In the present time, there are large databases with parameters related to the maintenance of different equipment and installations. Given that manual analysis of sensors connected to machines is practically impossible, maintenance decisions from these databases can be difficult if the information automatically updated from these sensors is huge. Those great amounts of information are essentially useless if the knowledge contained inside cannot be extracted. Rough set theory facilitates this work by detecting those parameters that are truly significant for establishing the decision rules of the maintenance. In order to show the power of rough sets this paper contains a real case of a plastic injection installation for the analysis. Practical implications. An effective use of resource allocation in manufacturing processes could be achieved by using certain decision rules to indicate where and when maintenance decisions and tasks should be undertaken. This paper illustrates how the powerful theory of rough sets handles these issues. Therefore, the use of this technique is highly recommended for those industrial processes with a great amount of data and time (or in general, any resource) limitations.
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