Discrete Production Management
A platform for driving R&D acceleration, yield optimization
& quality improvement.
Topological Data Analysis
The Discrete Manufacturing & Semiconductor sectors are experiencing a paradigm shift in productivity & product quality with the adoption of new AI Machine Learning applications.
The SymphonyAI Industrial Production Performance Management approach draws on the power of Topological Data Analysis (TDA) to reliably predict complex outcomes, gain deeper insights, optimize operational processes as well as understand probable root causes while diagnosing failures.
TDA goes beyond traditional machine learning and other established AI techniques to find patterns within complex data sets in an unsupervised fashion, accelerate the investigation of unknown-unknowns, and justify its findings and recommendations.
Discrete Production Management solution (DPM) delivers these improvements:
Productivity & Product quality
Yield Optimization & Test Time Reduction
Reliability & Performance predictions
White Papers
Understanding TDA
Our sister company has built an AI platform that powers the design, development, and deployment of enterprise-scale, intelligent applications. Our approach, our underlying technology, and our products are expressly crafted to deliver against an enterprise’s requirements in this area – with the goal of delivering extraordinary business value.
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Topological Data Analysis
This whitepaper will explore the main properties of topological analysis and explain how shapes are measured and represented. It also shows how TDA provides a framework for machine learning and why it provides a way to understand the overall organization of the data directly.
Download White PaperTDA and Machine Learning
High-performance machines and algorithms can examine complex data far faster and seek insights more comprehensively than ever before. However, we need to find exponential improvements in analysis techniques to meet the growing demand of exploding data volumes. Topological Data Analysis is one such technique.
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