Abstract
Process control, product quality, and the economics of production are based on decisions process personnel make. Data collected at the factories is exploited in many ways, e.g., in automatic control, problem solving and quality control as well as in maintenance. However, there is as well hidden information, tacit knowledge which can be captured and used to improve the production efficiency by learning from experience. Processes can be improved by the development of a process intelligence concept which integrates mathematical approaches with empirical information systematically collected and exploited. Novelty value of this paper is combination of different types of information to complement each other in context which is based on statistical decision theory so that it facilitates optimal decisions in situation where different types of information are respectively incomplete and uncertain.
Original language | English |
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Title of host publication | Paper Conference and Trade Show 2010 (PaperCon 2010) |
Subtitle of host publication | Atlanta, Georgia, USA, 2-5 May 2010 |
Publisher | TAPPI Press |
Pages | 826-853 |
Volume | 1 |
ISBN (Print) | 978-1-61738-789-0 |
Publication status | Published - 2010 |
MoE publication type | D3 Professional conference proceedings |
Event | Paper Conference and Trade Show, PaperCon 2010 - Atlanta, United States Duration: 2 May 2010 → 5 May 2010 |
Conference
Conference | Paper Conference and Trade Show, PaperCon 2010 |
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Country/Territory | United States |
City | Atlanta |
Period | 2/05/10 → 5/05/10 |
Keywords
- support
- uncertainty
- case-based reasoning
- ontology