Automation

How to enhance automation systems with instrumentation, advanced analytics

Automation can be enhanced in a number of ways whether its through improving process instrumentation or unlocking the power of the Internet of Things (IoT)
By Jack Smith December 8, 2018
Courtesy: CFE Media

Even though they are about different topics, both articles in this issue are about enhancing automation systems.

Regardless of the medium being controlled—flow, pressure, temperature, level—every control scenario begins with the sensor. There is no way to close the loop without it. The cover story in this issue is about how to get stronger readings from process instrumentation. Although its focus is primarily on measuring pressure, the concepts apply across much of the range of process instrumentation. The author explains in detail how pressure sensors develop signals and the issues that can impede that process.

In addition, she also explains the role and operation of the transmitter. “The transmitter takes the raw analog signal from the sensor and cleans it up. Depending on the type of sensor, it might generate a resistance, voltage, capacitance, or some other type of signal in response to the process variable. The transmitter must measure the signal and compare it against the desired range according to how the device is configured.”

Courtesy: CFE Media

Courtesy: CFE Media

The author also discusses what to do with instrumentation measurements from the transmitter. “It may be something as basic as a remote display with simple alarming functions, or a more elaborate platform such as a programmable logic controller (PLC) or a distributed control system (DCS).”

The other article in this issue focuses on how manufacturing, packaging, and logistics companies are unlocking new potential through digital transformation with the power of the Internet of Things (IoT) and advanced analytics. The author proposes three phases to unlocking full digital transformation: visualizing through factory connectivity and data integration; forecasting using predictive production modeling and responsive machine design; and self-regulating data-driven manufacturing and ongoing transformation.

This article appears in the Applied Automation supplement for Control Engineering and Plant Engineering.

– See other articles from the supplement below.

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Jack Smith
Author Bio: Content manager, CFE Media