Leading AI-powered Supply Chain Decision Intelligence and Analytics platform releases advanced parts management capabilities aimed at automating inventory replenishment for mission-critical Maintenance, Repair and Operations (MRO) of parts and kits to drive healthier cash flow
ThroughPut Inc., the Industrial AI Supply Chain Analytics and Decision Intelligence pioneer as recognized by Gartner, announced the release of innovative capabilities that enable businesses to strike the perfect balance between supply and demand of material and unlock value across business operations.
With this release, businesses will be able to proactively prevent inventory failure due to overstocking or understocking of spare parts and kits by identifying opportunities to cancel unnecessary planned orders, directly ship to inventory staging locations, and move existing spare stock faster internally. The advanced inventory flow management technology will help holistically optimize supply chain processes – from existing suppliers to individual workshops, improve asset availability while at the same time dynamically balancing inventories to reduce material waste and unnecessary spend.
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“ThroughPut.AI’s latest predictive parts management capabilities provide businesses with unprecedented actionability based on real-time inventory data in combination with AI-based predictions for maintenance requirements and prioritization recommendations aimed at optimizing asset usage and lead times,” said Seth Page, Chief Operations Officer and Head of Corporate Development at ThroughPut.AI. “This represents a significant leap forward in our predictive replenishment and parts management capabilities as we can empower our customers to get the right parts with kits to the right place at the right price and time – eliminating costly downtime, lost sales, and sub-par productivity. By leveraging real-time data regarding maintenance requirements and supply lead times, ThroughPut.AI delivers precise recommendations for safety stock levels and replenishment of individual parts and related kits.”
Some of the key capabilities in the new release include:
- AI-powered prediction of parts requirements, which minimizes production risk by anticipating asset failure and automatically ordering necessary parts in advance – thus avoiding downtime and surplus inventory, while enhancing overall operational efficiency.
- Categorization and prioritization of parts based on actual usage (critical vs standard) and recommending when, how and who to order from for the best lead-times, prices and service.
- Working capital spend reduction by identifying opportunities to optimize procurement, while at the same time dynamically ensuring parts readiness.
- Intelligent decision support for maintenance scheduling based on real-time data and supply lead times at the local and end-point levels.
- Supplier ranking based on their ability to fulfill requirements for the best right place, time, price and service levels.
- Dynamic Smart recommendations for safety stock levels and replenishment at the individual part and kit level.
Source: PRNewswire