Delivering High Value Condition Monitoring at Caterpillar

Transcription

1 Delivering High Value Condition Monitoring at Caterpillar Presented by Dick Douglas, Caterpillar Chris Wiseman, Casne Engineering

2 A Global Reach Global reach and presence is unmatched in the industry Serve customers in more than 180 countries around the globe More than half of our sales are outside the United States Manufacturing, marketing, logistics, service, R&D and related facilities along with our dealer locations total more than 500 locations worldwide Dealers 188 worldwide with more than 126,000 employees Independent, locally owned Key competitive advantage 2

3 A Broad Range of Products and Industries Cat equipment more than 3 million pieces globally is at work for our customers on highways, rail lines, oceans and rivers, in forests, quarries, mine sites and oil fields. 3

4 Advanced Engineering and Integration Services Power Systems, Instrumentation & Controls, Software Solutions 34 years of professional practice OSIsoft Solution Partners since 2001 CAT Solution Providers since 2009 Field services: site assessments and PI integration for CAT Global Petroleum, Global Mining, and Global Power CAT Equipment Care Advisor development, PI data integration, custom tools development 4

5 Condition Monitoring Turning Equipment Data into Actionable Information Creating notifications that are valid and actionable. Its about the end user s trust of the system and its proven history.

6 Business Challenge From information overload. To actionable intelligence Engage End User Visualize Analytics in a Way That s Easily Understood Help the End User Understand the Problem to Make More Intelligent Repair Decisions 6

7 Condition Monitoring - Challenges Getting data back consistently from mobile assets is a huge challenge Assimilating the data and building an analytic structure to process it. Turning the data into actionable information that the end user (repair planner) can fully understand and trust to help him make more efficient, accurate repair decisions 7

8 Performance Leveraging Early Warning Operational Change Prognostic deviation Predictive Minimum Damage Minimum Cost Planned Downtime Planned Some Damage Moderate Cost Moderate Downtime Reactive Extensive Damage High Cost Most Downtime Wear material Physical Indicator Machine Alarm Failure Time

9 Performance Why Focus on a Sensor/Harness Issue? Problem emergence (Small spikes in the exhaust split noticed) Alert about the Erratic (mostly high) behavior of the exhaust split Estimated Thermal Cycle Damage Engine derated low power reported by operator 74 days early warning March 3 rd Time to Failure May 16 th Unscheduled Functional Failure High Predictive Monitoring Early Warning Opportunities Approach Low Dealer/Customer Product Problem Management

10 Solution and Results Solution Implemented PI Asset Framework-Based Customized Analytics Implemented Salesforce Front- End 10

11 Architecture ACE SS Asset PI Analytics AF Information Repository 11

12 Equipment Hierarchy in AF Single Point of Data Aggregation 12

13 Referenced Templates in AF Table References Within All Attributes Attributes Referenced to Allow Changes at a Single Source 13

14 Meaningful Analytics Customized Simple Analytics Trend Violation, Statistical Methods, Alarms Advanced Analytics Anomaly Detection from Normal, Custom Alarm 14

15 Models Mapped Within AF 15

16 Operating Modes Different Operating Modes Require Different Limits 16

17 Limits on Demand 17

18 Asset Based Scorecards 18

19 PI Coresight Integration 19

20 SmartSignal Integration 20

21 Results 21

22 CM Analytics Results Study Done for 18 Month Period 2010 / 2011 Dealer Asset Overview: Actively monitored 4 customer mining sites ~ 125 machines (793C, 793D, 793F and 994F) CM Services Delivered to Dealer: Uninterrupted service - 78 consecutive weeks Delivered 312 reports Communicated over 800 issues with recommended action to dealers Action taken on over 90% of recommendations Results: 275+ sensor/harness issues 450+ system problems 6+ catastrophic engine failure preventions from air leak, premature bearing wear, broken valve stem guide and broken piston rings 75+ injector failures 15+ cases of coolant entry into engine oil 10+ boost/exhaust leaks Value $3.9M+ savings in dealer repair costs and improved efficiencies

23 Cat CM Analytics Dealer Repair Planner Feedback We have had some good wins to date specifically relating to exhaust leaks, sensor issues, voltage drops and engine filter DP. In short the system is operating as an early warning system, we can detect and track issues before they reach level 1 or 2 in the VIMS on board module. Greatest fear is that the direct interaction and help from the Cat service team will go away in the future in favor of automated downloads

24 Subject Matter Expert Caterpillar Senior Analytics Engineer Casne Engineering 24

25 Brought to you by