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How to Create a Check Sheet

Updated on January 8, 2018
tamarawilhite profile image

Tamara Wilhite is a technical writer, industrial engineer, mother of two, and published sci-fi and horror author.

What Are Check Sheets?

Check sheets are data collection forms used to record the occurrence of defect. A check sheet lets you collect attribute data, turning qualitative data such as an observation that an assembly is damaged into quantitative data.

Qualitative data from check sheets can be tallied to create quantitative data and information you can analyze for Six Sigma projects. Data from check sheets can used to create control charts. The process to convert check sheet data into control charts is discussed toward the end of this article.

Check sheets can turn cosmetic defects into discrete, numerical data you can analyze.
Check sheets can turn cosmetic defects into discrete, numerical data you can analyze. | Source

What Do You Need to Know to Create a Check Sheet?

There are several questions you need to answer before you can create a check sheet.

  1. What attributes will you track? Will you record defects, damage, blemishes or discoloration?
  2. What is the definition of each type of defect you will track? What constitutes a blemish? What do you consider to be a defect? When does discoloration become recordable on your checksheets?
  3. Who is responsible for collecting this data? Will data for the checksheet be captured through visual inspections by quality control staff, or will data be generated by operators as the items come off the assembly line?
  4. How will data be collected? Will you use automated cameras or human observation?
  5. What is the time interval for each check sheet? Will you fill out check sheets each shift, each day or each week?
  6. Who is responsible for collection check sheets when they are completed, if the data isn’t captured electronically? Where will check sheets be kept for tallying, analysis and storage?

What Does a Check Sheet Need to Include?

A check sheet must include the following information.

1. Put the project name or product name prominently on the check sheet. This information ensures that check sheets are only filled out for the correct item.

2. Require the data collector to list where is the data being collected. This could include the production line number, the building, the work site or the CNC machine.

3. Include a field to capture the identity of who is recording the data. This information allows quality staff to look for patterns based on the operator in charge, incomplete data collection by specific individuals or staffers who are better at catching defects than others.

4. The check sheet needs a header column that gives the name of the recorded defects, with a total column for all observations of that defect over the data collection period.

5. Include columns on the check sheet that let you enter information per data collection interval.

Example Check Sheet with Totals

Defect
1-Sep
2-Sep
3-Sep
4-Sep
5-Sep
6-Sep
7-Sep
Total Defects
Blemish
1
3
2
1
5
2
4
18
Crack
2
5
0
2
3
1
0
13
Paint Missing
0
0
0
2
1
5
2
10
Warped
1
4
2
3
2
1
0
13
Total Defects
4
12
4
8
11
9
6
54
In this example check sheet, the number of defects varies per day and in type. However, the check sheet data can be used to create a run chart and control chart to determine the average number of defects and set control limits.

How to Create Control Charts from Checksheet Data

You can create control charts or run charts from check sheet data. Using control charts based on check sheet data allows businesses to properly gauge the rate of defects or flaws and track their quality trends.

Here are the steps to convert qualitative data from check sheets into statistical, quantitative data for control charts.

  1. The central line of the control chart will be the average for the defect being tracked. This central line could be the average number of defects per lot or average defects per day. It could be based on the average number of defects per unit.
  2. The fraction of defective product is used as a central tendency when the lot size varies. If one lot has 3 defects out of 12 products, the fraction defective is 0.25. When another lot is produced and it has 3 defective units out of 10 produced, that lot has 30% or 0.30 defective.
  3. Find the variance for the data set. The square root of the variance is the standard deviation. The control limits will be the average plus or minus 3 times the standard deviation.

Comments

Submit a Comment
  • tamarawilhite profile imageAUTHOR

    Tamara Wilhite 

    7 years ago from Fort Worth, Texas

    These check sheets are for turning reports of qualitative defects like dings on metal chassis, blemished parts or off-color material into data and even SPC charts you can analyze just like average weight or dimensions.

  • rfmoran profile image

    Russ Moran - The Write Stuff 

    7 years ago from Long Island, New York

    This hub could be a very good resource for anyone assessing the hurricane damage and planning repairs.

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