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.
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 the powerful SAS 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.
- Customer Story 데이터 분석을 통한 비용절감 사례
- White Paper Artificial Intelligence for Executives Integrating AI Into Your Organization
- White Paper Text Analytics for Executives What Can Text Analytics Do for Your Organization?
- E-Book Making Sense of AI
- White Paper The Evolution of Analytics Opportunities and Challenges for Machine Learning in Business
- White Paper The Next Analytics Age: Machine Learning A Harvard Business Review Insight Center Collection
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 Processing실시간 빅데이터 스트리밍을 통하여 분석을 통한 인사이트를 기업의 의사결정에 즉시 반영할 수 있습니다.
- SAS® Field Quality Analytics초기에 문제점을 신속히 찾아내고 그 원인을 분석하여 제품의 품질과 브랜드 이미지를 개선합니다.
- SAS® Forecast ServerProduce large numbers of forecasts quickly and automatically to improve planning and decision making.
- SAS/OR®개선된 운영 조사 방식을 이용하여 비즈니스 프로세스를 최적화하고 문제를 해결합니다.
- SAS® Quality Analytic SuiteIdentify issues earlier, find root causes faster and greatly reduce costs associated with recalls and brand reputation erosion.
- SAS® Text MinerDiscover topics and patterns within entire document collections by mining unstructured data sources using supervised, semisupervised and unsupervised techniques.
- 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.