz) to detect the presence of an object and/or determine its distance in a non‑contact manner. It typically integrates one or more ultrasonic transducers together with drive, reception, timing, and signal‑processing electronics into a single housing, and outputs a standardized electrical signal (switching, analog, or digital) that represents the detected target or measured distance.
2. What is ultrasound?
To understand the operating principle of ultrasonic sensors, it is first necessary to understand sound and its propagation characteristics. Sound is essentially a mechanical wave generated by the vibration of particles in a medium. Its propagation must rely on a medium (such as air, water, or solids) and cannot occur in a vacuum. When a sound source (for example, an ultrasonic transducer) vibrates, it causes periodic compression and rarefaction of the surrounding medium particles, thereby forming a longitudinal wave that propagates through space. One key characteristic of sound is its frequency, which refers to the number of vibrations of a sound wave per second, measured in hertz (Hz). The frequency range of sound waves perceptible to the human ear is approximately from 20 Hz to 20 kHz. When the frequency of a sound wave exceeds 20 kHz, it is referred to as ultrasonic sound. This type of high-frequency sound wave lies beyond the upper limit of human hearing. Although it cannot be perceived directly by the human ear, it can be precisely generated and detected by electronic devices.
2.1 Main Physical Characteristics of Ultrasonic Waves
Compared with ordinary audible sound waves, ultrasonic waves exhibit the following distinct characteristics:
(1) Strong beam directivity
High-frequency sound waves have short wavelengths and concentrated energy, resulting in a small beam divergence angle. This enables high-resolution directional control and makes ultrasonic waves well suited for precise positioning and distance measurement.
(2) Excellent Reflectivity but Limited Penetration Capability
When ultrasonic waves encounter media with different densities or elastic moduli, part of their energy is reflected. The intensity of this reflection can be used to determine the position of an object or changes in material properties—this is the physical basis of echo ranging and energy-based detection technologies.
(3) Propagation Velocity Depends on the Medium
The speed of sound in air is approximately 344 m/s at 20 °C and is higher in liquids and solids. Since the speed of sound in a given medium is stable and measurable, precise distance calculation can be achieved using the Time of Flight (TOF) method.
(4) Two Typical Applications of Ultrasound in Sensing Technology
Ultrasonic sensors utilize the propagation and reflection characteristics of sound waves in a medium to realize automatic detection. According to different measurement principles, two common operating modes have been developed:
- Time of Flight (TOF) Distance Measurement
The distance to a target is calculated by measuring the round-trip time from emission of the ultrasonic pulse to the reception of the echo. This method is insensitive to the target’s surface color, ambient light, or transparency, and is widely used in positioning, level measurement, collision avoidance, and presence detection. - Energy Attenuation Detection
This method is based on the principle of energy attenuation during sound propagation—when ultrasonic waves penetrate or are reflected by different materials, the signal energy changes due to absorption, scattering, or multilayer superposition. By measuring differences in received signal intensity, the system can determine single-sheet/double-sheet conditions, detect web edges, or analyze the material characteristics of the object under test. This approach offers fast response and is particularly suitable for continuous processes in printing, packaging, and film processing, where it is used to prevent material jamming, overlapping, or web misalignment. Ultrasound is a high-frequency mechanical wave with excellent directivity and measurement stability. Based on the same acoustic propagation principles, ultrasonic distance measurement focuses on the precise extraction of “time information,” whereas ultrasonic energy measurement focuses on the analysis of “signal attenuation.” Together, these two methods form the core foundation of modern ultrasonic sensing technology, enabling sensors not only to measure “how far” but also to identify “what it is,” thereby supporting automatic detection, control, and quality assurance in complex industrial environments.
3. Working Principle
3.1 Time of Flight (TOF) Distance Measurement
Our ultrasonic distance-measurement product series is designed for a measurement range from 0.5 m to 6 m, covering typical industrial and robotics applications. Based on the “Time of Flight (TOF)” method: the sensor emits a beam of high-frequency sound waves, and when the sound waves encounter a target and are reflected back to the receiving end, the system calculates the target distance by measuring the time required for the sound waves to travel back and forth. This method has a clear physical basis, offers stable measurement performance, and is not sensitive to differences in the material of the object. Therefore, it has obvious advantages in traditional distance measurement, positioning, and presence detection tasks. The core operating mechanism of ultrasonic sensors is based on the propagation characteristics of sound waves in a medium, and their distance measurement process adopts the Time of Flight method. The basic idea of this principle is as follows: the sensor emits a beam of high-frequency sound waves, which propagate through the air. When they encounter the surface of a target object, they are reflected and return to the receiving end. The system uses a precise timing circuit to measure the round-trip time difference from emission to reception of the sound waves, and thus calculates the target distance. Theoretically, the distance can be calculated using the following formula, based on the speed of ultrasonic waves in air:
L=2C×T
Where:
- (L) is the distance from the sensor to the target object; in our product series, the typical range of ultrasonic distance measurement is from 0.5 m to 6 m.
- (C) is the speed of sound (about 344 m/s in air at 20 °C, with the actual value varying with temperature);
- (T) is the time taken for the sound wave to travel back and forth.
Working Principle of Distance Measurement The actual distance measurement process typically includes the following key steps:
(1) Transmission
High-frequency mechanical vibrations are generated by a transducer (usually a piezoelectric element), producing short ultrasonic pulses that propagate through the air.
(2) Propagation & Reflection
The sound waves propagate at the speed of sound, and when they encounter a target object, reflection occurs due to the acoustic impedance difference between media. The intensity of the reflected wave is influenced by the surface smoothness, inclination angle, and material of the object.
(3) Echo Reception
The receiving transducer converts the returned echo signal into an electrical signal, from which the system extracts the valid echo for subsequent calculation.
(4) Timing & Distance Calculation
The circuitry precisely measures the propagation time and calculates the distance using the corresponding formula. Signal filtering, averaging, and temperature compensation algorithms are applied to enhance measurement stability. This method features a simple structure, fast response, and insensitivity to target surface color, transparency, or ambient light conditions, while maintaining high reliability even in dusty environments, strong light, or complex geometric scenes. To address issues such as weak echoes or multipath propagation, modern sensors are often equipped with digital signal processing (DSP) and automatic gain control (AGC) functions, which significantly improve echo detection and noise suppression capability. Through TOF technology, ultrasonic sensors achieve stable and highly repeatable distance measurement over a range from several millimeters to several meters, providing a mature solution for level measurement and control, positioning, and collision avoidance systems.
3.2 Energy Attenuation Method
The basic principle of ultrasonic energy measurement is based on the energy attenuation characteristics of sound waves during propagation in a medium. A high-frequency ultrasonic signal is generated at the transmitting end, and after passing through the material under test, its signal intensity is detected at the receiving end. By quantifying the degree of energy attenuation of the received waveform, the system determines the extent to which the sound wave is affected by absorption, reflection, or scattering during transmission, thereby achieving material state identification and feedback control. The typical applications of this principle include the following categories:
(1) Sheet Detection
When ultrasonic waves penetrate materials such as paper, film, or metal sheets, the signal energy decreases significantly as the number of layers increases. By comparing the received signal intensity, the system determines whether a single sheet or double sheets are present; when multiple stacked layers are detected, an alarm or automatic shutdown can be triggered to prevent material jamming or abnormal feeding.
(2) Edge Detection of Web Materials
In the control of web or strip materials, the ultrasonic energy exhibits a sharp change at the material edge. By continuously monitoring variations in the amplitude of the received signal, the sensor determines the actual edge position of the material and provides adjustment signals to the servo or drive system, thereby stabilizing winding or conveying speed.
(3) Material Identification
In material inspection scenarios, the sensor typically adopts a single-transducer configuration, performing both transmission and reception. By analyzing the degree of energy attenuation in the reflected signal, it is possible to infer material density, thickness, or sound absorption characteristics, there by enabling identification and classification of different materials.
Compared with TOF distance measurement, the energy attenuation method focuses more on signal amplitude analysis rather than propagation time measurement, making it suitable for determining the physical state, number of layers, or structural differences of an object. Featuring fast response, compact construction, and ease of in-line integration, it serves as a key sensing technology in applications such as printing, packaging, and web processing.
3.3 Factors Affecting Measurement Accuracy
The measurement accuracy of ultrasonic sensors is influenced by several external factors, even though they can operate stably in a wide range of environments. A thorough understanding of these parameters and their compensation is essential to ensure precise distance measurement and long term stable operation.
(1) Effect of Temperature Variation on Sound Velocity
As the density and elastic modulus of air change with temperature, the speed of sound also varies accordingly. The speed of sound in air can be approximately expressed as:
C=331+0.6T(m/s)
Where (T) is the air temperature (unit: °C). From the formula, it can be seen that for every 1 °C increase in temperature, the speed of sound increases by approximately 0.6 m/s. For example, when the ambient temperature rises from 20 °C to 30 °C, the speed of sound increases from about 343 m/s to about 349 m/s. If no compensation is applied, this will introduce a considerable error in distance calculation. To avoid such effects, industrial ultrasonic sensors usually integrate temperature compensation circuits or digital temperature sensors. The control system measures the ambient temperature in real time and dynamically corrects the sound speed parameter used in calculations, thereby effectively improving overall distance measurement accuracy.
(2) Relationship Between Operating Frequency and Measuring Distance
The operating frequency of an ultrasonic sensor directly determines its measuring range and resolution:
- Low frequency sensors (20–80 kHz): Feature low attenuation and long propagation distance, capable of measuring ranges of several meters. They are commonly used for liquid level monitoring or long range obstacle detection.
- Mid frequency sensors (100–200 kHz): Offer a balance of higher accuracy and medium measuring range, suitable for mid range applications such as automated assembly and logistics inspection.
- High frequency sensors (above 300 kHz): Have short wavelengths and high resolution but exhibit significant attenuation, making them suitable for short range precision positioning or detection of small objects.
(3) Target Surface Characteristics and Reflection Intensity
Differences in the target surface’s acoustic reflection properties also affect the echo signal strength and measurement stability.
The main factors influencing echo intensity include:
- Surface material: Hard materials such as metal and glass provide good reflection, while soft or sound absorbing materials (e.g., rubber, fabric, foam) significantly attenuate acoustic energy.
- Surface smoothness: Smooth surfaces produce specular reflection, which facilitates signal return; rough surfaces tend to cause diffuse reflection, reducing received signal strength.
- Incidence angle:
When the angle between the target surface and the direction of the sound wave is too large, the reflected energy deviates from the sensor’s receiving range, potentially creating detection blind spots.
To address these challenges, the following engineering measures are commonly adopted:
- Design transducer structures with an appropriate emission angle to improve signal coverage.
- Employ automatic gain control (AGC) technology to automatically adjust the amplification factor based on echo strength.
- Use multiple sampling or signal averaging algorithms for complex surfaces to reduce fluctuations caused by random reflections.
4. Typical Application Scenarios
With non‑contact measurement, high environmental adaptability, and good reliability, ultrasonic sensors have been widely used in various industrial and automation systems. So, what does an ultrasonic sensor do in practice?
4.1 Object Detection and Positioning
In automated production lines, packaging, and logistics systems, ultrasonic sensors are commonly used for detecting the presence, position, or height of objects on conveyor belts (e.g., detecting objects on a conveyor: Compared with photoelectric sensors, ultrasonic detection is insensitive to surface color, transparency, or ambient light intensity, and can therefore reliably identify plastic, glass, metal, and coated objects, avoiding false detections caused by reflections or color variations. In robotic systems, ultrasonic sensors enable obstacle avoidance and spatial positioning. Through multi point placement and angle compensation, the system can perceive the three dimensional distribution of surrounding obstacles, providing real time data to support mobile path planning.
4.2 Level Measurement
Liquid level measurement is one of the earliest and most mature application fields of ultrasonic sensors (e.g., Ultrasonic Level Sensors: In storage tanks, liquid troughs, or wastewater treatment systems, the sensor is typically installed at the top of the container and measures the liquid level height by calculating the sound wave round trip time to the liquid surface and back. Its non contact measurement method prevents corrosion and contamination of the sensor by the liquid, making it particularly suitable for chemically corrosive or high temperature media. Modern ultrasonic level sensors are generally equipped with temperature compensation and signal filtering algorithms, enabling them to maintain stable readings even under complex conditions such as foam, vapor, or agitation.
4.3 Distance and Presence Sensing
In automatic door control, parking assistance systems, and intelligent transportation equipment, ultrasonic sensors are used to detect the presence of objects or people and their direction of movement. In automotive applications, the sensors serve as an important component of parking radar modules, enabling close range obstacle detection and identifying relative speed based on changes in the echo of sound waves, thereby assisting vehicle safety control. In addition, in industrial machinery protection and safety area monitoring, ultrasonic sensors can operate continuously in environments with dust or oil mist, helping to ensure the safety of both equipment and personnel.
4.4 Industrial Process and Material Monitoring
In continuous production fields such as packaging, printing, textiles, and food processing, ultrasonic sensors can be used for monitoring film thickness, double sheet detection, and roll diameter measurement. By working in conjunction with automated control systems, the sensors provide real time feedback signals to enable automatic feeding, tension regulation, and process optimization. Compared with radar or optical detection methods, ultrasonic solutions offer advantages such as fast response, high cost effectiveness, and ease of installation and integration.
4.5 Emerging Applications
With the development of the Internet of Things (IoT) and intelligent manufacturing, ultrasonic sensing technology is expanding into many emerging fields, such as:
- Agricultural environment monitoring: measuring feed level in silos or the water level in irrigation systems;
- Smart city infrastructure: monitoring the fullness of trash bins or detecting displacement of manhole covers;
- UAV ranging and terrain following: enabling stable altitude holding and obstacle avoidance during low altitude flight;
- Medical and laboratory equipment: used for non contact liquid level detection, reagent volume estimation, or microfluidic system monitoring.
These emerging applications further demonstrate the universality and engineering scalability of ultrasonic sensing in complex environments. With a solid foundation of applications and continuous technological refinement, ultrasonic sensors have gradually evolved from traditional process control devices into core sensing components in intelligent detection and automation systems. Whether in precise distance measurement based on time of flight, or condition monitoring based on energy attenuation, ultrasonic technology—by virtue of its high reliability, non contact nature, and scalability—will continue to play a key role in future intelligent manufacturing, industrial connectivity, and the broader IoT ecosystem.
5. Advantages and Summary
Thanks to their unique acoustic measurement principles and strong environmental adaptability, ultrasonic sensors have long occupied an important position in the fields of industrial automation and intelligent detection. Compared with other sensing technologies such as optical, inductive, and capacitive sensing, ultrasonic sensing demonstrates superior performance in both distance measurement (TOF, Time of Flight) and energy detection (amplitude/energy measurement) applications. Its main advantages are reflected in the following aspects:
5.1 Non-contact measurement with high reliability
Whether for time-of-flight distance measurement or energy-attenuation detection, ultrasonic measurement is based on the physical laws governing sound propagation in a medium, without requiring direct contact with the target. This non-contact characteristic effectively avoids probe damage caused by mechanical friction, chemical corrosion, or high-temperature environments, making it particularly suitable for complex media such as liquids, powders, and continuous webs. For energy-measurement type sensors, signals detect material state via transmission or reflection, likewise without physical contact, enabling single/double-sheet recognition or edge positioning. This provides significant advantages in keeping equipment clean and reducing maintenance frequency.
5.2 Low sensitivity to target characteristics and environmental influences
Unlike optical sensors, ultrasonic detection results are not affected by the object’s surface color, brightness, reflectivity, or transparency. TOF distance-measurement sensors can maintain stable echo detection in environments with dust, steam, and oil mist. For energy-measurement sensors, even when the surface of the measured material is rough or semi transparent, its energy attenuation characteristics can still be accurately captured, enabling reliable judgment of thickness or overlap conditions. Therefore, ultrasonic sensing is almost independent of external optical conditions and is one of the physical detection technologies with the widest environmental adaptability.
5.3 Wide measurement range with adjustable accuracy and sensitivity
The performance of ultrasonic sensors can be widely adapted by adjusting operating frequency, beam width, and internal signal processing algorithms:
- For distance measurement (TOF) sensors, high frequency, narrow beam devices can achieve sub millimeter accuracy, while low frequency modes provide better long range or strong penetration capability;
- For energy measurement sensors, by optimizing drive amplitude and receive sensitivity, they can achieve high resolution detection of subtle energy differences, meeting the needs of high speed web or film inspection.
5.4 Simple structure and easy integration
An ultrasonic sensing unit consists of a transducer, drive circuitry, and signal conditioning and processing modules, featuring compact structure, low power consumption, and flexible interfaces. In both distance and energy measurement applications, outputs can be directly integrated with upper level control systems via analog signals, switching signals, or digital communication buses (such as UART, RS485, IO Link, CAN). On printing, packaging, and automated assembly production lines, energy measurement sensors can be directly embedded into control systems to implement single sheet monitoring, web guiding, and tension control; distance measurement sensors can be deployed as position or level detection nodes, enabling distributed sensing and closed loop control.
5.5 Mature technology with wide application
After years of development, ultrasonic sensing technology has formed a complete product portfolio covering distance measurement, energy measurement, level sensing, and material detection.
With its stability, cost effectiveness, and environmental adaptability, ultrasonic sensors are widely used in:
- Automation and assembly line inspection (object presence and positioning);
- Process control and level monitoring (TOF distance measurement type);
- Printing and packaging web detection (energy measurement type, single/double sheet recognition, edge positioning);
- Automotive electronics and security systems (distance sensing and collision prevention).
Ultrasonic sensors, based on acoustic propagation principles, combine non contact operation, high stability, and environmental self adaptation, exhibiting excellent performance in both distance measurement and energy detection tasks. Their simple structure, controllable cost, and universal interfaces make them core sensing elements in intelligent manufacturing, process control, logistics automation, and IoT systems. In the future, with the development of acoustic material science, transducer design, and high performance signal processing algorithms, ultrasonic sensors—especially intelligent devices that integrate both distance and energy measurement functions—will offer higher sensitivity, stronger anti interference capability, and richer self diagnostic features, providing crucial support for precise measurement and the advancement of smart factories.
6. Outlook and Future Development Directions
With the continuously growing demands of intelligent manufacturing, robotics, autonomous navigation, and IoT systems, ultrasonic sensing technology is evolving from traditional basic distance measurement toward greater intelligence, integration, and adaptability. Future development trends will mainly be reflected in the following aspects:
6.1 Intelligent signal processing and algorithm optimization
Traditional ultrasonic sensors rely mainly on hardware characteristics and analog circuits to accomplish transmission and echo detection. However, with the rapid development of embedded processors and digital signal processing technologies (DSP, FPGA, MCU), future ultrasonic systems will possess more powerful intelligent recognition and data analysis capabilities. By adopting adaptive filtering, feature extraction, pattern recognition, and machine learning algorithms, sensors will be able to distinguish valid echoes from noise reflections, and achieve dynamic threshold adjustment and self-calibration of signals in complex environments, thereby further improving measurement accuracy and stability.
6.2 Multi-sensor fusion and spatial perception
Although a single ultrasonic sensor can measure distance accurately, it still has limitations in spatial localization, object recognition, and shape estimation. Future systems will increasingly adopt sensor fusion strategies, combining ultrasonic data with millimeter-wave radar, infrared, TOF laser, or vision systems. This fused perception approach can significantly improve spatial resolution and anti interference capability, making it particularly suitable for mobile robots, autonomous driving, UAV obstacle avoidance, and industrial collaborative robots, enabling more sophisticated 3D environment understanding and decision support.
6.3 Miniaturization and low-power design
Driven by the demand from portable devices and IoT terminals, future ultrasonic sensors will develop toward miniaturization, low power consumption, and high integration. New piezoelectric thin film materials (such as AlN and PZT thin films, as well as MEMS structures) are gradually replacing traditional ceramic transducers, enabling sensors to operate stably with smaller size, lower drive voltage, and higher frequency. At the same time, combined with low power microcontrollers and intelligent sleep strategies, sensors can operate efficiently in energy constrained systems, such as battery powered nodes or wireless sensor networks.
6.4 Broader scenario adaptability and intelligent compensation
Future ultrasonic sensors not only need to operate stably in ideal environments, but also must be able to automatically adapt to different media, temperatures, and climate conditions. By introducing environmental sensing modules and multi parameter compensation algorithms (including temperature humidity, air pressure, and wind speed correction), the system can maintain consistent measurement performance in open spaces, liquid media, or extreme environments. This trend will drive the widespread adoption of ultrasonic sensors in more challenging scenarios such as outdoor monitoring, intelligent transportation, marine equipment, and agricultural automation.
6.5 Networking and data driven development
In the era of Industry 4.0 and the Internet of Things (IoT), a single sensor is no longer an isolated functional unit, but an intelligent node in a distributed measurement and control network. Future ultrasonic sensors will support more digital communication protocols (such as IO Link, Modbus, etc.), and may even integrate wireless transmission capabilities, enabling real time data interaction with cloud platforms or edge computing units. Through data fusion and remote monitoring, the system can perform status diagnostics and lifetime prediction, and also realize predictive maintenance and self learning calibration, significantly improving overall operational efficiency.
Ultrasonic sensing technology, as a proven and mature measurement method, is evolving toward higher level intelligent detection and system collaboration. In the future, ultrasonic sensors will no longer be limited to the basic function of “distance measurement,” but will become the active perception core of intelligent devices, endowed with self learning, environmental self adaptation, and networked collaboration capabilities. Through integration with artificial intelligence, MEMS manufacturing, and digital communication technologies, ultrasonic sensing will demonstrate greater technical potential and commercial value in intelligent manufacturing, autonomous driving, medical diagnostics, and environmental monitoring.
7. Conclusion
As a core sensing technology in modern industry and intelligent systems, ultrasonic sensing has demonstrated lasting vitality across numerous industrial domains, thanks to its reliable acoustic measurement principles, mature engineering implementations, and excellent environmental adaptability. From its early use in distance and level measurement to today’s applications in complex scenarios—such as spatial perception, obstacle avoidance, material analysis, and process monitoring—ultrasonic sensors not only retain a key role in traditional manufacturing, but are also becoming a central bridge for intelligent equipment to achieve the loop of “environment perception → information feedback → autonomous decision-making.”
At the technical level, in depth research into acoustic propagation mechanisms, innovations in piezoelectric and composite transducer structures, and the integration of multi mode signal processing and algorithm optimization have enabled modern ultrasonic sensors to achieve a high degree of balance among accuracy, response speed, and robustness. At the system level, ultrasonic detection is being deeply integrated with control theory, embedded computing, artificial intelligence, and communication networks, providing perception enhanced, integrated solutions for industrial automation, robotics, and the Internet of Things.
In this sense, the role of ultrasonic sensing technology is shifting from a mere “measurement tool” to a key component of a “cognitive system.” From measuring distance to identifying states, from passive response to active understanding, it is becoming an indispensable foundational pillar in the ecosystem of intelligent manufacturing.
Looking ahead, with ongoing advances in MEMS micro-structured devices, low power electronics, and multi sensor data fusion technologies, ultrasonic sensors will inevitably evolve toward greater miniaturization, intelligence, and system level collaboration:
- from single point detection to multi dimensional spatial perception;
- from standalone units to system level integration;
- from passive ranging to active environmental understanding and prediction.
In an increasingly intelligent industrial landscape, ultrasonic sensors are not only executors of precise measurement, but also fundamental guarantors of system stability and safety. Their robustness, universality, and cost effectiveness ensure that they will continue to play a crucial perceptual and cognitive role in future integrated “sense–compute–control” smart manufacturing systems, providing sustained support for building a more efficient, safer, and more intelligent industrial world.
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