IoT data only brings value if you start analysing the data and making smarter decisions. Sébastien Verhelst Manufacturing Lead Advisory Western Europe, SAS
Move digital transformation from experimenting to action!
Manufacturing companies that do not transform their way of working and do not adopt digital transformation are in a risk of going out of business. Many are already experimenting with new technologies but often the projects stay as proofs-of-concept and never put in action to bring value.
In this article you will learn more about the analytics life cycle and the four-step approach that helps you get started.
Who is SAS?
Introduction to SAS
SAS is the leader in analytics with over four decades of expertise. We help to turn huge amounts of complex data into knowledge you can use. With SAS, you can apply the most advanced analytics, business intelligence, data management and AI solutions to your toughest business problems. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.
Why SAS is relevant to Manufacturing organizations
Manufacturers can move from reactive to proactive with scalable data integration and advanced analytics. Analytics is the way to utilize IoT to predict, detect, prevent and resolve quality and reliability issues. The strong data management and analytics solutions ensure the success of your connected factory, IoT and Industry 4.0 initiatives. We help you adopt a decision framework that guides your approach to analytics.
How we can help
Innovative technologies for manufacturing success
We help you manage and analyze your industrial IoT (IIoT) data where, when and how it works best for your business. Traditional approaches – Six Sigma, line-level reporting, MES systems – are no longer sufficient for gaining insights from data to improve decision making. AI enables you to automate complicated tasks and find useful signals in data that was previously too large or complex to tackle.
Put AI and IoT together and you get the Artificial Intelligence of Things, or AIoT – a revolutionary combination that according to our study helps to transform the industry, elevate customer experiences and accelerate business performance exponentially.
Read more about IoT and AIoT bring value to your industry.
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Demystifying Advanced Analytics in Manufacturing
Build your company’s digital capabilities and empower people
What actual value Artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT) can bring to your organization? Maybe you have already experimented with advanced analytics, but your analytics model never made it out of the lab?
Our manufacturing experts help you understand and assess the potential of your AI and advanced analytics potential better. You get an introduction to our methodology to go from vision to value.
Yield Prediction Demo with SAS
Predict and optimize yield in manufacturing processes with advanced analytics
Increasing yield is one of the critical issues in process manufacturing. Advanced analytics gives you powerful tools to work with data and build models to predict and optimize yield. Models are useless if they are not taken into action. Connecting IT and Analytics departments is key to successful cooperation in deployment.
In the demo you can see how to go from development to deployment of models using our analytics lifecycle path to make sure every step and action needed is taken care of.
Smart Factory in a Box
Combine the power of data science and your manufacturing expertise to jumpstart your analytics journey
Artificial intelligence (AI), machine learning (ML), and internet of things (IoT) can bring huge value to your organization. But how do you turn the hype into a scalable model that transforms your operations and improves your bottom line profit? A successful journey combines the best of both worlds. This means defining the right methodology, teaming up with data-savvy employees and implementing customizable technology.
Our manufacturing experts introduce you to a real installation that is performing poorly. Your challenge is to improve its current poor performance during a series of hands-on analytic assignments.