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Digitization of the temperature control unit, FHNW School of Engineering and Environment

School of Engineering and Environment


Innovative, model-based thermal industrial systems: Tool Temp AG and three institutes of engineering at the FHNW realized a novel control technology concept.

Project details

University
FHNW School of Engineering and Environment
Measurement data about the cycle progression is incorporated into a mathematical model architecture to develop model predictive control.

Technologies

  • Predictive process control
  • State variables
  • Injection molding and Moldflow simulation

Background

Tool Temp AG from Sulgen (TG) manufactures temperature control units for the plastic, chemical and pharmaceutical industries. These devices have a robust and simple analog control technology, which, however, has potential for improvement regarding a development and implementation of Industry 4.0 and a digitalized process chain. The realization of an intelligent process control for the temperature control of injection molds should help Tool Temp AG to offer the customer energy-efficient systems with the possibility of online diagnosis, monitoring and control.

The aim of the project was to optimize the temperature control process in injection molding using a simple digital control loop.

Goals

The aim of the project was to optimize the temperature control process in injection molding regarding more energy-efficient use with the aid of a simple digital control loop. Using the findings from filling and temperature field simulations, the respective dependencies of the individual process-dependent and dynamic state variables were to be mapped in a predictive control model and thus the process optimally controlled. A further objective was to include all essential parameters in relation to customer-specific wishes and requirements to enable continuous monitoring of the injection molding process.

Results

Overview of target achievement and outlook

All essential state variables were successfully included in a mathematical model and described with the help of a so-called "predictive control loop". The model-based prediction of the system behavior and the formulation of an optimization task to be solved is carried out for a specific point in time and continues to apply beyond this point based on the findings from many simulations and measurements. In this way, process control can be implemented in a relatively cost-effective manner without significantly interfering with the proven technology of analog temperature control.

Project information

Client

Tool-Temp AG, Sulgen

Execution

Institute of Automation
Chemistry and Bioanalytics
Institute of Polymer Engineering

Duration

2 years

Funding

Innosuisse

Project Team
Prof. Dr. David Zogg, Steffen Thierer, Andreas Zogg, Jonas Asprion, Halime Philipp

School of
Engineering and Environment FHNW University of Applied Sciences and Arts Northwestern Switzerland

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