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Kitchen extraction - data-driven frequency
A frequency band from a chart is a starting point, but your own system holds better information than any chart - if you capture it. Every clean measures how much grease built up since the last one, and that data, gathered over time, tells you exactly how fast your system fouls and precisely how often it needs cleaning.
The short answer
The most accurate cleaning frequency comes not from a general chart but from your own system's data. Every clean measures the grease deposit that built up since the last one, so the grease readings from successive cleans reveal how fast your system actually fouls - its real fouling rate. With that data, you can set the frequency precisely: clean at the interval that keeps the grease within the standard's limits, based on how quickly your system reaches them. Data from your own cleans turns an estimated frequency into a measured, precise one.
Your system knows better than a chart
The standard's frequency bands are a useful starting point, but they are general - based on cooking hours as a proxy for how fast a system fouls. Your own system holds far more specific information: exactly how fast it actually fouls, given its particular cooking, ventilation, ductwork and everything else. The bands estimate that from a proxy; your system, measured, reveals it directly. So the most accurate frequency for your kitchen comes not from a general chart but from the data your own system generates - if you capture and use it.
This is the shift from an estimated frequency to a measured one. A frequency band tells you roughly what a kitchen like yours might need; your own grease data tells you what your specific system actually needs, because it reflects how your system genuinely behaves rather than a general assumption. The information to set a precise frequency is being generated every time your system is cleaned - the question is whether it is captured and used. Recognising that your own system is the best source of data on how often it needs cleaning is the basis of a data-driven approach.
Every clean is a measurement
The key insight is that every clean generates a data point about your fouling rate. When a system is cleaned to the standard, the grease deposit is measured - and that measurement records how much grease built up since the last clean. So a grease reading is not just a compliance check; it is a measurement of how much your system fouled over the period since it was last cleaned. Each clean, with its grease measurement, tells you how far the system had fouled in that interval.
This makes each clean a source of information about how fast your system fouls. If a clean finds the grease near the limit after a given interval, the system fouled fast over that period; if it finds the grease well below the limit, the system fouled slowly and could have gone longer. Read this way, the grease measurement at each clean is feedback on whether the interval was right - too long if the grease was high, potentially too short if it was low. Every clean, properly measured, is a data point on your system's real fouling rate, waiting to be used to refine the frequency.
Data over time reveals the rate
The real power comes from gathering the data over time. A single clean's reading is one data point; the grease readings from successive cleans, tracked over time, reveal your system's fouling rate clearly - how much grease it accumulates over a given period, consistently. With several data points, you can see the pattern: your system reaches a certain grease level in a certain time, reliably, which is exactly the information needed to set the precise interval that keeps it within the limits.
This turns the frequency question into a data-driven one. Rather than estimating from a band and adjusting by judgement, you can see from your own readings how long your system takes to reach the standard's grease limit, and set the cleaning interval to clean before it does - with margin. The data tells you the fouling rate, and the fouling rate tells you the frequency. And because it is your system's own data, it accounts for all the specifics - cooking, ventilation, ductwork - automatically, without having to estimate each. Tracking the grease readings over time is what converts scattered measurements into a clear picture of how often your system genuinely needs cleaning.
Refining it continuously
A data-driven frequency also stays right over time, because the data keeps updating. Each new clean adds another reading, so the picture of your fouling rate stays current - and if your fouling rate changes, because the kitchen gets busier or the cooking changes, the data shows it, and the frequency can be adjusted to match. Rather than an interval set once and left, the frequency is continuously informed by the latest measurements, so it tracks how your system actually behaves as that changes.
So using data is not a one-off calculation but an ongoing process: measure the grease at each clean, track the readings over time to see the fouling rate, set the interval to keep the grease within the limits with margin, and refine it as new data comes in. This keeps the frequency both precise and current - matched to your system's real, present fouling rate rather than a general estimate or an outdated assessment. The data your own system generates, captured and used over time, is the most accurate basis there is for how often it needs cleaning, and it keeps the frequency right as things change.
The takeaway
The most accurate cleaning frequency is not guessed from a general chart but built from your own system's data. Every clean measures the grease that built up since the last one, so each clean is a data point on how fast your system actually fouls. Gathered over time, the grease readings from successive cleans reveal your fouling rate clearly - how much grease your system accumulates over a given period - which is exactly what is needed to set the interval precisely.
So a data-driven frequency uses your own measurements: track the grease readings over time to see the fouling rate, set the interval to keep the grease within the standard's limits with margin, and refine it as new data comes in. Because it is your system's own data, it accounts for all its specifics automatically and stays current as things change. It turns an estimated frequency from a band into a measured, precise one - which is why letting your system's own data set the frequency is the most accurate approach there is.
Questions
Every clean measures the grease that built up since the last one, so the readings from successive cleans reveal how fast your system actually fouls - its real fouling rate. With that data you can set the interval precisely to keep the grease within the standard's limits, based on how quickly your system reaches them.
Because the standard's bands estimate fouling from a proxy (cooking hours), while your own grease readings measure it directly - reflecting how your specific system genuinely behaves, given its cooking, ventilation and ductwork, rather than a general assumption. Your system knows better than a chart.
When a system is cleaned to standard, the grease deposit is measured, and that records how much grease built up since the last clean. A high reading means the system fouled fast over the interval; a low reading means it fouled slowly and could have gone longer - feedback on whether the interval was right.
Your system's fouling rate - how much grease it accumulates over a given period, consistently. Several data points reveal the pattern: your system reaches a certain grease level in a certain time reliably, which is exactly what is needed to set the interval that keeps it within the limits.
Yes. Each new clean adds another reading, so the picture stays current, and if your fouling rate changes - because the kitchen gets busier or the cooking changes - the data shows it and the frequency can be adjusted. It tracks your system's real, present fouling rate as it changes.
Measure the grease at each clean, track the readings over time to see the fouling rate, set the interval to keep the grease within the standard's limits with margin, and refine it as new data comes in. It is an ongoing process that keeps the frequency precise and current.
We measure the grease at every clean and track it over time - building the data on your system's real fouling rate that sets the most accurate, precise cleaning frequency for your kitchen.
