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Sensors in Real-time and Edge Computing: Transforming Manufacturing Practices
Sensors in Real-time and Edge Computing: Transforming Manufacturing Practices

May 11, 2022

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While edge computing has been around since the early 2000s, it is only recently that it has gained accelerated traction. They are helping manufacturers collect real-time data from their machinery and equipment, eliminating the need for human intervention for preventive maintenance and monitoring.

The proliferation of smart sensors, combined with rapid advancements in communication and processing capabilities have accelerated the deployment of edge computing in industrial markets. Edge computing has piqued the interest of businesses, especially in the manufacturing and industrial sectors undergoing digital transformations. Recognizing the "edge," therefore, has become vital for driving business success.

Some of the leading application areas where smart sensors and edge processing might be useful include:

  • The temperature of a pump is measured using a standard two-three wire thermal junction in a factory setup. The data is processed remotely, and the pump is then turned off. An edge solution will be able to provide a solution for impromptu pump breakdowns and other issues that result in deferred action.
  • Edge computing can help with the operations in combating and detecting anomalies in plant operations.
  • Edge computing assists manufacturers with a variety of operations for which they would otherwise have to rely on retrofit solutions.
  • In manufacturing and factory units, hazardous areas require a real-time and rapid response to shut down machinery operating therein. Smart sensors and edge processing play a key role here, eliminating the need for human oversight.
  • During the changeover process of a process plant, the neutrality of the substrate is tested. Currently, methods are conducted in offline labs or based on time. Sensorization could help streamline the process flow.

Smart sensor technology, combined with edge computing capabilities, could therefore enable robust signals and data processing, helping drive enhanced business outcomes for manufacturers and plant operators.

Advantages of Edge Computing: Speed, Scalability, Security, and Efficiency

  1. Deterministic approach: When a sensor predicts unscheduled downtime, the system must be predictable and ample to respond to the situation in order to avoid damage. The use of edge computing can also prevent the lag from occurring during the transmission of data over a longer distance.
  1. Cloud cost savings: The output spawned from time-series data is enormous, which makes retaining and handling data in the cloud extremely expensive. Edge computing can assist in the recording, analysis, and summarization of data, hence eliminating unnecessary costs.
  2. Data security and control: Smart sensors and edge processing provide improved data security and control by reducing long-distance data travel. Meanwhile, data handling by different devices may not be as secure as a centralized system, thereby posing security risks. Therefore, an approach to controlling vulnerabilities and mitigation measures is required when developing a system with edge processing.

Sensors for Smart Industries

Electrical signals are emitted by sensors when physical and environmental changes occur. These signals are converted into data after signal processing.  This is accomplished with additional circuitry in a subsystem. These devices are called smart sensors.

Modules for I/O and Vibration Sensors

Smart sensors with MEMS have a wide range of features and are available at a low cost. A vibration sensor, for example, sends signals to signify events like double-tap detection and threshold detection. These features benefit modules for input/output because they receive ready-to-use data.

In the manufacturing industry, motors are a critical component that must be maintained on a regular basis to avoid malfunctions and unnecessary downtime. Smart sensors can be used to regularly monitor the condition of these assets. Sensors will then transmit an event to the I/O controller if the noise level exceeds the threshold, instructing it to act on existing activities such as lowering the RPM, reducing the burden on the motor, or shutting it down. Predictive maintenance technology like this is both cost-effective and infrastructure friendly.

Many smart sensors can encounter items or individuals entering a risky zone. Sensors are intelligent enough to determine an object's speed and arrival angle. When an object or individual enters the perilous zone, the sensor sends an Input/Output signal to the I/O module, which takes decisive precautions and halts the machines and equipment.

Edge Processing: What’s Next?

Whilst smart sensors are a relatively new technology, many sensors on the market today require external encoding because the availability of smart sensors is not pervasive, as well as involves an additional cost. A key trend in the industry is zero-touch sensing: audio, video and olfaction (sense of smell) are examples of these requirements. Companies are experiencing swift, accelerated operational changes, since digitized facilities with edge computing and smart sensors.

Industries can use these technologies to monitor equipment efficiency and use advanced predictive equipment to detect and repair future conflicts, allowing for real-time asset monitoring and greater exposure. The industrial setting is ever-changing, and its resilience is consistent with the growing leveraging of data for driving efficiency and productivity. With the evolution of the edge ecosystem other technologies will also evolve – helping drive all-round business success.


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