Transform to Valve 4.0: Digital Control + Analytics

Imagine, receiving a notification on your phone when a control valve is underperforming or when failure is predicted by analytics. Or any time being able to open a dashboard showing the health of all your control valves, and other instrumentation. Or a business model where a factory control valve expert monitors your valves for you and sends you a periodic report recommending which valves need overhaul and what should be done. Then Augmented Reality (AR) or RFID guiding you to the location of the valve. And even the SME remotely assisting you fixing the issue step-by-step in a handsfree live video call. This is the vision of digital transformation and Industrie 4.0 for control valves. Sure, anyone can rattle off a list of all the technologies above. But let’s take a detailed look at the readymade solutions available. A poorly designed, installed, or maintained control valve will affect plant availability, product quality, and energy efficiency. So what is the best way to digitally transform control valve management? Here are my personal thoughts:

Predictive Valve Analytics

Just like pumps and compressors, valves are mechanical equipment and therefore subject to wear and tear. Control valve problems can be related to design issues such as sizing, or installation issues, and maintenance issues. Because valves are installed in line with the process, removing them for service is time consuming and costly. Conversely, not pulling out a valve which is in good condition for overhaul can save precious time and a lot of money. Therefore control valve performance and condition must be monitored to predict problems. For pumps, compressors, and other equipment types you must install many sensors and bring the data back to a server running equipment analytics software. For valves it is much easier.

Travel deviation is a useful indicator (symptom) of many control valve problems. Travel deviation means the valve (stem) is not in the position called for by the controller output (setpoint for the valve). Travel deviation is incorrect valve opening and is caused by sluggish or limited valve travel due to low regulator pressure, filter plugging, friction, or jamming. The incorrect valve opening results in incorrect flow or pressure thus affecting the process.

Travel deviation is a useful indicator of many control valve problems.

Analytics for a control valve don’t have to be as complicated as installing pressure sensors upstream and downstream of the valve, or an inline flow meter, and use general purpose data analytics with machine learning to try to build your own analytics models to detect travel deviation caused by underlying issues or clean 10 years of historical data to train an AI algorithm. And the analytics may not be as straight forward as it first appears, so with general purpose data analytics not trained and built on a sufficiently large dataset and maintained some problems may go undetected and there may be false positives for others. It may only detect travel deviation, not other failure modes, and will not pinpoint the cause. That is, the approach which works in some other use cases may not be the best fit for control valves. Moreover, you need finer granularity diagnostics than “travel deviation”; and there are other valve failure modes you want to be able to predict. There are other use cases where machine learning and AI are applied.

The most interesting fact is that a better way to do control valve analytics is to use a control valve positioner with built-in direct sensors for position feedback and other variables, and embedded valve analytics (diagnostics) and readymade software that eliminate the need to recreate valve diagnostics in general purpose data analytics software.

A modern control valve positioner has built in sensors that automatically collects the raw data required by the predictive valve analytics. Additional external sensors are not required. Built-in sensors include:

• Valve stem position
• Supply air pressure
• Output air pressures (2)
• Temperature
• Internal pneumatic relay position

The most important valve analytics is in-service diagnostics; which is non-intrusive and diagnoses the valve continuously while the valve is controlling the process; without disturbing the process. A key is that control valves are constantly moving. By monitoring these movements continuously software can diagnose health and performance. There is no need to fully stroke the valve. The large number of sensors enable more predictive and more precise analytics. The raw data first feeds into the predictive analytics embedded in the valve positioner. Because the sensors are built into the positioner the data update can keep up with the fast dynamics of a control valve movements; another reason why analytics in the valve positioner performs better. You can say it is a case of extreme edge analytics. In-service valve diagnostics includes:

• Travel deviation (opening)
• Supply pressure (regulator, filter)
• Actuator pressure imbalance
• Air leak (fittings, pipe/tube, actuator)
• Valve friction / deadband (deteriorated packing)
• Limit cycle (tuning)

Descriptive Analytics and Prescriptive Analytics Software

The valve diagnostics is not just detecting “anomaly” but distinguishes between many failure modes (descriptive analytics) indicating probable cause, as well as providing recommended action (prescriptive analytics).

Valve analytics is displayed in a purpose-built ready-made valve analytics app. The user interface of the software is built by valve engineers for valve engineers. Evolved based on feedback from users over many years. You don’t need to be a data scientist to use the software since the underlying analytics algorithm is hidden from the user. I&C engineers can use this software.

For instance, if friction which will lead to stiction/stick-slip, or dead band, starts developing for the valve this is detected by the positioner. Similarly, if the valve response time starts getting poor this will trigger a travel deviation alarm. Looking at actual valve position trend you can see limit cycle oscillations; and from the frequency you can tell if it is due to positioner tuning or control system tuning. The positioner cycle counter also helps with limit cycle detection.

There is additional analytics which strokes the valve and therefore can only be done when the process is not running, such as when the unit is shut down.

Don’t leave your valve diagnostics app in the CCR or workshop where it is not used. Make sure it is deployed in an architecture such as with the server at level 3.5 of the enterprise architecture, such that it can be accessed from office desks for ease of use. If analytics can only be accessed from a dedicated workstation in another room or building, it will fall into disuse.

That is, a modern control valve positioner is part valve control and part valve analytics.

2nd Channel Digital Communication

Thanks to the digital valve positioner the control valve is fully instrumented. Each valve might have 5 sensors on it. These sensors continuously monitor movement, pressure changes, and temperature of the environment the valve is operating in. In one day each valve may produce 30 MB of data. Thanks to onboard analytics you don’t have to store it all.

A valve may produce 30 MB of data each day

The valve diagnostics is digitally communicated from the valve positioner to the valve analytics apps on a “second channel”. This 2nd channel is not separate wires. It is the same wires as the valve setpoint (controller output). In the case of a system built on 4-20 mA as primary channel, the 2nd channel is HART, possibly over WirelessHART. In the case of a system built on FOUNDATION fieldbus, both the primary channel and 2nd channel are Fieldbus; the primary channel is using publisher/subscriber (pub/sub) communications for the setpoint and feedback and the 2nd channel is using client/server communications for configuration and diagnostics. Similarly, future Ethernet-APL will also use pub/sub for real-time valve setpoint and position feedback, but client/server for diagnostics, configuration/setup, calibration, internal variables, and identification.

HART Communication

Some very old control systems do not support HART in their 4-20 mA AO cards. In this case you can either use a HART multiplexer (MUX) to tap the HART communication into the valve analytics software, or you can fit WirelessHART adapters on each control valve. The second option is usually easier but requires that the plant has a WirelessHART infrastructure. But these days many plants already do. Older control systems may also a require a HART output filter (impedance) to be installed on the AO card for the HART signal to not be affected by the AO card. Safety barriers used with MUX must support HART communication. Lastly, make sure the 4-20 mA wiring is free from noise and installed as per HART guidelines.

Position Feedback

When doing valve analytics, don’t assume the actual valve position is the same as the valve setpoint (output from the control system). Many issues cause travel deviation so valve may not be in the position it is supposed to be. Therefore, actual position feedback from control valves is a very important measurement. Make sure to use valve positioners with built-in position feedback, or worst case use a separate position transmitter. Most digital positioners have built-in position feedback. Position feedback is easy with fieldbus valve positioners since the communication is already established for the valve setpoint, you can simply start using the actual valve position feedback as well to make the most of your valve positioner.

On-the-Go Valve and Instrument Management

Since you are not always at your desk, maybe you are away from your desk most of the time, you can also get an on-the-go at-a-glance overview of the health of your valves and instrumentation on a mobile Intelligent Device Management (IDM) app with HTML5 web-based user interface on your phone or tablet. You get status overview even when you are away from your desk; outside in the plant, in the workshop, instrument lab, or working from home. Valve experts working from home can identify the tasks to be performed by the onsite crew.

Note: this is a detail instrument dashboard specific to instrument engineers and technicians. This kind of dashboard is different from the higher-level kind of operational dashboards for overall plant KPIs covered in previous essays.

From the instrument dashboard you can zoom into ever greater level of detail; list of devices, list of issues in each device, and lastly the diagnostics and recommended action for each issue.

Mobile Notifications

You don’t have to look at the instrument dashboard all the time. If analytics predicts a problem with a valve, a notification is sent to your mobile device such as phone or tablet to get your attention. Notifications are configured to route to the persons responsible, not to everyone. That is, it doesn’t send a notification of pending valve problem to everybody; only those that can do something about it.

Digital Reporting

If you spot something of interest while in the plant, you can open the message app on your hazardous area approved phone selecting the tag from a dropdown list, set the priority, type in a short message, and take a photo and attach for clarity. The message automatically makes its way to the people responsible. You don’t have to remember to do it later. This saves time and drives continuous improvement: kaizen. Since the message is digital, it is also searchable. This is digitization of work practices.

IIoT-Based Connected Services

If you don’t have time or enough experts at site to review the valve diagnostics, you can subscribe to (Industrial Internet of Things) IIoT based Connected Services. This means the valve data collected by the valve positioner and the real-time diagnostics information from the real-time edge analytics embedded in the positioner are sent to the next level of analytics in the cloud. A valve SME in another location extracts a monthly report summarizing the health of the valves and your plant and lists the valves which need your attention, with description (descriptive analytics) and recommendation (prescriptive analytics). This way you get not only analytics, but the know-how of a human.

Industrial Auto-ID by Industrial RFID

Finding a particular control valve among many other valves can be difficult. Particularly in an older plant where the tag plates for many valves may have dropped off, are damaged to the point they are unreadable, or have been painted over. And, you need positive ID of the valve before working on it. There are two new ways to locate equipment like control valves in a plant. One is Radio Frequency IDentification (RFID) tags. You sweep the immediate environment from a distance with the RFID reader and pick the tag from the list of nearby tags which now appears on your hazardous area approved tablet. As you sweep again and move closer, the signal strength bar tells you when you home-in and have found the right control valve. A positive identification even though the tag plate is missing and the nameplate is painted over. This saves time and you can continue with confidence knowing work is done on the correct valve. Because the RFID tag has on-chip valve data storage. the tablet does not even need a network connection to display the data.

Remote Assistance

Sometimes you need outside help with a control valve but can’t wait for expert to travel to the site. If the plant has Wi-Fi infrastructure in the field you can attach a hazardous area approved wearable tablet to your helmet; a video camera and display. You join a regular live video call with the valve vendor which sees what you are looking at for easy collaboration. The SME guides you step by step to confidently resolve the issue and can also share documents on your helmet display to make sure you get the job done right the first time. Problems are resolved faster.

Augmented Reality (AR)

The other way to quickly find a piece of equipment like a valve in a plant is using Augmented Reality (AR). AR is an app that runs on your mobile device like a hazardous area approved phone or tablet. The mobile device needs a network connection for the data; either Wi-Fi or data plan. In a plant full of steel, a well-engineered Wi-Fi network works best. You select the valve tag in AR and it will give you direction to the valve – a little bit like a video game. This is digitalization of standard operating procedures.

The AR app also displays important valve information; status, actual valve position, prescriptive and prescriptive diagnostics, even guides you to the junction box it is connected to. All of this available by tapping on the screen. No need to radio the CCR. This saves time. That is, you get the information, self-service, without unnecessarily disturbing anybody. The AR app gets the actual valve position and diagnostics from the positioner through the control system and analytics over the Wi-Fi connection, not direct.

ERP/CMMS Integration

Once analytics predicts an issue with a valve, action must be taken. Therefore a workorder ticket is issued to the CMMS/ERP system. The maintenance planner accepts and releases the workorder which the maintenance technician in the field receives on their tablet through the CMMS/ERP web browser interface. After finishing the job the technician closes the workorder on the tablet. These are the new digital ways of working: new digital Standard Operating Procedures (SOPs). Therefore, the predictive equipment analytics at level 3 (L3) must connect to the CMMS or ERP system at level 4 (L4) of the enterprise architecture ISA95/Purdue reference model.

There is no need to merge the IT and I&C (“OT”) departments to integrate the analytics with the CMMS/ERP, they just need to collaborate. This is made easier when the integration between Digital Operational Infrastructure (DOI) and the ERP is made through a standard off-the-shelf software rather than through custom programming.

NAMUR Open Architecture (NOA)

As work practices around the plant are digitalized it is important to maintain the robustness and safety of the existing DCS for core process control. Instrumentation & Control (I&C) engineers achieve this by deploying the new Digital Operational Infrastructure (DOI) for monitoring and optimization as a separate second layer of automation on the side of the DCS. That is, the DCS and DOI are two independent systems; yet connected using open interfaces to exchange information based on the NAMUR Open Architecture (NOA) for Industry 4.0. NOA does not define the components inside the DCS or DOI, but rather the interface between the DCS and the DOI. The DCS-DOI interface is mostly based on OPC-UA with verification of request and data direction control. For instance, main IDM may be integrated as part of the DCS and changing device configuration is possible from these full featured clients, while the DOI side of the IDM may be a web-based read-only client for diagnostics as explained above, not permitted to change device configuration. Most valve and instrument diagnostics, particularly predictive diagnostics, is of no interest to the operators at the DCS console, so it is important this information instead reaches those that can do something about it. NOA includes a second channel interface for instrumentation and valve diagnostics over HART, unscheduled Fieldbus H1, or acyclic PROFIBUS-PA communication. In the future these instruments will use Ethernet-APL. This 2nd channel use corresponding HART-IP, FF-HSE, and PROFINET-IO enabling EDDL files to be used to fully access all the information in field instruments.

Digital Valve

The Fourth Industrial Revolution (4IR) means work practices and automation going digital. Digital valves result in greater process availability and higher control loop performance for higher product quality and energy efficiency. Start by upgrading to digital valve positioner for all control valves. Get the purpose-built valve analytics software. Your I&C engineers can work with the automation vendors to do this. Plan for how the valve positioners will be digitally integrated; the sort of thing system engineers are very good at. If not already digitally integrated with the DCS, wireless adapters are probably the best way to go. You don’t have to upgrade all positioners at the same time. Start with the most critical control valves. Engineers in plants know where the issues are, when the upgrade can be made, and thus where to start. When selecting digital positioner, make sure to pick a model which provides position feedback, either as 4-20 mA or real-time digital fieldbus, plus the required diagnostics like friction and deadband. This should also include valves on package units with local PLCs, not just those connected to the main control system. Forward this essay to your I&C manager and schedule a meeting with your valve team. And remember, always ask for product data sheet to make sure the product is proven, and pay close attention to software screen captures in it to see if it does what is promised without expensive customization. Well, that’s my personal opinion. If you are interested in digital transformation in the process industries click “Follow” by my photo to not miss future updates. Click “Like” if you found this useful to you and “Share” it with others if you think it would be useful to them.