What is a check sheet
A check sheet is a simple, pre-structured form used to record data where and when it happens, just by adding tally marks or numbers. It is one of the seven basic quality tools and usually the first step: before analyzing anything, you need reliable data.
A good check sheet answers three questions without effort: what happened, how many times, and where or when. The data comes out organized and ready to become a Pareto chart or a control chart.
Check sheet visual map
The map shows the sheet layout, the tally of the 52-defect example and the path to the Pareto chart.
The most common types
| Type | What it is for | Example |
|---|---|---|
| Defect type (tally sheet) | Count how often each defect type appears | Scratches, burrs, color, dimension |
| Defect location | Mark on a drawing of the part where the defect occurs | Paint blisters on a coated part |
| Defect cause | Cross defects with machine, shift, operator or material | Defects by machine and by shift |
| Process distribution | Record measurements in ranges and see the histogram shape | Diameters grouped in classes |
| Item verification | Confirm that all steps or items were done | Start-of-shift checklist |
The first three types collect count data. The distribution sheet feeds the histogram, and the item verification sheet is a checklist: it confirms tasks and does not count occurrences.
How to build a check sheet in 7 steps
- Define the goal. What do you want to know? Which defects dominate, at what hour it gets worse, which machine fails most.
- Define what will be counted. Write an operational definition for each defect so that two people classify the same part the same way. Sample photos help. If measurement itself is the problem, see MSA and gauge R&R.
- Define the period and the sample. For example, 50 parts per hour for 4 hours.
- Draw the form. Header with product, line, date, shift, recorder and period; rows with defect types; columns with hours or machines; a total column.
- Add an “Other” row with space to describe, so you do not lose defects you did not foresee.
- Pilot it with a few parts and fix whatever causes doubt.
- Train the people who will fill it in and keep the sheet at the point of collection, with the pen tied to it, not in a folder in the office.
Worked example: 200 parts in one shift
Fictional example: a line making machined and painted parts inspects 50 parts per hour for 4 hours, 200 in total. Each defect found gets a tally mark on its row; the fifth mark strikes through the previous four.
| Defect | Tally | Total | % of defects | Cumulative % |
|---|---|---|---|---|
| Scratches | ||||| ||||| ||||| ||||| ||| | 23 | 44.2 | 44.2 |
| Out-of-tolerance dimension | ||||| ||||| |||| | 14 | 26.9 | 71.2 |
| Burr | ||||| |||| | 9 | 17.3 | 88.5 |
| Color | |||| | 4 | 7.7 | 96.2 |
| Other | || | 2 | 3.8 | 100.0 |
| Total | 52 | 100.0 |
Calculation: 23 + 14 + 9 + 4 + 2 = 52 defects in 200 parts, or 52 ÷ 200 × 100 = 26 defects per 100 parts. (Note this counts defects; one part can have more than one, so it is not the same as the percentage of defective parts.) Scratches account for 23 ÷ 52 = 44.2% and, with dimension, reach 71.2%. That is the order for the Pareto chart.
Now the cross-tabulation by hour, on the same sheet:
| Hour | Parts inspected | Defects | Defects per 100 parts |
|---|---|---|---|
| 1st | 50 | 10 | 20 |
| 2nd | 50 | 14 | 28 |
| 3rd | 50 | 12 | 24 |
| 4th | 50 | 16 | 32 |
| Total | 200 | 52 | 26 |
The rate climbs through the shift (20, 28, 24, 32). That pattern is a clue, not a conclusion: it could be tool wear, operator fatigue or a lot change. Time to investigate with a fishbone diagram and 5 Whys.
Using the collected data well
- From tally to Pareto: sort the totals from largest to smallest and compute the cumulative percentage, as in the table above. Attack the few causes that hold most of the defects first.
- From count to control: to monitor stability, turn the numbers into a proportion and plot a p chart; for continuous measurements use statistical process control.
- Stratify: separate the data by machine, shift, operator and lot before summing. Mixing everything hides the pattern.
- Review the sheet: if “Other” goes above 10 to 15% of records, create a new category.
Common mistakes
- Vague defect definitions that make each inspector count differently.
- Filling the sheet at the end of the shift from memory instead of when the event happens.
- Collecting data without a goal, data nobody will analyze.
- Not recording date, shift, machine and lot, which rules out stratification.
- An overcomplicated sheet with dozens of categories that operators stop filling in.
- Treating the defect count as the percentage of defective parts.
- Not feeding results back to the people who collected: without feedback, data quality drops.
Frequently asked questions
What is a check sheet?
A structured form for recording data where and when it occurs, using simple marks, so the data is ready for analysis.
What is the difference between a check sheet and a checklist?
A check sheet counts occurrences (how many defects, where, when). A checklist confirms whether tasks or items were done.
What are the types of check sheet?
Defect type, defect location, defect cause, process distribution and item verification.
How do you read the tally in the example?
There are 52 defects in 200 parts; scratches (23) and dimension (14) add up to 37, or 71.2% of the total.
How do you go from the check sheet to a Pareto chart?
Sort the totals from largest to smallest, compute each percentage and the cumulative percentage, then plot the bars with the cumulative line.
What sample size should I use?
It depends on the goal and volume. A practical approach is sampling at regular intervals, such as 50 parts an hour, to see variation across the shift.
Sources
- TAGUE, N. R. The Quality Toolbox. Milwaukee: ASQ Quality Press.
- ISHIKAWA, K. Guide to Quality Control. Tokyo: Asian Productivity Organization.
- MONTGOMERY, D. C. Introduction to Statistical Quality Control. Wiley.
- KUME, H. Statistical Methods for Quality Improvement. Tokyo: 3A Corporation.
Keep studying: trusted sources and links
Save this address: Manufatura Enxuta is your school for lean manufacturing. Come back whenever you need to study, with a complete article, a visual map and trusted sources. Follow one of the learning paths or check the A–Z glossary.
Want the tools ready to use?
Download the free "Problem Solving Kit" e-book, with PDCA, A3, 5 Whys and Ishikawa.
Download the e-book
About the author
Lean Manufacturing & Behavioral Management Specialist
Over 20 years in the automotive and metalworking industries (GM and Dana), Lean Manufacturing practitioner since 2006. SENAI instructor and mentor in Brazil’s Brasil Mais Produtivo program, delivering consulting, training and audits for 50+ companies, combining quality, productivity and people development.
