Effective automation is vital for reducing operational risk. The ongoing evolution of system intelligence has opened up many possibilities. They range from predicting and proactively preventing failures to deciding whether benefits of new processes outweigh the risks.
Knowledge can be represented in many different ways. By far, the most common way humans represent knowledge is in their natural language. For machines, however, it is difficult to use this to share and to expand and maintain the knowledge base. One way to tackle this is to understand the OODA loop of the business: Observe, Orient, Decide and Act.
This loop provides an understanding of the domain. It allows for a definition of possible solutions and a selection of required techniques that fit the business case. The resulting model is then subjected to hypothesis, diagnostic rulesets, fuzzy agents and other methods. Machine understandable graphical rules, which follow a specific syntax and are not tied to a specific language, can then be applied to model the knowledge-base. The main goal is to make all data shareable among all platforms, regardless of nature or location.
Failure prediction: Early detection of compressor failure using advanced data analysis methods and knowledge engineering approaches. This prevents failures and reduces negative environmental impact.
Remote surveillance: Development and deployment of a rule based surveillance system linked to data streams generated by production assets. Online 24/7, only generating alarms on issues requiring attention.
Regulatory compliance: Complex real-time data generated by inspections and maintenance help determine if assets comply with regulations. Legal information, operational knowledge, history and location must be included for accurate analysis. The system can also provide immediate advisories to staff, providing more insight while reducing the risk.
Pollution spread simulation: Development of a scenario based calamity simulation system to experiment and understand acute changes in water quality across water distribution networks.
Unleash the full potential of data within your organization?
UREASON assists you in tackling the business challenges within your organization. Our one week intake workshop is the first step in our collaboration proposal, during which we work with you to analyze your challenges, what knowledge needs to be extracted, data availability and data quality. Together we decide what level of support fits your needs best.
http://ureason.com/cms16/wp-content/uploads/2016/02/Ureason_logo_hoog.png00Erwin van Heldenhttp://ureason.com/cms16/wp-content/uploads/2016/02/Ureason_logo_hoog.pngErwin van Helden2016-03-02 09:37:262016-05-31 15:42:33Artificial Intelligence
Data has become a vital asset for many industries. It helps gaining new insights that help identify new business opportunities and areas within the internal organization that need improvement. Machine learning, predictive analytics, probabilistic reasoning, simulation and event stream processing are some of the techniques that can help organizations in optimizing their operations.
UREASON works together with organizations that want to leverage their data to its fullest potential by bringing in a creative team with vast specialist knowledge. They can help gaining insight into large amounts of complex data in order to reduce risk and business uncertainty.
Since its founding in 2001, UREASON has built a proven track record with customers in a wide variety of industries. Active in process industries – petrochemical/chemical – telecom, smart grid and smart cities. The majority of our customers are in Europe, North America and the Middle East.
UREASON brings best-of breed-(real-time) reasoning solutions to its customers through innovative software development.
Sensing your environment to create a tailored response.