Übelacker David Multifactorial monitoring rules for industrial multi-stage forming processes “MultiiMePro“

Multifactorial monitoring rules for industrial multi-stage forming processes “MultiiMePro” (HA-Project-No.: 485/15-27)

 

Motivation

Industrial forming processes are characterized by an increasing component complexity and a rising cost pressure. Typically, these processes are multi-stage processes with more than one machining step. Characteristics of automatically linked processes are high investment costs and a high productivity. Because of the high quality requirements and penalty payments, the avoidance of faulty parts has an important role. Therefore, the knowledge of the mechanisms of error emergence and propagation in interlinked stages is indispensable to avoid cost-intensive production losses. A robust process monitoring can prevent these negative aspects.

Aim

The aim of this project is to realize a safe process monitoring system based on simple monitoring algorithms.

Methodical approach

Based on the process monitoring technology of the ConSenses GmbH and with the collaboration of the Werner Schmid GmbH and the VACUUMSCHMELZE GmbH & Co. KG as well as the PtU, three different types of monitoring rules shall be investigated and tested. With a combination of these different rules a universal process monitoring system can be realized:

1. Type: Simple rules

Force signal from a single measuring point can be monitored with one or more rules. Thereby, actual force values can be compared and analyzed with known force values of a good part. An alert or a shutdown of the machine follows, if it is necessary.

2. Type: Value-added rules

Additional information can be observed when using several measuring points in one stage. Several measured values can be compared and cleared against each other. As well as described above an alert or a shutdown of the machine can be the consequence.

3. Type: Follower rules

Several measuring points in different process stages generate additional information. This information can be used to recognize wear mechanisms and healing processes in higher process stages. This enables a comprehensive view on the mechanisms of error emergence and propagation in interlinked stages

Acknowledgment

The research project is funded via the Hessen Agentur GmbH by the State of Hessen.