Funded projects

As a software solution provider for Manufacturing Excellence, camLine intents to participate in supra-regional funding projects for high-tech companies with industrial production. The many years of experience, know-how, and software components made by camLine provide a good basis for the development of innovative and novel ideas. Furthermore, camLine benefits from these collaborations that affect the company in its future-oriented development.

For projects in many areas, European Union (EU) fundings are available. Intensive research and development (R&D) are not only the basis of economic progress. It rather is a condition that in the future, the European countries will be able to occupy one of the top places in the global high-tech and life science markets. Therefore, the EU promotes activities that help create and save competitive jobs for skilled workers.

PRO-OPT
Smart Data - Innovationen aus Daten
Bundesministerium für Wirtschaft und Energie

PRO-OPT – Big Data Production Optimization in Smart Ecosystems

Harvesting advanced data values in decentralized cooperative organizations

PRO-OPT is a Research and Development project as part of the technology program “Smart Data – Innovations in data” of the German Federal Ministry of Economy and Energy.

The main goal of PRO-OPT is to enable companies in decentralized cooperative structures (Smart Ecosystems) to perform effective and intelligent analysis of large data sets. In production, mainly caused by digitization and automation, an increasing amount of data accumulates. Available data sources are distributed among economically independent ecosystem’s stakeholders, especially as many sub-suppliers are involved in industrial production processes. PRO-OPT develops and evaluates Big Data methods and tools to enable local and global analysis on big data. The solutions are exemplified in the automotive domain, because this industry has a key position in Germany and, as such, has a significant effect on other sectors.

Duration: January 2015-December 2017

Project partners:

  • DSA Daten- und Systemtechnik GmbH (Konsortialführung)
  • AUDI AG
  • camLine GmbH
  • Deutsches Forschungszentrum für Künstliche Intelligenz GmbH
  • Fraunhofer-Institut für Experimentelles Software Engineering IESE
Eniac INTEGRATE project

Eniac INTEGRATE project

Integrated Solutions for Agile Manufacturing in High-mix Semiconductor Fabs

Maintaining and developing a profitable and consistent manufacturing base in Europe is of key strategic relevance both in economic and political terms. The ENIAC JU project INTEGRATE shall enhance the wafer fab efficiency by improving the overall cycle time, decreasing the equipment cost of ownership, enabling simultaneous management of standard and non-standard lots and enhancing product quality. This will be achieved thanks to state of the art advances in manufacturing sciences and to reinforced collaboration within the local/regional ecosystems.

Eniac IMPROVE project

Eniac IMPROVE project

IMPROVE (Implementing Manufacturing science solutions to increase equipment productivity and fab performance) is a focused 36-month project within the "advanced line operations" industrial project of the ENIAC sub-programme SP8 "Equipment & Materials for Nanoelectronics“.

Maintaining the lowering of costs per function, reducing cycle times, improving reproducibility and equipment effectiveness, and reducing the environmental impact of factories are all key challenges. Addressing them successfully is key to enabling European SC manufacturers to maintain their competitiveness. Manufacturing science is the main enabler that will allow these challenges to be overcome.

IMPROVE aims to improve European semiconductor fabs’ efficiency by providing methods and tools to exert better control over process variability, reduce cycle times and enhance the effectiveness of production equipment.

To achieve these objectives, IMPROVE will focus on 3 major development axes:

  • The development of virtual metrology techniques allowing the control of the process at wafer level, whilst suppressing standard metrology steps.
  • The development of predictive equipment behavior techniques to improve process tool reliability, whilst optimizing maintenance frequency and increasing equipment uptime.
  • The development of dynamic risk assessment and dynamic control plan concepts, suppressing unnecessary measurement steps whilst dynamically improving control plan efficiency.