Corrective maintenance is carried out after failure detection and is aimed at restoring an asset to a condition in which it can perform its intended function. In the Dynaway EAM module, a variety of corrective work flows are supported:
- The machine operator can identify a machine failure and create a downtime registration that automatically triggers a service request for the maintenance department.
- The maintenance worker can identify a failure and immediately create a corrective work order on which he can register work hours, spare parts and other related costs.
- A machine can by itself report a failure through its PLC interface.
Structured registration processes around corrective maintenance are key in a fact-based approach to continuously improving the maintenance processes.
Condition-based maintenance (CBM) is maintenance performed after one or more indicators show that equipment is going to fail or that equipment performance is deteriorating. In Dynaway EAM, you can specify condition assessments and trigger maintenance based on those assessments.
Preventive Maintenance is supported through maintenance sequences, which can be calendar-based (date, time, weekday, …), counter-based (produced units, hours, miles,..), or condition-based.
Counters can be linked to Dynamics 365 resources and thereby be automatically updated from production with hours in use or number of units produced. They can also be updated manually using the Dynaway Mobile Client as part of an inspection.
Preventive maintenance jobs are scheduled based on linear projections of registered counter values.
Asset counters can be defined for individual asset types and then updated either manually or automatically, for example, through direct integration to PLCs. Those counters are an integral part of predictive maintenance, which covers advanced statistical analysis of one or more mathematical models underlying a given counter.
The Azure Machine Learning engine is a well-suited companion for Dynaway EAM as Azure ML can be linked directly to EAM data. Learn more about Predictive Maintenance using Azure here.