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  • BHC3 Inventory Optimization

    Optimize inventory and service levels for raw materials

    BHC3 Inventory Optimization

    Optimize inventory and service levels for purchase parts

    BHC3 Inventory Optimization

    Optimize inventory and service levels for finished goods

    BHC3 Inventory Optimization

    Optimize energy companies’ inventory and service levels for in-transit industrial goods

    Reduce Inventory Costs, Free Up Working Capital and Reduce Stock-Out Risks

    BHC3™ Inventory Optimization applies advanced AI/machine learning and optimization techniques to help oil and gas companies reduce industrial parts and equipment inventory levels, while maintaining confidence that they will have stock when and where they need it.

    Oil and gas companies often carry excess industrial component inventory to address uncertainties in operations or demand. This often manifests as excess inventory of industrial parts and equipment to prevent unplanned downtime. Many downstream manufacturers also carry large inventories of industrial components to prevent stock-outs or to offer better lead times and flexibility to customers. Over the years, companies have deployed Material Requirements Planning (MRP) software solutions that support planning and automated inventory management. However, most MRP software solutions were not designed to optimize industrial component inventory levels by continuously learning from data.

    BHC3 Inventory Optimization considers several real-world uncertainties including variability in demand, supplier delivery times, quality issues with parts delivered by suppliers, and production-line disruptions. The application dynamically and continuously optimizes reorder parameters for industrial parts and equipment and minimizes inventory holding and shipping costs for each industrial part or product.

    Features

    Real-time recommendations

    Real-time recommendations

    Allows energy sector companies to get real-time recommendations to optimize reorder parameters by part and by location and keep them updated as new data is available.
    Real-time monitoring

    Real-time monitoring

    View inventory metrics of industrial parts and equipment in real time to anticipate issues with inventory levels and get notified when certain KPIs exceed thresholds.
    Optimization by confidence level

    Optimization by confidence level

    Specify the maximum acceptable risk of stock-out for any industrial part to optimize recommendations.
    Summary view for operators

    Summary view for energy operators

    View inventory savings to date, actual and optimized inventory by location, and prioritized lists of high-opportunity parts, leading to faster value realization.
    Detailed view of individual parts performance in the supply chain

    Individual parts performance view

    View details of individual industrial parts and equipment and compare a range of KPIs such as actual vs. optimal inventory and actual vs. recommended reorder parameters.
    Benchmark parts performance

    Benchmark industrial parts

    Compare and benchmark different industrial parts or industrial suppliers over time using a range of KPIs such as OTIF, defect rate and average cost.
    What-if scenario planning

    “What-if” scenario planning

    Define scenarioses and understand potential energy business implications of changing reorder parameters before committing the changes to the system.
    Live optimization

    Optimization with real-time data

    Allows energy sector operators to dynamically optimize reorder parameters for industrial parts and equipment as new data is received and bidirectionally connect to source systems to update reorder parameters.
    Scalability to millions of parts

    Scalability to millions of parts

    Individually optimize inventory levels of millions of industrial parts at different production locations across a company’s global footprint.

    Demo

    Testimonials

    Scott Parent
    Scott Parent

    Scott Parent

    VP, Enterprise Engineering & Technology

    “What the teams found is ingestion is happening about 80% faster with about 1/10 the resources.”

    Scott Fedor
    Scott Fedor

    Scott Fedor

    Digital Transformation Leader, Global Supply Chain

    "The value of the 高清美女图 C3.ai partnership comes from the fact that we're both experts in our own domains."

    高清美女图 Inventory Optimization
    高清美女图 Inventory Optimization

    高清美女图 Inventory Optimization

    Benefits

    Reduce

    Reduce inventory holding costs for industrial parts and equipment and improve cash flow without compromising part availability. Optimize reorder parameters for industrial components such as safety stock and safety time with necessary confidence levels.

    Improve

    Improve energy supplier management and negotiations through improved understanding of supplier performance. Simulate effects of changes in component order parameters on supplier performance KPIs.

    Increase

    Increase visibility into critical energy-sector uncertainties such as seasonality, uncertainty in arrivals, potential quality issues with suppliers, transportation bottlenecks and production-line disruptions.

    Enhance

    Enhance organizational efficiency of industrial operations through a common view across various departments (e.g., material management, supplier management, logistics management), leading to optimized inventory of industrial parts and equipment that is aligned with organizational goals.

    Gain

    Gain productivity of industrial part and equipment inventory analysts through automated recommendations based on new data and live integration with operational systems. Consistently apply recommendations to supplier orders.

    Minimize

    Minimize total landed costs of industrial component inventory that include standard and expedited shipping costs, as a result of reduced inventory in the supply chain.

    BHC3 Inventory Optimization Data Sources

    BHC3 Inventory Optimization aggregates data in the BHC3™ AI Suite from different disparate source systems including production orders (actuals and planned), product configurations, bills of material, inventory movements (e.g., arrivals from suppliers, consumption in a production line, intra- and inter-facility shipments), historical settings of reorder parameters, lead time and shipping costs from suppliers, and part-level costs for each location where industrial component inventory is maintained.

    BHC3 Inventory Optimization factors in several real-world uncertainties including variability in demand, supplier delivery times, quality issues with industrial parts delivered by suppliers, and production line disruptions. The application uses machine learning to analyze variability, dynamically and continually optimize reorder parameters, and minimize industrial part and equipment inventory holding and shipping costs for each item.

    Model-driven architecture for BHC3 Inventory Optimization

    Proven results in weeks, not years

    timeline
    Get insights into BHC3 capabilities, enterprise AI best practices and highest-value use cases.
    Understand BHC3™ AI Suite's capabilities, its model-driven architecture and test it against your company's sample data set.
    Identify a high-impact business problem and collaborate with the BHC3 team to rapidly build an AI application that solves it.
    Scale and deploy a tested BHC3 application into production. Incorporate user feedback and optimize algorithms to drive maximum economic value.

    Thank you for your interest in BHC3.ai

    We'll review your information and a team member will get back to you within 24-48 hours.

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