asset health client deck

1 1 Source: T.A. Cook, Maintenance Efficiency Report 2013, August 2013. http://uk.tacook.com/fileadmin/files/3_Studies/Studies/2013/T.A._Cook_Maintenance_Efficiency_Report_2013_En.pdf?tracked=1 2 Source: Oniqua Enterprise Analytics, Reducing the Cost of Preventative Maintenance, http://www.plant-maintenance.com/articles/PMCostReduction.pdf

A time-based approach is embraced by a traditional preventive maintenance program. Problems that arise:

•  Consuming expensive resources

•  Potentially introducing failure by disrupting stable systems

40% of preventive maintenance costs are spend on assets with negligible affect on uptime 1

45% of all maintenance efforts are ineffective 2

30% of preventive maintenance activities are carried out too frequently 2

Watson IoT / Insights into Asset Health

Preventive Maintenance programs effectively improve reliability, however…

•  Manyorganiza+onshavemorePMsthantheyhavestafftoexecute•  Op+miza+onandPriori+za+onofPMsisbecomingnecessary•  Effortneedstobebasedonthehealthoftheasset

Watson IoT / Insights into Asset Health 2

Condition based maintenance uses IoT data to assess asset health

40% of preventive maintenance costs are spent on assets with negligible affect on uptime 1

The results speak for themselves

Reduce maintenance costs by up

to 25%

Eliminate up to 70% of

breakdowns

Reduce downtime by

up to 50%

Cut unplanned outages by up to 50%

Reduce scheduled

repairs by up to 12%

Reduce capital

investment by 3-5%

Monitor and analyze asset health data, both historical and real-time

Intervene at the right time, before assets go down

Prioritize and optimize resources


Sensor data Real time and Historical

Maximo Asset Information Asset Health

Condition data is enhanced when combined with contextual information to give a more perfect picture of Asset Health

•  Real time sensor data from the equipment via individual sensors (add-on or embedded)

•  Real time sensor data or alerts from SCADA systems •  Historical trends of sensor data from historian or other data repository •  Inspection data that might include measurements, observations, photos gathered

manually or from mobile devices •  Maintenance history of the asset •  Related information: environmental (temp, humidity, etc.), weather, usage, output

Understanding current condition alone, is not enough…

IBM Maximo Asset Health Insights

Designed with Reliability Engineers in mind Subscribe to warnings and notifications for response to Asset issues prior to failure Define Asset Health using data from many sources including Maximo and Real-time

Remaining useful life Maintenance and failure history Asset Condition based on real time and historical information

Leverage Historical Weather as a Key Element in determining Asset Health Minimize unnecessary maintenance based on Asset Health score Insights to determine repair vs. replace


Available now

•  Contextualizes device data • Monitors streaming data to

detect situations •  Filters the data for analysis by

Maximo Users •  Stores data for further analysis

IBM Watson IoT Platform

3 Historical sensor data

Real time filtered data from automation systems 2

4 Historical weather data

IBM Maximo Asset Health Insights

•  Enables Immediate action and/or

•  Provides engineers with rich set of sensor and asset data to determine proper course of action

•  Visibility into asset condition, from asset lifecycle perspective

•  Consolidates Asset data, historical and real-time, including data from external data systems, weather data, etc.

•  Advanced dashboard view enables proactive asset and maintenance decisions

1 Real Time data from low cost add-on sensors


How IoT information is used within Maximo Asset Health Insights

Customizable Work Center for Reliability Engineers


Consistent look and interface with Maximo 7.6

Drill into Specific Contextual Data for Assets


MeterReadings

Asset detail

Weather can be an important element for Asset Health

Transmission line sag is a key factor in determining power line health. Temperature and humidity can significantly affect sag. Understanding sag in the context of historical weather for that location, engineers can more effectively determine asset health.

Correlation of high temperature readings from a pump with current weather can be used to determine a potential problem vs. normal operation given ambient temperature.

The number of times an asset has operated in weather outside its recommended operating parameters (i.e. over 90 degrees F.) can be a driver in determining overall asset health


Why Consider Leveraging Asset Health?

Reduce the cost and frequency of asset failures

•  Perform maintenance while the asset is working to reduce disruptions to operations

•  Improves overall equipment reliability

1

•  Optimizes time spent on maintenance

•  Reduces overtime costs by scheduling the activities

•  Decreases requirement for emergency spare parts

Minimize unscheduled downtime due to catastrophic failure 2

•  Defer unneeded maintenance

•  Prioritize PM workload based on condition

2 Reduce maintenance workload and costs with PM optimization 3


Take-aways from today

Maximo Asset Health Insights lets businesses capture knowledge about the true health of valuable assets and maximize the value of your maintenance investment.

Understand what data your organization is using to make Preventive Maintenance decisions. Where can you start to unlock value quickly?

1

2

Maximo Asset Health Insights represents a new way of maintaining equipment - one based not only on current condition-based readings coming from the equipment, but also informed by other influences like age, maintenance history, weather incidents and historical context of subcomponents.

Your next steps

1

2 Schedule a demo of Asset Health Insights to discover how a consolidated view of asset data improves reliability. Check out the details at IBM.co/asset-mgt. Then contact your IBM solution seller to get started!

11

Thank you

Visit ibm.com/iot Watson IoT / Insights into Asset Health

asset health client deck

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