Welcome to Smart Manufacturing
Process excellence needs
more than just KPIs
Your production processes are the heart of your enterprise. Rely on specialized technology and state-of-the-art methods for analysis and optimization of those processes. Our process mining platform IQ/A brings your production process excellence to the next level by leveraging process mining and artificial intelligence methods. IQ/A integrates seamlessly into your IT infrastructure and incorporates existing data pools as well as your experts’ domain knowledge.
Process Mining and AI for the shop floor
Get to the bottom of your production processes
No matter what you produce, the complexity of your production processes is enormous – and so is the array of automation technology, monitoring, planning and scheduling software you already use. But can you ensure that your process flows are truly optimal?
IQ/A uses process mining methods to automatically create a digital twin of your production processes based on real event data. In combination with artificial intelligence methods, especially machine learning, even large amounts of data are analyzed, process inefficiencies can be identified and effects on the overall process can be predicted.
IQ/A enables both retrospective analyses based on historical data and continuous operational support of your live production systems. To achieve this, IQ/A can be seamlessly connected to a wide variety of IT systems such as Manufacturing Execution Systems (MES), ERP or SCADA to enable comprehensive optimization across all automation levels and also include adjacent value-added areas.
Your benefits from IQ/A
Get the most out of your business
With IQ/A, we have developed a platform that seamlessly integrates into your existing processes and IT landscape and provides live support for your production management. What you gain:
understand your production processes down to the automation level and identify inefficiencies, anomalies and planning errors
through continuous detection and fixing of deviations, inefficiencies, bottlenecks and planning errors
through identification of root causes, forecasts and actionable decision support
through transparency on carbon footprint and energy demand per product as well as rapid identification of quality defects
by creating transparent, flexible and efficient processes in order to be able to react quickly to changing requirements and circumstances