Predictive Maintenance & Service (PdMS) Outline and Value Proposition Oliver Mainka, Strategic Projects November 2014 What is “Predictive Analysis”? Predictive analysis encompasses a range of analytic techniques “ … the exploration and analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns and rules.” Gordon Linoff and Michael Berry Authors of “Data Mining Techniques” “ … the process of discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques.” Gartner Group © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 2 Predictive Analytics Needs (with Consumer Products samples) Forecasting What anomalies might exist and conversely what groupings or clusters might exist for specific analysis? Anomalies What are the correlations in the data? What are the cross-sell and up-sell opportunities? Challenges Relationships © 2014 SAP AG or an SAP affiliate company. All rights reserved. How do historical sales, costs, key performance metrics, and so on, translate to future performance? How do predicted results compare with goals? Key Influencers Trends What are the main influencers of customer satisfaction, customer churn, employee turnover, and so on, that impact success? What are the trends: historical / emerging, sudden step changes, unusual numeric values that impact the business? Customer 3 Predictive Maintenance is an Important Building Block for Improving Failing Assets Sense Act Sensor Data Business Data Environmental Data Pattern and Root Cause Analysis Predictions Predict - Create notification - Alter maintenance schedule - Preposition spare parts - Find “bad” suppliers - Change product specs - Service scheduling - Recommend services - Lower cost for PowerByHour -… IT/OT 50 billion devices connected by 2020* 1/5 IoT M2M 40-50% CAGR for M2M market until 2020* price of sensors, microprocessors & wireless technologies today vs. 4 years ago** *Source: Gartner – “Top 10 Tech Trends for 2013” – 2012 **Source: Economist Intelligence Unit – ”The Rise of the Machines” – 2012 © 2014 SAP AG or an SAP affiliate company. All rights reserved. Source: Gartner Customer 4 Predictive Maintenance and Service Illustrated: The P-F Interval Curve Machine Capability / Resistance to Failure “Can” Preventive Maintenance & Monitor Condition Equipment Unusable Repair or Replace P Potential Failure Early Signal 1 – Ultrasonic Energy Detected Effect of PdMS Early Signal 2 – Vibration Analysis Fault Early Signal 3 - Oil Contamination Detected Audible Noise Hot to Touch Mechanically Loose “Want” F Functional Failure Ancillary Damage Total Failure Time Cost to Repair © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 5 SAP HANA Platform SAP InfiniteInsight © 2014 SAP AG or an SAP affiliate company. All rights reserved. SAP Lumira SAP Predictive Analysis Customer 6 2013 PdMS Co-Innovation Projects (all OEMs) Industry Country Scope Automotive Germany Manufacturing Quality Assurance by automatic failure identification and anticipation based on machine data. Automotive Germany, US Vehicle health prediction to improve manufacturing quality, service planning and customer satisfaction based on business and telemetry data. Very big data: Hana / Hadoop Automotive Tuning Germany Product improvement in R&D based on vehicle test data. Agricultural Equipment US Early identification of emerging issues for product improvement and failure prediction to reduce downtime based on business and telemetry data. Agricultural Equipment Germany Identification and prioritization of machine failure pattern for product improvement based on business and machine data. Compressed Air Equipment Germany Machine health prediction to lower service costs and increase machine up-time. Enable service, sales and R&D to transform the company to an industrial service provider. Food Industry Equipment Germany Identification of health finger print based on vibration analysis. Integration of and monitoring of machine health using failure pattern for product improvement from business and machine data. Aerospace US Systems trending and alert management framework which allows customer support to propose alternative maintenance schedules which may avoid unplanned downtime, increase aircraft availability and increase service and maintenance revenues. © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 7 2014 PdMS Co-Innovation Projects Industry Country Scope Aerospace USA Aircraft Health Management / work order creation Mining Canada Yield prognosis for wells based on asset measurements Rail Italy Optimized maintenance schedules based on telematics Chemical Germany Data mining of all manufacturing data from assets and production Aerospace MRO Switzerland Root cause analysis / new customer services Flooring USA Relationship between customer warranty cases, production issues, and faulty machines Oil & Gas USA Lower unneeded preventive maintenance activities; predict breakdowns Industrial Equipment USA New customer services based on telematics data Food and Beverage USA Lower downtime of bad actor equipment by root cause analyses and predictions Started / Confirmed Discussing © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 8 Demo Predictive Maintenance & Services Application © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 9 Demo “Emerging Issues Detection” © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 10 Visualizing Sensor / Tag Event Data © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 11 Correlating Sensor Data and Maintenance Events © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 12 Vibration Analysis Identification of health finger print based on vibration analysis Trend analysis and pattern comparison on vibration and process data Detect emerging dangerous vibrations Change from manual, reactive vibration analysis process to an automated, proactive process Improvement of machine uptime and reduction of maintenance costs. © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 13 Lower-level machine data analysis Analyze motor test bed data Find metal cracks and compare heat signatures Oven temperature © 2014 SAP AG or an SAP affiliate company. All rights reserved. Press force Press temperature Customer 14 Association Rules and Decision Trees © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 15 Practical Example for Association Rules and Decision Trees © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 16 Applying Association Rules to New Vehicle Readouts © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 17 Sample Decision Tree © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 18 Integrating data from unstructured text © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 19 Text Cluster Analysis © 2014 SAP AG or an SAP affiliate company. All rights reserved. Customer 20 Thank you Contact information: Oliver M. Mainka VP Product Management oliver.mainka@sap.com +1 (650) 391-4701 © 2014 SAP AG or an SAP affiliate company. All rights reserved. © 2014 SAP AG or an SAP affiliate company. All rights reserved. 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