Alberta Machine Intelligence Institute

Reliable Material Access: AI-Driven Supply Chain Optimization in Manufacturing

Industry

Manufacturing

Timely Supply Access

Get what you need, when you need it. AI helps manufacturers combat supply chain challenges by predicting demand, optimizing inventory, and improving supply chain responsiveness—minimizing delays, reducing costs, and enhancing operational efficiency.

The Problem

As global supply chain volatility persists, manufacturers face critical delays in accessing the equipment, parts, and materials essential for production. Extended lead times, averaging 79 days for key materials, combined with inefficiencies in responding to disruptions, lead to production slowdowns and increased costs. Efforts to adapt through supplier diversification, supply chain relocation, and selective inventory management are challenging without precise forecasting and dynamic coordination.

The AI Opportunity

AI enhances supply chain efficiency by predicting demand patterns, identifying risks, and optimizing logistics. It enables manufacturers to secure the equipment, parts, and materials they need, precisely when they need them. By analyzing real-time data, historical trends, and external factors, AI ensures supply chain processes are responsive, reliable, and resilient.

Why It Matters

Access to the right materials and parts at the right time is vital for uninterrupted manufacturing. Delays can halt production, erode customer trust, and increase costs. AI-powered solutions enable manufacturers to anticipate demand, manage risks, and streamline logistics, ensuring operational continuity and reducing downtime.

Benefits & Impact

Reliable, Efficient Production

Reliable access to materials helps manufacturers minimize disruptions and maintain production schedules.

Improved Supply Chain Resilience

Identifying risks early allows manufacturers to proactively adjust sourcing and logistics plans​​.

Cost Optimization

Efficient inventory and logistics strategies reduce holding costs, overstocking, and emergency procurement expenses​​.

AI Methods & Models

  • Purpose: Predict material needs based on historical and real-time data.

  • Why: Reduces stockouts and improves procurement accuracy.

  • Tools/Models: Time-series models (e.g., ARIMA), machine learning (e.g., Random Forest), deep learning (e.g., LSTMs).

Build Your AI Solution with Amii

As one of Canada’s three national AI institutes, Amii brings decades of expertise, advancing AI innovation and delivering industry solutions to your team. Whether you’re just starting to explore the possibilities of AI or are ready to develop advanced AI models, Amii is here to help.

Training

A successful AI solution requires both technical know-how and a strong understanding of your business. Our training aligns technical and non-technical teams, creating a shared language and fostering the collaboration needed for successful AI implementation.

Strategy

We collaborate with your team to brainstorm, evaluate, and prioritize AI use cases aligned with your business goals, building your internal capacity along the way. Our experts then validate the top idea, positioning your team for a smooth transition into development.

Development

Our unique approach places a full-time Machine Learning Resident within your team, supervised by Amii experts, to help build a custom AI solution. After the project, you have the option to hire the resident, ensuring continuity to deployment and expanding your internal AI capacity for future AI innovation.

Ready to get started?

Connect with our Investments & Partnerships team to explore how Amii can help make AI work for your business.