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Building an Effective Monitoring & Diagnostics Program
Industrial machinery operators are under mounting pressure to improve station efficiency, capacity and reliability through cost-effectively solutions. Modern facilities have access to an abundance of data but struggle with managing and utilizing that data. Monitoring and Diagnostics (M&D) programs employing Smart Analytics enable owners and operators to use this process data gainfully as a low-cost, low-risk answer to operational challenges. This paper describes why M&D programs are critical to improve operations, as well as how operators can cost-effectively deploy a program for a single facility or across a fleet. The success of an M&D program rests on a few important steps: 1) establish a data infrastructure; 2) apply advanced analytics to gain operational insights; 3) relay information to operations and maintenance personnel who can turn insights into corrective action. Data infrastructure includes the instrumentation, wiring, and a data historian to collect and store the information. The data historian collects data from a number of different sources (such as PLC, DCS, SCADA or other systems) and stores it in a readily accessible format. Advanced analytics programs use software and applications to provide early warning of a developing problem related to a specific piece of equipment or within the operating process. The analytics platform applies performance calculations to the data so that an operator can receive continuous feedback on equipment performance relative to its design specifications. A well-defined set of M&D processes and procedures is also necessary to leverage the available tools fully and to ensure effective use of limited facility resources. M&D processes identify, prioritize, track and resolve important issues optimally, which boosts personnel resource effectiveness.
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