The 7 basic quality tools are a set of simple charts and forms brought together by Kaoru Ishikawa and spread by JUSE, the Union of Japanese Scientists and Engineers, through the quality control circles of Japanese factories from the 1960s on. The idea was that anyone on the shop floor, with no training in statistics, could collect data, see the problem and follow the solution.
Each tool answers one question: where and how often something happens, which few problems weigh the most, what the possible causes are, how the values are distributed, whether two things move together, whether the process is stable and whether the groups behave differently. Below, each one has its own page where you paste your data and download the finished chart.
What it is for: Record quickly and in a standard way how often each defect or event happens, already organized for analysis.
When to use it: At the start of any study, when the data do not exist yet or are scattered in notes.
The inspector makes a tally mark for each rejected part under each defect type (flash, bubble, scratch) and each shift, for two weeks.
What it is for: Rank problems from largest to smallest and show the few items that account for most of the losses.
When to use it: To choose where to act first, when there are many types of defect, stoppage or complaint.
Of the filler’s 12 stoppage causes, three (reel change, missing caps and jams) make up 78% of the downtime.
What it is for: Organize the possible causes of a problem by category (machine, method, material, manpower, measurement, environment).
When to use it: After choosing the problem with the Pareto, in a session with the people who know the process, before trying out solutions.
The team lists 25 possible causes for sheet thickness deviation and votes for the 4 most likely ones to check with data.
What it is for: Show how the values of a measurement are distributed: where the center is, how much they vary and what shape they have.
When to use it: To compare the variation with the specification and to spot mixed machines, cut-off data or strange values.
The histogram of 200 shaft diameters shows two peaks: the two machines making the part are set at different points.
What it is for: See whether two variables move together and how strongly, plotting one point per pair of values.
When to use it: To confirm with data a cause raised on the fishbone or to find the setting that controls a characteristic.
Tool feed on the X axis and roughness on Y: the cloud rises with r = 0.85, and the worn insert sits above the new one.
What it is for: Follow the process over time with limits computed from its own variation, separating common causes from special causes.
When to use it: To know whether the process is stable, to react only to real signals and to hold the gain after an improvement.
The X̄-R chart of fill weight shows a point above the limit every Monday morning, after the doser is cleaned.
What it is for: Split the data by source (machine, shift, supplier, operator, lot) to find where the problem really is.
When to use it: Whenever the data come from different sources; it applies to any of the other tools, such as a Pareto by shift or a histogram by machine.
The overall defect Pareto looks balanced, but split by shift it shows that 70% of the bubbles come from the night shift.
Use it in: Pareto chart, Histogram, Scatter plot
The tools pay off more in sequence than on their own. In the Plan step of PDCA (Define, Measure and Analyze in DMAIC), the check sheet produces the data, the Pareto picks the problem, the fishbone gathers the causes, and the histogram, scatter diagram and stratification show which causes the data confirm. In Do and Check (Improve), the run chart and histogram compare before and after. In Act (Control), the control chart holds the gain and warns when something changes.
Compares several groups side by side (median, quartiles and outliers) in little space; good for machines, shifts or suppliers.
Values in time order with the median; it shows whether an improvement shifted the process even before there are enough data for a control chart.
Shows how a starting value becomes the final one, item by item: OEE losses, price to profit or budget to actual.
Check sheet, Pareto chart, fishbone (cause-and-effect) diagram, histogram, scatter diagram, control chart and stratification. Some lists swap stratification for the flowchart or the run chart; the idea of the set is the same.
The set was organized by Kaoru Ishikawa and promoted by JUSE through Japan’s quality control circles from the 1960s on. Several tools are older (the Pareto and Shewhart’s control chart, for example); the contribution was bringing them together in plain language for everyone in the plant.
A common sequence is: check sheet to collect, Pareto to choose the problem, fishbone to list causes, stratification, histogram and scatter to confirm them, and control chart to hold the result. You do not have to use all of them on every problem.
No. The 7 tools were designed for people with no statistics training: count, sort, draw and look at the chart. When a decision needs more rigor, the full-analysis pages (capability, ANOVA, regression, hypothesis tests) are linked from each tool.
ISO 9001 requires analysis and evaluation of data and corrective action based on causes, and these tools are the most common way to do it. In Six Sigma they appear mainly in the Measure, Analyze and Control phases of DMAIC.
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