the role of predictive technologies in attaining ...fittings, testing & development...

The Role of Predictive Technologies in

Attaining Competitive Advantage

by

Dr. Klaus M. BlacheUniversity of Tennessee

Director – Reliability & Maintainability CenterResearch Professor – College of Engineering

May 12, 2016

Reliability & Maintainability Center- Blache

Thanks for the help

Klaus.

Battleship run-time

is much better now

since using the UE

Systems Ultraprobe

I am not your father

UT-RMC at Galactic R&M Conference

… in a Galaxy far away

Is your Ultrasound PdM

Program working ?


Sketch from UE Systems

Today’s DiscussionFive areas will be focused on from an industry perspective:

1. What the data says about the extent of PdM use (1991-2015), 2. Observations from industry3. Issues and opportunities4. The role of PdM in making companies more competitive5. What companies are planning to focus on to get better in R&M



1. What the data says about the extent of PdM use

(1991-2015)

2. Observations from industry3. Issues and opportunities4. The role of PdM in making companies more competitive5. 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.


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

Examples of Products from Companies

5UT - Reliability & Maintainability Center

0

10

20

30

40

50

60

Reactive Predictive Preventive

1991 & 2008 Actual Maintenance Percents

1991 Actual 2008 Actual


0

10

20

30

40

50

60

70


2008 Actual & Perceived World Class Maintenance Percents

2008 Actual 2008 Perceived World Class


0

10

20

30

40

50

60

1991 2008 2015


1991, 2008 & 2015 Actual Maintenance Percent


0

10

20

30

40

50

60

1991 2008 2015

Reactive

Predictive

Preventive

1991, 2008 & 2015 Actual Maintenance Percent



0102030405060708090

100

Total Maintenance Compliance Predictive Maintenance Compliance

Pe

rce

nt

2015 Study of Total and Predictive Maintenance Compliance

(122 Companies representing > 3,000 facilities)


0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

Total / Predictive Maintenance Compliance (ratio)

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

http://scars-of-the-past.wikia.com/wiki/TitanicReliability & Maintainability Center- Blache


Monitoring the composition

and physicochemical properties of

food components and products

during processing and storage.

(emulsification, filtration, tenderization

and functionality modification)

Boilers

Pipes

Vessels

Steam traps

Drilling small holes

Metal cutting

Rock cutting

Plastic joining

Medical

Surgical

Dental cleaning

Pediatrics

U

l

t

r

a

s

o

n

i

c

s


1. What the data says about the extent of PdM use (1991-2015) 2. Observations from industry

3. Issues and opportunities

4. The role of PdM in making companies more competitive5. What companies are planning to focus on to get better in R&M


The Reliability of Everything (RoE)

- The Future Is Now (MARCON 2017 theme)

• RCM History and PdM

• What’s Needed

• What Next

• Parade of Technologies



1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

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

?

First Generation Second Generation Third Generation

Fo

urth

G

en

eratio

n

Evolution of Maintenance / Reliability

Impacted by changing complexity, expectations, business needs, new understanding of R&M

N&H Study RCM2

Adapted from J. Moubray, RCM2


“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

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%

How do you measure PM Compliance to Schedule ?


0

10

20

30

40

50

60

70


Actual and Perceived Maintenance Percents versus Top 20% (based on Maintenance Expenditure /

Investment in Machinery & Equipment)

2008 Actual

2008 Actual (Top 20%)

2008 Perceived World Class

2008 Perceived World Class(Top 20%)

North America

20% Time Based45% Corrective (2/3 from Predictive Checks & 1/3 from PM Checks)

10%

25%

Where you should be

65%


(2008/2009)

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 PdMTechnologies + 30 % more on corrective fixes for what is found

Actual is 73.5%PdM Compliance

Actual is 15% of total time on PdM Technologies



0

10

20

30

40

50

60

0 10 20 30

Percent PdM

Pe

rc

en

t To

ta

l P

dM

Ac

tivity

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

PdM Benefit Attained


1. What the data says about the extent of PdM use (1991-2015) 2. Observations from industry3. Issues and opportunities4. The role of PdM in making companies more

competitive

5. What companies are planning to focus on to get better in R&M


NDT

Source: Adapted from 1997 Benchmarking Study in Chemical Processing industry, John Schultz to be featured inRon Moore’s new book What Tool? When? Selecting the Right Manufacturing Improvement Strategies and Tools


All PdM Technologies Have A Positive Impact on Maintenance

Cost / % RAV With Increasing % Equipment On PdM


Too many companies are

not doing enough

Predictive Maintenance to

attain the related benefits.

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

0 5 10 15 20 25 30

Other

Better Administrative Processes & Practices

Better Facility/Machinery/Equipment

Better Production & Operational Processes &

Practices

Engaged Workforce (buy-in)

Leadership

How Future Improvements Can Be Obtained

(ROI, Bottom-Line Results)

Percent



1. What the data says about the extent of PdM use (1991-2015) 2. Observations from industry3. Issues and opportunities4. The role of PdM in making companies more competitive5. What companies are planning to focus on to get

better in R&M



26%

20%

19%

16%

13%

6%

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

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

Major Changes Envisioned in Reliability & Maintainability in Next 10 Years

Black = North American and Global responsesBlue = North American responseGreen = Global response


0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8

Organizational Culture and Reliability Process Maturity

R= 0.86; R2= 0.73

Org

aniz

atio

nal

Cu

ltu

re In

dex

(1

0 p

oin

t sc

ale

)

Plant Reliability Process Maturity (10 point scale)

Source: Book - The Relativity of Continuous Improvement, Dr. Klaus Blache, 2015Reliability & Maintainability Center- Blache

It is expected that the “likelihood of success”

is 7 times higher if the workforce is engaged

(supports the change)


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




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




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




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




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




RMC Data Mining & Benchmarking Lab

Weibull Analysis

Benchmarking

Reliability Modeling


Six Metric areas to Top Quartile Performance


Plant Services , 2014

PdM in Action report

K. Blache, UT-RMC, 2015

R&M in Industry study

1. Uptime Improvement

2. Reduce Maintenance

Cost

3. Reduce Operational

Cost

1. Throughput / Uptime

Improvement

2. Reduce Cost

Why is PdM performed ?


Top Quartile Companies in Reactive



(over 120 companies representing about 3,000 facilities)

• 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

(2nd

& 3rd

Quartile) and 11% higher OEE

than Bottom Quartile


0

10

20

30

40

50

60

70

80

Top 25% Middle 50% Bottom 25%

PdM

Reactive

Preventive

Average Maintenance Type Percent

(sorted by Reactive Quartiles)

UT-RMC R&M Modeling

54

325432

62

77

54


Top Half of Companies in

Suggestions per Employee



(over 120 companies representing about 3,000 facilities)

• 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

Safety

People

Quality

Delivery

Cost

What Company

Goals Want To

Be Great At

> 100 KPI / Metrics

Six Metric Areas to Top

Quartile Performance

Industry Specific Data


http://www.smrp.org/i4a/pages/index.cfm?pageid=1

http://www.smrp.org/i4a/pages/index.cfm?pageid=1


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)

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)



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).



Demonstrations – Applications – Discussions

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