Predictive Analytics for Monitoring, Maintaining and Optimizing Assets
Join us on June 15th, 2017 at 11:30am for our presentation by Oscar Cruz: How Asset Intensive Organizations Employ Machine Learning and Predictive Analytics to Monitor, Maintain and Optimize Assets for Better Availability, Utilization, and Performance.
We look forward to sharing with you tips on how to save on maintenance costs, and improve the availability of your assets using predictive analytics.
BMO Centre, Calgary, AB
- Production (Arabian Room B)
- June 15, 2017
- 11:30 am – 12:00 pm
Learn more and register here:
Asset-intensive industries in Calgary, such as oil & gas, mining, energy and utilities, use complex equipment such as rotary, compressors, haul trucks, and turbines, in their day-to-day operation. Any unplanned downtime or major unforeseen failure of this equipment has a direct impact on production downtime, which affects the financial performance of the organization. Potential component and equipment failure, plus machine health of in-service equipment needs to be monitored by identifying early signs of possible downtime. The goal of our solution is to maximize the uptime of the component/equipment. Driven by machine learning, Artificial Intelligence and predictive analytics we can detect even minor anomalies and failure patterns to determine the assets and operational processes that are at the greatest risk of problems or failure. This early identification of potential concerns helps to deploy limited resources more cost effectively, maximize equipment uptime and enhance quality and supply chain processes and helps you monitor, analyze, and report on information that is gathered from high-value assets and recommend maintenance activities for them.
• Predict the failure of a monitored asset in order to fix it and avoid costly downtime
• Search stored maintenance logs to determine the best repair procedures and cycles
• Identify the root causes of asset failure to take corrective actions
• Predict where, when, and why asset failures are likely to occur
• Minimize product quality and reliability issues to meet customer delivery schedules.
• Optimize spare-parts inventory to reduce inventory costs associated with stockouts and overstocks.
• Predict warranty claims to increase customer satisfaction.
• Inform upcoming issues to planning and budgeting teams prior to costly event failures occurring.
We look forward to seeing you at this year’s Global Petroleum Show in Calgary.