Objective
IQ created a system to optimise the ultimate quality of end-products by harmonising the needs of process quality control, maintenance, and customer after-sales servicing. In principle on-line quality control (and optimisation, which is closely allied), maintenance and customer return reports share large amounts of information, and can contribute information to each other: for instance a customer return may indicate the need for maintenance of a particular machine. For historical reasons normally they are not integrated, and opportunities for improving in all three areas are lost: IQ rectified this omission. This is demonstrated in the two markedly different fields of pulp/paper manufacture (Portucel Viana) and tyre manufacture (Pirelli), which stress different aspects of the problem, in order to develop a generic tool capable of application in most production industries.
The system developed incorporates data acquisition (from PLC systems in the case of Portucel, and from corporate databases in the Pirelli case) linked to intelligent fault diagnosis support. It includes a common case database to store relevant historic results from both product and process diagnosis. It includes reliability and quality-oriented analysis tools and it uses a conceptual clustering module, capable of learning by observation and generalising from the data gathered by process monitoring, product quality assessment and customer after-sales follow-up. The system works on data made available by the partners and has been validated in the pulp production of Portucel Viana and in the Pirelli tyre plant as Izmit.
The goal of IQ is to create a system to optimise the ultimate quality of end products by harmonising the needs of process maintenance, quality assurance and customer after-sales servicing. IQ will develop an integrated on-line approach based on recent advances in Artificial Intelligence, particularly in what is known as Data Mining or Knowledge Discovery. As the name intends to convey, the work in this area is concerned with uncovering information and detecting patterns in large amounts of accumulated data buried in databases. This powerful technique will allow the merger of the three activities mentioned above within an overall system of manageable complexity. Q will incorporate Data Acquisition and PLC Systems linked to intelligent Fault Diagnostics support. It will include a common Database to store all historic results from both product and process diagnosis. It will comprise Reliability and Quality-oriented analysis tools and, finally, it will make use of a Conceptual Clustering Module, capable of learning by observation and generalising from the data gathered by process monitoring, product quality assessment and customer after-sales follow-up. IQ will work on data made available by the partners and will be tested and validated in the pulp and paper and tyre plants of two of the participants.
IQ will lead to a cut in the number of machine interventions, a rise in production quality and turnover, and an increase in profit margins.
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.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences databases
- natural sciences computer and information sciences data science data mining
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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Coordinator
20126 Milano
Italy
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