As new methods and technologies evolve for maintenance planning, such as expert systems, constraint-based reasoning, belief networks, and artificial neural networks, there is an important need to develop a broader framework to ensure that these methods become integrated into the modus operandi of an organization. Otherwise, there exists the real possibility that the new methods and technologies for maintenance management may become "islands of automation" that will not provide any meaningful feed-back to improve organizational performance.
New methods for reliability prediction and maintenance diagnoses coupled with the use of maintenance automation technology offer significant promise in helping to meet the global demands of competitive pricing, quality, and on-time deliveries.
As new methods and technologies evolve for maintenance planning, such as expert systems, constraint-based reasoning, belief networks, and artificial neural networks, there is an important need to develop a broader framework to ensure that these methods become integrated into the modus operandi of an organization. Otherwise, there exists the real possibility that the new methods and technologies for maintenance management may become "islands of automation" that will not provide any meaningful feed-back to improve organizational performance. New methods for reliability prediction and maintenance diagnoses coupled with the use of maintenance automation technology offer significant promise in helping to meet the global demands of competitive pricing, quality, and on-time deliveries.
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