How might predictive analytics be refined to improve asset lifecycle modeling, and which advanced methods are most effective for forecasting maintenance needs?
In evaluating total cost of ownership, how can indirect costs such as downtime and productivity losses be better integrated into financial models?
What best practices exist for integrating real-time IoT data, maintenance logs, and financial metrics into a unified asset management approach?
How can sustainability and regulatory compliance be incorporated into asset lifecycle evaluations, and what role do financial models play in this?
What limitations exist with data-driven maintenance models, and how might a balance with human expertise be ensured in critical decision-making?