Use Case

Defect production analysis in Visplore

Problem:

Unknown reasons for production of defects

High defect rates incur significant costs and waste precious resources. However, in today’s complex and dynamic manufacturing processes, it is hard or impossible even for process experts to identify reasons for insufficient product quality by sole intuition. Product defects can be caused by many factors along the production line including the material, process parameters, and varying environmental conditions. The size and complexity of all that data makes an analysis tedious and inefficient with conventional statistics and spreadsheet software.

Solution:

Joint visual analysis of process and quality data

The intuitive analysis in Visplore makes it easy and fast for process experts to validate the expected, and to discover unexpected correlations between process characteristics and insufficient quality – often in a matter of a few minutes or even seconds. Flexible, high-performant visualizations of non-aggregated data reveal any type of pattern and process change in periods right before defect production. Intelligent analytical guidance suggests relevant process parameters for further inspection and speeds up the investigation by orders of magnitudes. Linked visualizations make it straightforward to consider effects of different product types or process changes and even allow for including complex data characteristics such as parameter curves from discrete production steps in the analysis. Finally, having the process experts themselves as drivers of an-depth analysis enables them to fully bring in their knowledge, intuition, and experience.

Result:

Actionable insights for reduction of defect rates

Discovering potential root causes for product defects is a major step towards taking informed countermeasures. Gaining this knowledge as early as possible means avoiding costs due to rejects in the future. Insights from effective data visualizations increase the transparency of decisions made and facilitate the communication. The in-depth visual analysis of the own process data with Visplore also fosters a deeper understanding of the own process as a whole. This generates new inspirations for process improvements that may go far beyond the reduction of defects and include, for example, measures to reduce energy consumption.

Defect production analysis in Visplore

Unknown reasons for production of defects

Joint visual analysis of process and quality data

Actionable insights for reduction of defect rates

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