(9b) Improving Asset Effectiveness through Data Analytics and Predictive Modeling | AIChE

(9b) Improving Asset Effectiveness through Data Analytics and Predictive Modeling


Thorat, S. - Presenter, Ingenero Inc.
Plant operating performance is dependent on the asset effectiveness of key equipment. Surprisingly equipment is often operated at sub-optimized conditions. The two primary reasons for sub-optimal operation are:

  • Information availability
    • When information is not on hand to make the right decisions, decisions are not made in a timely manner
  • Equipment constraints
    • Operation is controlled below maximum due to fear of deteriorating equipment health

Utilization of data analytics through smart tools can address the above two issues to optimize asset effectiveness confidently while ensuring operational safety. The power of industry specific advanced analytics of both historic and real-time data can be leveraged to achieve improvements that are difficult to accomplish using the traditional approaches.

These tools/analytical techniques convert information into intelligence that can be used effectively on a real-time basis to make operational changes to maximize asset effectiveness. Continuous assessment of measured and derived parameters against known engineering boundaries is possible and can identify opportunities and potential reliability issues. Appropriate techniques, tools and equipment models can be applied to track the performance and identify the quantum of deviation from normal. Further, predictive and prescriptive analytics can help determine the impact of deviation, need for corrective action and assist in reaching challenging solutions.

Substantial economic gains are achieved when data analytics is coupled with the overall plant operating strategy. This paper discusses how various applicable techniques, tools and models are utilized effectively in ethylene and other process industry to achieve production levels and asset effectiveness to best possible.