Supply Chain Automation for MRO
SCAS mitigates unplanned machine breakdowns with artificial intelligence; minimizing overstock, cross-warehouse movement, and asset expiration.
With customer demands and market volatility increasing daily, Asset Intensive enterprises rely heavily on Maintenance, Repairs, and Operations (MRO) supply chains to ensure business continuity.
Aside from ongoing efficiency challenges related to planned maintenance schedules, unexpected interruptions often present exponential risks.
Unplanned Machine Breakdowns, when coinciding with the unavailability of requisite spare parts, or stockouts, often result in delays, shortages, and heightened market volatility.
Reactive MRO supply chain management techniques typically entail holding excess inventory of parts for such scenarios, resulting in increased carrying costs and excessive tied-up capital via overstock, with the potential for downstream loss resulting from asset expiration.
The compounded MRO challenge for unplanned stoppages is further amplified by the increasing velocity, complexity, and uncertainty of global supply and demand, creating management scenarios which are proving to be beyond human capacity.
SCAS for MRO Supply Chain Planning
SCAS, Seeloz’ Supply Chain Automation Suite, uses AI to autonomously optimize MRO resource availability through a continuous flow of learning, evaluation, and execution.
Rapid Diagnostic: SCAS connects to existing ERPs and EAMs to extract historical MRO supply chain data, creating a holistic real time view of supply chain performance and behaviors.
Cross Supply Chain View: From the diagnostic, SCAS generates a cross supply chain view based on consumption, inventory, and supply, factoring in constraints as well as relevant external data. This all-encompassing view is the foundation of SCAS' behavioral learning capabilities, far exceeding those of traditional MRO forecasting and rule-based optimizations.
Behavioral Learning: Through ongoing behavioral training, SCAS generates hundreds of millions of probable consumption scenarios which cover all possible supply chain events, learning to beat each scenario with precisely timed replenishment and transfer orders.
AI Model: The output of behavioral learning exercises is an AI model which is effectively an optimized MRO playbook, equipped to handle all possible planned events and unplanned machine breakdowns.
Scoring Engine: Continuously leveraging the AI Model, SCAS' scoring engine dynamically evaluates the current supply chain state to generate planned purchase and transfer orders, intelligently minimizing overstock, cross-warehouse movement, and asset expiration.
Autonomous Execution: Outputs from the scoring engine are autonomously pushed to the ERP for execution.
Continuous Optimization: This ongoing cycle of learning, modeling, scoring, and execution enables continuous optimization of MRO resource availability with no need for separately-generated forecasts or inventory planning parameters.
Through this AI-driven approach to MRO Supply Chain Planning, SCAS autonomously ensures business continuity and inventory optimization for both planned and unplanned events.
Benefits and ROI
Autonomously optimizing MRO planning and management, SCAS minimizes delays and shortages throughout the supply chain, delivering tangible benefits to P&Ls and balance sheets.
For a MRO supply chain with 2.5 billion in inventory on 2 annual turns, SCAS reduces inventory by up to 40%, maintaining business continuity and mitigating interruption risks to mission critical operations.
This revolutionary approach to MRO supply chain planning delivers 200 million in total annual savings, drastically improving financial performance while ensuring optimal inventory across asset intensive supply chains.
Get in Touch
To learn more about how SCAS is transforming global distribution supply chains with AI, watch this video and contact us to set up a demo.