AI for Global Manufacturers
Dramatically increase manufacturing throughput, supply chain efficiencies, and services revenue using AI at enterprise scale.
Global manufacturers today must build a digital transformation strategy while facing a combination of business forces
These market complexities put pressure on profit margins and growth. Manufacturers are looking to overcome these challenges via digital transformation strategies that utilize IoT and AI. To date, such efforts have faced significant integration challenges and proven hard to operationalize at enterprise scale, and therefore seldom evolve beyond a pilot. This has led to long delays, mixed results, elusive ROI, and haphazard progress.
The C3 AI Suite enables manufacturers to rapidly deliver enterprise AI applications that leverage existing applications and data
The C3 AI Suite provides the necessary, comprehensive services for organizations to build enterprise-scale AI applications 25x to 100x faster than alternative approaches. The C3 AI Suite enables manufacturers to rapidly integrate data from any/all enterprise systems, operational sources, sensor networks, and external providers to power machine learning models that generate predictive insights and solve previously unsolvable problems. Many large, global manufacturers are already using the C3 AI Suite to drive their digital transformation efforts, generating results such as: reducing inventory stocks by as much as 35%, lowering waste due to quality defects by over 20%, and generating $100’s of millions in economic value annually.
C3.ai Applications for Manufacturing
Reduce inventory holding costs, improve cash flow and supply chain visibility, and increase the productivity of inventory analysts. C3 Inventory Optimization applies advanced machine learning to analyze variability in demand, supplier delivery times, quality issues, and product line disruptions to build real-time recommendations and monitoring, so users can set optimization by confidence level and receive real-time notifications and root cause analysis. Global manufacturers have deployed C3 Inventory Optimization to decrease inventory levels by 35%.
Aggregate petabyte-scale data from sensors, devices, enterprise systems, and operational systems (e.g., SCADA, OMS, GIS) to generate accurate predictions of asset failure. C3 Predictive Maintenance provides planners and operators with comprehensive insight into asset risk, enabling them to maintain higher levels of asset availability, deliver services-based differentiation, and lower maintenance costs.Learn More
Leverage real-time AI / machine learning to drive operational excellence and improve profitability across sales, marketing, and customer service. C3 CRM delivers AI-generated forecasts and scores in real time using insights from internal and external data sets.
C3 Energy Management
Reduce energy costs and improve building operations through real-time tracking, analytics, and optimization. C3 Energy Management utilizes machine learning techniques to enable accurate forecasting, benchmarking, building optimization, demand response, and anomaly detection to lower costs, improve operations, and meet energy efficiency goals.
C3 Sensor Health
Ensure the operational health and optimal deployment of IoT sensor devices with machine learning. C3 Sensor Health uses advanced AI/ machine learning to predict sensor failures and identify sensor and network health issues with a high degree of precision.
Supply Chain and Manufacturing Use Cases addressed by the C3 AI Suite
Multi-Echelon Inventory Optimization
Access a comprehensive view of global inventory levels across individual lines and factories and entire supply networks. Perform scenario planning and root cause analysis, optimize inventory levels, and manage suppliers comprehensively.
Supply Network Optimization
Address supply network variability by pinpointing issues and streamlining operations across individual supply chains and collective supply networks. Perform scenario planning, improve understanding of supplier performance, and generate recommendations based on live data.
Improve throughput and product quality by quickly detecting and mitigating emergent process issues. Apply advanced machine learning techniques to predict downstream product yield issues and pinpoint problematic process steps.
Aggregate sourcing data into a unified federated image to perform pricing analytics and visualization. Build optimal price estimates for raw materials based on advanced machine learning analysis of previous pricing and expected consumption.
Identify componentry at risk and proactively alert customers to potential issues to increase service satisfaction levels and reduce downtime. Maintain visibility of individual components at factory, distribution, or customer locations.
Maintain accurate bill of materials (BOM) pricing and componentry for highly complex products at each stage of engineering, delivery, and after-market. Calculate profitability for design, as-built, and added components for after-market stages.