The spread of advanced automation technology in manufacturing is advancing rapidly, with facilities—both old and new—implementing the latest in smart manufacturing and intelligent robotic systems. The need for precise motion control is driven by all of the demands now placed on the line, from moving products around on the manufacturing floor to the stations they are worked on to the logistics of moving the finished product through a facility.
These intelligent systems share three primary needs: detection, decision, and action. Modern sensors provide the detection, advanced microcontrollers (MCUs) and smart management software develop the decision, and precision motors perform the action. Each of these legs are as important as the next, since the best motor is useless without precise control, and neither can perform adequately without feedback. In this article we’ll go over the latest in motion and motor control from the point of the controller and logic.
Performing in an industrial environment is a challenge under the best of conditions, as fast, efficient, and effective operation is often hampered by harsh environments, tight confines, and noise in both power and signal from facility equipment. Devices serving this space must be smart, small, and rugged.
Sensors provide the information from the real world, but that information must be filtered, interpreted, and acted upon. The latest system-on-chip (SoC) devices and microcontrollers are starting to incorporate advanced functionality that lend themselves well to the automation space. Today, a key feature is the ability to communicate both wired and wirelessly with a variety of protocols for as seamless a deployment as possible.
Communication
The argument can be made that the last frontier of the cloud is to bring together all wireless devices, legacy and modern. This need will diminish as devices migrate toward a more homogenous universal protocol, but until then, system controllers will need to be multilingual.
One example can be found in Texas Instruments’ SimpleLink MCU platform (Figure 1). Created to meet the myriad connectivity needs in smart buildings, intelligent factories, and next-gen grid applications, this family of wireless and wired microcontrollers also have industry-leading low power consumption.
Figure 1: Texas Instruments’ SimpleLink MCU platform is a family of wireless and wired microcontrollers designed to meet the myriad of connectivity needs in smart buildings, intelligent factories, and next-gen grid applications.
The devices provide multi-standard and multi-band connectivity for Thread, Zigbee, Bluetooth 5, and sub-1 GHz, with memory and connectivity options, and 100 percent code reuse across TI’s Arm Cortex-M4-based MCUs to support and connect sensor networks to the cloud.
In the case of Silicon Labs, they developed dynamic multiprotocol software for their existing family of wireless Gecko SoC and modules (Figure 2) to enable simultaneous operation of Zigbee and Bluetooth low energy, bringing together the key application benefits of both protocols while reducing the wireless subsystem bill-of-materials cost and size by up to 40 percent.
Figure 2: Silicon Labs developed dynamic multiprotocol software for its existing family of wireless Gecko SoC and modules to enable simultaneous operation of Zigbee and Bluetooth low energy.
The dynamic multiprotocol software allows users to commission, update, control and monitor Zigbee mesh networks directly over Bluetooth with smartphone apps, and enable the deployment of scalable indoor location-based service infrastructure by extending Zigbee-based connected lighting and building automation systems with Bluetooth beacons.
Incorporating multiprotocol and multifunction management at the highest levels is important, and Cypress Semiconductor’s unified software tool suite can streamline designs for the Internet of Things (IoT). Their ModusToolbox suite includes the design resources of Cypress’ WICED IoT connectivity libraries and the analog and digital peripherals libraries of its PSoC MCUs within the open-source Eclipse Integrated Design Environments.
The software enables IoT developers to design in the connectivity, processing, sensing, and security functionality they need, leveraging WiFi, Bluetooth, and combo solutions, along with low-power, flexible, and secure PSoC MCUs. Developers can personalize their user experience in the software to meet the unique requirements of their specific development with plug-ins, libraries, and solutions from Cypress partners, as well as from the open source community.
Security is an issue far too few engineers take seriously enough, but part of that was the lack of comprehensive tools. To address this need HCC Embedded released an embedded Extensible Authentication Protocol (EAP) framework to support secure wireless connections for embedded devices. The framework easily extends to include other protocols, and commonly used algorithms including EAPOL, EAP-TLS, EAP-IKEv2, and EAP-MD5 are available immediately.
EAP device authentication supports many types of secure access, and provides a basic request/response protocol framework over which specific security algorithms can be implemented to give developers a way to ensure that IoT devices joining a wireless network are authenticated. The EAP framework is developed according to HCC’s MISRA coding standard, and provides reliability on any embedded target.
Sensing
It is impossible to achieve any level of accuracy and precision without measurement and feedback, and that goes doubly so for an automated system, where any error can result in a catastrophic situation. The ability to detect and determine the nature of objects and surroundings are critical, as well as the other sensory aspects of environmental awareness, motion feedback, and surface determination.
In the case of range-finding, a Time of Flight (ToF) approach is very powerful, using emitting light rather than sound. Compared to ultrasound, ToF provides for a greater range, enables much faster readings, and delivers a greater level of accuracy while still being able to create a solution that is small in size, and low in weight and power consumption. For example, Infineon developed the 3D Image Sensor REAL3 family of highly integrated single-chip imagers for ToF detection to directly address this space. The ability to establish 3D depth data can serve a large number of applications where precise position detection is needed, from factory automation to remote robotics, not even considering the consumer applications.
Going to more of a gestalt vision approach, the Qualcomm Vision Intelligence Platform (Figure 3) is a family of SoCs for the development of smart devices for the IoT, from the home to the street to the factory floor. The platform is anchored by their 10-nanometer process QCS605 and QCS603 SoCs, which include advanced camera processing software, machine learning, and computer vision software development kits, as well as connectivity and security.
Figure 3: The Qualcomm Vision Intelligence Platform comprises SoCs, including the QCS605 and QCS603, for the development of smart devices for the IoT.
This approach is part of the expanding field of Edge Computing. When it comes to complex image-related information, the processing could be done in the cloud, but that takes resources and time. In the Qualcomm Vision Intelligence Platform the camera itself is smart and can decide how to respond to situations based on what it knows, instead of waiting for video data to be sent to the cloud and analyzed. The advantages of edge computing include faster processing, local control, better security and privacy, along with the use of less network bandwidth.
Of course, it is important to also gather data beyond what is capable of being captured by optical and RF-oriented sensor methodologies. One such example is geomagnetic and inertial information, vital to a device’s self-awareness and ability to navigate in space. This applies to robotic and autonomous systems of all sizes and application spaces, but again is most important in mission-critical capacities.
For example, the BMM150 from Bosch Sensortec (Figure 4) is a 3-axis digital geomagnetic sensor for compass applications. The low-power and low-noise 12-pin device comes in a wafer-level chip-scale package (WLCSP) measuring 1.56 x 1.56 x 0.60 mm, making it easy to integrate into most systems. Due to the stable performance over a large temperature range, the BMM150 is also especially suited industrial environments or for supporting drones that must operate in harsh weather.
Figure 4: The BMM150 from Bosch Sensortec is a three-axis digital geomagnetic sensor for compass applications housed in a WLCSP measuring 1.56 x 1.56 x 0.60 mm.
The BMM150 can be used with an inertial measurement unit with a 3-axis accelerometer and gyroscope like the company’s BMI055, along with available sensor data fusion software tailored to the hardware for determining absolute spatial orientation as well as motion vectors with high accuracy and dynamics. The terrestrial field sensor BMM150 is based on Bosch’s high-volume proprietary FlipCore technology.
Input and Action
Automated industrial systems are like any other complex system, in that they must have input, the ability to manage that input, and a means to act. Today’s creators of automated solutions must take into consideration not only the motors and power systems, but also the processors, sensors, and software infrastructure involved. Proper system integration is more important than ever to an optimal solution.
Filed Under: Industrial automation
