Representative End User Clients
Representative Automation Clients
Representative Software Clients
Overview
Data integrity of intelligent sensors has been a persistent problem in the process industries for decades. The ubiquitous spread of intelligent field devices, control valves, and analytical equipment held the promise of better management and 
maintenance of these devices, but – instead – created a huge data management problem. Sensor data almost always show inconsistencies across different applications that rely on their data. There is no “single version of the truth” that provides the true state of the sensor in a consistent manner across applications.
Plant asset management systems (PAM), distributed control systems (DCS), safety instrumented systems (SIS), and engineering applications like Hexagon’s PPM division’s Intergraph Smart® Instrumentation frequently show a different picture of what the intelligent device looks like. These inconsistencies affect change management, device maintenance, overall plant performance, and can increase cybersecurity risk. Poor sensor data management is also a huge contributor to unplanned downtime, which ARC estimates costs the process industries over $1 trillion a year.
ARC Advisory Group recently met with PAS to discuss the company’s new solution to solve the sensor data management problem. To the best of ARC’s knowledge, the PAS Sensor Data Integrity solution is the first vendor-independent solution to manage and provide consistent sensor data integrity across all applications in the plant or enterprise.
Why Intelligent Devices Create a Data Integrity Problem
Most field devices in today’s process plants are intelligent, with onboard microprocessors and bidirectional communication capabilities. ARC estimates that over two-thirds of the total installed base of process field devices are 
intelligent. With their onboard diagnostics capabilities, these devices offered the promise to improve device reliability and availability. While many end users have realized this promise, most have found that intelligent devices also create a huge data management problem, creating myriad inconsistencies in device data across applications.
When a system is designed, an application like Smart Instrumentation from Hexagon’s PPM division is typically used to capture the baseline configurations of intelligent field devices and control valves. However, during system installation, commissioning, and checkout, other procedures are executed on those devices that can result in a change in configuration, additional devices, and more. During the device lifecycle, field technicians perform routine maintenance, adjusting for sensor drift, updating device firmware, and other procedures. Many technicians use handheld devices to execute these procedures, and the proper change management logs are not captured in the plant asset management system, DCS, SIS, or other systems.
To date, no single mechanism has been available to rationalize the inconsistencies between the field device data shown in these different sources and applications. These applications don’t all talk to each other and dynamically update and rationalize the relevant data. The Smart Instrumentation application, for example, will still have the “as-built” information, which is likely to be different than the information that resides in the devices themselves, the DCS, SIS, PAM system, and other systems.
Why We Need Data Integrity at the Sensor Level
This is more than just a data management problem, it’s a data integrity problem. Not knowing what you have installed or the current firmware version and lack of visibility into change management records quickly becomes a huge problem since most process plants have thousands of intelligent sensors and actuators installed across multiple functional areas. It also creates a potential cybersecurity risk due to poor asset inventory and lack of an accurate record of firmware updates or other cybersecurity-related procedures needed to identify and address vulnerabilities.
Scope and scale are also issues. The number of sensors in an average process plant can easily reach into the thousands, and this number is increasing significantly with the accelerated deployment of less expensive, more easily connected IoT and wireless sensors. Add to that the number and diversity of vendors, the varied model numbers and versions, and the need to properly configure diagnostic data, and the scope and impact of the problem becomes even more challenging.
The Cost of Poor Data Integrity
Lack of data integrity also greatly increases the risk of unplanned downtime due to a failed sensor or valve. Unplanned 
downtime is probably the single biggest avoidable cost for the process industries. Many field devices, particularly valve actuators and positioners, control critical plant processes. Without an accurate picture of how that sensor, actuator, or positioner is configured and its associated maintenance and diagnostic data, it’s easy to miss an impending device shutdown or malfunction. ARC estimates that unplanned downtime costs the process industries more than $1 trillion annually worldwide. At the very least, poor sensor data integrity degrades plant performance, results in poor diagnostics management for smart sensor deployments, and causes delays in startup after maintenance turnarounds.
Many unexpected plant shutdowns can be traced to a failure in a critical field device or, as is more often the case, a control valve. Process safety systems are a good example of this risk. Safety systems rarely fail. Logic solvers almost never fail, and when a safety system does fail to perform its task, it’s almost always because of a failure in the safety-instrumented field device or control valve. The safety instrumented systems’ world also has its own set of standards and data reporting requirements for the health of SIS devices, such as periodic proof testing for SIS valves.
PAS Introduces Sensor Data Integrity Solution
End users have tried to tackle the field device data integrity problem manually, using spreadsheets or other tools. This is typically a time-consuming, costly, and error-prone process. To date, there has not been an effective, vendor-neutral solution for sensor data integrity that can rationalize sensor data across multiple applications and systems from a wide range of suppliers. We recently met with PAS to talk about the company’s new Sensor Data Integrity solution, part of the PAS Automation Integrity™ suite of applications.
You may know PAS for its presence in the alarm management, safety management, and system configuration management markets, but the company has greatly expanded its offering. Its current mission is to provide overall integrity for process operations, from cybersecurity to safety management, configuration management, and asset management. PAS solutions are designed to improve the management of Industrial IoT, smart sensor, and traditional field sensor devices by centralizing visibility and configuration management. In 2020, PAS was acquired by Hexagon and operates within its PPM division, a leading industrial engineering software provider.
The vendor-neutral Sensor Data Integrity solution works with both traditional process field devices and newer, Industrial IoT-connected sensors alike to provide a single central source of sensor data visibility and configuration management. It can aid with new sensor discovery and configuration management and be used to detect errors automatically. The solution can automate the detection of sensor configuration errors or issues and cross-check parameters like ranges and units against various databases. It also allows end users to evaluate large sets of sensor data quickly.
Sensor Data Integrity Enables Better Device Templates
Many end users have adopted a practice called device templating, where they create known good configurations for intelligent devices that are to be used throughout a plant or the entire enterprise. Many companies use these templates to ensure consistency of configuration and deployment of intelligent devices, with specific configuration templates for supplier-specific devices or certain types of devices. Sensor Data Integrity can also be used to create templates to define known good configurations for intelligent devices and identify devices that don’t conform to specific templates.
Better Sensor Data Integrity Reduces Cyber Risk
Since most sensors in today’s process plants are intelligent, with on-board microprocessors, firmware, and unencrypted bidirectional communications; poor visibility and inconsistent process sensor data can increase cybersecurity exposure and risk. The risk is compounded and the threat surface expanded further by the wide variety of Industrial IoT sensors that are currently being deployed in today’s plants.
Accurate asset inventory is fundamental to the cyber risk profile and risk reduction. Sensor Data Integrity helps reduce risk by providing a more accurate picture of asset inventory. Data like sensor manufacturer, model, rev number, software, and firmware versions are all accurate and traceable. Since Sensor Data Integrity is part of the PAS Automation Integrity suite of applications, the information can be readily shared with the other applications as well as with the PAS offerings for cybersecurity, including the PAS Cyber Integrity™ suite. This includes solutions for asset inventory management, vulnerability management, configuration management, backup and recovery, and other functions. Combining the functionality of Sensor Data Integrity and Cyber Integrity allows end users to gain visibility into how sensors expand the OT cyber-attack surface.
For sensors and other intelligent devices, the Internet of Things (IoT) is a double-edged sword. Certainly, digitalization and connectivity simplify installation and streamline the collection and forwarding of data. However, these same advantages also make it easier for hackers to use sensors to break into networks and cause harm. This is especially true in the industrial sector where hackers could potentially threaten production, create safety and environment incidents, or steal intellectual property.
Making Better Data Available to a Wider Number of People
Many different workers with different roles interface with intelligent and IoT devices, but the applications they use don’t always talk to each other. Sensor Data Integrity makes this consistent data available to a wide range of workers in the plant or enterprise. The process control and instrumentation teams will find this information valuable, but it is also valuable to engineering managers, plant managers, reliability teams, chief digitalization officers, IT/OT convergence leads, and SOC directors and managers.
Improving Reliability and Availability at the Sensor Level
Sensor Data Integrity is also designed to increase reliability and availability at the device level. Better and more consistent data can reduce sensor configuration and drift errors by 40 percent or more. The solution also allows users to automate the detection of sensor configuration errors. Users can also cross check parameters like ranges and units against various databases, as well as trace and visualize how sensor signals traverse through various systems. Plant asset management systems (PAM) can also leverage the data to support instrument calibration.
Faster Installation, Checkout, and Turnarounds
Projects typically experience sensor-related cost overrun. Delays in commissioning and checkout can be significant. Having a consistent dataset and good templates for smart sensors can help get it right the first time and checkouts loops faster. Even if a fix is required, it’s much less expensive to do this before startup.
How a Major Oil & Gas End User Applies Sensor Data Integrity
ARC recently had an opportunity to interview an end user at a major oil & gas company that already uses the PAS Sensor Data Integrity solution to help overcome a number of related challenges.
Like many end users, this company must synchronize multiple sources of instrument and control system data, particularly for its large installed base of HART-compatible field devices. Also like many end users, this company has field maintenance technicians that go out into the field with handhelds, making changes and applying updates to field devices. This results in different device configurations showing up in the in DCS, SIS, and PAM systems.
While the company encourages its maintenance and engineering groups to use asset management systems to keep everything synchronized, they still encounter scenarios where the engineering range for devices is different than what is reflected in the control system or safety system. At the same time, the company wants to gain maximum value from asset management diagnostics. This requires consistency in configuration of device alerts.
The company has worked extensively on device and asset management templates to set up and maintain some level of consistency in instrument and control valve device and equipment alerts. Control valves, for example, can have several hundred diagnostic parameters. Determining the best configuration for asset management diagnostics and rationalizing this data across different systems involves a lot of manual work. The company previously tried to address this problem by manually entering data into an Excel spreadsheet, but found this to be a burdensome and costly process involving lots of manual work.
As we learned, the end user found it relatively easy to deploy Sensor Data Integrity into its engineering and maintenance work processes and now uses the solution to extend the existing capabilities in those two groups. Note that the company had already deployed both PAM systems and PAS’ Asset Integrity applications, making the deployment of SDI an extension of an existing toolset (rather than an entirely new deployment), which helped reduce training and other associated costs. The company has developed an exception-based action list to ensure that people have consistency across systems, and the deployment of SDI was used to create that exception list.
Conclusions
Certainly, between the proliferation of both intelligent process sensors, control valves, and other intelligent field devices and increasing use of low-cost IIoT-connected sensors in industrial process plants, the sensor data management challenge will only get worse over time. End users should avoid doing the manual, labor intensive process of rationalizing sensor data across applications. Users should seek a solution, such as PAS Sensor Data Integrity, that provides a vendor-independent solution for sensor data and integrity management that works across multiple applications and systems.
ARC Advisory Group clients can view the complete report at ARC Client Portal
If you would like to buy this report or obtain information about how to become a client, please Contact Us
Keywords: Sensor Data Integrity, Cybersecurity, PAS, Plant Asset Management, Intelligent Field Devices, ARC Advisory Group.