Automatic readings and production logs

Record operational and production data automatically

Done by about 15.2 million people across 82 job roles, several times a day.

When an operational or production event occurs → then Record the data point to the system

Acts every time the trigger fires.

Reads

record id, event type, quantity, recorded at, station

Evidence

Proved in test: n8n execution 1348, 9 of 11 nodes ran in 347 ms.

Log operational or environmental data

3 builds of this one. The same workflow, fitted to what each business calls it and the field it checks — listed in the teardown below.

Done by about 2.8 million people across 15 job roles, several times a day.

When an operational or environmental reading is captured → then Record the data point to the system

Acts every time the trigger fires.

Reads

data point id, metric name, metric value, captured at, source

Evidence

Proved in test: n8n execution 1264, 9 of 11 nodes ran in 412 ms.

Log environmental readings automatically

Done by about 166,000 people across 3 job roles, several times a day.

When an environmental reading is taken → then Log the reading to the environmental record

Acts every time the trigger fires.

Reads

reading id, reading type, reading value, location, recorded at

Evidence

Proved in test: n8n execution 1254, 9 of 11 nodes ran in 352 ms.

Log daily activities and visit locations

Done by about 31,000 people across 1 job role, more than weekly.

When A field activity or site visit is completed → then Record the logbook entry

Acts every time the trigger fires.

Reads

visit id, activity description, location, visit date, completed by

Evidence

Proved in test: n8n execution 1246, 9 of 11 nodes ran in 414 ms.

Record green energy operational data automatically

Done by about 1.1 million people across 4 job roles, several times a day.

When a green-energy process generates a data point → then Log the data point to the operational record

Acts every time the trigger fires.

Reads

data point id, metric name, metric value, unit, recorded at

Evidence

Proved in test: n8n execution 1346, 9 of 11 nodes ran in 335 ms.

Log each production activity as it finishes

Done by about 269,000 people across 5 job roles, several times a day.

When a production activity is completed → then Add the activity to the production log

Acts when the duration minutes is more than 0. Otherwise it logs that the activity logged no recorded duration, and stops.

Reads

activity id, activity name, duration minutes, completed by, completed at

Evidence

Proved in test: n8n execution 1251, 10 of 13 nodes ran in 358 ms.

Append new readings to the compiled dataset

Done by about 125,000 people across 4 job roles, more than weekly.

When a new environmental or climatological reading is submitted → then Append the reading to the compiled dataset

Acts every time the trigger fires.

Reads

submission id, reading type, reading value, dataset name, submitted at

Evidence

Proved in test: n8n execution 978, 9 of 11 nodes ran in 439 ms.

Log activity counts after each program task

Done by about 66,000 people across 1 job role, more than weekly.

When a tracked program activity is completed → then Increment the activity count in the log

Acts every time the trigger fires.

Reads

activity id, activity type, assisted count, completed at, staff name

Evidence

Proved in test: n8n execution 1226, 9 of 11 nodes ran in 417 ms.

Log weight or measurement readings automatically

2 builds of this one. The same workflow, fitted to what each business calls it and the field it checks — listed in the teardown below.

Done by about 2.6 million people across 21 job roles, several times a day.

When a material or sample is measured → then Record the measurement reading

Acts when the measurement value is more than 0. Otherwise it logs that the reading came back at zero, and stops.

Reads

sample id, measurement value, unit of measure, measured by, measured at

Evidence

Proved in test: n8n execution 1298, 10 of 13 nodes ran in 355 ms.

Log temperature readings on a schedule

Done by about 894,000 people across 1 job role, several times a day.

On a schedule Every 30 minutes, a temperature sensor reading is due → then Temperature reading logged to record

Acts every time the trigger fires.

Reads

reading id, sensor id, location, temperature value, unit, recorded at

Evidence

Proved in test: n8n execution 1294, 9 of 11 nodes ran in 402 ms.

Log production quantities when batch finishes

Done by about 527,000 people across 4 job roles, several times a day.

When a production run or batch is completed → then Production quantities logged to record

Acts every time the trigger fires.

Reads

batch id, product name, quantity produced, quantity target, completed at, line id

Evidence

Proved in test: n8n execution 1274, 9 of 11 nodes ran in 377 ms.

Record each customer visit in their file

Done by about 438,000 people across 1 job role, daily.

When a customer visit takes place → then Log the visit in the customer’s record

Acts every time the trigger fires.

Reads

visit id, customer id, staff id, visit date, visit notes

Evidence

Proved in test: n8n execution 1344, 9 of 11 nodes ran in 327 ms.

Log survey and experiment results into records

Done by about 142,000 people across 3 job roles, daily.

When a measurement, experiment, or report is completed → then Result logged to records database

Acts every time the trigger fires.

Reads

record id, project name, measured value, expected value, completed at, recorded by

Evidence

Proved in test: n8n execution 1292, 9 of 11 nodes ran in 328 ms.

Ingest scheduled sensor or satellite data feeds

Done by about 10,000 people across 1 job role, several times a day.

On a schedule Every hour, a scheduled data feed pull is due → then Data feed ingested into system

Acts when the record count is more than 0. Otherwise it logs that no new records arrived in this feed, and stops.

Reads

feed id, source name, record count, retrieved at, feed type

Evidence

Proved in test: n8n execution 1211, 10 of 13 nodes ran in 338 ms.