Google > Case Studies > Toyota Develops AI Platform for Enhanced Manufacturing Efficiency with Google Cloud

Toyota Develops AI Platform for Enhanced Manufacturing Efficiency with Google Cloud

Customer Company Size

Large Corporate

Region

Asia

Country

Japan

Product

Google Cloud AI Infrastructure
Google Kubernetes Engine (GKE)
Google Cloud AI Hypercomputer
Google Cloud's Tech Acceleration Program (TAP)
Gemini Code Assist

Tech Stack

Hybrid Cloud
Microservices Architecture
SCRUM Development Methodology
Google Cloud VPC
Google Cloud Build

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Productivity Improvements
Cost Savings
Innovation Output

Technology Category

Analytics & Modeling - Machine Learning
Platform as a Service (PaaS) - Data Management Platforms
Infrastructure as a Service (IaaS) - Cloud Computing

Applicable Industries

Automotive

Applicable Functions

Process Manufacturing
Quality Assurance

Use Cases

Predictive Maintenance
Machine Condition Monitoring
Process Control & Optimization

Services

Cloud Planning, Design & Implementation Services
System Integration
Training

About The Customer

Toyota, a global leader in the automotive industry, is renowned for its innovative production system, the Toyota Production System, which emphasizes efficiency and quality. The company has been at the forefront of automotive manufacturing, setting the gold standard with principles like 'Jidoka' (automation with a human touch) and 'Just-in-Time' inventory management. Despite its success, Toyota recognized the need to adapt to the evolving landscape of the automotive industry, characterized by the rise of connected cars, autonomous driving, shared mobility, and electrification. To maintain its competitive edge, Toyota embarked on a digital transformation journey, focusing on integrating AI into its manufacturing processes. The company's Production Digital Transformation Office played a pivotal role in this initiative, aiming to democratize AI development and empower factory workers to create and deploy machine learning models. By leveraging AI, Toyota sought to enhance manufacturing efficiency, automate labor-intensive tasks, and improve overall productivity. The company's commitment to innovation and continuous improvement has positioned it as a leader in the automotive sector, driving advancements in manufacturing technology and setting new benchmarks for the industry.

The Challenge

The automotive industry is undergoing a significant transformation driven by the rise of connected cars, autonomous driving, shared mobility, and electrification. Manufacturers, including Toyota, face the challenge of increasing efficiency, automating manufacturing processes, and improving quality. Despite Toyota's renowned production system, certain parts of the system resist conventional automation. Additionally, Toyota faced a bottleneck in promoting AI due to a shortage of employees with AI expertise. To overcome these challenges, Toyota's Production Digital Transformation Office aimed to democratize AI development within its factories, enabling factory floor employees to create machine learning models easily. This initiative sought to automate manual, labor-intensive tasks, allowing human workers to focus on higher-value activities such as process optimization and data-driven decision-making.

The Solution

Toyota developed an AI Platform using Google Cloud's AI Infrastructure to empower factory workers to create and deploy machine learning models. The platform, built on a hybrid architecture combining on-premises infrastructure and cloud computing, facilitates agile development and resource optimization. By adopting a microservices-based architecture and agile methodologies like SCRUM, Toyota rapidly iterated and deployed new features while maintaining robust security. The hybrid cloud approach allowed Toyota to use on-premises resources during normal operations and scale to the cloud during peak demand, reducing GPU usage costs and optimizing performance. This approach also minimized the need for extensive on-premises hardware investments, aligning with Toyota's 'Just-in-Time' method. Toyota chose Google Cloud for its flexibility in using GPUs, ease of use, and speed of build and processing. Google Cloud's unique features, such as multi-instance GPUs and time-sharing GPUs, optimized costs and increased business value. The speed of communication and processing, facilitated by Google Kubernetes Engine (GKE), Autopilot, and Image Streaming, improved cost-effectiveness and operational efficiency. The collaboration with Google Cloud enabled Toyota to complete the large-scale development of the AI Platform in 1.5 years with a small team of six developers, significantly enhancing the development experience and user adoption.

Operational Impact

Enhanced Developer Experience: The development experience improved with reduced waiting times for tasks and lifted operational and security burdens, allowing developers to focus more on development.
Increased User Adoption: The AI Platform's use on the manufacturing floor is growing, with a 20% reduction in learning model creation time, enhancing the user experience and leading to a surge in the number of users.
Expanding Impact: The AI Platform is in use at all of Toyota's car and unit manufacturing factories, with applications expanding to various manufacturing processes, increasing the number of active users and participants in training programs.
Cultural Shift: The project sparked a shift within Toyota, reducing resistance to cloud technology and encouraging other departments to consider adopting it.
Future Plans: Toyota plans to develop AI models for more detailed detection criteria, implement them in automated processes, and use them for maintenance and predictive management, with an eye on utilizing generative AI.

Quantitative Benefit

The AI Platform saved Toyota as many as 10,000 hours of mundane work annually through manufacturing efficiency and process optimization.
The number of models created in manufacturing increased from 8,000 in 2023 to 10,000 in 2024.
The number of active users in the company increased to nearly 1,200, with more than 400 employees participating in in-house training programs each year.