In modern production, intelligent data management with acquisition, storage and evaluation of all production data and parameters provides the basis for optimization of production processes and for seamless traceability.


Traceability of process and component data

Integrated test processes are of crucial importance, especially in the production of safety-relevant components. Detailed data management must be established in order to be able to trace the production parameters and the results of the test in retrospect. Data acquisition by integrated testing systems and transmission to a higher-level production control system ensure 100 percent traceability of production parameters and component data.

Among other things, the results of electrical and optical tests are stored here, joining forces and paths are documented, laser welding parameters are evaluated and stored, and general information on the product - such as part number, production time, product variant, and much more - is saved. - is saved. This data is transferred from the production system to a higher-level, so-called Manufacturing Execution System (MES). Using a serial number on the component, production data can be checked even years later in order to make a reliable statement about correct assembly or the delivery of a qualitatively flawless component.


Optimizing production by networking plant components and intelligently adapting processes

Intelligent data management also enables the networking of individual plant components. For example, the pre-production section of a line communicates with the main line and adapts the production flow to the current requirements of the main line. Thanks to the communication of the individual sections and the linking via buffer systems, the production flow is optimized and the productivity of the entire plant is increased.

The processes themselves can also be optimized through functioning data management and the return flow of information values. In this way, processes are developed that optimize the production process on the basis of data from components produced in advance. In the process, accumulating process data (such as joining forces or torque values) are intelligently evaluated. In other words, not only individual components are considered, but also the trend of the last 50 or 100 parts produced. Based on the results, upstream or downstream processes automatically adapt to changed conditions. This may be necessary, for example, in the case of different batches of components to be processed. The aim here is to avoid manual adjustment work in the event of product and process fluctuations in order to minimize downtimes. It also counteracts the effects of wear on certain components, which extends maintenance intervals and reduces scrap rates.


Lessons Learned – Data management as a basis for process optimization for downstream equipment

Sophisticated data management also reveals the potential for optimization at plants. The production data over a certain running time serves as a basis for discussion for future optimizations on the plant itself or also on downstream plants. Intelligent software tools can also be used to view, evaluate and optimize individual stations. In this way, we work together with our customers to continuously increase productivity in automated production.