Using smart instrumentation
All you need to know to deploy smart instruments throughout your processes, and get the highest performance available. The capabilities are there if you put them to work.
Craig McIntyre, Endress+Hauser
The evolution from simple pneumatic to sophisticated smart instruments has been driven by user demands for better performance, easier maintenance, and more uptime. Smart instruments have met these demands and more, albeit with increasing complexity. But once smart instruments are understood and deployed, the payoff is less complexity, better performance, and reduced costs throughout the balance of the process control and information system lifecycles.
There’s an old adage that says one must measure a process in order to control it, and this is just as true today as it was in the past. A corollary to this adage is that trustworthy process measurement information is required so that users feel comfortable enough to risk making tighter control improvements.
For example, let’s say a process requires a minimum flow rate of 10 gpm (gallons per minute). If an operator doesn’t trust the accuracy of the flow measurement instrument, he or she might set the flow to 11 gpm just to be on the safe side, even though the excess flow adds both raw material and disposal costs. With a trusted and accurate smart flow instrument, the operator might feel comfortable reducing the flow to 10.1 gpm, saving money through increased efficiency.
Smart instruments also reduce disruptions by informing plant operators of a current or pending compromise in operation in advance of a total instrument failure. Outright failures are easy to spot with most types of measurement devices, but only smart instruments can detect subtle problems that can generate inaccurate measurements and are often a prelude to failure.
What makes an instrument smart?
The definition of a smart instrument has evolved over the past decades (Table 1). Older dumb instruments were 3-15 psi pneumatic-based devices that performed control via local single-loop controllers. Information was shown locally, often with gauges, and generally recorded manually with pen and paper as a technician made his or her rounds. If data needed to be saved automatically and analyzed, the solution was a local chart recorder.
A small degree of intelligence was next added to instruments in the form of a 1-5, 4-20, or 10-50 mAdc output proportional to the PV (process variable). Once data could be transmitted remotely, it created the possibility of remote measurement, display, and control.
The parallel development of control systems with central processing and I/O introduced more effective means to capture the information produced by these 4-20 mA instruments, scale this information into engineering units, and centrally act on and record the information. Loop-powered instruments then became feasible, making it possible to power multiple transmitters via one current source, often via an analog I/O module.
A major step forward occurred when microprocessors became robust enough for direct installation in field instruments, enabling local digital-based signal processing. This created what might be categorized as the first truly smart instruments, as these devices could process the analog 4-20 mA variable into a digital signal suitable for transmission over a network. The local microprocessor could also manage other tasks at the instrument level, namely calibration and diagnostics.
Now that smart instruments could produce digital representations of the PV and other parameters, fieldbus networks began to emerge. First among them were networks using the existing 4-20 mA signal wiring as the physical transmission media, largely to support handheld calibration device access anywhere on the 4-20 mA current loop. In addition to handheld device access, some distributed control systems became able to host these communications and digitally access the PV along with device diagnostic data.
In time, HART (Highway Addressable Remote Transducer) technology unified the multiple and incompatible vendor-specific networks that were using the existing 4-20 mA signal as a transmission medium. HART was placed into a vendor neutral foundation, and ultimately rose to become the preeminent form of superimposed field device communications, garnering support from most instrument and control system providers. As a result, a smart instrument came to be defined as one that supported HART.
But HART was limited, and higher performance was needed to use the digital value of PV for real-time control and to deliver more information to remote hosts. As microprocessors became more powerful, smart instruments gained intelligence and soon were capable of producing large amounts of valuable information in addition to the PV, further spurring the need for more powerful networks.
Digital networks specifically designed to link instruments to automation systems began to emerge, chief among them Foundation fieldbus H1 and Profibus PA. These platforms abandoned the well-established 4-20 mA output and leveraged enhanced electronics and software standards to increase speed, enhance diagnostics, and add functions such as embedded local control. These two, as well as others, achieved recognition by standardization bodies and became embedded communication options in smart instruments produced by multiple vendors.
More recently, the advent of robust and proven wireless technologies resulted in the development of vendor-specific and standards-based solutions focused on communication of field device information to and from remote access points. The HART Communication Foundation developed backwards-compatible wireless technology and gained standardization recognition via IEC 62591. The ISA SP 100.11a committee is also moving toward an approved standard for wireless instrument communications.
Today, a smart instrument is generally defined as a device that includes one or more digital network communication options. Because provision of digital communications requires a microprocessor, a wide range of other capabilities are also typically provided with a modern smart instrument.
Smart instrument capabilities
Success of a measurement is built on the proper type of instrument technology correctly installed in the right application. Aside from input from its direct sensors, a dumb instrument can’t perceive any other process information. But smart instruments have diagnostics that can detect faults in the installation or problems with the application, each of which could compromise measurement quality and/or reliability. Smart instruments can also respond to inquiries or push condition information to the automation system, as well as to other networked platforms.
One of the keys to unlocking the information produced by a smart instrument is the operator interface. This interface can be the instrument’s local display, a local handheld HMI (human machine interface), or a networked HMI. Information can more readily flow between a technician or an engineer and the instrument with an HMI as opposed to a local display.
Multivariable instruments that simultaneously measure several PVs via multiple internal sensors and communicate data digitally or wirelessly are the highest form of smart instrument. An example is a Coriolis flowmeter that measures and/or calculates mass flow, viscosity, density, temperature, and totalized flow.
Some smart instruments equipped with communications protocols such as HART 6+, WirelessHART, or Foundation fieldbus H1 can exchange PVs directly among similarly equipped instruments. These PVs are then used to perform added calculations in the field without an automation system or an additional calculation agent. For example, a vortex flowmeter can interface with a pressure transmitter and produce corrected energy flow, or two gage pressure transmitters can be linked to produce a differential pressure value.
The Internet age has brought about a wide range of connectivity, information management, and access options. Although many of these technologies have been adapted to automation platforms such as programmable logic controllers, programmable automation controllers, and distributed control systems, security and safety concerns must be addressed before connecting critical process instruments via the Internet or related technologies.
In part because of security and safety concerns, the great majority of installed instruments still provide the PV to the automation system via the venerable 4-20 mA signal, which is rescaled and managed within the automation system. But digital communication systems such as Foundation fieldbus, Profibus, and EtherNet/IP, and wireless mesh networks like WirelessHART, are increasingly providing digital PVs from the instrument directly to automation platforms, eliminating the need for the 4-20 mA signal and its associated I/O infrastructure.
PVs defining energy usage, environmental reporting, supply chain monitoring, and process unit monitoring are typically not part of the automation system’s real-time control schemes—and so these variables can be delivered directly from smart instruments to stakeholder databases via IT connected access points, greatly simplifying the automation and information system architecture.
Beyond the process variable
But smart instruments can do a lot more than just measure and deliver the PV to multiple hosts. One or more engineered PVs, basically raw analog values that are scaled, linearized, and/or otherwise conditioned, along with instrument status data are created within a smart instrument. These engineered PVs along with device data are communicated digitally via a fieldbus or wireless network to the automation system and/or to other networked access points.
Table 2 lists some of the key data points delivered by smart instruments available currently, and details the benefits that can be derived. For example, instrument status data can indicate a data quality fault or warning. Engineering or maintenance tools can then be used locally or over the network to drill down, assess the problem, and determine a solution. Possible remedies could include recalibration, configuration change, or instrument replacement.
Instrument measurement outputs are assessed against calibration standards to confirm the quality of the measurement information. This is accomplished via calibration against a traceable standard. Internal self-test diagnostics within many smart devices, such as Coriolis flowmeter tube dynamics checks, can indicate if verification of the calibration by a traceable means should be performed. Some smart flow instruments provide National Institute of Standards and Technology traceable verification tools to support ISO 2001 Chapter 7.6 traceable verification and calibration requirements.
Manufacturers of smart 4-20 mA instruments that can be used when designing a safety instrumented system (SIS) are increasingly following IEC 61508 device design, manufacturing, and lifecycle management guidelines. Safety system designers often adhere to IEC 61511, ISA, and ANSI 84.01-2004 safety system lifecycle management standards, in part by using IEC 61508 certified instruments with internal diagnostics.
These certified instruments can help designers achieve the required Safety Integrity Level (SIL) for the process. Smart SIL instruments can also communicate diagnostics information to instrument condition monitoring tools to help with instrument maintenance.
As smart instruments proliferate, the diagnostic information has increased in volume and complexity, requiring standards for identifying error and diagnostic codes. One part of this standardization effort is recommendation NE107 from NAMUR that suggests structuring diagnostic information from smart instruments into five standard status signal categories (see Table 3).
Self-monitoring and error diagnostics within instruments that follow NE107 separate and group the diagnostic information into actionable indications. This cuts complexity and reduces the training required for operators and technicians, contributing to improved safety and instrument availability.
Other tools to standardize smart instrument data delivery are standards that define what each data point should look like in terms of descriptors and terminology. The two main standards currently in use for this purpose are the Electronic Device Description Language (EDDL) and the Field Device Tool (FDT).
As instruments evolve to transmit large amounts of data digitally at high speeds, they become truly intelligent, delivering more benefits to users along with simpler deployment and operation.
Smart to intelligent
Instruments have advanced from dumb to smart, and true intelligence is on the near horizon. Expect instruments of the future to have multiple communication channels, each one with built-in security, much like a present-day Ethernet managed switch. These channels will be managed with IP addressing and server technology, allowing the instrument to become a true data server.
A high-speed channel will be used for transmitting the PV to a real-time controller, and this channel will take priority over all others in terms of the instrument’s communication resources. Other communication channels will be used to link the instrument directly to applications such as process monitoring, equipment monitoring, environmental monitoring, energy management, asset management, predictive maintenance, and advanced diagnostics. This direct link will bypass the real-time control system, simplifying overall automation and information system architecture.
Industrial wireless standards beyond WirelessHART and ISA100.11a may develop to address user requirements such as compliance with NAMUR NE124. As users become more comfortable with wireless as a mainstream solution, intelligent instrument information will increasingly be directed to wireless access points, which will in turn be integrated directly into control or IT network data servers.
System designer and end-user frustration with complex integration issues is forcing the major instrument manufacturers and fieldbus protocol organizations to agree on an integrated Field Device Integration (FDI) specification. This FDI specification will consolidate the existing EDDL and FDT specifications, and should result in a truly universal field device integration scheme to connect nearly any field device over any fieldbus network.
Fieldbus-based safety process instruments will come into wider use, as instrumentation is now being developed to meet safety-relevant recommendations like NE 97 and standards like IEC 61508-2. Safety-certified instruments will work in tandem with field bus safety protocols such as CIP Safety, Foundation fieldbus SIS, and PROFIsafe.
Combining all of these advances will result in a truly intelligent instrument that can be integrated easily into the automation and information systems of the future. This will make it practical for users to realize all of the advantages that smart instruments offer: better process control, higher efficiency, lower energy use, less downtime, and higher quality.
Craig McIntyre is chemical industry manager for Endress+Hauser.
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