At Testify, we have developed a modular kit that allows you to digitally control, document and analyze all types of mobile testing and quality processes.
In this article we will take a closer look at trend analysis in Testify.
To ensure quality in manufacturing processes, monitoring is required throughout the entire production process. With Testify’s reporting packages, you get a significant insight into your data situation through interactive, controllable dashboards with individual filters. This enables you to identify current trends and developments at a glance and make informed decisions based on the data you have collected.
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The trend analysis: detailed default-analysis over time
Identifying course deviations and causes of defects at an early stage is an important tool for controlling and minimizing risks throughout the product life cycle.
The trend analysis shows the number of defaults over time that were recorded within the defined process sections. It allows you to read detailed KPIs of your defects and deviations and allows in-depth analysis of default categories, time history, test objects and associated resolution time.
Use the Trend Chart wherever quality measurements are made and you want to see where the trend is going. For example, within individual process steps such as pre-assembly or for the analysis of parts to be manufactured.
Note that the more information is collected about a defect, the more detailed the analysis can be.
In the trend chart, the values are shown linearly over time. In addition, you can see in the chart:
- Trend line as mean value
- Number of defaults over time
- Upper Control Limit – trend line + standard deviation
- Lower Control Limit – Trendlinie – standard deviation
KPIs
The Key Performance Indicators (KPIs) in the box at the top right of the dashboard show:
- Number of categories of defaults
- Number of defaults
Filter options
One of the main advantages of our reporting dashboards is that very granular data analysis is possible due to the filtering options.
In the trend-chart-dashboard, you can filter according to the following criteria:
- By time period
- By default category
- By status
- By custom fields (e.g. order number)
- By test object type
- By test object
By using the filter criteria “default category”, for example, it is possible to find out for each individual default category in which direction the trend of defects is developing.
If filtered by “test object”, more detailed information on individual process sections or objects, such as pre-assembly or components, can be found out.
List of defaults with detailed information
In the bottom section of the dashboard, you will see the defaults listed. This list includes the following information:
- URL for the default
- Deficiency description
- Description
- Default category
- Test object type
- Test object
- Status
- Due date
- Resolution time
If a due date of a defect is exceeded, the entry is marked in red. This makes it possible to see at a glance which defects are still unprocessed.
Common use cases for trend analysis
- Analysis of individual parts of the manufacturing process according to defaults and default category
- Analysis of components according to defaults and default categories
- Analysis of defects according to further test objects such as order numbers, serial numbers, components, etc.
- Recognition of where optimization is needed and which type of defaults occur frequently
- Data evaluations to get to the bottom of why defects in certain areas or the type of faults occur more frequently
- Evaluations of optimization measures carried out within the framework of the KVPs
This reporting offers the possibility to bring transparency into the processes. Whether a trend is good or bad cannot be answered in a general way. The dashboard offers subject matter experts and data scientists in the company an insight into detailed processes in order to initiate further measures.
To get a holistic picture of deficiencies, an additional view of test cases over time is recommended. These can be evaluated and analyzed in the Quality Control Chart dashboard. This provides a combined analysis of the recording of defaults and the number of test items performed.
Analysis of inspections and results in the control chart
With the help of the quality control chart, you can monitor and continuously check your digital business processes for defined quality characteristics over a defined period of time as part of process analysis or risk analysis.
Checks with intervention & warning limits over time: The control chart compares the recorded data from the workflow with the target values, warning and action limits defined by you. A filter in the background ensures that you are only shown test cases that have target values, warning and action limits stored.
Analysis of measurement results: The detailed analysis of the measurement results with the most important key figures on maximum, minimum, median, average as well as the standard deviation give you useful information and statistical parameters about the recorded values of the selected test case.
Distribution of measurement results: The distribution of the validity of your measurement results is divided into three areas. This allows you to proportionally record the distribution of the numerical measurement results according to action, warning and target ranges at one glance.
Table and KPIs
Colored fields in the table in the columns >OEG and >OWG as well as <UWG and <UEG, setpoint give you information about the range in which the measured value is located.
The Key Performance Indicators (KPIs) in the box at the top right of the dashboard show:
- Number of test cases
- < Warning limit
- < Intervention limit
This way, an informed decision can be made as to whether and to what extent countermeasures need to be taken.
Filter options:
In the Quality Control Chart Dashboard, you can filter according to the following criteria:
- By time period
- By checklist
- By revision
- According to test case
- By test object type and test object
- By identification number
Feel free to contact us, if you want to learn more about Testify.
Conclusion
In this article, we have gone into detail about two of our integrated dashboards, which provide information about the development of defects and test cases and can serve as an early warning system in the context of process optimization. Again, the more structured and comprehensive the data collection, the better detailed analyses can be made. Would you like to analyze trends and developments in quality management in your company as well? Feel free to contact us!
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