Emerson Automation Experts - Connecting with the People behind the Technologies and Expertise - Emerson Automation Experts

Rapid Exhaust Pneumatic Valves for Safer Machine Operations

Despite advancing automation, operators in many of the hybrid and discrete manufacturing industries must interact with the machinery and avoid getting injured.

In a Hydraulics & Pneumatics magazine post, Reliable Pneumatics Ensure Safe Machines, Emerson’s Andreas Blume and Dusko Markovic share how technology advancements have helped create safer machine operations. They open describing the perils of some machinery.

The operator holds the open package in the machine with his left hand and seals it by moving an axle with his right. All it takes is a single second of distraction and his hand is caught in the axle.

The operator would likely require: Continue Reading

How to Install a Rosemount Non-Contacting Radar Level Transmitter

Here’s a quick one-minute YouTube video, Rosemount 5408 How To – Mechanical Installation showing the mechanical installation of a Rosemount 5408 Non-Contacting Radar level transmitter.

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Filters-Regulators-Lubricators for Reliable Pneumatics

Hybrid industries manufacturers having a combination of process manufacturing and discrete manufacturing, as well as discrete industries manufacturers, require pneumatic controls in their machine automation. A critical component in reliable pneumatic control are filters, regulators, and lubricators (FRLs).

In a Machine Design article, The 6 Things Engineers Should Know About Pneumatic Filters, Regulators, and Lubricators, Emerson’s Jeff Disbrow provides a 101 overview of FRLs and key considerations for reliable operations.

FRLs, such as the ASCO Numatics 651/652/653 series, provide the air preparation for the:

…valves, manifolds, cylinders, and actuators that control machine motion…

As the Industrial Internet of Things technologies are incorporated into FRLs, these devices can measure:

…critical variables such as flow, contamination, and pressure—using the information for further data analytics and decision making.

Jeff breaks down each of these components for those of us less familiar with the operation of pneumatic systems. FRLs are found:

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Automating Power Generation Startup Sequences

Plant staff at electrical power generating facilities are having to change the way they operate given the increasing amounts of intermittent renewable energy being added to the grid. More startup and shutdown cycles are being required to manage the constantly shifting energy supply to the grid.

In a Power magazine article, Automated Plant Startups Reduce Fixed and Fuel-Related Costs, Emerson’s Doug Morris highlights the importance moving beyond traditional manual startup procedures to improve reliability and efficiency in these demanding conditions.

While automation systems have been controlling power plants for a long time, Doug explains that plant personnel traditionally follow written procedures, and:

…operators typically adhere to a routine of making sure process conditions (permissive conditions) are met, then interact with the site’s automation system, and then proceed to the next step in the startup procedure. Lather, rinse, repeat. At some plants, operators will go through close to 200 manual acknowledgements with their controls as they start up.

Beyond just increased maintenance caused by more frequent equipment cycling:

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Using a High-speed Oilfield Simulator to Enhance Oilfield Automation

Author: Michael Thambynayagam, Emerson Distinguished Contributor

The oilfield is made up of three constituents: the reservoir, overburden, and surface facilities. Data are acquired from these constituents and archived continuously. The information is continuously used to construct the model of the oilfield that evolves in real time. A prerequisite to oilfield automation is the ability to seamlessly connect real-time streaming data from sensors to simulation and analytics. Central to such a mission is a high-speed oilfield simulator. The simulator must be capable of mathematically modeling the oilfield as one entity. Combined with built-in AI, it enables automation of both optimization and history matching. The model of the oilfield evolves in real time, garnering predictive capability with each update from the history-matched data. Continue Reading