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Design assistance for applying pattern recognition to continuous improvement goals
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Detecting and learning from patterns and trends in data, processes, and asset conditions allows organizations to improve their production processes and maintenance practices.
Digging through this information to find a problem and then its solution can be an impossible task, and trying to master the information to make decisions is becoming more and more difficult.
An unplanned downtime event in a mining/refining process is expensive and undesirable. The time and money spent to react to these downtime events is hard to recover. We at Ciner are successfully using Falkonry’s Pattern Recognition technology to create a proactive vs reactive approach to avoiding unplanned downtime events. Falkonry recognizes patterns in our operation that precede unplanned downtime events. This proactive intelligence approach combined with operator training will allow us to avoid unplanned downtime adding cost savings for some process-critical equipment. Falkony leverages the knowledge of operation subject matter experts making for rapid development and deployment. We are adding value and meaning to our data collection, and promoting more efficient use of operation resources with the help of Falkonry.
With technologies like Falkonry Service, which provide real-time pattern recognition across complex processes, we empower our process engineers to impact process operations through early awareness of known good or bad states and more importantly new or unknown operating states. Falkonry Service – in combination with PI Asset Framework - eliminates the need for additional software development or custom data science projects and makes available deep insights to allow for more focused, meaningful actions.