The seven quality tools (Q7) go back to the father of Japanese quality control, Prof. Ishikawa Kaoru. He compiled them for dealing with quality problems in business processes.
The quality tools have two uses: defect detection and defect analysis. Defect collection lists, histograms and control charts are used for defect recording. Pareto diagrams, flow charts, correlation diagrams and cause-and-effect diagrams are used for error analysis.
Q1 – The error collection card.
The error collection card or list is a frequently used method for evaluating counting tests. Tally lists are a tool for recording data. The error summary list does not contain any measured values, but only the number of errors. The number is entered in a tally list in a table that contains the error designation and the number of error possibilities.
In many cases, it is possible to make statements about error frequencies after a short time. The causes of errors can be derived from this. An error collection list is therefore the basis for statistical evaluations and analyses. The information in a defect collection list is usually evaluated using the Pareto diagram.
Advantages of an error collection list:
– Simple list
– Data can be easily visualized
– Error trends can be identified at an early stage
– Error lists are quickly understood by employees
– Focal points and causes of errors are quickly identified
Disadvantages of an error collection list:
– No analysis of error causes possible
– Clarity decreases with increasing number of recorded error types
As a prerequisite for the format of the error list must/must:
– Problem must be defined
– Known error types must be listed
– Space must be left for “Other errors”
– Recording location and time must be defined
– Sample size must be defined
Q2 – the histogram.
A histogram is a graphical representation of a frequency distribution of measurement data over a certain period of time. It is a bar chart that shows a frequency distribution of metrically scaled characteristics. It is based on data ordered by size and divides the entire sample area into k areas, which are called classes.
The numerical value that separates two classes is called the class boundary. Class boundaries are particularly important, as a poor choice of these boundaries can severely distort the facts and the information from the measurement data is lost.
The results displayed using the histogram allow a comparison to be made between the actual values and the target values. The classification and visualization of the frequency distribution make it possible, for example, to positively influence future process behavior with regard to the target value. It is this visual information in particular that creates added value for the viewer with this tool, as this cannot be derived from pure measurement data. Difficulties may be expected with an unfavorably selected class division
Advantages:
- Large amounts of data can be summarized in one image
- It is easy to understand
Disadvantages:
- It is limited to metric data
- No root cause analysis possible
Q3 – The quality control chart.
A quality control chart is a form for the graphical representation of statistical characteristic values for a series of samples with action limits (upper and/or lower) and often also with warning limits and a center line. The quality control charts show whether the changing individual values of a repetitive process are within tolerated limits. If defined limits are exceeded, the process must be regulated.
In the case of quality control charts for counting characteristics, a certain number of errors are already taken into account in advance, as they do not warn of negative process changes until they have occurred. They therefore only show the proportion of products that are not OK. This is a major disadvantage compared to control charts for continuous characteristics. These charts also show the direction and size of the scatter.
Advantages:
- Time recording of the process flow
- Statistically sound
Disadvantages:
- No error analysis
- Training is required
- No short-term results
Q4 – The Pareto diagram.
The Pareto principle states that the majority of the effects of a problem, around 80%, can often be attributed to a small number, around 20%, of causes. The Pareto diagram and the subsequent Pareto analysis are used to organize existing data, e.g. in a tally list, according to their importance and to derive priorities from them. The characteristics are ordered either by impact or frequency, e.g. costs, in descending order of size.
The aim of this analysis is to identify the cause and weighting and to initiate measures to solve or improve the problem according to their priorities.
It makes sense to tackle the biggest, most important or most cost-intensive problem first. The application of the Pareto diagram is relatively easy to understand and implement. Difficulties can arise due to many different types of errors that require classification.
Advantages:
- Important errors are highlighted
- Can use data from different sources
Q5 – The correlation diagram.
The correlation diagram (scatter diagram) graphically depicts the relationship between two statistical characteristics. A pair of values forms a point. After entering the values in a Cartesian coordinate system, an accumulation of values is obtained, which in turn provide conclusions about statistical correlations. There are different types of correlation depending on scattering and tendency.
The correlation diagram can be used to make a simple statement about the strength and direction of an interaction. Linear relationships are the quickest and easiest to investigate. Another positive aspect is that a suspected cause-and-effect relationship determined by a cause-and-effect diagram can be checked and thus refuted or confirmed.
Advantages:
- The diagram can be created from 30 data pairs
- Examines the direction and strength of a correlation
Disadvantages:
- Exact calculation is mathematically complex
- Spurious correlations are possible
Q6 – The flow chart.
The flowchart is often used to illustrate processes and procedures. First and foremost, the flowchart is used to gain an initial visual impression of processes. This shows where there are superfluous or missing process steps that can subsequently be adapted.
Advantages:
- Comprehensible visualization through simple symbols
- High level of detail
- No previous knowledge necessary
Disadvantages:
- Plenty of room for interpretation, as there is a lot of freedom in design
Q7 – Cause-effect diagram / Ishikawa diagram / Fishbone diagram.
The Ishikawa diagram, invented by the father of Japanese quality control, Prof. Ishikawa Kaoru, and named after him, is a cause-and-effect diagram. Other common names are fishbone diagram or fishbone diagram.
It is a tool for visualizing a problem-solving process and depicts causal relationships by searching for the primary causes/influences of a problem/effect. It is suitable for analyzing any kind of problem.
The Ishikawa diagram is divided into main groups. Depending on the problem, these can be expanded to make it easier to recognize the dependencies between the individual causes. The analysis is most effective when carried out by an interdisciplinary team. In this way, different aspects are taken into account when identifying causes.
The systematic nature of the Ishikawa diagram and teamwork makes it possible to identify the various causes of the problem. In this way, one-sided approaches or the consideration of interests can be avoided. Further advantages are the number of suggested causes and the recognition of the affiliations and dependencies of the individual causes. Cross-departmental influences can also be recognized through the cooperation of cross-departmental team members.
A disadvantage of using the method for the first time is the attitude of employees who see it as a “gimmick”. This difficulty is quickly overcome with the help of a knowledgeable moderator. Another disadvantage is the rather confusing presentation of complex problems. Dividing the problem into individual problems can be used here as a solution approach. The biggest weakness is that a time dependency cannot be represented.
Advantages:
- Systematic search for the “true causes”
- Visualizes connections and enables further statements by viewing
Disadvantages:
- There is no link between the cause found and the time of occurrence
