OEE increase – Productivity maximization through intelligent data analysis in sheet metal processing 4.0 – Secured second-order learning of maximum productivity (21572N)
The “Productivity Maximization” project is dedicated to the challenge of systematically increasing the number of strokes of progressive dies and, subsequently, increasing productivity. Within the scope of this project, an industry-oriented, modular progressive die is being developed and equipped with multiple sensors. The primary objective is to identify dynamic effects that lead to process limits and the associated process parameters in the areas of machine and periphery, tool, semi-finished product and process. From these effects, action strategies for improvements, such as optimization or replacement of tool components, are then derived and validated in an industrial environment.
Multi-stage forming processes often represent the most economically significant part of the value chain. Progressive dies combine a large number of forming processes with almost simultaneous engagement of the tools in a single press stroke. The range of parts produced by this process covers a wide range in machine, electronics and automotive manufacturing.
In the industrial environment, progressive dies are operated on presses at 20-100 strokes/min. High performance stamping presses, by contrast, perform with up to 2.000 strokes/min. The reason for the discrepancy between actual and theoretical speed is a large number of manipulated and disruptive variables for the progressive die, whose complexity increases with the number of stages. The determination of the maximum permissible speed is currently based on employee-defined know-how and is usually chosen conservatively in order to ensure part quality and to protect the tool and machine.
The aim of the project is to gain a better understanding of dynamic effects in progressive dies in order to derive suitable countermeasures for the increase in the speed thus to extend the currently existing process limits.
The method can be seen in figure 1. Within the scope of the project, a multisensory and modular progressive die within the industrial standard will be developed and put into operation. In order to make dynamic effects in the operation of the progressive die visible, the recording of relevant process variables by means of suitable sensor technology is necessary. Sensor selection, positioning and integration as well as data analysis play a key role.
In test series, critical machine, tool and process components are identified by introducing artificial detuning into the system. The process data obtained in this way are used for the targeted differentiation of faulty process states, their cause and the derivation of suitable countermeasures.
The results are used to derive action guidelines for sensor selection and integration as well as a catalogue for tool components to extend the process limits.
The presented research work takes place within the framework of IGF project no. 21572N of the research association Europäische Forschungsgesellschaft für Blechverarbeitung e.V. (EFB). It is funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK) through the German Federation of Industrial Research Associations (AiF) as part of the program for the promotion of Industrial Collective Research (IGF) based on a resolution of the German Bundestag.
We like to thank all industrial partners who support the research project “Productivity Maximization” in the project accompanying committee.