Pump Monitoring and Analysis

A principle challenge in creating an effective maintenance system for pumps is producing a systematic framework to link static pump properties, high- fidelity operational data, and operational context. Examples of attributes, data streams, and events that should be brought together so that users can see asset information in context are shown in Table 6.1.

Having this information in the EIDI means that pump data can be organized according to asset attributes and topology (Figure 6.11). The asset object model creates a template for a basic pump that includes available information that applies to the majority of pumps, such as nameplate data, maintenance data, date installed, criticality to the process, next scheduled maintenance date, and so on. Once templates are populated with data

TABLE 6.1

Pump Characteristics and Variables

Manufacturer

Best Efficiency Point (ВЕР) (Total Dynamic Head [TDH], Efficiency, 80%, 110%)

Type

Pump on/off pump run hours

Size

Pump start/stop number and frequency

Horsepower

Motor temperature

Available net positive suction head (NPSH), a

Flow rates and pressures (in, out)

Required NPSH, r

Vibration monitoring points

Static head

Bearing temperatures

Friction loss

Motor current signatures

EQ number

Motor power, kW

Process

Visual inspection results

FIGURE 6.11

Simplified pump efficiency evaluation to generate an event.

streams, calculations, and static data values, users have access to a single, consistent method to shape and prioritize pump maintenance. CBM implementations are more costly to manage through manual inspections.

For example, users can track run hours of the pump or track basic conditions related to the operation and maintenance of the pump. When pump issues or failures occur, historical data can be analyzed to develop condition indicators and link root causes to vendor, use conditions, or external conditions. Once this first phase is complete, the team can consider implementing a more robust strategy of incorporating alarm data and integrating the EIDI with a CMMS system (to drive a true CBM solution). For example, if the number of pump run hours is approaching the vendor-specified limit for maintenance or calibration, operators can use EIDI to define a trigger that creates a work order in the local CMMS system. When this work order is complete, a message can be returned to reset the run-hours counter on the asset. Now that both systems are configured for operations, maintenance, engineering, and production planning, the various teams will be able to collaborate and support each other in numerous ways.

Simply deploying condition-based monitoring on plant pumps can lead to improvements in operation and maintenance and is a first step to true CBM. Condition-based monitoring can be accomplished using operational data and condition-specific data and eventually lead to information that serves as the basis for other predictive techniques, such as APR, which can be particularly useful in pump maintenance.

Visualizing Pump Actionable Output

A key part of an effective PM solution is to develop accurate condition indicators and methods to display actionable asset condition information. The EIDI system provides visualization options that can be reused, shared throughout the enterprise, and easily modified as operations and data needs evolve. Operators can use real-time displays to monitor asset conditions within any maintenance strategy (Figure 6.12). Users can create standard visuals and KPIs of pump data for knowledge workers in multiple roles using EIDI visualization tools (OSIsoft's PI Vision).

When organizations use the EIDI asset object model to structure asset data, operators, maintenance personnel, or engineers can use asset-relative displays that toggle between different pump assets associated with the same template. Over time, users can determine how one vendor's pumps perform relative to other vendors' pumps or comparative maintenance costs. Users do

FIGURE 6.12

Sample condition-based monitoring display for field checks.

FIGURE 6.13

Equipment totalized run time with service history information.

not have to create individual graphics or calculations for each pump. Using standard asset templates simplifies the creation and maintenance of the data management system.

Maintenance and engineering personnel can drill down into archived condition-based monitoring data for post hoc analyses. Engineering can conduct root cause analyses, develop more precise indicators to optimize CBM solutions, or create analytics for equipment replacement evaluation. In some cases, maintenance may need to access this information to evaluate what maintenance to perform and when to perform it.

Another example report showing totalized run times and service history is shown in Figure 6.13.

 
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