Location: 73035 Göppingen, Germany · Industry: Mechanical engineering, hydrostatic systems, precision machines, plant construction · Products: Hydrostatic guides, spindles, bearings, rotary tables and precision components for machine tools · ERP: Unipps · Website: https://www.hyprostatik.de · S4P modules: FELIOS|BDE powered by 4BDE
Initial situation
Manufacturing at Hyprostatik Schönfeld GmbH, with around 150 employees, is characterised by complex processes and high quality requirements in the production of hydrostatic guides and precision machines. With Unipps as the central ERP data source, the goal was to link production and shop-floor data collection more closely and increase transparency across the factory floor. Hydrostatic spindles, bearings and rotary tables require the highest manufacturing precision and a reliable documentation of all production processes.
Challenge
Without continuous, up-to-date capture of production data, actual manufacturing progress and potential delays were difficult to monitor in a timely manner. The objective was to capture operating data directly in the manufacturing process and evaluate it transparently. Integration with Unipps had to be seamless while also enabling connectivity to the existing APS planning system, so that planning and feedback could be combined in a single, unbroken data chain.
Solution
To optimise its manufacturing processes, Hyprostatik Schönfeld GmbH relies on FELIOS|BDE powered by 4BDE. Through integration with the ERP system Unipps and the FELIOS|APS planning system, order, manufacturing and operating data are used end-to-end to enable reliable shop-floor data collection and transparent production control. Operators report order times and quantities at the shop-floor terminal; data flows automatically back into Unipps. Shift supervisors receive an up-to-date overview of order progress and capacity utilisation.
Results and benefits
With the S4P solution, Hyprostatik Schönfeld GmbH achieved significantly higher transparency in manufacturing. Production data is captured in real time, processes are better understood, and deadlines are met more reliably – resulting in improved on-time delivery and efficiency. Manual feedback effort was reduced, data quality in Unipps improved, and a solid basis for evaluations and continuous process optimisation in precision machine manufacturing was established.