Take 8 steps to debug process control system
When business is good, demand increases, and plant systems are strained by operating at or beyond capacity. When business drops off, so does budgets and staffing. As a result, plant systems often suffer from reduced maintenance and replacement schedules.
Through it all, plant managers must keep systems running and product shipping. They need to make tough decisions about what gets done, what gets deferred, and when to escalate concerns “up the chain.” Taking a strategic approach to this complex and demanding job can save you time and money, and on some days, even your sanity.
A strategic approach to identifying and debugging system shortfalls doesn’t have to be an overwhelming proposition, and this article certainly isn’t intended to introduce anything as sophisticated or complicated as a SCADA system.
The eight-step plan outlined here can be developed and applied as time allows. You can start with just a pencil and paper and commonly available tools while focusing on a single system or process.
1. Plot the process
Start by drawing a diagram of the system of interest and its core processes. You don’t need to break out a drawing program like Visio yet (though you may want to eventually); a “back of the envelope” drawing that captures the core processes in the system is enough to get started.
2. Identify key components
Next, identify the key components in each process. Key components will vary by industry, but some key components of many industrial processes that you’ll want to consider are:
- Variable Frequency Drives
- Power Supplies (especially the supplies that provide power to sensors)
- Electromechanical devices (actuators, valves, etc.)
- I/O modules and switches
- Cabling and interface junctions
- Switch gear and breaker panels
- Operator interfaces (such as control panels)
3. Assign metrics for key components
For each of the key components that you identified in the previous step, identify some “operational metrics”. These are that you can measure that reveal important information about the state of the component.
Good candidates for metrics are information about a component that:
- You can measure easily
- You can gather at a single point in time (for example, meter measurements, waveform captures, observations, and photos)
- Capture relevant quantitative information (for example, a temperature measurement) or qualitative information (for example, the shape of a waveform from a variable speed drive).
- Are listed on the equipment nameplate or in the manufacturer’s specifications
For example, for a motor-driven conveyor belt, good operational metrics could be:
- Throughput (average, maximum, and minimum rates)
- Conveyor load (that is, how much weight is being transported by the conveyor)
- Motor peak power demand
- Motor and drive train vibration data
4. Take measurements
Measure and record the metrics of the key components. Capturing this data doesn’t have to be a complicated process. Although you may eventually want to record and analyze component metrics in a spreadsheet or database, you can get started with pencil and paper.
Your experience and training is the best guide for both what and how to measure, (and for more ideas you can review the sidebar) but here are some simple “rules of thumb” for making effective measurements:
- Start measuring at the power source.
- Follow the current flow.
- Work towards the furthest point or device, capturing measurements as you go, and at the input and the output of each step or key component.
- Keep track of key metrics over time.
- Take measurements when the system is running at peak capacity. Measurements taken when the system is not being taxed are of much less value.
- Look for changes (which can indicate that something may have happened) or measurements that exceed limits.
5. Create a data “dashboard”
Statistical information such as that which you gathered in step 4 can be a powerful tool for analysis and prediction, but interpreting rows and columns of raw data can be overwhelming. An effective way to deal with this kind of data overload is to decide in advance the range of values for each metric that is OK, suspicious, serious, and extreme.
With data ranges in place, you can create a simple, color-coded status for each component in the system that you can view in a notebook, on a whiteboard, or in a spreadsheet. The simplified, high-level view of the system that results, free of distracting detail, can make data analysis and decision making for complex systems much simpler.
6. Prioritize components for attention, maintenance, and budget
Now that you have a clear and uncluttered view of the status of the key components in the system, you can prioritize components for attention as needed.
7. Make the decision
For each component on your prioritized list, make a decision about what to do next: Does it require attention (for example, resizing the motor on the conveyor to better handle the load demand)? Does it need replacement? Should you just keep an eye on it?
Another option is to simply let it run to failure, planning ahead by allocating budget and resources. Objective, prioritized information about key components can be a big help to the decision-making process.
8. Refine and extend, but stay flexible
When you have a working strategy in place, you can refine and extend it as needed in an ongoing process. As your system strategy evolves, be sure to keep flexibility in mind. Taking a variety of measurements with general purpose, hand-held tools gives your system strategy the flexibility to adapt as processes, components, priorities, and your needs change.
Some questions to ask include:
- Are there additional processes or components that should be included?
- Would your strategy benefit by choosing other metrics or additional ones?
- Do you need to invest in additional tools, training, or staff to fully implement the strategy?
- Should your system diagram be more detailed or rendered with higher quality?
- Do you want to invest in better storage and analysis tools, such as spreadsheets, databases, or proprietary solutions?
Strategy in the long run
An accurate, understandable, and manageable view of core processes and key components in a system empowers plant managers to make the best use of limited time, budgets, equipment, and personnel. The measurements you gather are also the kind of hard data that can justify process changes, equipment purchases, and staffing improvements.
Whether you start small and keep it simple or jump in and develop a detailed strategy with hundreds of metrics managed in a computerized system, the time and effort required to create and maintain an effective system strategy will pay off in more effective decisions, in time and money saved, and in the peace of mind that comes from knowing both where you stand and where you’re going next.