Objective
On completion of the project, the following deliverables provide an integrated tangible opportunity for exploitation in high-speed production environments:
1. Dynamic weighing sensor and signal processing technology;
2. High-accuracy acoustic structural analysis technologyl;
3. Vision hardware and signal processing technology;
4. Modular multi-sensor neural network technology.
The overall outcome at the end of the Soquetec project is a new 'Sorting and Quality Control Enabling Technology Integrated by Neural Networks'. Several end-user based prototypes of (cost) efficient sorting and quality control machine modules integrated by neural networks for use in high-speed, high accuracy, discrete mass-produced products (industrially tested and optimised).
Focus is on a range of sectors, including eggs, poultry meat, ceramics, seeds, pharmaceuticals, wood.
a. Vision: A high-speed real-time general purpose surface inspection tool for individual but similar production goods, that is able to detect deviations from a predefined ideal model, in a user-settable way, and is also able to return a visually sensible similarity measure between different objects;
b. Acoustics: Industrial or lab scale proved acoustic or vibration sensor concept with advanced signal processing methods offering the possibility to do high-speed online classification of single products in mass production in an industrial environment by contact or contact-free acoustic analysis technology and A.I.-based classifiers;
c. Weighing: Tangible design of high-speed low-cost accurate (wired or wireless) weighing unit based on a high-capacity standard load cell and flexible real-time noise reduction filter technology and matches the end-user requirements;
d. Data fusion: A prototype fusion system (incl. application dependent user interface for the inspection system, signal analysis methods to the SPU, automation of measurement cycles by the use of a script language) in which the results of the sensor data fusion field trials are translated into a fusion system that properly integrates the enabling technology signals for an high-correlated quality control or sorting decision.
Objectives and content
The overall objective of SOQUETEC is the development of technologies and their integration to allow for more efficient quality control & sorting of discrete mass-produced products. These are needed to allow for increased production speeds, which are now limited by the capacity of the quality control / sorting step that is either executed by single-input systems or by labourers. The increased speeds (>0,5m/s) in turn are required by the market, which dictates either very low wages and labour intensive processes, or very high efficiency using affordable automation wherever possible. The latter is the only viable option in Europe, where the wage level is higher than that in the US, Asia or Africa. This ongoing efficiency race is valid in a range of sectors, including (but not limited to) agro-products, pharmaceuticals, ceramics, glassware, gemstones, wood, metal parts, plastic parts, light bulbs, lenses, CRT screens, electronic parts, etc. The technical objectives in this project are focussed on allowing for the use of advanced quality control methods using low-cost hardware and modular software. This objective is concretised for dynamic weighing, for high-resolution vision and for non-contact acoustic analysis of the integrity and composition of discrete products. Furthermore, the integration of various input devices into one decision making neural network system requires innovations in the field of neural network composition, application of these innovations is demonstrated and guided by three 'example systems' that focus each on a type of industry.
The project structure is illustrated by the scheme below:
Main innovations are:? Custom-selectable multi bandwidth / high-resolution vision with C-MOS sensors& low-cost optics? Contact-free acoustic internal structure analysis? Wireless and electronically dampened dynamic weighing technology using regular (cheap) load cells? Self-Organising Maps neural networks that allow for smart integrative decision making using two or three input devices in real-time sorting.
These innovations are end-user driven and also based on detailed insight into the barriers to adoption that exist for highly qualified quality control systems. The work is focussed primarily on end-user driven enabling technology development up to the MTA. After the MTA focus is shifting towards the demonstrator integrative systems and the testing of prototype set-ups under real life conditions. The consortium consists of 1 university (2 faculties), 1 institute, 6 companies involved as technology provider or system integrator, and 3 end-user companies. Close interaction between each of these categories is guaranteed by the project structure. All steps in the production chain are represented: end-users, system integrators, technology suppliers and RTD organisations. Innovative technologies are developed and also validated technically and economically under real life conditions. Partners in the consortium intend to extend their cooperation into the exploitation phase, where cross selling of complementary technologies can create pan-European market coverage even for the smaller partners. Further licensing and agent agreements are planned to realise commercialisation within+2 years after the project. The project aims to participate in the Thematic Network PLAN and contributes to the objectives of Targeted Research Action flexible and clean manufacturing - machine tools. BE97-4794
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering control systems
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering signal processing
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- engineering and technology materials engineering ceramics
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Coordinator
3770 AA Barneveld
Netherlands
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