Industry Technology Applications
AI for Manufacturing
Gain unprecedented artificial intelligence (AI) capabilities to remain competitive in a complex global market.
Business Challenges
In manufacturing, you're under pressure to continuously improve quality while reducing costs and increasing productivity. You also strive to right-size inventory and boost profitability while driving year-over-year cost improvements. Finding new ways to extract value from the deluge of sensor and IoT data would enable you to move from a reactive to a proactive approach to minimizing unplanned downtime, reducing scrap and rework, and developing innovative new revenue streams.
Managing the unexpected is a constant challenge. Traditional approaches – Six Sigma, line-level reporting, MES systems – are no longer sufficient for gaining insights from data to improve decision making. Finding new ways to harness the value of industrial data is essential to enabling modern manufacturers to manage today's data volume, velocity and variety.
How AI Can Help
Advances in AI enable us to automate complicated tasks and find useful signals in data that was previously too large or complex to tackle. From quality and equipment performance, to supply chain and spare parts optimization, to service improvements and monetization of IoT data, AI techniques can unlock new insights across the spectrum of manufacturing data, enabling you to:
- Find early indicators of potential quality issues. AI capabilities go far beyond what simple rule-based systems can do, continuously learning to automatically detect patterns in data that a human would likely never see.
- Avoid costly scrap and rework. Use image recognition to identify flaws during the manufacturing process so you can address them promptly.
- Identify areas for improvement. Text analytics, including natural language processing, lets you link customer sentiment, service comments and other written records to quality and production variables to identify areas for improvement.
- Improve yield. Apply deep learning in industrial operations to optimize product composition and production techniques, combining audio, video, text and other data at efficiency levels that were previously unimaginable.
Why choose SAS for AI solutions?
As the leader in advanced analytics, SAS understands that a carefully designed and well-implemented analytics strategy enables manufacturers to meet their production and profitability goals more efficiently and effectively. It’s not just about getting the technology right; it’s about using data to manage complexity, reduce risk, improve margins and even create new sources of revenue.
That's why we embedded AI capabilities in our software – from our powerful analytics platform to solutions that help manufacturers confidently detect, resolve, predict and prevent quality and reliability issues. SAS simplifies data integration from diverse systems, extracts deeper insights from data to drive productivity improvements, and can be deployed wherever and whenever you need the insights in your operations – on-machine or across the enterprise.
AI Solutions for Manufacturing
- SAS® Asset Performance AnalyticsM2M 및 센서 데이터를 이용해 가동시간, 성능, 및 생산성을 개선하는 동시에 유지보수 비용과 매출 감소 리스크를 줄여줍니다.
- SAS® Event Stream Processing머신 러닝과 스트리밍 분석을 통해 엣지에서 인사이트를 발견하고, 클라우드에서 실시간으로 지능적인 결정을 내립니다.
- SAS® Field Quality Analytics초기에 문제점을 신속히 찾아내고 그 원인을 분석하여 제품의 품질과 브랜드 이미지를 개선합니다.
- SAS® Forecast Server많은 양의 예측을 신속하게 자동 생성하여, 계획 및 의사 결정을 개선합니다.
- SAS/OR®Optimize business processes and address challenges with enhanced operations research methods.
- SAS® Quality Analytic Suite문제를 조기에 탐지해, 근본적인 원인 색출과 더불어 리콜 및 브랜드 평판 저하와 관련된 비용을 크게 줄입니다.
- SAS® Text MinerDiscover topics and patterns within entire document collections by mining unstructured data sources using supervised, semisupervised and unsupervised techniques.
- SAS® Visual Data Mining and Machine LearningSAS 비주얼 데이터 마이닝 및 머신 러닝은 통합적인 시각화 인터페이스를 통해 모든 데이터 마이닝, 머신러닝 프로세스를 지원할 수 있습니다.
- SAS® Visual Forecasting기업이 직면한 광범위한 비즈니스 계획 과제에 따라 다양한 예측을 자동으로 실행할 수 있습니다.
- SAS® Visual Text AnalyticsSAS 비주얼 텍스트 애널리틱스는 자연어 처리, 머신 러닝 및 언어학적 규칙을 결합하여 비정형 데이터에 숨어있는 인사이트를 제공할 수 있습니다.