Implementing a smart structure in the operations of the maintenance and repair department is essential for organizations, given that maintenance and repair are generally one of the largest cost components. By incorporating intelligent systems based on RCM logic, integrated with data science concepts and utilizing a set of algorithms, it becomes possible to predict maintenance and repair intervals and causes efficiently. This proactive approach aims to determine appropriate maintenance and repair times before equipment failure or inactivity, emphasizing optimization principles in the selection of replacement parts, tools, specialized human resources, and time management. This plays a pivotal role in achieving desirable outcomes, such as increasing the useful life of equipment and enhancing efficiency.

– Early detection of anomalies and observable functional deficiencies in each equipment
– Use of various (and extensible) algorithms to detect fault conditions and causes, with the system’s ability to choose based on certain constraints
– Issuance of comprehensive work orders, including all necessary parameters for proper maintenance and repair operations
– Management of relevant resources with default settings for system functional components
– Optimization capability in selecting human resources and work teams based on quantitative, qualitative, expertise, location, and temporal considerations, among others
– Optimization capability in selecting tools and equipment suitable for available inventories and facilities
– Alarm, logging, reporting, chart display, and ticketing capabilities for the self-system and other related systems