Innovative Wind Maintenance Management CMMS Innovative Wind Maintenance Management CMMS James Parle Muir Data Systems James Parle Muir Data Systems
Nov 21, 2014
Innovative Wind Maintenance ManagementCMMS
Innovative Wind Maintenance ManagementCMMS
James ParleMuir Data SystemsJames ParleMuir Data Systems
Example CMMS Savings without MobileExample CMMS Savings without Mobile
Company Benefit Savings
Improve production capacity (maintenance efficiency) 5 – 15%
Increase equipment efficiency 20%
Increase in production (preventative maintenance) 40%
Reduce maintenance budget 30%
Reduce production downtime 20%
Reduce maintenance labor costs (better scheduling) 10 – 30%
Reduction in overtime 10 – 50%
Labor productivity increase 30%
Inventory cost reduction 25%
Decrease maintenance material cost 20%
Source: industry benchmarks A.T. Kearny, Grant Thornton, PWC, Gartner, ARC, Tomkins, DOE
15 – 50% O&M
Savings
Hydro Asset Management Partnership (HydroAMP)
Hydro Asset Management Partnership (HydroAMP)
Evaluation Method
Data standard
Single database
Plant / utility reports
Open to all users
Expanding US Wind MarketExpanding US Wind Market
28% Growth $50B End of Warranty
30% Spent on Maintenance
$6B O&M 2025
0
10,000
20,000
30,000
40,000
50,000
60,000
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Win
d C
apac
ity (M
W)
Year
Why Wind CMMS?Why Wind CMMS?
Harsh Environmental
ConditionsRemote Locations
Lots of Moving PartsHighly Distributed
Safety Concerns
Complete Maintenance Management SolutionComplete Maintenance Management Solution
Tablet
Management Office
Cloud Server
Analytics
EnterpriseMgmt.
GridSCADA Data
Blades TowerNacelleGeneratorGearbox
API
Maintenance Management Solution DetailsMaintenance Management Solution Details
CMMS Infrastructure / Database / Analysis
DataSharing
Data Source: Tablet in the FieldData Source: Tablet in the Field
Data MovementData Movement
Data In-Take Software Modules
Data In-Take Software Modules
Large Scale Data AggregationLarge Scale Data Aggregation
Plant 1 Plant 2 Plant 1
Plant 3
Plant 2
Plant 2
Plant 4
Plant 3
Plant 1
Owner 1Owner 1Owner 2Owner 2
Owner 3Owner 3
Predictive Maintenance Anonymous Data
Aggregation System
Predictive Maintenance Anonymous Data
Aggregation System
Predictive Maintenance ValuePredictive Maintenance Value
47% O&M Cost Reduction 47% O&M Cost Reduction Source: Electric Power Research Institute
Survey OverviewSurvey Overview
Field Data Office Storage Reporting Demographics
Technology · Time · SatisfactionTechnology · Time · Satisfaction
Work Orders per YearWork Orders per Year
Average 10 Work Orders per Day Average 10 Work Orders per Day
Time in Current PositionTime in Current Position
60% Changed Job Title in Last 2 Years60% Changed Job Title in Last 2 Years
Work Order Process ChangesWork Order Process Changes
72% Change Annually or Less Often72% Change Annually or Less Often
Work Order AnalysisWork Order Analysis
0
3
5
0.00
2.50
5.00
Field Office Storage Reporting
0
30
60
SatisfactionSatisfaction
TimeTime
TechnologyTechnology
Extremely
Moderately
Not at all
Analog
Digital
SomewhatDigital
0 Mins
30 Mins
60 Mins
Satisfaction vs. Employee TypeSatisfaction vs. Employee Type
0.00
2.50
5.00
Field Office Storage Reporting
Technicians
Engineers
Managers
Executives
Moderately
Not at all
Extremely
Technology vs. Company TypeTechnology vs. Company Type
0
2.5
5
Field Office Storage Reporting
ISP
OO
OEM
Digital
SomewhatDigital
Analog
CMMS Company PrioritiesCMMS Company Priorities
0
3
6
Reducedinventory costs
Customersatisfaction
Increaseduptime
Greateraccuracy
Predictiveanalysis
Scheduling
ISP
OO
OEM
Aveage
Linear (Aveage)
Least important
Somewhat important
Most important
Wind CMMS LandscapeWind CMMS Landscape
INDUSTRYSPECIFICINDUSTRYSPECIFIC
INDUSTRYAGNOSTICINDUSTRYAGNOSTIC
LOW COSTLOW COST
HIGH COSTHIGH COST
Generic Low CostGeneric Low Cost
Generic High CostGeneric High Cost In-House SolutionsIn-House Solutions
Wind Specific Low CostWind Specific Low Cost
Demand Better SolutionsDemand Better Solutions
CMMS reduces O&M costs
Technology is ready
Wind lagging behind other industries
Data becoming competitive advantage
Predictive maintenance is the prize