AAISM · Question #4
An automotive manufacturer uses AI-enabled sensors on machinery to monitor variables such as vibration, temperature, and pressure. Which of the following BEST demonstrates how this approach contribute
The correct answer is A. Scheduling repairs for critical equipment based on real-time condition monitoring. AAISM highlights that AI-enabled predictive maintenance improves operational resilience by using real-time sensor monitoring to schedule repairs based on actual conditions rather than fixed schedules. This prevents unexpected breakdowns, reduces downtime, and ensures continuity o
Question
An automotive manufacturer uses AI-enabled sensors on machinery to monitor variables such as vibration, temperature, and pressure. Which of the following BEST demonstrates how this approach contributes to operational resilience?
Options
- AScheduling repairs for critical equipment based on real-time condition monitoring
- BPerforming regular maintenance based on manufacturer recommendations
- CConducting monthly manual reviews of maintenance schedules
- DAutomating equipment repairs without any human intervention
How the community answered
(21 responses)- A71% (15)
- B14% (3)
- C5% (1)
- D10% (2)
Explanation
AAISM highlights that AI-enabled predictive maintenance improves operational resilience by using real-time sensor monitoring to schedule repairs based on actual conditions rather than fixed schedules. This prevents unexpected breakdowns, reduces downtime, and ensures continuity of operations. Regular maintenance based on recommendations is static and may not reflect real conditions. Manual reviews are slow and inefficient. Full automation of repairs without human oversight is not realistic or safe in critical manufacturing. The approach that best demonstrates resilience is real-time condition-based repair scheduling.
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