How to Close the Operator Competency Gap in Process Industries

How to Close the Operator Competency Gap in Process Industries

This guest blog post was written by Martin Ross, product manager for UniSim Competency Suite at Honeywell Process Solutions. This is part two of a two-part series. Click here to read part one.

Developing and maintaining competent process operators is critical to business performance in the process industries. This blog post, the second part in a two part series, looks at operator competency. In the first post I focused on four signal classes that are leading and lagging indicators of potential competency gaps in process operators. In this post I look at how to close the competency gap.

Operator Performance Evaluation Framework

To close competency gaps it is necessary to use some form of framework of evaluation and intervention. The framework provides a consistent approach and a mechanism for sustaining the benefits into the future. A recommended framework is based on continuous performance evaluation. For example, a new hire typically receives initial classroom training on the basics skills of an operator. This first training could include an introduction to some of the advanced skills that would be acquired through on the job experience and mentoring by experienced colleagues. During this stage the new operator is subject to continuous performance monitoring to identify any short falls in specific competencies. Monitoring could be triggered by a number of conditions such as observation that variables are deviating from expected values or analysis of incidents that occurred. During this early phase the new operator would typically display a wide variation in performance from expected norms. The variation is expected to reduce over time until at some point the operator is judged to be “certified”. Once certified, the operator remains subject to continuous performance monitoring which will identify any drift away from expected performance norms. Refresher training triggered by events or by a standard schedule brings the performance back to the expected norm. This continuous performance evaluation is the key to sustaining optimal performance over time.

Competency Based Evaluation and Training

The evaluation framework provides an approach to drive towards optimal performance. The big picture pieces that are needed are:

  • Deviation from expected norms
  • Map deviation to a competency gap
  • Provide training to close the gap
  • Continue to monitor and close gaps that emerge

Central to this framework is a competency model for the process operators that permits the identification of the specific competency gap and suggests a training intervention. One way to address this is to look at the roles and responsibilities of the operator and identify competencies required and the level of proficiency in a particular competency required for a specific role. First, the responsibilities of a job function are identified. For example, in the case of console and field operators two key responsibilities are:

  • Operate under normal conditions
  • Anticipate and respond to abnormal conditions

Each responsibility is then broken down into a set of competencies. For example, the responsibility “operate under normal conditions” requires the following competencies:

  • Operate unit controls
  • Interact with other units
  • Execute a shift handover

Next, each competency is linked to a set of associated behaviors, described in terms that can be measured. For example, the competency “operate unit controls” requires a console operator to exhibit the following behaviors:

  • Explain unit control schemes
  • Manipulate controls without adversely affecting the unit
  • Troubleshot control loops
  • Explain process chemistry and physics

Finally, each behavior learned by a trainee can be assigned a proficiency, ranging from ‘aware’ to ‘knowledgeable’, ‘skilled’ and ‘master’.

The operator competency model allows not only for the identification of gaps, but is also used to specify the training interventions needed to close the gaps. The learning and development team specifies interventions targeted at developing the competency and level of proficiency necessary for a particular role. Following the model is pertinent to decrease the risk of non-optimal outcomes leading to reduced performance or even worse business failure.

Click here to read part one of this two-part series.

About the Author
Martin Ross is Honeywell Process Solutions product manager for UniSim Competency Suite. Martin has spent 25 years supporting customers with operator training solutions based on advanced simulation technologies. Martin earned BSc and Ph.D. degrees in chemical engineering from Imperial College in London, UK.


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What Are Indicators of Potential Competency Gaps in Industrial Process Operators?

What Are Indicators of Potential Competency Gaps in Industrial Process Operators?

This guest blog post was written by Martin Ross, product manager for UniSim Competency Suite at Honeywell Process Solutions. This is part one of a two-part series. Click here to read part two.

Developing and maintaining competent process operators is critical to business performance in the process industries. This blog post focuses on four signal classes that are leading and lagging indicators of competency gaps in process operators. The evidence of history is that if not addressed, these gaps increase the risk of non-optimal outcomes leading to reduced performance or even worse business failure. Take action now to identify vulnerabilities in your operations.

I have divided the four signal classes in two leading indicators (operator performance and work environment) and two lagging indicators (production performance and external factors).

Two Leading Indicators

Operator Performance

A review of operator performance reveals fundamental gaps in competency. Can staff provide adequate explanation of the process, what are the important process variables and how are they controlled, what are the typical disturbances that the systems need to accommodate? How are procedures managed and implemented, is there good knowledge of standard procedures and when to apply them with follow-up reviews on compliance to the standards? Are operators consistently completing tasks, making good use of the control systems with effective upset condition management? Lack of process and control knowledge of complex unit operations such as reactors and complicated separation columns (e.g. multi-draw, columns with pumparounds, divided wall columns, use of heat pumps) increases risk because these are often the units which are most critical to process safety and economic performance. Poor understanding impedes the operator’s ability to troubleshoot the unit when things go wrong leading to higher risks to profitability and safety.

Work Environment

Consider the work environment. Do people show symptoms of high stress and low morale? Is there a high turnover of staff and high absenteeism? The job of an operator is high skilled, requires knowledge and high level thinking ability. Operators will feel worried that they cannot run the plant well because they lack the necessary competency. This increases their typical stress and makes the levels of stress higher than necessary during upsets. Not only does this mean that they may not respond quickly to problems and may be very cautious when dealing with upsets but may also have long term health implications (both mental and physical). Low competency levels lead to a number of problems which in turn lead to low morale. Problem areas can be higher incident rates and lower profitability. Low morale aggravates the situation as the operations team will be less willing to undertake extra activities, propose improvements and support change. To be effective staff need to be motivated and engaged. A low quality work environment will have adverse effect on competency of key staff to perform tasks diligently and if the unexpected happens, recover plan stability before an incident escalates.

Two Lagging Indicators

External Factors

On a more macro scale the impact of competency can be observed through indirect measures such as poor external reviews by safety and environmental authorities identifying human performance as an issue. Cost of insurance rising to reflect underwriter’s view of risk based on observed increases in upsets and environmental emissions. Customer satisfaction issues may be observed such as increasing difficulty to maintain supply on time or product may frequently fail to meet required quality or specification requirements. If these things start to occur customers could start to look for new suppliers.

Production Performance

Trends in production performance can reveal competency issues. Signals to look out for are operating costs rising due to lower yields, higher energy and chemicals costs and falling catalyst activity. Is there more re-run of off spec products and is there a rising number of incidents at the plant? While it is true that some of the indicators identified here may be arising from other root causes, it is also true that operator competency contributes to operations team performance for safe, reliable and profitable operations.

Once you have identified gaps, the next step is to decide what to do about closing the competency gap. The complexity of the problem means that deciding what to do can be challenging. I will discuss this in the second part of this two-part series.

Click here to read part two.

About the Author
Martin Ross is Honeywell Process Solutions product manager for UniSim Competency Suite. Martin has spent 25 years supporting customers with operator training solutions based on advanced simulation technologies. Martin earned BSc and Ph.D. degrees in chemical engineering from Imperial College in London, UK.


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What Are the Benefits of Guided Wave Radar for Level Measurement in Process Industries?

What Are the Benefits of Guided Wave Radar for Level Measurement in Process Industries?

This guest blog post was written by Adam Krolak, marketing product manager with Honeywell Process Solutions.

Level is among the most frequently measured process variables in industrial plants. Level readings are used for local indication, process automation and visualization in control systems. Additionally, they are crucial for managing inventory and enforcing safety limits for overfill, leak detection or dry-run protection of pumps. Other applications range from automated ordering systems, to communicating low limits to suppliers to streamline the logistic process.



With so many level measurement technologies currently available, it can be difficult for end users to select the right solution for their particular application. Parameters such as changes in temperature, pressure, density, dielectric constant or the measured material can all affect the technology choice. Other important considerations include agitation, foaming, corrosive properties, dust and construction of the tank. The desire to use a single type of instrument for all level measurements is another common factor. Lastly, the selection of a level measurement device may hinge upon unit price, lifecycle cost, ease of mounting, maintenance, accuracy, relevant certifications, and ease of integration into the control system.

Rising labor costs and the need for uninterrupted production are driving interest in electronic measurement technologies. With no moving parts and built-in diagnostics, these solutions enable lower maintenance costs and higher reliability. They also provide significantly lower lifecycle costs than traditional mechanical and electromechanical level instruments.

Today, guided wave radar (GWR) based on time-domain-reflectometry is one of the fastest growing electronic technologies for level measurement in the process industries. GWR sensors are handling applications that previously employed technologies such as capacitance, hydrostatics or ultrasonics. Their common accuracy specification is ±10 mm to ±5 mm (basic models) and ±3 or ±2 mm (advanced models), with a typical repeatability of ±1 mm.

A GWR sensor is mounted at the top of a tank facing down, and sends electromagnetic pulses toward the measured product. It uses the reflected signal to calculate the level in the tank. The measured signal travels along a waveguide that can be made of a stiff metallic rod, flexible wire, or a coaxial construction. GWR sensors are available with certification for hazardous areas and with safety-integrity-level ratings.

Experience has shown that GWR technology offers key advantages in a wide range of industrial applications. For example, the GWR measuring signal and reflection are concentrated around the waveguide or inside the waveguide (in the coaxial option), and this narrow path of signal propagation minimizes the potential impact of stray signals caused by construction elements or obstacles in the tank. The concentration of the signal along the waveguide results in a cleaner, stronger signal of the echo reflection. Plus, without the need for an antenna, the GWR’s waveguide can be installed easily through narrow mounting holes or nozzles.refinery-guided-wave-radar-process-industries

The GWR solution also offers benefits in applications subject to dust, foam and heavy vapors. Where there is a need for interface measurement (such as oil on water), it allows the measuring signal to penetrate the upper product and provide measurement of the lower product. The waveguide can be mounted on an angle or even formed to follow the contours of an irregularly shaped tank.

Like any technology, there are limiting factors to the use of GWR devices. Because their waveguide is in constant contact with the product in the tank, the potential for corrosion exists. Automation suppliers address this concern by offering a variety of process connections and waveguides constructed of corrosion-resistant materials such as type-316 stainless steel, high-nickel alloys or rods coated with perfluoroalkoxy (PFA) polymer.

Movement of the product in the tank can also subject the waveguide to pulling and bending forces acting upon it. However, readily available calculation formulas enable checking that the forces are within the operating limits for a given type and length of waveguide.

GWR deserves consideration for a wide variety of level measurement applications and, indeed, is an excellent fit for many demanding services. The increasing availability of flexible configurations, selection of probes, materials, process connections, certifications, and competitive pricing make it a natural and preferred choice for many applications.

About the Author
adam-krolakAdam Krolak is a marketing product manager for the Honeywell Process Solutions SmartLine level transmitter portfolio. Adam has over 15 years of experience in field instrumentation, including research and development at Honeywell and as a Service Manager at Endress+Hauser. Adam holds a master’s degree in process automation and a management degree. He is an author of several patents and is an active member of the Institute of Electrical and Electronics Engineers (IEEE).

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How to Select a pH Sensor for Harsh Process Environments

How to Select a pH Sensor for Harsh Process Environments

This guest post is authored by Vickie Olson, product marketing manager at Honeywell Process Solutions.

For today’s process plants, pH is an important parameter to measure in a host of demanding applications. A good example is flue gas desulfurization (FGD) control with systems using wet scrubbers in lime or limestone slurries. Proper pH can maximize sulfur oxide (SOx) removal and minimize the 160826412build-up of scale. Selection of the best sensor type will also enable longer life and more reliable control.

Choosing a pH sensor for use in harsh process environments requires careful consideration of numerous key factors. Extreme temperature at higher pH ranges reduces pH life due to consumption of hydrogen-sensitive ions on the glass membranes. An electrolyte (typically potassium chloride in gel or liquid form) tends to diffuse faster with temperature and high flow. In addition, abrasion removes the membrane surface over time.

Many process industry users specify a pH sensor of the combination style, meaning the device has a measuring electrode — either glass or ion-sensitive field effect transistor (ISFET) — or a reference electrode, which is usually based on silver/silver chloride. These pH sensors are considered rugged or robust compared to general-purpose sensors, since they are better able to withstand abrasive and alkaline conditions such as in FGD slurry. General-purpose pH sensors may not last a single day in sulfuric, abrasive and high-temperature environments. Depending on the style of ruggedized pH sensor and its maintenance frequency, this device can last from a few weeks to many months in operation.

Various types of reference protection on the market allow electrolyte diffusion, but reduce the infiltration of contaminants from the process fluid that can plug the junction or cause fouling of the reference. The porous junctions at the tip areas may be composed of double or multiple sections designed to slow contamination, which can result in poisoning of the silver reference material. Typically, the junction material in rugged pH sensors is composed of solid polytetrafluoroethylene (PTFE), ceramic or fibrous polyvinylidene fluoride (PVDF).

Several pH sensor designs employ wood or acrylic material containing electrolytes to slow the spread of contaminants while maintaining the required electrical connection of the reference with the measuring electrodes. An additional method to delay poisoning with solid reference designs is to locate the reference wire at the back of the sensor body, rather than hang it from the back, approaching the front of the device.

In terms of ruggedized glass measuring electrodes, the tip may have thicker glass and more hydrogen-sensitive material on the membrane. Flat glass is sometimes substituted for hemispherical or round glass on the tip to avoid breakage due to hard materials. This is less important in FGD applications, although the design is successfully used in the pulp & paper industry with heavy pulp slurry. In lime slurry, the flat tip does not have as large a measuring surface — leading to faster wear than rounded-type tips.

Most recently, ISFET measuring electrode technology was been paired with rugged reference technologies to provide a durable pH measurement solution. The advantages of ISFET include robustness, stability and precision. Sensors of this type utilize an integral automatic temperature compensator in one-piece construction, making them well suited for varying pH and temperature ranges.

The more demanding the application, the more critical it is to consider process operating conditions and expectations for a pH sensor. This is particularly important when harsh environments require frequent sensor replacement. Users employing the right device can realize savings from extended sensor service life, reduced replacement and maintenance costs, and ultimately, accurate and reliable pH measurement.

About the Author
Vickie OlsonVickie Olson is an analytical product specialist for Honeywell Process Solutions based in Atlanta, Ga. She has been involved in process instrumentation and analysis for industrial and municipal applications for more than 25 years as a chemist, product specialist and sales manager for Honeywell, Hach, and other companies. Vickie has spoken on a variety of topics related to water analysis and control at ISA and numerous other symposiums. She earned a bachelor’s degree in textile chemistry from the Georgia Institute of Technology and a master’s degree in business administration from Georgia State University.
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What is an Optimal Control System for Batch Manufacturing?

This guest post is authored by Tao Shen, a product marketing manager at Honeywell Process Solutions.

If you’re working in batch manufacturing, you are painfully aware of the ever-increasing demand to produce more and more and – while you’re at it – cut costs. Well, hey, you weren’t doing much this week anyway, so you may as well increase production and lower operating costs, right?hot steel processing

Reducing the total cost of ownership of your distributed control system (DCS) or PLC/HMI system is one area in which you can increase profitability and efficiency. But sifting through vast amounts of technical information and weighing alternatives to find the right solution for your application can be daunting. The urgency for higher system performance has, in some instances, created pressure to implement a “do it yourself” solution in an attempt to save time and money. But the DIY method may actually cost more in the long run and can subject you and your team to unanticipated costs and risks.

In batch environments, DCS architecture has long been favored over creating a control system using PLCs. In considering these two options, price points are now more comparable than ever before, so the decision is no longer solely based on the cost of the hardware and software.

Many aspects of the architecture will factor into the decision, including network topology and performance, reliability and repeatability of the controls configuration, HMI graphics functionality, method of abnormal situation management, controls configuration, integration and interoperability, and data management.

Batch automation requires tight coordination between phases, units, recipes, and formulae. With so many diverse elements, the batch data model is the key to the solution. With recent advances in technology, all aspects of the batch automation solution can be captured in a single DCS data model. All the elements needed to manage the batch can be run in the process controller, eliminating the necessity of a PC acting as a batch server.

Because the batch would actually run in the controller – not in the server – it is closer to the process resulting in faster batch execution, tighter batch cycles, and increased throughput. If one controller goes down, redundant systems would take over without resets or a loss of the recipe which is critical in regulated industries.

Implementing new automation elements necessarily entails operator training. With the DCS solution, operators learn one system in a consistent environment so that fewer errors are made. Alarms, security, abnormal situation management, displays and control functions are all supported in one tool with no duplication in engineering.

The open architecture of the DCS also allows third-party devices and smart devices to be integrated into the same data model, incorporating your existing controllers where necessary, and making the operator view of all controllers available in a consistent fashion. This also makes training on the new system easier and faster, so that downtime is minimized. Most DCS suppliers offer advanced simulator technology to support improved performance throughout the lifecycle of the plant.

Fast project implementation, lower training costs, less configuration effort, and easier maintenance can make the DCS solution the most desirable in batch applications. The total cost of ownership is lowered resulting in the desired increased throughput and lower costs, without subjecting the system to the probability of the unforeseen costs and problems associated with attempting to integrate independent PLCs and HMI software in the “do it yourself” method. The DCS solution also takes into consideration future plant expansion and scalability, and leaves the plant in a more agile posture to better respond to business changes.

About the Author
Tao ShenTao Shen is a product marketing manager for Experion LX at Honeywell Process Solutions. He has more than 15 years of experience in process monitoring, control and optimization in various roles from engineering to marketing with experience on a number of different product platforms. Tao earned a PhD degree in Energy and Power Engineering from Huazhong University of Science and Technology in China and is a certificated Project Management Professional (PMP).
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How to Select the Optimal Temperature Sensor

How to Select the Optimal Temperature Sensor

The following technical insight is part of an occasional series authored by Greg McMillan, industry consultant, author of numerous process control books and a retired Senior Fellow from Monsanto. This insight was adapted from Greg’s book, Advanced Temperature Measurement and Control.

In industrial environments, high process temperatures, pressures, and vibration make it necessary to have a robust temperature sensor. Fast response time, accuracy, and stability are also needed. While several types of temperature sensors are available, such as thermistors, infrared pyrometers, fiber optic, and others, the two most commonly used in the process measurement industry are resistance temperature detectors (RTD) and thermocouples (TC).Pressure Meter

The RTD provides sensitivity (minimum detectable change in temperature), repeatability, and drift that are an order of magnitude better than the thermocouple, as shown in Table 1-1. Threshold sensitivity and repeatability are two of the three most important components of accuracy. The other most important component, resolution, is set by the transmitter. Drift is important for extending the time between calibrations and the temperature loop running at the right setpoint. The data in this table dates back to the 1970s and consequently doesn’t include the improvements made in thermocouple sensing element technology and premium versus standard grades. However, the differences are so dramatic that the message is still the same.

The temperature range shown for the RTD in the table is optimistic. At temperatures above 500°C, changes in sensor sheath insulation resistance have caused errors of 10°C or more.

There are many stated advantages for thermocouples, but if you examine them more closely you realize they are not as important as perceived for industrial processes. Thermocouples are more rugged than RTDs. However, the use of good thermowell designs and good installation practices makes an RTD sturdy enough even for high-velocity streams and nuclear applications. Thermocouples appear to be less expensive until you start to include the cost of extension lead wire and the cost of additional process variability from less sensor sensitivity and repeatability.

The case of using TC or RTD input cards in a distributed control system (DCS) is not considered because of the error introduced by these input cards as a percent of span is large and individual sensor offset and drift errors cannot be individual corrected as they are with a dedicated temperature transmitter.

Table 1-1 Accuracy, range, and size of temperature sensing elements

Table 1-1 Accuracy, range, and size of temperature sensing elements

The IEC 751 standard describes an ideal relationship between the resistance of a platinum RTD and the temperature to which the RTD is subjected. The difference between the actual RTD curve and the ideal RTD curve results in a measurement error, which is referred to as a sensor interchangeability error.

The Callendar-Van Dusen equation offers an alternative to the IEC 751 standard. This equation can be programmed into a transmitter so that the transmitter can use the actual RTD curve rather than an ideal curve (e.g., IEC 751 standard) to translate the sensor’s resistance signal into a temperature value. The Callendar-Van Dusen equation enables the transmitter calibration to be matched to the sensor. When a sensor is replaced the parameters for the equation are entered into the transmitter.

The main reasons for selecting RTDs or T/Cs can be summarized in the following lists. In all cases, field temperature transmitters are assumed to be used rather than DCS TC or RTD input cards.

Why Use an RTD Rather Than a TC?

  • RTDs have better accuracy and repeatability.
  • RTD signals are less susceptible to noise (higher signal-to-noise ratio).
  • RTDs have better linearity over temperature ranges.
  • RTDs can use the Callendar-Van Dusen equation to provide transmitter-sensor matching
  • Cold junction compensation and related errors are not associated with RTDs.
  • RTD drift is predictable, while T/C drift is erratic and unpredictable. In addition, TC drift errors can be large as a result of element poisoning and oxidation at high temperatures.
  • The changes that affect the output of an RTD or TC occur over time due to mechanical shock, poisoning, and temperature cycling. These changes can be eliminated by an in-line RTD calibration, an option not available for a TC.
  • RTDs do not need special extension wire.

Why Use a TC Rather Than A RTD?

  • TCs function better at higher temperatures (above 1100 °F [593 °C]) than RTDs.
  • TCs sensors are less expensive than RTDs in the common temperature range. Total installed cost of TCs is less for integral mounted transmitters.
  • TCs have a faster response time than RTDs but this is only a consideration for bare elements in very fast temperature processes (process time lag < 10 seconds).

You should now recognize the importance of drift, threshold sensitivity, repeatability and range in the selection of temperature sensors. This knowledge provides the fundamental essential first step that sets a control loop’s ability to keep temperatures and consequently many compositions at their optimum operating point. The principles here can be extended to other sensors. In the next post we will take a look at the next step, which is sensor installation.

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