Why Plant Equipment Maintenance Procedures Benefit from Digital Data CollectionJuly 10, 2018
The best way to prevent unexpected downtime is to establish sound equipment maintenance procedures focused on asset reliability. In addition to prescribed maintenance schedules, conditional maintenance based on your equipment’s current state will help you catch problems while they’re still insignificant or manageable. By digitally collecting readings and observations from your equipment instead of relying on paper forms and round sheets, you’ll easily stay ahead of your plant’s equipment and asset maintenance needs.
How Digital Data Collection Benefits Equipment Maintenance Procedures
Plant equipment maintenance procedures focused on asset reliability management typically rely on scheduled, preventative maintenance to keep important equipment running consistently. These granular schedules dictate when each component of your assets should be repaired or replaced. Schedules are determined by calculating the mean time between failure (MTBF) and mean time to failure (MTTF) for each component, based on historical failure data.
As the logic goes, if you know, on average, when a part is going to fail, you can fix it before it does. As a Plant Operations Manager, this allows you to schedule downtime for repairs in a way which minimizes the cost of your equipment’s lost production. If you don’t catch the potential failure in time, though, it can lead to expensive repairs and extended, unscheduled downtime. There’s your stitch in time.
Why Efficient Plant Equipment Maintenance Procedures Combine Calendered and Conditional Maintenance
Calendared maintenance has a blind spot: assets don’t always fail according to plan. Averages will get you close, but they can’t account for the actual reality of a busy plant and hard-working equipment. In order to detect outlier failures, or failures which occur significantly before the average expected time, you need to keep a careful eye on your equipment.
By closely monitoring and managing your plant asset performance, with the help of your Field Operators, you’ll be able to detect signs of impending failure. These signs will inform you of maintenance actions you must take to prevent failure and unscheduled downtime. This is called conditional maintenance, and works in tandem with your calendared maintenance to predict, expose, and respond to potential causes of downtime.
Conditional maintenance depends entirely on the accuracy, visibility, and timeliness of your plant equipment information. If the data you collect from readings or observations is late, inaccurate, or skipped altogether, you won’t be able to appropriately assign maintenance resources in time. Digitizing and enforcing your data collection procedures will significantly improve both their timeliness and its visibility.
Digitizing Qualitative Data to Inform Conditional Plant Equipment Maintenance
There are two types of data you can collect about your plant’s equipment: quantifiable and qualitative. Both can be digitized. Quantifiable data largely already is.
Examples of quantifiable data include oil temperature, oil pressure, or revolutions per minute—anything that can be expressed numerically. Much of this data is instrumented and captured automatically by your DCS or PLC systems then transmitted and made available to your IT team and control room operators.
Once there, it can be stored, compiled, and displayed to give you oversight of your plant’s current condition. Fluctuations, anomalies, or deviations from norms can be highlighted, allowing you to take appropriate actions.
Qualitative data is the next frontier in digitization.
Crucial Qualitative Equipment Data for Your Plant Procedures
Not all information about your plant’s equipment can be quantified or instrumented. Qualitative information describes the quality of your equipment’s condition and operation; it corresponds to sensory information, observed by sight, hearing, smell, or touch.
Action-oriented qualitative data collection is essential to conditional plant equipment maintenance procedures. Examples include, but are not limited to:
Rust, corrosion, leaks, unsafe work conditions, cracks, dents, welds, shattered glass or plastic, fraying fibrous material, peeling rubber or fiber, excessive grime, signs of infestation, unusual footprints, signs of sabotage
Grinding; screeching; ringing; belching; unusual harmonic resonances; concussive reports; change in pitch, frequency, or tone of common operating noises
Excessive vibration, heat, or humidity; sticky or slippery footing, indicating leaks; burning sensation in eyes, nose, or throat; condensation buildup
Unusual odors, like the smell of rotten eggs, smoke, sewage, rot, or natural gas; absence of usual odors, like diesel exhaust
How Digitized Qualitative Data Can Better Inform Plant Equipment Maintenance Procedures
Having your mobile workers collect conditional information on your equipment is only a first step in your plant equipment maintenance procedures. You also need to compile and review their observations in order to make appropriate, timely maintenance decisions. If your Operators only record their observations on paper round sheets, you may not be able to detect and respond to emergent situations in time to prevent equipment failure or a hazardous situation.
In contrast, if your Field Operators digitize their observations using electronic mobile round sheets and equipment maintenance checklists, the qualitative data they report on can be communicated and acted on as easily as the quantitative data your automatic sensors report. Once your Operators fill in the asset-specific form on their tablet or smartphone, it’s instantly transferred to your control room to be analyzed and stored.
This system of digital data collection eliminates the need for redundant data entry, and facilitates easy information retrieval and record-keeping. Anomalies can be highlighted and brought to your attention by running an exception report, allowing you to make timely decisions about out-of-the-ordinary conditions. These same mobile applications can also inform your Operator if immediate corrective action is required, such as turning off a valve, calling you, or completing an incident report.
Comparing Digital vs. Analog Conditional Equipment Maintenance Procedures
Consider a situation in which one of your Field Plant Operators detects a faint smell of rotten eggs while making his rounds. This smell can indicate the presence of H2S gas, otherwise known as hydrogen sulfide. Hydrogen sulfide occurs naturally from crude oil or natural gas and can be found in refineries, wastewater treatment facilities, tanneries, and paper mills. H2S is a colorless, flammable, explosive, and potentially deadly chemical asphyxiant and nerve agent. It’s the bogeyman.
How Analog Response Procedures Can Delay Necessary Plant Equipment Maintenance
Understanding that the smell of H2S is important to record, your Field Operator duly notes it on their paper form and heads to the next piece of equipment on their scheduled round. At the end of their shift, they turn in their paper form. At the end of the week, all the paper forms from all Operators are collected, reviewed, and entered into your data system.
In this data collection system, by the time you or another plant employee notices the implications of the smell, though, H2S levels could have increased significantly, the result of a corroded internal valve and gasket. As your next Operator enters the area on his rounds a week later, their eyes burn, they get nauseous and dizzy, their breathing becomes difficult, and they begin to experience significant drowsiness. Luckily, they get out of the area before suffering more serious harm, then radio you to tell you something is wrong.
To clear out the area and repair your asset, you now need to shut down your equipment for several hours and bring in an emergency response team equipped with SCBA gear. The total cost of your asset’s downtime exceeds fifty thousand dollars.
Why Digital Data Collection Creates Timely Plant Equipment Maintenance Procedures
Now picture how the same situation might play out if your Field Operator was using an electronic mobile rounds sheet. Your Operator smells rotten eggs and records it on their tablet. As that input is flagged as anomalous, their observation is passed directly to your control room. You recognize it as a potential harbinger of a serious, emergent hazard. At the same time, your Operator’s tablet notifies him to inform you and clear the area, ensuring there’s no way the incident escapes your attention.
You respond immediately, dispatching a maintenance team to find the source of the gas and repair it. They quickly ventilate the area and replace the faulty components. Downtime is minimized, safety is preserved, and the total cost of the mishap is kept below a thousand dollars.
Which situation would you prefer?
How to Seamlessly Digitize Your Plant Equipment Maintenance Procedures
In order to keep your plant’s equipment up and running efficiently, you need to employ both a calendared and a conditional maintenance regimen. Each regimen buttresses the other. Calendared maintenance procedures allows you to automate the assignation of maintenance resources based on an established schedule; conditional maintenance procedures detect and prevent outlier failures.
Conditional maintenance is only as good as the accuracy, visibility, and timeliness of the data it generates, though. Digitizing both your quantifiable and qualitative data collection processes ensures that your conditional plant equipment maintenance procedures are designed to respond to problems with your assets as soon as they’re detectable. If you can see where the jeans are beginning to fray, you can make that stitch in time.
GoPlant, an asset-centric mobile data collection platform for your Field Operators, is designed to help you get the actionable information you need to make smart maintenance decisions. Using mobile technology allows you to see your equipment’s condition in real time, as soon as your Operator records it. To see GoPlant in action, request a no obligation demo, or get in touch with our team today.