Level Measurement Intermittent Power Protection

Let’s end the week with a quick look at how some instrumentation protects against intermittent power outages.

This short, 1-minute Youtube video, How to Secure Safe Operations During Power Outages shows the power reserve function of the Rosemount 5408 level transmitter which ensures safe operations even during power outages.

Visit the level measurement area on Emerson.com for more on the best technologies for your applications. You can also connect and interact with other level measurement experts in the Measurement Instrumentation group in the Emerson Exchange 365 community.

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Partial Stroke Test for Final Elements—Diagnostic Coverage Factors

Emerson's Riyaz Ali

Author: Riyaz Ali

Partial stroke test is one of the viable means to check mechanical integrity of Final Element of Safety Instrumented Function (SIF) loop. Generally, end users struggle on question of credit of PST for improvement in SIL (Safety Integrity Level).

IEC 61508 and IEC 61511 define diagnostic coverage factors (DCF), but do not provide a prescriptive way to estimate the number applied in real process applications.

Diagnostic coverage (DC) as defined in IEC 61511 is ratio of the detected failure rate to the total failure rate of the component or subsystem as detected by diagnostic tests. Diagnostic coverage does not include any faults detected by proof tests.

For safety applications the diagnostic coverage is typically applied to the safe and dangerous failures of a component or subsystem. For example, the diagnostic coverage for the dangerous failures of a component or subsystem is DC = λDD / λDT , where λDD is the dangerous detected failure rate and λDT is the total dangerous failure rate (Dangerous Detected and Dangerous Undetected).

Let’s look at factors to be considered in estimating diagnostic coverage factors, DCF’s, required for calculating Probability of Failure on Demand (PFDavg) for the “final control element” when an online partial stroke test is initiated by the digital valve controller: Continue Reading

Digital Twin for Digital Transformation

Digitalization has brought a wealth of streams of data. Data by itself does nothing to improve performance but channeling this flow into analytical tools and revised work processes is a basis for undergoing a digital transformation.

A new white paper, Emerson Digital Twin: A Key Technology for Digital Transformation, highlights the important role of digital twin technology in this transformation. The white paper opens with a definition:

The Digital Twin is a representation of the physical plant assets (i.e. process equipment, instrumentation and controls) and the processes that take place within them (i.e. chemical reactions, separation processes, heat transfer).

The Emerson approach has some unique characteristics to this technology: Continue Reading

Driving Manufacturing Performance Gains with Cloud-based Optimization

The U.S. National Science Foundation (NSF) is:

…an independent federal agency created by Congress in 1950 “to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense…”

In 2006, the NSF funded a research project to create a step change in the performance of US manufacturing. The grant was won by professors from the University of Texas here in Austin and University of California at Los Angeles (UCLA).

Emerson's Pete Sharpe

Emerson’s Pete Sharpe joined senior members from other automation suppliers, manufacturing companies and academic institutions for a three-day workshop with the challenge to generate ideas that could create a step change in manufacturing efficiency on the order of the Industrial Revolution itself.

What came out of this kickoff meeting was the need to make advanced automation technology more easily accessible to a broader number of manufactures, lots of low-cost sensors, increased use of models, better computing infrastructure and improve skills for manufacturing personnel. From a technology perspective, more measurements and broader use of models throughout the manufacturing lifecycle—design & prototyping, engineering, planning & scheduling, and ongoing optimization and maintenance were needed. From an infrastructure perspective, cloud-based software-as-a-service (SAAS) providers were needed with a focus on manufacturing applications.

A Smart Manufacturing platform was needed to provide common services like databases, connections to plant equipment and cybersecurity. Also, these manufacturing processes needed many more sensors to improve safety, reliability, energy & emissions and production. Easier to add wireless, “lick-and-stick” and disposable measurements were needed.

The vision that came out of this initial study was to develop an open, cloud-based marketplace for manufacturing applications that would have these characteristics: Continue Reading

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Actionable Information with Plantweb Insight

Let’s end the week with a quick 1:48 YouTube video about Plantweb Insight to better analyze and use the data for safe, reliable and compliant operations. Plantweb Insight is enabled by wireless sensors and networks and gives users the knowledge to make effective and timely decisions

The suite of Plantweb Insight applications provide instant access and visibility into plant assets in an intuitive way without the need for training. Analytics built into the software turn vast streams of data into actionable information.

Learn more in the Plantweb Insight area of Emerson.com or connect and interact with other digital transformation experts in the IIoT/Digital Transformation group in the Emerson Exchange 365 community.

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