The same number, typed four times
An operator measures a diameter with a digital calliper and writes 25.03 on a paper inspection sheet. At the end of the shift, the sheet goes to the quality office, where someone types the values into a spreadsheet. Once a month, the spreadsheet is copied into a report for the management meeting. When a customer asks about a batch, someone searches the binders.
The value 25.03 has been written or typed four times, by four people, with four chances of error and days of delay. By the time anyone sees a trend in it, the parts have shipped.
What digitalisation means
Digitalisation is the work of replacing paper forms, automating manual routines and removing administrative tasks and distribution steps, while making information available regardless of time and place.
It is more than digitisation, which is simply turning paper into files. Scanning inspection sheets to PDF digitises them; it does not change the way of working. Digitalisation changes the flow: who records what, where it goes and who can use it.
What changes for quality data
When the value is recorded digitally at the point of measurement, several things change at once:
- One entry. The value is recorded once, ideally read directly from the gauge or machine, and used from there in the check, the chart and the report.
- Immediate feedback. A value outside a limit can be flagged as it is entered, and a control chart can be updated in real time instead of at the end of the month.
- Context is kept. Operator, order, machine and time can be attached automatically as annotations, instead of being lost in the margin of a sheet.
- History is searchable. Answering a customer about a batch becomes a search, not an afternoon in the archive.
- Evidence is easier to keep. ISO 9001:2015 (clause 7.5) requires documented information to be controlled, available and protected. Digital records make that easier to do consistently.
Worked example
Illustrative figures for a cell with 40 measured values per shift on paper:
- Writing values by hand: about 10 seconds each, 7 minutes per shift.
- Typing them into a spreadsheet later: about 5 seconds each plus checking, 5 minutes per shift.
- Errors: if one value in two hundred is mistyped, the cell produces about three wrong values a week on three shifts over five days (600 values).
With values read directly from the gauge, the typing step and its errors disappear, and the values reach the chart in seconds instead of a day. Your own figures will differ; it is worth counting them before you start, because they become the baseline for judging the result.
How to start
- Pick one flow. Choose a concrete problem, for example inspection sheets at one cell or calibration records, rather than “digitalise quality”.
- Map it as it is. Follow a value from measurement to final use, and note every copy, wait and hand-over.
- Remove steps, not just paper. If a digital form is printed, signed and scanned, nothing has been gained.
- Involve the people who do the work. Operators know where the current flow breaks down, and a tool that slows them down will not be used.
- Connect what exists. Gauges, machines and business systems often hold data that can be read rather than retyped.
Limitations and pitfalls
- Bad data stays bad. A digital system collects poor measurements just as efficiently as good ones. Measurement system analysis still applies.
- More data is not more insight. Decide what decisions the data should support before collecting everything.
- Systems that do not talk. Several digital islands can recreate the retyping problem, only between screens. Think about how values move between systems.
Digitalisation is also the foundation for what is described as Industry 4.0: connected equipment and systems are only useful if the information in them is digital in the first place.
In short
Digitalisation is about the flow of information, not the medium. Record each value once, keep its context, make it available at once, and remove the steps that only existed to move paper around.
