A Predictive Maintenance Strategy based on Real-Time Systems

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Presentation transcript:

A Predictive Maintenance Strategy based on Real-Time Systems SPE Paper 161906 ADIPEC 2012 Presented by Dileep Chandran National Drilling Company, Abu Dhabi

Outline Introduction: Predictive model & Advantages Aims and objectives Methods of analysis: Manual & Real-time measurements Data analysis Performance trends analysis Optimization requirements Proposed real-time system Recommendations Outline

Maintenance plays an important role to realize full productive capability of industry Preventive maintenance involving inspection, servicing, repairing or replacing physical components of machineries, plant, and equipment is general practice Predictive maintenance represents a further improvement in preventive maintenance strategies Predictive maintenance is based on actual condition of the machine and performance trends, rather than some pre-set schedule Introduction

Predictive Maintenance Uses Equipment Specifications Compares past and current Performance Measurements Enables optimized scheduling of maintenance activities Predictive Maintenance

Advantages Increased Equipment efficiency and reduced operation losses Minimize probability of unexpected failures Reduce maintenance cost and secondary damage Extend the life of plant items Improve product quality Advantages

Develop strategies for optimization of maintenance schedules based on performance measurements Propose improvements by using modern real-time data collection and analysis systems Recommendations for construction of predictive models to optimize maintenance schedules using real-time systems Aims and Objectives

Manual Measurements Equipment identification information Description of the measurements Date of the maintenance Lower operational window limit Upper operational window limit Measured value Manual Measurements

Method of Analysis Data Collection Manual Measurements Real-time Trend Display & Analysis Trend Display & Analysis Plan Maintenance Plan Maintenance Method of Analysis

Manual Data Collection

Performance is represented with the use of trend lines Data Analysis

Fast changing performance measurements Data Analysis

Variability in performance measurements Data Analysis

Performance Trend Analysis Stable performance within the tolerance levels Performance Trend Analysis

Performance Trend Analysis Equipment exhibiting degrading performance Performance Trend Analysis

Performance Trend Analysis Equipment with faulty performance Performance Trend Analysis

Post-Intervention Graphs Performed overhaul solves performance degradation Post-Intervention Graphs

Post-Intervention Graphs Performance degradation that merits a new intervention Post-Intervention Graphs

Results for Manual Data Positive Results Predicted degraded performance and failure points Repeated identified interventions An optimized maintenance strategy Results for Manual Data

Results for Manual Data Shortcomings Measurements of low resolution and density Time consuming treatment of the data Fast changes in performance cannot be detected Lack of automation Results for Manual Data

Real-time Measurements

Results for Real-Time Data Positive Results Detected smaller performance changes Allowed higher frequency of measurements Absence of transcription errors Results for Real-Time Data

Results for Real-Time Data Shortcomings Not widely used Requires additional data collection techniques Results for Real-Time Data

Optimization Requirements Reduce down time and eliminate failure points Automate the work orders, and Automate the performance measurements and analysis Optimization Requirements

Proposed Real-Time System General Characteristics Automated and frequent data collection Monitoring by exception Overall view of all operations Integration with the current systems Proposed Real-Time System

Criteria for a Real-Time System Platform considerations Data management considerations Modeling tools System functionality Criteria for a Real-Time System

Components of a Real-Time System

Real-Time Functionality Data Collection Real-time Measurements Monitoring by Exception Integration with existing Systems Trend Display & Analysis Plan Maintenance Real-Time Functionality

Recomendations Increase the maintenance frequency when required Establish post-maintenance quality control reviews Expand the classification of normal operational windows Classify equipment according to their criticality Monitor critical equipment on a continuous basis Monitor non-critical equipment on a regularly scheduled basis Recomendations