Predictive maintenance uses condition and operating evidence to judge when an asset needs attention. A failure probability alone is not a maintenance decision: the business must also consider consequence, lead time, spares, access and the effect of intervention on operations. Ranking assets only by predicted failure can therefore direct effort away from the equipment that matters most. Marketways connects the model with maintenance reality so the client can choose which asset to inspect, monitor or intervene on and update that choice as evidence changes.
When this service may be needed
What we assess
We assess the defined asset population, the function each asset must perform and the failure events that matter to the business. The scope can consider maintenance and failure history, condition or sensor signals, operating conditions, reliability patterns and signs of deterioration.
We also distinguish current asset health from the likelihood of a future failure, the likely timing of deterioration and the consequence of a failure. That distinction matters because an asset with poorer condition is not always the asset that should receive the earliest attention.
Predictive Maintenance & Reliability
Predictive Maintenance & Reliability helps organisations assess how physical assets are performing, how their condition is changing and where maintenance attention is most needed. It supports practical decisions about the assets that matter most, while recognising that a prediction is an estimate rather than a certain failure date.
How this helps the business
Clearer maintenance priorities. The work relates asset condition and reliability to the operational consequence of failure. Maintenance leaders can direct limited time, parts and shutdown windows towards the assets where intervention matters most.
A more informed view of reliability. Patterns in failure, downtime and operating history can show where an asset population is dependable and where its performance is less certain. This helps the business separate recurring concerns from isolated incidents when planning maintenance.
Better-timed intervention. Evidence about deterioration can indicate when an asset may require attention, within the limits of the available data and operating conditions. The business can weigh earlier action against the cost and practicality of waiting for a suitable maintenance opportunity.
Greater visibility of operational exposure. The assessment connects potential equipment failure with its effect on production, service, safety or other defined operational priorities. Leaders can make maintenance choices with a clearer view of the disruption each failure could create.
How Marketways connects failure evidence to maintenance action
We combine condition, duty cycle, alarms, work orders and maintenance history with the consequence and feasibility of intervention. Survival, predictive or Bayesian models estimate and update the evidence of deterioration, while optimisation compares inspection, monitoring and maintenance choices under resource constraints. The model is judged by whether it provides useful warning and supports better intervention, not by a technical score alone. The client can direct maintenance to consequence-adjusted need and measure availability, avoided failure and lead time.
Methods and technologies that support this service
Marketways selects, combines and adapts the method mix to the business question, the available evidence and the decision the work must support.
Getting ready
Bring the asset population, failure and maintenance records, operating conditions and the maintenance decision that needs improvement. Marketways will define the failure event, prediction horizon, intervention options and evidence gaps before selecting or testing a model.
Where this service fits
Predictive Maintenance & Reliability sits within Business Efficiency. It focuses on the condition and reliability of physical assets so that maintenance choices can support more dependable operations.
Operational Performance Diagnostic can be useful where the business first needs to establish the wider pattern of utilisation, throughput, downtime or operating loss. That wider view helps distinguish an asset reliability concern from another operational constraint. Where equipment failure signals need earlier investigation, Risk Detection can help identify unusual activity or deterioration that warrants attention. Risk & Uncertainty Modelling may be relevant when the business needs to consider the likelihood and consequence of defined failure risks across a wider decision.
AI may create a practical opportunity to interpret larger volumes of condition or sensor data, or to identify changing patterns sooner. Where an AI or statistical model is intended to influence maintenance decisions, the reliability, limits and controls of that system may also require attention through AI & Model Risk. AI is not required for every engagement, and this service does not assume an AI system will be implemented.
Related AI pathway
When AI will interpret condition data or influence maintenance action, AI Transformation connects the analytical system to the maintenance workflow, operating responsibilities and controls.
Discuss the scope
If asset reliability, deterioration or maintenance priorities are affecting an important operational decision, we would be pleased to discuss the context. We can agree a scope around the assets involved, the information available, the operational constraints and the uncertainties the work should help address.