Sustainability, Energy Optimization and Mechanical System Downtime Reduction through Advanced HVAC Operation and Control

Heating, ventilation and air-conditioning systems sit at the intersection of building decarbonisation, occupant wellbeing and asset reliability. Yet energy optimisation programmes often treat control efficiency and mechanical downtime as separate problems, even though fouling, sensor drift, valve leakage, unstable sequencing and degraded heat transfer simultaneously increase consumption and failure exposure. This review synthesises research published from 2020 to 2025 on advanced HVAC operation, predictive control, fault detection, digital twins and maintenance analytics. Its aim is to explain how an integrated operating model can minimise energy and carbon intensity while preserving comfort, equipment health and service continuity. A structured evidence review was undertaken across control, energy and building-engineering literature, with studies assessed according to operational scope, data requirements, verification quality and relevance to real facilities. The evidence indicates that forecasting, model-predictive control, reinforcement learning and occupancy-responsive ventilation can reduce avoidable load, but savings are sustained only when control actions are constrained by equipment limits and supported by reliable sensors. Machine-learning fault detection and predictive maintenance improve early recognition of degradation, yet their practical value depends on diagnostic precision, maintenance capacity and post-intervention verification. The paper proposes a unified architecture linking sensing, state estimation, optimisation, supervisory control, fault diagnosis and work management. The central conclusion is that advanced HVAC management should be evaluated as a resilience capability rather than a narrow energy-saving intervention. The strongest programmes jointly govern energy, comfort, emissions, mean time between failures, repair time and unplanned downtime, thereby converting intelligent control into durable operational performance.