AI in Aerospace Manufacturing
Leverage AI in manufacturing to drive unprecedented efficiency, productivity, and quality, while minimizing risks and enhancing decision-making throughout your operations.
The Impact of AI in Complex Discrete Manufacturing
Complex discrete manufacturing requires precision, traceability, and compliance, making it an ideal domain for AI applications. Our vision to harness AI will provide our customers with an intelligent, data-driven foundation that enhances everything from risk management to operational efficiency. With the wealth of manufacturing data it captures, Solumina is well-positioned to support the rapid adoption of AI technologies in the industry.
Solumina GPT:
The Future
of Vertical GenAI
in Manufacturing
We propose a specialized AI model, Solumina GPT, designed specifically for complex discrete manufacturing. Unlike general-purpose generative AI, which is trained on public data, Solumina GPT can be trained on the vast amounts of manufacturing data you have in your Solumina instance, enabling it to understand and optimize manufacturing processes at a granular level.
From automating routine tasks to generating on-demand reports and dashboards, Solumina GPT will be a game-changer for A&D manufacturers. Imagine asking Solumina GPT to generate a process plan, create a discrepancy report, or even simulate a production scenario—all with the ease of a conversation. This tailored AI will know the intricacies of A&D manufacturing, allowing it to provide actionable insights and solutions that are uniquely relevant to our industry.
iBase-t’s approach will include:
- A Digital Subject Matter Expert
- Integration with Technology Partners
- AI-enabled Enterprise Search
- Knowledge Graph
- IIoT Integration
- Large Language Model
Applications of AI in A&D Manufacturing
Digital Thread & Traceability
AI can transform traceability by leveraging the vast manufacturing data in Solumina to create a “digital tapestry” of an assembly’s history. Manufacturers can instantly drill down into all the data associated with the assembly, including the origin of every raw material, every component, and every step in the production process. This would enhance regulatory compliance and facilitate faster, more informed decision-making in response to production issues.
Dynamic Production Planning
AI can streamline production workflow planning by analyzing real-time data and historical trends to optimize task sequencing, resource allocation, and machine usage. It can dynamically adjust schedules based on shop floor conditions, minimizing bottlenecks and downtime. This would ensure smoother operations, faster decision-making, and improved overall production efficiency.
On-Demand Dashboarding & Reporting
The traditional approach to building reports and dashboards requires time-consuming development. With AI-enabled on-demand dashboarding, manufacturers can generate interactive dashboards in real time without technical expertise. Users can query vast datasets in natural language and get instant responses in the form of charts, tables, or dashboards to view KPIs or trends. This on-demand functionality is designed to accelerate data-driven decisions.
Automated Discrepancy Management
Managing discrepancies is often slow and error prone. AI can allow discrepancies to be detected and even resolved autonomously. Analyzing data from sensors and logs, AI can detect a component outside of acceptable tolerances or a process that had deviated from the norm, and either generate corrective actions or escalate the issue to human operators with detailed recommendations. This would significantly accelerate discrepancy management, ensuring smooth production and consistent quality.
Predictive Quality Control
Beyond defect detection, AI can also predict potential quality issues before they arise by analyzing factors such as material properties, environmental conditions, and process parameters. This proactive approach to quality control would reduce rework and scrap and ensure that every product leaving the factory meets the rigorous standards required in the A&D industry.
Enhanced SQM
AI can revolutionize supplier quality management by analyzing vast amounts of supplier data in real time to detect trends in quality performance, generating more intelligent supplier ratings and dynamically adjusting inspection requirements in response. By predicting potential issues and automating quality checks, AI would help identify inconsistencies earlier, reduce delays, and enhance overall supplier performance, boosting product quality and compliance.
Predictive Maintenance Execution
By analyzing the maintenance data in Solumina, AI could identify trends in the type and frequency of overhaul or modifications needed for specific complex assets, enabling smarter predictive maintenance scheduling and execution. It could also recommend additional services during maintenance and inspection execution, flag recurring issues, and even identify potential design flaws for investigation by engineering. This would lead to more proactive, efficient maintenance, repair and overhaul execution and improved asset reliability.
Leverage AI to Accelerate Your Success
The integration of AI is driving significant advancements in operational efficiency, production quality, and decision-making processes, paving the way for a more agile and responsive manufacturing environment.
Faster Time-to-Market
Optimized Production Processes
Enhanced Quality Control
Improved Sustainability
Dynamic User Experience
Superior Supplier Quality Insights
Fast Chat with Sung Kim
Hear from our Chief Product & Technology Officer as he shares his vision of how AI can help our customers in the Aerospace & Defense industry.
Revving Up Discrete Manufacturing: Is Your Manufacturing Data Ready for AI?
AI is transforming discrete manufacturing, enhancing efficiency, quality control, and predictive analytics in aerospace and defense. Learn why data readiness and digital infrastructure are crucial for effective AI adoption and how Solumina can optimize your data for AI and boost operations.
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