HANNOVER MESSE 2019,
01 - 05 April
PSI FLS Fuzzy Logik & Neuro Systeme GmbH
Deep Qualicision efficiently learns how to set decision-making and optimization algorithm (EOA) parameters so that nearly any EOA method that works on business process data can auto-adjust itself. The core of Deep Qualicision is a machine learning method based on the automatic detection of KPI conflicting goals in business process data using extended fuzzy logic. The goal conflict analysis helps to organize the process data in such a way that the Deep Qualicision algorithm can independently recognize in which situations how to label. Data directly labeled by human analysts (data scientists) is not needed anymore. The manual assignment (manual labeling) whether the available data led to good or to bad KPI results in the process, is automatically taken over by the analysis of qualitative optimizations.
PSIaps is a comprehensive solution for production planning. The software was designed to meet the complex requirements of the process industry. PSIaps supports the ...
PSIpep makes staff planning easy. The software's interactive planning table enables the planner to do detailed shift planning based on staff availability and demand. ...
Software for prognosis decisions and forecasts.
Global market conditions have an increasing influence on a company's mid-term and long-term sales expectations. ...
Software for sequencing on planning and productive level e.g. in automotive industry, transport content optimization, production control in ERP environments and process automation.
Qualicision is our basic software module developed for solving multi-criteria decision support tasks. Working with focused evaluation of soft and hard facts, the ...
Qualicision-Imaging-Systems can be used as inspection systems in the field of active quality control. Here an example from the automotive supplier industry: in a ...