Scalable Industrie 4.0 retrofit solutions

A key function of Industrie 4.0 applications is the acquisition of process data by means of powerful sensor technology. Detailed data collection and evaluation form the basis for increased performance and efficiency.

Implementing Industrie 4.0 applications usually requires cost-intensive investments in new infrastructures as well as the replacement of existing machines due to missing Industrie 4.0 interfaces and insufficiently accessible machine data. More cost-efficient are so-called retrofitting solutions, which functionally upgrade existing machines and integrate them into an Industrie 4.0 network. How this can be implemented conceptually and step by step has been elaborated by Fraunhofer IOSB-INA in cooperation with the VDMA in the Industrie 4.0 Retrofit Guide.

A key function of Industrie 4.0 applications is the acquisition of process data by means of powerful sensor technology. Detailed data collection and evaluation form the basis for increased performance and efficiency.

Implementing Industrie 4.0 applications usually requires cost-intensive investments in new infrastructures as well as the replacement of existing machines due to missing Industrie 4.0 interfaces and insufficiently accessible machine data. More cost-efficient are so-called retrofitting solutions, which functionally upgrade existing machines and integrate them into an Industrie 4.0 network. How this can be implemented conceptually and step by step has been elaborated by Fraunhofer IOSB-INA in cooperation with the VDMA in the Industrie 4.0 Retrofit Guide.

Fraunhofer IOSB-INA develops retrofitting solutions based on intelligent sensor systems, cloud connections and machine learning methods for data analysis. Without high investments, these make it possible to make processes simpler in the future and to gain more transparency, control, plannability, security and flexibility in one's own production. These range from mobile production data acquisition systems in suitcase format for potential studies to permanently installable retrofit solutions. Our machine learning processes ensure intelligent evaluation of your production data.

Our service offer:

• Potential studies for operators of technical systems: We take into account the existing technical infrastructure and specific requirements, while investigating the economic and technical potential through the implementation of retrofitting solutions.
• Design, implementation and integration of retrofitting: The focus is on synchronized measurement acquisition, sensor data fusion and preprocessing, connection to cloud systems and intelligent data analysis.
• Customized training programs: We bring your company up to date with the latest technology and research and train you in the use of retrofitting technologies.

 Core benefits:

• More transparency for your production to optimize and increase the efficiency of your processes
• No high costs for the test and evaluation of Industrie 4.0 retrofit implementations
• Competent consulting for permanent Industrie 4.0 retrofit implementations
• Simplified integration of data analytics and machine learning options
• Knowledge transfer on the topic of Industry 4.0 for your employees

Our mobile production data acquisition systems in suitcase format or even smaller enable us to carry out potential studies for data acquisition and evaluation without high investment costs.

References / Publications:

• VDMA Retrofit Guide for Industry 4.0 
• INAsense: Mobile sensor case for training and analysis
• INArice: Fast (over) instrumentation of larger machines and systems with largely contactless or low-contact sensor technology
• INAcarry 5G: Energy-autonomous sensor data acquisition system for plug&play process data acquisition on machines 
  
• Retrofit potential analysis  and permanent retrofit  for lathes
• Companies Bosch Rexroth and Friedrichs & Rath: Implementation of practical examples on the topic of Industry 4.0 Retrofit. In: VDMA Guide Retrofit for Industry 4.0
• Schulte, Bastian; Flatt, Holger; Schulte, Reinhold; Kleinhans, Chris: Automated quality control: Retrofit for existing plants. atp magazin 08/2022, p. 46 ff, 2022.
• Fraunhofer lead project ML4P, Machine Learning for Production
• ML Center in the Fraunhofer Cluster of Excellence: Cognitive Internet Technologies (CIT)
• Bilateral industry projects on model identification, diagnosis, optimization and predictive maintenance