EINS Research and Development Projects:

Which technology a document was printed with (source printer) or whether all pages were produced by the same printer and on the same paper (substrate) is valuable information when detecting document forgery, even if the primary security features were successfully copied. 
This is where the "MLForPrint" project comes in: However, while manual forensic document examination can take hours and requires the examiner's many years of experience and is therefore comparatively rarely used, the project uses automated procedures based on machine learning for this purpose. 
The goal is that a software-based and automated examination of printed products and substrates can bring about a reduction in the examination effort with comparable accuracy. For this purpose, the project uses neural networks (CNNs), with which it has already been possible to demonstrate in prototype form that it is possible to classify documents efficiently with regard to properties such as printing technology (such as offset, dry/wet toner or ink jet). 
The goals of the "MLforPrint" project are, on the one hand, to research and improve the robustness of the CNN against disturbances that could be specifically used by counterfeiters and, on the other hand, to classify substrates for which a software solution is to be demonstrated for the first time that can derive paper types, aging states and condition predictions from scans. The challenge of a learned, i.e., data-oriented approach is to be able to react quickly to unknown documents and textures. For use in digital forensics, it is further important to improve the explainability of the deployed CNN in order to better understand its decisions and optimize parameters of the network for deployment purposes.

This joint project is funded by the BMBF. Funding measure KMU-innovativ: IKT.

Intelligent tools for a network based manufacturing of the future

The upcoming requirements for dynamic production and logistics processes systems can only be fulfilled by so-called Cyber Physical Systems (CPS), which use integrated intelligent sensors to perceive their environment and actuators with which they can influence them.

CPS can be integrated into products, machinery and equipment, which then can customize itself by self-tuning and reconfiguration to changing orders and operating conditions. Their use represents a paradigm shift in the production and Germany will become the world's leading supplier for Cyber-Physical Systems.

The aim of this project is to develop a cyber-physical system smart tool consisting of an intelligent tool system and its interaction partners in the tool cycle, such as machine tool or instrument. The intelligent tool system is the core innovation of the project.

This cooperative project is funded by the BMBF.

Developing innovative products and production systems:

Manufacturing companies should be encouraged to develop and implement that enable strategic development of product innovations and the development of innovative products and production systems efficient new methods and tools. Technological trends to be identified early in order to tap the development potential for innovations in time.

The EINS GmbH assumes as part of the joint project, in particular the role of a software developer to provide support for the development and implementation of methods and procedures in appropriate software solutions and the development of interfaces to existing systems, which are to be used as part of a technology adaptation process.

This joint project was funded by the BMBF.


OPUR - Original Product Security and Traceability System

Counterfeit products threaten the consumer:

In spring 2006, the world was fighting against bird flu. The company Roche had developed with the drug Tamiflu® a drug that could possibly keep the epidemic in check. A little later appeared fake pharmaceutical packaging in which glucose tablets were. For the consumer, it was practically impossible to identify the packaging and fake drugs.
But in other areas, the counterfeiting of goods has become a sad "growth market".

OPUR -the Original Product Security and Traceability System:

Marking technology against piracy - the already standardized bar codes are designed so that a forgery by the simplest means is reliably detected. It is enough to read the barcode thus generated with a commercial flatbed scanner or mobile phone and check.

This joint project was funded by the BMBF.