Predictive Maintenance using AI/ML
Predictive Maintenance using AI/ML
Transform your MRO service with AI/ML-driven predictive maintenance, offering proactive solutions, minimizing downtime, and ensuring a seamless, customer-focused experience
Anticipates and prevents equipment failures by analyzing historical and real-time data
Aims to optimize maintenance strategies by predicting when equipment is likely to fail, allowing for timely and cost-effective maintenance activities
Cost Efficiency
Improved Accuracy
Condition-Based Maintenance
Data-Driven Insights
Extended Lifycle
Improved Safety
Features
Early fault detection for early signs of equipment failure
Real-time monitoring and analysis
Maintenance scheduling optimization
Significantly reduces unplanned downtime by proactively addressing maintenance needs before they lead to failures
Minimizes maintenance costs through lifecycle management by preventing major repairs and extending the life of aircraft parts
Facing any of these Challenges?
Pain Points
Limited Visibility of Work Incoming for Manpower Planning and Inventory Management:
MROs often do not have visibility into upcoming work and the required inventory levels. This leads to workflow disruptions, staffing inefficiencies, and delays in procuring necessary parts. It is challenging to optimize manpower planning and inventory management, affecting operational efficiency and customer satisfaction.
Reactive Cross-Training and Qualifications Planning:
MROs often find themselves in a reactive mode when it comes to cross-training and qualifications planning for their employees. The lack of visibility into future workloads makes it challenging to proactively identify and address skills gaps or enhance qualifications to meet demand fluctuations. This approach can result in workforce inefficiencies and resource shortages during peak periods.
Missing Parts On-Hand Impact on Work-in-Progress:
MROs encounter challenges when required parts are not readily available on-hand. This situation can create significant roadblocks in the work-in-progress (WIP) phase, resulting in delays in repairs and operational disruptions.
Travel Surge Causing Capacity Strains on MROs:
With travel activity rebounding to pre-COVID levels and expected to surpass by 5.2% in the next year, the demand for MRO work is set to rise significantly. This surge poses additional capacity constraints within the existing footprint of MROs, resulting in challenges in meeting the increased demand efficiently.
Solutions
Implement Sales and Operations planning system with real-time tracking and forecasting capabilities. Use sales forecasting analytics to gain insights into upcoming work and inventory needs, enabling proactive manpower planning and efficient procurement.
Implement a workforce management system that uses predictive analytics to forecast skills requirements based on historical data and future workloads. Proactively identify skills gaps and provide targeted training and qualifications planning to employees to ensure a flexible and well-prepared workforce.
Implement sales and operations planning, predictive maintenance and demand forecasting tools that leverage historical data and usage patterns to proactively identify parts that are needed based on demand volume of repair work, replacement factors, and supplier lead times, ensuring necessary parts are pre-ordered and available on-hand when required
Invest in digital technologies and automation to enhance existing capacity without the need for significant physical expansion. Implement predictive maintenance solutions to reduce downtime and increase operational efficiency. Use workforce management tools to optimize labor resources during surges in demand, and proactively cross-train technicians to ensure there is no gap in qualifications required to perform the forecasted demand.