Fundamental characteristics, common to all meat transformation processes are the biochemical complexity and cost of the raw material, the difficulty in making objective measurements through non-destructive techniques, and the lack of sensors suitable to describe all the processes.
The project addresses these problems to improve process control capabilities, final product quality and to reduce costs.
The Promeat project achieved several results that can be exploited and applied in meat transformation industry. These results comprise both theoretical developments and prototype implementation.
In the field of food science:
- assessment of the parameters able to characterize the raw material/end product quality
- formalization of the knowledge involved in the cured and cooked ham production.
About process control methodologies:
- identification and experimentation of a raw meat classification methodology based on computer vision
- development of a general knowledge-based system for the process supervision able to integrate data about the classification of the raw material, a priori process knowledge, operator observations (containing qualitative, non-numerical information), on line process data.
About industrial application of the above results:
- realization of prototypes to demonstrate and test the developed modules:
- raw meat classification for cured ham production
- raw meat classification for cooked ham production
- supervision of the aging of the cured ham
- supervision of the production of the cooked ham
- automatic visual evaluation of cooked hams
The prototypes have a highly modular structure, and all modules can run both stand alone and integrated; this flexibility increases the capability to meet market needs.
- validation of the prototypes into industrial sites: slaughterhouses and cured/cooked ham factories.
A system based on computer technology is developed to be integrated within present-day manufacturing installation.
It will improve data collection process supervision and quality control. The implementation of two demonstrators will permit the assessment of system performances into two important meat processing sectors.
Two advanced Information Technology branches, will provide the necessary technological background to address the above problems : Artificial Intelligence and Computer Vision.
The main tasks of the project are :
- to realize a general system architecture allowing reduction of miseconomies and production costs and improving the final product quality both in meat processing and in related industrial sectors
- to develop an innovative data acquisition system, based on computer vision, to measure, in an objective way, meat quality parameters usually evaluated only in subjective manner
- to develop an intelligent module able to integrate input information from multiple sources to support process supervision and quality control
- to experiment and assess the developed prototype system through two demonstrators.
Seven partners from three EEC countries will participate in the proposed project, according to a well-balanced structure showing both a horizontal (among countries) and a vertical one (among technological sectors).
Fields of science
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