Duerr introduces new software for better first-run rate
22 Jul 2022
3 Min Read
CW Team
Higher first-run rate, less rework, systematic fault analysis: DXQplant.analytics helps paint shop operators improve production quality and effectiveness. The latest software tool from D眉rr鈥檚 DXQanalyze product family detects systematic fault patterns and their causes early, making it much easier to find the relevant fault source. AI algorithms and data-driven machine learning make this possible.
With the Advanced Analytics module, the first market-ready AI application for paint shops, DXQplant.analytics has access to a wealth of data for fault analysis. The software can then detect whether the fault is a one-time or systematic issue, such as recurring quality defects with particular colours. Data from recognized patterns can identify the process step responsible for the fault. This makes it possible to analyse systematic production quality deficiencies, which can be hard to recognise, and quickly identify and fix their causes.
Simplified detection and cause analysis make it possible to avoid the fault in the future and increase the first-run rate.
The basis of DXQplant.analytics is quality information recorded digitally for each workpiece during the surface inspection. In addition, process parameters, alarms, and anomalies from the individual processing steps supplement the workpiece-related data records. This creates a digital file for each body that models the entire production and life cycle, including any faults found. Machine learning can help identify patterns and correlations in data records. If there are frequent contaminants in the paint, the software will detect this and immediately assign information about the underlying cause to the fault pattern.
Detecting recurring paint defects is very laborious, and locating faults is time-consuming and expensive. DXQplant.analytics flags problematic fault sources to the quality manager and provides targeted help with analysing the cause. Correlating graphics and automatically generated reports easily document insights to share with colleagues, workers, and management. Integrated documentation functions allow the DXQplant.analytics user to save and manage defined optimisation measures and track their impact on quality. Therefore, DXQplant.analytics helps the paint shop operator increase the first-run rate in a targeted way, thus boosting overall equipment effectiveness.
Software solutions must always be kept up to date for users to leverage their full potential. With DXQsupport, Duerr offers its customers a comprehensive service package for use and maintenance of its digital solutions. Providing support for the entire software life cycle increases availability, performance and quality and maintains them at this level. In addition to regular updates, Duerr offers a team of experts who constantly monitor live production activity to react quickly in the event of failures or irregularities. These services are complemented by a comprehensive modular training catalogue, allowing operators to leverage the full potential of their digital portfolio.
Higher first-run rate, less rework, systematic fault analysis: DXQplant.analytics helps paint shop operators improve production quality and effectiveness. The latest software tool from D眉rr鈥檚 DXQanalyze product family detects systematic fault patterns and their causes early, making it much easier to find the relevant fault source. AI algorithms and data-driven machine learning make this possible.
With the Advanced Analytics module, the first market-ready AI application for paint shops, DXQplant.analytics has access to a wealth of data for fault analysis. The software can then detect whether the fault is a one-time or systematic issue, such as recurring quality defects with particular colours. Data from recognized patterns can identify the process step responsible for the fault. This makes it possible to analyse systematic production quality deficiencies, which can be hard to recognise, and quickly identify and fix their causes.
Simplified detection and cause analysis make it possible to avoid the fault in the future and increase the first-run rate.
The basis of DXQplant.analytics is quality information recorded digitally for each workpiece during the surface inspection. In addition, process parameters, alarms, and anomalies from the individual processing steps supplement the workpiece-related data records. This creates a digital file for each body that models the entire production and life cycle, including any faults found. Machine learning can help identify patterns and correlations in data records. If there are frequent contaminants in the paint, the software will detect this and immediately assign information about the underlying cause to the fault pattern.
Detecting recurring paint defects is very laborious, and locating faults is time-consuming and expensive. DXQplant.analytics flags problematic fault sources to the quality manager and provides targeted help with analysing the cause. Correlating graphics and automatically generated reports easily document insights to share with colleagues, workers, and management. Integrated documentation functions allow the DXQplant.analytics user to save and manage defined optimisation measures and track their impact on quality. Therefore, DXQplant.analytics helps the paint shop operator increase the first-run rate in a targeted way, thus boosting overall equipment effectiveness.
Software solutions must always be kept up to date for users to leverage their full potential. With DXQsupport, Duerr offers its customers a comprehensive service package for use and maintenance of its digital solutions. Providing support for the entire software life cycle increases availability, performance and quality and maintains them at this level. In addition to regular updates, Duerr offers a team of experts who constantly monitor live production activity to react quickly in the event of failures or irregularities. These services are complemented by a comprehensive modular training catalogue, allowing operators to leverage the full potential of their digital portfolio.
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