Analytics for the "Industrial Internet of Things"

Analytics for the "Industrial Internet of Things"

The modern industrial world is faced with the continuing challenge to meet and exceed a variety of demanding and ever-increasing expectations. Whether it is to reduce downtime, contain costs, meet regulatory requirements, or improve operations, analytics can help your organization leverage your own "data tsunamis" to meet your particular business challenges.

What do we mean by analytics?

We define analytics as the technologies and applications, along with the people and processes, that enable organizations to transform their data into actionable insights that are key to making better decisions at work.
Ready Engineering possesses the analytics expertise to help you grow your business in the Industrial Internet of Things era.

Some of our services include the following:

  • Leveraging "real-time" data sources. Your industrial facilities have an enormous influx of data that arrives in real-time. Obtaining meaningful information from that data requires analytics that can quickly extract insights and process them for you.
  • Bringing together multiple data sources. As many more data sources across and outside your facilities become available, your organization requires analytics that can integrate data from a variety of sources.
  • Developing predictive and prescriptive models. The proper analysis of data transforms your organization's role from reacting to historical events and outcomes to taking predictive, proactive stances.
  • Building flexible solutions. Ready offers custom analytics applications and tools with flexible capabilities to help you recognize and respond to changes in your industry.
  • Increasing automation. Ready's analytics solutions provides not only the information to make better decisions, but also the capability to make automated decisions once the data is analyzed.
  • Supporting the high-level identification of business opportunities. Through analytics, Ready provides the support you need to facilitate the innovation process and help your team recognize and develop business opportunities.
  • Training in data analytics. We offer training for your staff as part of our comprehensive data analytics solutions to help you drive decisions based on data.

Some of the methods and technologies we routinely use in our analytics projects include the following:

  • Programming Languages. Java, VB .Net, Visual C++, C#, JavaScript, R, Perl, Python, MATLAB, Transact SQL, Base SAS, SAS/STAT, SAS/IML
  • Data Analysis and Visualization Products. Microsoft Excel, Processing, Tableau
  • Big data technologies. Hadoop, MongoDB, DynamoDB, Hive
  • Statistical Modelling/Methods. PCA, Regression, Clustering, Decision Trees, Neural Networks, Support Vector Machines
  • Advanced Analytics Modelling/Methods. Machine Learning, Data Mining

Some of our Previous Analytics Projects:

  • Junior Oil & Gas Company - Data Analytics Projects, Venezuela. Worked on the management of data communication logistics from the oilfields to production department. Automated the process for data conversion to relevant information (production forecasts, evaluation, visualization at different levels, and multi-departmental data integration).
  • Power Generator - Operations Diagnostic Centre Expansion, CanadaManaged the integration of six additional plants into a centralized monitoring and diagnostic centre. Managed multiple vendors providing performance/reliability models and identification of plant instrumentation. Facilitated the exchange of information between plants and vendors.
  • Mining Company - Port Facility Monitoring System, AustraliaDeveloped an analytics software interface for collecting iron ore stockpile profile data from laser scanners, for use in 3D stockyard visualization.
  • Research Institute - Data Analytics Project, Canada. Developed a pattern recognition application for the analysis of weather radar data to automatically classify severe storm cells.
  • Cancer Centre - Data Science Management, Canada. Provided Technical leadership for a data science team analysing medical images for the characterization of brain tumours and liver lesions.
  • Rehabilitation Hospital - Data Analytics Project, Canada. Developed a decision support system for predicting the risk of progression of Adolescent Idiopathic Scoliosis from radiographic indicators.

Please contact us to discuss how we can contribute to the success of your project!

Lino RamirezLino Ramirez, Ph.D., P.Eng.
Solution Architect
877.892.9104 x607
Jeff WilsonJeff Wilson, P.Eng.
Manager, Control Systems
877.892.9104 x126