The Role of Predictive Technologies in Attaining Competitive Advantage

Transcription

1 The Role of Predictive Technologies in Attaining Competitive Advantage by Dr. Klaus M. Blache University of Tennessee Director Reliability & Maintainability Center Research Professor College of Engineering May 12, 2016

2 Thanks for the help Klaus. Battleship run-time is much better now since using the UE Systems Ultraprobe UT-RMC at Galactic R&M Conference in a Galaxy far away Is your Ultrasound PdM Program working? I am not your father

3 Today s Discussion Five areas will be focused on from an industry perspective: Sketch from UE Systems 1. What the data says about the extent of PdM use ( ), 2. Observations from industry 3. Issues and opportunities 4. The role of PdM in making companies more competitive 5. What companies are planning to focus on to get better in R&M

4 Today s Discussion Five areas will be focused on from an industry perspective: 1. What the data says about the extent of PdM use ( ) 2. Observations from industry 3. Issues and opportunities 4. The role of PdM in making companies more competitive 5. What companies are planning to focus on to get better in R&M Based on 3 studies with several hundred companies representing several thousand facilities.

5 Examples of Products from Companies maintenance engineering/repair/overhaul, beverages, oil / gas production & field services, electricity, mining (coal & metals), aluminum, steel, food products, salt, seals, chemicals, petroleum, pharmaceuticals, vehicle transmissions, engines, automobiles / airplanes / trains manufacturing and maintenance, silica, natural gas production and transmission, lumbar, CNC machine tools, pulp & paper, folding cartons, plastics, flooring, gypsum wallboard, building materials, valves and tube fittings, testing & development aerospace, military, nylon, polymers, fibers, pigment, flavor and fragrance ingredients, labels, and manufacturing / recycling nuclear materials UT - Reliability & Maintainability Center 5

6 1991 & 2008 Actual Maintenance Percents Reactive Predictive Preventive 1991 Actual 2008 Actual

7 Actual & Perceived World Class Maintenance Percents Reactive Predictive Preventive 2008 Actual 2008 Perceived World Class

8 1991, 2008 & 2015 Actual Maintenance Percent Reactive Predictive Preventive

9 1991, 2008 & 2015 Actual Maintenance Percent Reactive Predictive Preventive

10 Percent 2015 Study of Total and Predictive Maintenance Compliance (122 Companies representing > 3,000 facilities) Total Maintenance Compliance Predictive Maintenance Compliance

11 Total / Predictive Maintenance Compliance (ratio) Distance above baseline (=1.0) relates to less PdM being done versus Total Maintenance Percent Compliance

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13 Monitoring the composition and physicochemical properties of food components and products during processing and storage. (emulsification, filtration, tenderization and functionality modification) Medical Surgical Dental cleaning Pediatrics Drilling small holes Metal cutting Rock cutting Plastic joining Boilers Pipes Vessels Steam traps U l t r a s o n i c s

14 Today s Discussion Five areas will be focused on from an industry perspective: 1. What the data says about the extent of PdM use ( ) 2. Observations from industry 3. Issues and opportunities 4. The role of PdM in making companies more competitive 5. What companies are planning to focus on to get better in R&M

15 The Reliability of Everything (RoE) - The Future Is Now (MARCON 2017 theme) RCM History and PdM What s Needed What Next Parade of Technologies

16 Fourth Generation Evolution of Maintenance / Reliability Impacted by changing complexity, expectations, business needs, new understanding of R&M First Generation Second Generation Third Generation Fix it when it s broke Systems to plan & control work Large scale maintenance projects Some computer usage Design for R&M Sophisticated CMMS & Expert Systems FMEA, Hazard/Integrity Windows Multiskilling, Teams Condition Monitoring, Predictive Technologies ? Adapted from J. Moubray, RCM2 N&H Study RCM2

17 Those who understand how to implement the IIoT, enabling reliability & maintainability to improve assets have a great opportunity to gain competitive advantage. This refers to such items as learning systems, cloud based applications, wireless connects to monitor and control, embedded intelligence in equipment, real-time analytics on dashboards and more. Klaus Blache Plant Services, 2016

18 How do you measure PM Compliance to Schedule? Assume that your plant has 10,000 PM s (1,000 are PdM) If you do zero PdM tasks, but do all of your other ones, you are still at 90% If you do 50% of your PdM tasks and do 94.5% of all others, you are over 90%

19 North America Actual and Perceived Maintenance Percents versus Top 20% (based on Maintenance Expenditure / Investment in Machinery & Equipment) 25% (2008/2009) 65% 20% Time Based 45% Corrective (2/3 from Predictive Checks & 1/3 from PM Checks) 2008 Actual % Reactive Predictive Preventive 2008 Actual (Top 20%) 2008 Perceived World Class 2008 Perceived World Class (Top 20%) Where you should be

20 PdM Compliance to Schedule is at 73.5%, but not enough PdM is done. 100% of PdM tasks needed to be done >25% of total time should be on PdM Actual is 73.5% PdM Compliance Technologies + 30 % more on corrective fixes for what is found Actual is 15% of total time on PdM Technologies

21 Percent Total PdM Activity PdM Benefit Attained Using 55% Total Pdm as Baseline (=100% of potential benefit) North American average of 15% PdM is only getting about 60% of the potential benefit At 15% PdM is only getting about 20% of the potential benefit Percent PdM

22 Today s Discussion Five areas will be focused on from an industry perspective: 1. What the data says about the extent of PdM use ( ) 2. Observations from industry 3. Issues and opportunities 4. The role of PdM in making companies more competitive 5. What companies are planning to focus on to get better in R&M

23 All PdM Technologies Have A Positive Impact on Maintenance Cost / % RAV With Increasing % Equipment On PdM NDT Source: Adapted from 1997 Benchmarking Study in Chemical Processing industry, John Schultz to be featured in Ron Moore s new book What Tool? When? Selecting the Right Manufacturing Improvement Strategies and Tools

24 Too many companies are not doing enough Predictive Maintenance to attain the related benefits.

25 Don t assume your PM s are correct Use As Is Delete Replace w/pdm Re-engineer-SFMEA Xfer to Ops Xfer to Lube Source: John Schultz, Allied Reliability, Inc. 20,000 Tasks analyzed From Ron Moore, UT-RMC Bootcamp

26 How Future Improvements Can Be Obtained (ROI, Bottom-Line Results) Leadership Engaged Workforce (buy-in) Better Production & Operational Processes & Practices Better Facility/Machinery/Equipment Better Administrative Processes & Practices Other Percent

27 Today s Discussion Five areas will be focused on from an industry perspective: 1. What the data says about the extent of PdM use ( ) 2. Observations from industry 3. Issues and opportunities 4. The role of PdM in making companies more competitive 5. What companies are planning to focus on to get better in R&M

28 Major Changes In Reliability & Maintainability Envisioned In Next 10 Years People & Cultural Improvements More Design-In Reliability & Maintainability More Data Driven Processes & Tools (including Predictive) Maintenance Process Improvements Specific Maintenance Improvements More Sensors & Timely Feedback 13% 6% 26% 16% 19% 20%

29 Major Changes Envisioned in Reliability & Maintainability in Next 10 Years People & Cultural Improvements (26%) (13%) More production operator involvement/shared goals Add/hire full-time Reliability & Maintainability Engineers Training (RCM, cross-training, R & M, skills improvement) More involvement by all employees Improve the culture (management, operator, maintenance) Better cooperation with machine suppliers Black = North American and Global responses Blue = North American response Green = Global response

30 Organizational Culture Index (10 point scale) Organizational Culture and Reliability Process Maturity R= 0.86; R 2 = Plant Reliability Process Maturity (10 point scale) Source: Reliability Book &-Maintainability The Relativity Center- of Continuous Blache Improvement, Dr. Klaus Blache, 2015

31 It is expected that the likelihood of success is 7 times higher if the workforce is engaged (supports the change)

32 Major Changes Envisioned in Reliability & Maintainability in Next 10 Years More Design-In Reliability & Maintainability (20%) (22%) More design-in reliability & maintainability Standardized components/replacement parts on equipment Component reliability improvements Better use of R & M in decision making Standardized controls architecture Reduce complexity Black = North American and Global responses Blue = North American response Green = Global response

33 Major Changes Envisioned in Reliability & Maintainability in Next 10 Years More Data Driven Processes & Tools (19%) (15%) Better use of Predictive Tools Better use of data to drive KPI s/improve processes Better integration of SPC and R & M metrics Better data on the lifespan of critical components Improve OEE Better trend analysis Black = North American and Global responses Blue = North American response Green = Global response

34 Major Changes Envisioned in Reliability & Maintainability in Next 10 Years Maintenance Process Improvements (16%) (28%) Implement full TPM process Dedicated resources for R & M tasks Better CMMS use and capability Less reactive maintenance More timely repairs Implement Reliability Centered Maintenance More Condition Based Monitoring Improve maintenance quality Review maintenance frequencies Black = North American and Global responses Blue = North American response Green = Global response

35 Major Changes Envisioned in Reliability & Maintainability in Next 10 Years Specific Maintenance Improvements (13%) (17%) Better inventory/spare parts control & local sourcing Better lubrication program More kaizen events More reliable electrical/electronics Better system components (i.e., water quality) Better handling of critical spare parts Better equipment upgrade/replacement schedule Improved machine cooling systems Black = North American and Global responses Blue = North American response Green = Global response

36 Major Changes Envisioned in Reliability & Maintainability in Next 10 Years Better Sensors & Timely Feedback (6%) (5%) More machine self-monitoring/feedback/self diagnostics More/better error-proofing/prognostics Improved sensors & data acquisition More equipment troubleshooting/diagnostics More real-time data accessibility & feedback/corrections More remote monitoring More self-calibration Black = North American and Global responses Blue = North American response Green = Global response

37 RMC Data Mining & Benchmarking Lab Weibull Analysis Benchmarking Reliability Modeling Six Metric areas to Top Quartile Performance

38 Plant Services, 2014 PdM in Action report K. Blache, UT-RMC, 2015 R&M in Industry study Why is PdM performed? 1. Uptime Improvement 2. Reduce Maintenance Cost 1. Throughput / Uptime Improvement 2. Reduce Cost 3. Reduce Operational Cost

39 K. Blache, UT-RMC, 2015 R&M in Industry study (over 120 companies representing about 3,000 facilities) Top Quartile Companies in Reactive Average 23% resources allocated towards PdM Were 27% better in OSHA Recordable Incident Rate than the average of the remaining facilities Averaged 7% higher OEE than Middle (2 nd & 3 rd Quartile) and 11% higher OEE than Bottom Quartile

40 Average Maintenance Type Percent (sorted by Reactive Quartiles) PdM Reactive Preventive 10 0 Top 25% Middle 50% Bottom 25%

41 54 UT-RMC R&M Modeling

42 K. Blache, UT-RMC, 2015 R&M in Industry study (over 120 companies representing about 3,000 facilities) Top Half of Companies in Suggestions per Employee Average 3.9 suggestions/employee versus 0.3 for lower half of companies Were 21% better in OSHA Recordable Incident rate Average over 13% higher OEE versus lower half of companies

43 > 100 KPI / Metrics What Company Goals Want To Be Great At Safety People Quality Delivery Cost Six Metric Areas to Top Quartile Performance Industry Specific Data

44 Six Metric Areas to Top Quartile Performance Reactive Maintenance (data on predictive and preventive maintenance, and capital projects will also be collected when available) Maintenance Cost/Replacement Asset Value Overall Equipment Effectiveness (OEE) and Total Effective Equipment Performance (TEEP) when available Inventory Turns (Product and MRO Spare Parts)

45 Six Metric Areas to Top Quartile Performance Mean Time Between Failure (MTBF) Suggestions/Implemented/Employee Asset Utilization Percent (will be used to normalize the data for performance variation)

46 Six Metric Areas to Top Quartile Performance When appropriate, the SMRP BOK definitions will be used. The effort will be performed in three steps. Analysis of SMRP Benchmarking Data Add data from other sources Target industries where data is needed (goal is minimum of three data points on each industry type).

47 Demonstrations Applications Discussions

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