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Process mining is a family of techniques used to analyze event data in order to understand and improve operational processes. Part of the fields of data science and process management, process mining is generally built on logs that contain case id, a unique identifier for a particular process instance; an activity, a description of the event that is occurring; a timestamp; and sometimes other ...
Business process discovery (BPD) related to business process management and process mining is a set of techniques that manually or automatically construct a representation of an organisations' current business processes and their major process variations. These techniques use data recorded in the existing organisational methods of work ...
The outer circle in the diagram symbolizes the cyclic nature of data mining itself. A data mining process continues after a solution has been deployed. The lessons learned during the process can trigger new, often more focused business questions, and subsequent data mining processes will benefit from the experiences of previous ones.
These elements are used in event-driven process chain diagrams: Event Events are passive elements in event-driven process chains. They describe under what circumstances a function or a process works or which state a function or a process results in. Examples of events are "requirement captured", "material in stock", etc.
Although heap leaching is a low cost-process, it normally has recovery rates of 60-70%. It is normally most profitable with low-grade ores. Higher-grade ores are usually put through more complex milling processes where higher recoveries justify the extra cost. The process chosen depends on the properties of the ore. The final product is cathode ...
Mineral processing is the process of separating commercially valuable minerals from their ores in the field of extractive metallurgy. [1] Depending on the processes used in each instance, it is often referred to as ore dressing or ore milling .
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