Q-DAS v13 statistical software

Version 13 broadens the Q-DAS portfolio of web-based software products by introducing Q-DAS RTM Web, a real-time monitoring tool to visualise any kind of attribute, and Q-DAS QCP, a quality control panel to visualise the status of different production processes in a plant. Q-DAS QCP will be the single entry point for all Q-DAS users to start working with the software, providing dashboarding functionality for information and navigation points to start exploring quality matters. The existing browser-based product Q-DAS qs-STAT Web now also features the line selection for a top-down navigation through the production process. 

Users of Q-DAS V13 will benefit from two new options when directly interacting with measuring devices and machines. Q-DAS DS is a dynamic sampling option helping operators already running O-QIS procella to reduce the number of samples to be taken within a certain period by adjusting the optimal sampling period. Q-DAS DI helps to optimise the scope of part inspection programs and is also an optional add-on to Q-DAS O-QIS. It reduces the number of characteristics to be measured in an inspection and thus optimises measurement times.

Q-DAS version 13 also starts to unlock the power of machine learning and artificial intelligence. As an option, users can apply machine learning algorithms to find the best suitable distribution model. Additionally, an innovative Python interface module allows operators to apply machine learning and AI algorithms from any source to process data.

An additional upgrade to the ease of use and efficiency offered with Q-DAS 3D-CAD is the ability to generate a complete Q-DAS inspection plan based on a provided 3D CAD model. The software easily transfers these inspection plans to PC-DMIS, helping operators with part routine creation.

Version 13 makes all Q-DAS statistical software products available on a flexible subscription-based licensing model for the first time. The individual software products also feature a number of usability enhancements, including better support for positional tolerances and multivariate characteristics, new and advanced graphics, and optimised user experience for tablets.