TranSIT-Transferable Smart Industry Templates

A significant proportion of the SME companies in our region engineer and assemble custom or small series products. The emphasis is on short lead times and high quality. Quality control is very important. Process improvements are almost always aimed at reducing errors, searches and unnecessary actions. But they don't want to invest in the wrong technology or working methods and are very wary of vendor lock-in or lengthy projects with external consultants. Automation of production steps 'as-such' is, due to the single piece/small series nature, only interesting if the programming effort is limited and the return of investment (ROI) is short.

Early adopter companies are taking steps, e.g., with the use of robots, the use of autonomous transport and image recognition. Examples of SMEs that have successfully implemented Industry 4.0 across the board are scarce. Also, there are no SME best-practice examples available for other SMEs. 

Digitisation in an SME manufacturing company

The dot on the horizon is a fully integrated 'manufacturing system' in which the individual elements are aware of each other, can communicate in real time and collaborate. The physical processes use virtual information to work efficiently and without errors, even with small series or single piece products.

This requires action at the front end of the process: - good product data management; - re-using engineering data; - generating work instructions and production routing; - proper integration of the various engineering and production IT applications (CAD-PDM-ERP-MES) 

During the operation the following is needed: - real-time tracking of products in the system, - generating or storing manufacturing instructions on/via a tag, - the network to communicate between elements in the manufacturing system, etc.

Finally, for monitoring and process improvement there is a need for: - analysing, visualising and using the collected data for process control and improvement; - being able to carry out simulations in advance; - using digital shadows; - integrating (autonomous) transport and logistics in the system, etc.

The crux is to be able to collect and process as much data and information as possible with as little effort as possible. This brings virtualisation of the production system for small series and single pieces for 'First Time Right' within reach.

Transforming best practices into templates

Companies that make very different products have similar questions about the process and can learn from each other without competing. The aim of this project is therefore to develop, share and disclose knowledge on 'how to realise a digital and smart production process' via templates. And in such a way that developed methods, snippets, modules, applications etc. can also work at other companies with products in small series. Companies then run less risk and the necessary knowledge is anchored more broadly than with just the experts in their own organisation. 

Approach & Collaboration

Companies that are interested in collaborating with our lecturer-researchers, students and other companies on the topics listed below are more than welcome to contact us. We will then discuss what is possible and in what form.

• Process analysis and real-time monitoring of the process by means of tags;
• Manufacturability check and risk management tool;
• Simulation model/Digital Shadow of the process;

Team 

• Jenny Coenen, professor of the research group Smart Sustainable Manufacturing, [email protected]
• Rufus Fraanje, Robotics & Vision Minor Coordinator  and researcher within the research group Smart Sustainable Manufacturing, [email protected]
• Wouter Hijink, lecturer Control Engineering, Automation, Control Theory and System Engineering and researcher within the research group Smart Sustainable Manufacturing, [email protected]

We will keep you informed of developments here.

Team 

• Jenny Coenen, lector Smart Sustainable Manufacturing, [email protected]
• Rufus Fraanje, coördinator Robotics & Vision Minor en docent-onderzoeker, [email protected]
• Wouter Hijink, docent BARS (Besturingstechniek, Automatisering, Regeltechniek, Systeemkunde) en docent-onderzoeker, [email protected]

We houden jullie hier op de hoogte van de ontwikkelingen.