1. Managing Asset Performance With Data From Machines

2. What is my asset performance?
Success metrics:
Are we maximizing ROA?
Am I reducing my risks?
Are we improving asset availability?
Are we doing the right level of preventive maintenance? Is it effective?
What is our performance against downtime targets?
Are we minimizing inspection hours and mean time between failure (MTBF)?
Are we improving our first-time-fix-rate (FTFR)?
Are we optimizing the useful life of the asset?
How do I reduce costs without sacrificing reliability?
What is asset performance, how do you measure it? Availability, costs (maintenance & lifecycle), unscheduled maintenance and metrics such as MTBF, FTFR, MTTR
But also asset health scoring, fleet profiling – how are assets performing relative to each other
The only way to answer these questions is with data
Source:

3. APM improves asset performance using data, analytics & AI
Asset Performance Management (APM) is designed for decision support
Advanced analytics and artificial intelligence (AI) are driving differentiation. It helps engineers and planners make better decisions by shifting asset maintenance strategies from preventive to predictive and prescriptive
APM improves asset performance using data, analytics & AI
APM is about optimizing the performance of operational assets, increasing asset availability while minimizing costs of maintaining them
Enterprise Asset Management (EAM) is designed for maintenance execution and asset data
EAM and APM are inter-related by very different systems. The focus of EAM is around execution related activities like work order tracking, etc
APM allows you to measure and improve your asset performance using data, analytics and AI
And your biggest source of data is Maximo!
APM is a natural complement – while EAM is about how you manage assets, APM is about decision support – measuring, evaluating, analyzing and making better decisions about your maintenance strategy
Maximo contains data about WO history, meter readings, PM schedules, etc. that we can analyze to improve asset
Planning & Scheduling
Health Monitoring
Predictive Maintenance
Prescriptive Repair
Execution
Capital Planning
Prioritization

4. Leaders of asset-centric and asset-intensive businesses recognize they must focus on optimizing asset support as the primary mode of differentiation
But how?
50%
of asset-intensive organizations have some form of asset analytics
But...
<10%
have an APM platform
Source: IDC, 2018

5. Asset Lifecycle & APM EAM APM 2 1 3 4 6 5 APM Execution
Strategy Selection 2 3 1
Plan & Schedule
Operationalize Strategy
Criticality, Risk, & Failure Modes Analysis
Health Monitoring
Predictive Monitoring
Condition
Predictive
Run to fail
Time based 4
Execute 5 6
Capital Planning Prioritization
Root Cause Analysis
AIP
Prescriptive Repair
Bad Actor Analysis
Planning & Execution
Analysis
Actions & Adjustments
Maximo
IBM APM Capabilities
Partner capabilities

6. APM enhances EAM with Analytics and AI
APM Capabilities
APM Benefits
Increase asset life
Reduce lifecycle costs
Optimize spare inventory levels
Asset and fleet level insights to optimize maintenance strategy
Strategy & Fleet Analysis
Reliability Engineer
APM
Prioritization of activities based on asset health and predictive insights
Increase MTBF
Improve reliability
Reduce PM cycles
Planning & Scheduling
Maintenance Supervisor
MTBF = Mean time between failures
FTFR = First time fix rate
MTTR = Mean time to repair
EAM
Improve FTFR
Decrease MTTR
Decrease maintenance costs
AI assistant for improved repair efficiency
Maintenance Technician
Execution

7. IBM APM supports an analytics journey
Optimize
Improve models through continuous learning
Predict
Use sensor Data and work history To Predict Failures
Recommend
Monitor
evaluate your assets in context
Maintain assets with intelligent insights
Enrich your data ecosystem
Connect
Continuous Learning
Feedback loops enable ongoing model improvements
There is a natural progression
… and you CAN get started with APM simply by leveraging the data you already have in Maximo
But you also have data from operations – your PLCs, SCADA/DCS systems, sensors and IoT
Equipment Maintenance Assistant
Helps identify the right steps to fix an issue given current symptoms and history
Predictive Maintenance
Analyzes device properties to predict failures and performance degradation
Asset Health
Insights
Analyzes maintenance and IoT data to help prioritize maintenance & replacement activities
IoT Connection Service

8. Maximo Asset Health Insights drives improved asset strategies
Reduce downtime and maintenance cost with objective asset health metrics
Enables reliability engineers and maintenance supervisors to gain a deeper understanding of the health of their assets. Provides capabilities to model, map, monitor, and optimize the health of assets.
Visibility into asset condition, from an 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.
Enables Immediate action and/or provides engineers with rich set of sensor and asset data to determine proper course of action.

9. IoT Platform and MAHI for an online view of Asset Health and Condition
Sensors or SCADA
via IoT Gateway
Connect, Store and Derive
in IoT Platform with Analytics add-on
Asset Health
via MAHI rules ∑
Raw data
Meaningful
Metrics
Inspection via
Mobile client
Meters & WO history

10. Watson IoT Platform | Connect
Connect your devices, equipment, and workforce to gain a new level of insight into your business
ANALYTICS
Real-time
Machine Learning
Cognitive
Edge
RISK MANAGEMENT
Proactive Protection
Security Analytics
Anomaly detection
COMMERCE | BLOCKCHAIN
PLATFORM FOR BUSINESS
CONNECT
Secure connectivity
Device management
Visualization
INFORMATION MANAGEMENT
Store & Archive
Transform & Integrate
Augment
Weather
PLATFORM
Focus Areas
Our users include embedded developers, cloud application developers, IoT system administrators and operators plus IoT device end users
Want to compose IoT applications quickly and be able to operate and manage resulting systems.
Expect fast time-to-value, simplicity, flexibility, clear documentation. 1
Secure Connectivity
Connect devices via MQTT(S) or HTTP(S)
Authentication and Encryption
Authenticate Devices via Token and/or Certificates, encrypt Payload
Monitoring
Monitor Device Status, Connectivity Logs, Device Logs
Device Management
Device Metadata, Reset, Factory Reset, Upload Firmware, Install Firmware
Visualization
Quick Data Visualization directly of incoming data streams, easy Drag&Drop Dashboards 2 3 4 5

11. Watson IoT Platform

12. Analytics | Real-Time Analytics1
Use the build-in Real-Time Insights to create powerful stream analytics rules processed in real-time and scaling with all onboarded devices.
Build Rules with logic equations by drag and drop based on device data schemas and assign different rule Severity Levels.
Trigger Rule Actions such as sending , SMS, calling REST APIs or IFTTT.
Show all Rule violations on build-in Alerts Dashboards or access the full data via REST APIs.

13. IBM Predictive Maintenance
7/2/2019
IBM Predictive Maintenance 2
analyze & predict 3
report & recommend 1
connect
act
Identify and manage asset reliability risks that could adversely affect plant or business operations
aggregate
This is the one chart that summarizes the IBM Prescriptive Maintenance solution.
Data can be ingested from multiple sources. At a minimum, the solution needs event data that includes failure records, it needs profile data which can include such information as the assets name, manufacturers name and date of manufacture, and it needs maintenance data which can come from EAM systems like Maximo.
The solution analyzes the data and provides a prediction of the asset’s next failure date and compares this to the next planned maintenance. This enables the Reliability Engineer to Identify and manage asset reliability risks that could adversely affect plant or business operations
IBM Prescriptivee Maintenance on Cloud :
Is a SaaS offering;
Easier implementation and faster time to value
Designed for line of business users - enables you to load data, analyze that data, make and test predictions, and preview reports and dashboards.
Solves specific asset-related problems with prebuilt analytics
Provides meaningful insight at point of engagement
Reduces need for data scientists and data integration expertise
Enables organizations to apply a wide range of analytic capabilities to operational data generated by production assets and products to gain a more detailed and accurate understanding of asset and product performance.
Combines asset maintenance and performance data from disparate sources and analyzes these data to develop predictive models.
Models calculate asset health scores and predict potential failure with the goal of preemptively deploying maintenance and repair resources to increase asset availability and reduce maintenance costs.
Connect to IBM IoT Foundation (represented by the blue circle with the chip, and other devices) to collect device data.
Integrate with EAM systems such as IBM Maximo to accelerate response time for inspection and maintenance activities.
Assess current asset health and provide advanced warning of potential asset or component failures, thereby, enabling preemptive deployment of maintenance and repair resources.
Line-of-business personnel responsible for operations and maintenance of critical assets are able to:
Consolidate data from disparate sources such as from sensors, Supervisory Control and Data Acquisition (SCADA) systems, telemetry, and work order history.
Analyze historical maintenance information to determine top failure modes and recommend optimum maintenance schedules and procedures.
Analyze historical asset performance data to develop predictive models for asset health scores and potential failure.
Perform asset predictive maintenance analytics and reporting to identify assets that are at risk of failure by providing asset condition and failure projections.
Watson IoT
gateway
IoT device
Maximo

14. Equipment Maintenance Assistant Data Inputs
Announcing: IBM Equipment Maintenance Assistant: AI assistant & shared expertise for every field technician
Improves problem diagnosis and provides guidance to help technicians identify the right repair the first time
Aggregated data views
Watson AI-Powered learning
Point of impact insights
Equipment Maintenance Assistant Data Inputs
Equipment & Engineering Manuals
Data from EAM Systems
IoT Sensor Data
Regulatory Standards
Speaker Notes
As some may have heard, we made an announcement Monday for a new offering called IBM Equipment Maintenance Assistant
This exciting offering brings an AI assistant to your field technicians
Helps technicians improve problem diagnosis and privides prescriptive repair guidance to help technicians identify the right repair the first time
Interest from clients that are experiencing aging workforce, risking maintenance costs, and equipment that is increasingly complex to repair and understand
One of the biggest benefits is a very tight integration with Maximo. Very easy add-on to quickly bring AI to Maximo field technicans.
Watson learns from the Best Technicians, sharing expertise to Every Field Technician

15. IBM Equipment Maintenance Assistant How it works
Events
Collect documentation and data
Queries
Business user prepares, loads, and marks documents
Refine model
SME such as Reliability Engineer uses studio to refine model
Watson Assistant for Equipment Maintenance
Ask questions
Field Technician receives work orders and query to understand repair procedures, identify parts, materials, & tools needed or update situation information.
Sample Triggers
Unscheduled work order in Maximo
Predicted failure alert from PM
IoT Reading Anomaly
Visual problem detected by VI …and more
Training & Modeling
Day-to-Day Operations

16. Supporting Work Execution with a Little AI from Watson IoT
Equipment Maintenance Assistant
PAUL

17. How it looks from Maximo

18. Begin a workorder

19. Launch EA from a workorder

20. Open in a new tab, automatically brings the topic and equipment into the query.
The results queried from the asset knowledge base will be displayed on the page.
The knowledge base can be anything — e.g. asset manual or the field operation manual, etc.

21. Open the corresponding paragraph
User can read whole section of the document where EA queried for the user.

22. Change the search criteria
User can also place the W.O. descriptions automatically by clicking the “Search by” drop down menu.
description
Long description
asset
location
failure class
or custom search
Labor,
Materials Services,
Tools,
Attach files,
Specs
Safety Plan (Hazard)
Failure Details (Failure code)
Downtime history
Work log and communication log
Work order
Details
Plan (task, spare parts)
Comments
Attachments (Spec., imgs)

23. Search historical work-orders of… The selected asset Similar asset
Search the result in the historical work-orders, in order to find the similar w.o. related to current.
Search historical work-orders of…
The selected asset
Similar asset
All assets
Each of the cards contains…
Failure class
Descriptions
Asset
Location
Assigned labor
View details should expose the job plans (tasks, items and materials), work log, and attachments (to view photos etc).
Work order
Details
Plan (task, spare parts)
Comments
Attachments (Spec., imgs)

24. KPI Templates: Easy way to build groups of KPIs

25. KPI Templates: Easy way to build groups of KPIs

26. KPI Templates: Define Variables
Watson / Presentation Title / Date

27. KPI Templates: Main screen

28. KPI Templates: Generated KPIs from Template

29. KPI types you could configure
- Measure Operational data - Open WO? Overall Expenses? SLA compliance? PM Compliance? - Measure User Compliance - On time closure? Is Labour Reporting hours? Is Failure Reporting entered? - Measure Maximo License compliance? - Measure MAXSESSIONS?

30. Thank you!