A properly established asset management program can deliver significant optimization of costs through a combination of increased asset availability and reliability, and optimized maintenance strategies. Whether in the design or operation phase, Reliability, Availability, and Maintainability (RAM) modeling is an effective tool for decision-making when it comes to developing or enhancing your asset management efforts.
Reliability is defined as the probability that an item will perform its intended function for a specified period of time.
Availability refers to the total time a system is in an operative state.
Maintainability describes the ability of an item to be retained or restored to specified conditions when maintenance is performed by qualified personnel.
RAM Modeling is a component of PinnacleART’s Reliability Centered Maintenance (RCM)-based asset management service that simulates configuration, operation, failure, repair and maintenance of equipment data, in order to identify critical components and failure modes that could eventually cause production losses.
By simulating all of the probable future performance metrics of a given process design, RAM modeling is an effective tool for determining whether estimated availability and production will meet business objectives, and for identifying where systems can be optimized, in order to further optimize costs in the long-term. For example, the results of a RAM analysis are used to quantify the economics or other performance criteria of equipment-related decisions such as redundancy, spare parts, equipment sizing, maintenance practices and policies, quality of components, etc. For new designs, RAM is a powerful tool for evaluating design decisions affecting such things as:
Probability of unplanned events and impacts on life cycle performance
Buffer sizing and location
Unit/equipment redundancy and sizing
Capital or insurance spares requirements for major equipment
Throughout the life cycle of existing processes and units, RAM can be a vital tool for assisting in decisions such as:
Maintenance philosophy, scope and timing
Obsolescence and end of useful life (repair or replace/upgrade)
Impact of actual failures on risk exposure and priorities of repairs
Impact of design or process changes to maintenance, operations and control strategies
Spare parts stocking strategy optimization based on actual parts usage and criticality
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