The Use of Operational Data to Improve Results

The Use of Operational Data The Use of Operational Data to Improve Resultsto Improve Results

Eric Allen

Data Driven Manufacturing LLC

DataDrivenManufacturing.com

AgendaAgenda

Background on use of dataRanking data by importanceHow data is usedData, Design, and Start-upsRecommendations

Introduction Introduction Data is an important tool in reducing costWe often focus on less important dataThe things we measure for result improvement are

the same as those we should measure for start-upsEngineering plays a key role in the design of

processes, the acquisition of data, and the level of long-term costs

It takes a lot of data to tell the whole story

The Goal of Data is… ???The Goal of Data is… ???

VocabularyVocabulary

Uptime/DowntimeStopMTTR/MTBFAvailabilityOEE

Uptime and DowntimeUptime and Downtime

Uptime is the total time the line is runningDowntime is the total time the line is downA Stop is every event when the line stops

running, no matter how long it has been running or why it stopped

Overall Equipment Effectiveness (OEE) is a standard measure that quantifies the production made as a percentage of what was possible to have been made.

MTTR & MTBFMTTR & MTBF

Mean time to repairMTTR = downtime / stops

____________________Mean time between failuresMTBF = uptime / stops

AvailablityAvailablity

Availability is the percent of time the line is running.

Availability = uptime / scheduled timeAvailability = MTBF / (MTBF + MTTR)OEE = Availability - Uptime Losses

Overall Equipment EffectivenessOverall Equipment Effectiveness

OEE = Availability x Rate Performance x %Acceptable Quality, a holistic measure of Efficiency or Reliability.

Rate Performance = Actual Rate / Planned Rate, a measure of Rate Loss/Gain

% Acceptable Quality= Amount of Shippable Product / All product produced, a measure of Quality Loss or “Scrap”

Another way to calculate OEE is to divide quality product made by the the ideal amount that could have been made during the scheduled time.

Traditional OEE ImprovementTraditional OEE Improvement

R eliab ility L osses

U n it O p 3 AL oss = 4 %

U n it O p 3 BL oss = 4 %

U n it O p 5L oss = 1 %

U n it O p 4L oss = 6 %

U n it O p 2L oss = 3 %

U n it O p 1L oss = 5 %

L in e B L in e C

P rod u c t F eedL oss = 2 %

Track Downtime for each unit op

Pareto LossesFocus on biggest

Downtime unit opGo after chunks of

downtimeGet operators to fix it

faster (MTTR)0%

2%

4%

6% Unit Op 4

Unit Op 1

Unit Op 3

Unit Op 2

Supply

Unit Op 5

The Goal of Data is…The Goal of Data is…

to Reduce Downtime???

Downtime LossesDowntime Losses

BreakdownsMinor StopsPlanned MaintenanceChangeoversLunches/Breaks/MeetingsMaterial Supply

Downtime LossesDowntime Losses

BreakdownsMinor StopsPlanned MaintenanceChangeoversLunches/Breaks/MeetingsMaterial Supply

Equipment Specific Stops- The rest are associated with the whole line.

Downtime LossesDowntime Losses

BreakdownsMinor StopsPlanned MaintenanceChangeoversLunches/Breaks/MeetingsMaterial Supply

Since Minor Stops are shorter in duration than all other stops, reducing the number of minors stops will increase MTTR.

Downtime LossesDowntime Losses

BreakdownsMinor StopsPlanned MaintenanceChangeoversLunches/Breaks/MeetingsMaterial Supply

Eliminate with Equipment Design, Prevention, and Planning

Downtime LossesDowntime Losses

BreakdownsMinor StopsPlanned MaintenanceChangeoversLunches/Breaks/MeetingsMaterial Supply

Reduce with planning and skills. Of all downtime, only these two are truly speed dependent. (With proper design, most of this work can be done during uptime anyway.)

OEE and STOPSOEE and STOPSOEE

COMPONENTSSHIFT

COMPONENTSIN-PROCESS MEASURES SENSITIVITY

RuntimeMTBF (Variable)

Availability StopsMTTR (Constant

Downtime w/in Range)% OEE

% Scrap (Constant ~ 1%)

Rate Loss (Constantexcept start-up)

OEE and STOPSOEE and STOPS

Downtime Focus only addresses part of Reliability

OEE COMPONENTS

SHIFT COMPONENTS

IN-PROCESS MEASURES SENSITIVITY

RuntimeMTBF (Variable)

Availability StopsMTTR (Constant

Downtime w/in Range)% OEE

% Scrap (Constant ~ 1%)

Rate Loss (Constantexcept start-up)

OEE and STOPSOEE and STOPSOVERALL EQUIPMENT EFFECTIVENESS & STOPS

OEE COMPONENTS

SHIFT COMPONENTS

IN-PROCESS MEASURES SENSITIVITY LEVER

RuntimeMTBF (Variable) Stop Elimination

Availability StopsMTTR (Constant Stop Elimination

Downtime w/in Range)% OEE

% Scrap (Constant ~ 1%) Stop Elimination

Rate Loss (Constant Stop Eliminationexcept start-up)

OEE and STOPSOEE and STOPS

Stop Elimination addresses all components of Reliability

OVERALL EQUIPMENT EFFECTIVENESS & STOPS

OEE COMPONENTS

SHIFT COMPONENTS

IN-PROCESS MEASURES SENSITIVITY LEVER

RuntimeMTBF (Variable) Stop Elimination

Availability StopsMTTR (Constant Stop Elimination

Downtime w/in Range)% OEE

% Scrap (Constant ~ 1%) Stop Elimination

Rate Loss (Constant Stop Eliminationexcept start-up)

Downtime Reduction, Stop Downtime Reduction, Stop Elimination, What’s the difference?Elimination, What’s the difference?

Focus on Time Get it back up Repair Skills Focus

Focus on Events Stay down until fixed Root Cause

Elimination

Downtime Stops

The Goal of Data is…The Goal of Data is…

to Reduce Downtime

to Eliminate Stops???

OEE and STOPSOEE and STOPS

Stop Elimination won’t fix uptime losses

OVERALL EQUIPMENT EFFECTIVENESS & STOPS

OEE COMPONENTS

SHIFT COMPONENTS

IN-PROCESS MEASURES SENSITIVITY LEVER

RuntimeMTBF (Variable) Stop Elimination

Availability StopsMTTR (Constant Stop Elimination

Downtime w/in Range)% OEE

% Scrap (Constant ~ 1%) Stop Elimination

Rate Loss (Constant Stop Eliminationexcept start-up)

Uptime LossesUptime Losses

Scrap (Destructive Quality Sampling & Rework)

Rate Losses (speed ramp-ups at start-up and running off target speeds at steady state)

Empty or missed products (could be rate or scrap loss depending on situation)

Quality Samples, Defective Quality Samples, Defective Product, and Rate Can Be Product, and Rate Can Be Hidden LossesHidden Losses

10.2%

11.5%

78.3%

Dow ntime

Uptime Losses

Making Good Product(%OEE)

Uptime Losses Can be Uptime Losses Can be SignificantSignificant

Source: Case Study- Oct ‘99

Uptime Losses, Stops,Uptime Losses, Stops,What Else?What Else?

Eliminate Stops & Uptime Losses to Increase PR

The Goal of Data is…The Goal of Data is…

to Reduce Downtime

to Eliminate Stops???

to Eliminate OEE Losses???

Show Me the Money!Show Me the Money!

We are in business to make money, not OEE

Our Biggest On-going Cost Our Biggest On-going Cost is...is...

People!

Stops and Touches Tie Stops and Touches Tie Operators to EquipmentOperators to Equipment

Unit Op A

50 stops/shiftUnit Op A

30 stops/shift

Unit Op A

60 stops/shift

Unit Op B

75 stops/shift

Eliminating Stops Improves Eliminating Stops Improves ProductivityProductivity

Every stop requires operator effort.

The more stops there are, the closer the operator is tied to the line.

The closer the operator is tied to each unit operation, the more operators are required.

TouchesTouches

Operators often adjust and assist the line to keep it from stopping

Often these assists are jam clearsMany adjustments can be automatedFind ways to detect and count

How Do You Eliminate?How Do You Eliminate?

StopsTouchesScrapRate Loss

AdjustmentsAssists

How Do You Eliminate?How Do You Eliminate?

StopsTouchesScrapRate Loss

Stabilize the Process

AdjustmentsAssists

All processes vary-All processes vary-The challenge is to minimizeThe challenge is to minimize

Steady State Variation- when the line is running normally, how much does the process vary and why?

Start-up Variation- during ramp-up of the equipment, what is impacted and how can the variation be reduced in magnitude and time?

Process Upsets- How do sudden events (splices,batch changes, etc.) affect stability?

What Varies?What Varies?

Materials Equipment Utilities Control Systems Environment Set Points Operators Cleanliness

Eliminating VariationEliminating Variation

Use stops and touch data to determine area where variation is impacting

Investigate process for variation

Develop methods to eliminate or control the source

Stability gets ResultsStability gets Results

Quality is improved with lower Standard Deviation and reduced defects

Touches are needed less as adjustments are not needed

Most stops can be traced to instability in part of the process

More stable processes need less sampling

Don’t forget ThroughputDon’t forget Throughput

OEEOEE

==

ThroughputThroughput

Know your rate limiter(s).

List them.

Study them.

Stabilize them.

Speed them up.

Cost = Cost =

Throughput Throughput xx Productivity Productivity Rate Stops uptime Losses

Material Handling Quality Sampling Touches Equipment Geography

The Goal of Data is…The Goal of Data is…

to Reduce Downtime

to Eliminate Stops???

to Eliminate OEE Losses???

to Reduce Cost!

Data Overload!Data Overload!What Data is Most Important?What Data is Most Important?

1. Quality1. Quality

Without quality, there is no reliabilityGet quality data easy to access and analyzeAutomate quality data collectionGet in process data to replace destructive

finished product samplingIdeally, incorporate quality data into same

system as Reliability measures

2. Count Stops2. Count Stops

Line StopsUnit Op Stops

Eliminating Stops improves every aspect of OEE

Stops are the best in-process measure of progress of work

3. Uptime Losses3. Uptime Losses

Track Availability vs. OEESeparate Rate from ScrapSplit Quality Sampling Scrap from Quality

Defect Scrap

4. Process Stability Measures4. Process Stability Measures

More in-process data leads to faster improvement capability and root cause analysis

Track all variable data (pressures, temperatures, tensions, weights, speeds, amps, etc.)- Install transducers to get data

Utilize to discover sources of variationEliminate or use as feedback to other parts of

the process to reduce

5. Causes5. Causes

Stop CausesReject/Scrap CausesCauses are hard to determine automatically

but valuable to know

6. Other Data6. Other Data

TouchesDowntime

Ranking of Data ImportanceRanking of Data Importance

Quality Stop CountsUptime LossesProcess Stability MeasuresCausesTouches and Downtime

Data can be collected and Data can be collected and used many waysused many ways

PLC programming is critical to capturing events for operator display and long-term storage.

Find effective ways to display data to operator

Store data for long-term trending in databases

Data has many sourcesData has many sources

Counts (stops, starts, products, defects, rejects, cases, touches)

Time (uptime, downtime)Variables (pressures, tensions, temperature,

speeds, currents)Causes (stops, rejects)

Customer is the OperatorCustomer is the Operator

Turret Stops

0

20

40

60

80

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120

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160

5/5

-Nite

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Date

Sto

ps

Stops-Turret System

No Datato Operator

Data Broken out

Data Helps Focus Efforts DailyData Helps Focus Efforts Daily “You get what you measure” Results occur minute-by-

minute and are controlled by operators

With updated data, operators can make good decisions

Use on-line data to eliminate short-term data variation

Use data averages and trends to Use data averages and trends to develop long term improvementsdevelop long term improvements

MTBF shows progress and opportunities in stop reduction

Scrap rates show uptime losses

Variation measures show stability opportunities

?

For Stable OperationsFor Stable OperationsYou need good Design plus You need good Design plus good Process Managementgood Process Management

vs.

Built in Impacts of Design on Built in Impacts of Design on Manufacturing CostManufacturing Cost

Simplicity of Equipment (# of unit ops)Geography- Position of Touch PointsDesigned in Stops/Touches (material changes,

etc.)Data Systems- How much information does the

operator have?Ease of ChangeoverMaintainability- resistance to Breakdowns

Impacts of Process Impacts of Process ManagementManagement

Outage ResolutionIf-Down-Do / Planned InterventionsRun to Target

What does this have to do with What does this have to do with Engineering and Vertical Start-ups?Engineering and Vertical Start-ups?

Design is a critical component of long-term costs

Data is essential to make wise decisions

Vertical start-up tools and targets lead to right methodology if used correctly

Use of Data and ResultsUse of Data and Results in Case Study in Case Study

A multiple unit-operation line used these principles in a rigorous method to make substantial improvement. The following slides show results as measured by the site.

Uptime Results

10.1

13.0

17.3

11.0

18.8

15.4

26.4

24.9

39.4

30.7

34.2

9.18.1 8.1 7.8

10.4 10.29.5

7.7

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MTBF

Goal

MTTR

MTBF GOOD

Scrap Results

41.0%

28.7%

21.9%

24.8%

18.2%

20.9%

16.7%

11.0%

8.9%

11.2%

12.9%

0.0%

5.0%

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25.0%

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45.0%

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GOOD

FFS Stops

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nu

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Stops

6 per. Mov.Avg. (Stops)

Month to Date Results Averages

Turret 1 Turret 2 Turret 3 Turret 4 Turret 5

System MTBF 87.0 49.8 35.4 57.9 45.9 Scrap % 0.4% 1.3% 2.4% 0.8% 1.3%Turret Stops/Day 6.1 12.4 17.8 10.4 13.0 Bag Stops/Day 2.2 2.0 2.5 2.1 2.7

Total Turret Scrap 1.9%MD Phasing Scrap 1.1%No Poly Cut Scrap 2.7%Start-up/Manual Scrap 2.5%Sampling/Quality Scrap 4.0%

Oct 12, ‘99

This type of data was posted and reviewed daily with operators to focus their efforts.

Later ResultsLater Results

Results on this line continued to improve in over time after this case study was completed, and the line became a benchmark for re-application.

OEE routinely exceeded 90%Downtime for unplanned stops generally

was less than 2% of scheduled time.

ReviewReview

Cost = Cost =

Throughput Throughput xx Productivity Productivity Rate Stops uptime Losses

Material Handling Quality Sampling Touches Equipment Geography

OEE and STOPSOEE and STOPS

Stop Elimination addresses all components of Reliability

OVERALL EQUIPMENT EFFECTIVENESS & STOPS

OEE COMPONENTS

SHIFT COMPONENTS

IN-PROCESS MEASURES SENSITIVITY LEVER

RuntimeMTBF (Variable) Stop Elimination

Availability StopsMTTR (Constant Stop Elimination

Downtime w/in Range)% OEE

% Scrap (Constant ~ 1%) Stop Elimination

Rate Loss (Constant Stop Eliminationexcept start-up)

Stops and Touches Tie Stops and Touches Tie Operators to EquipmentOperators to Equipment

Unit Op A

50 stops/shiftUnit Op A

30 stops/shift

Unit Op A

60 stops/shift

Unit Op B

75 stops/shift

Ranking of Data ImportanceRanking of Data Importance

Quality Stop CountsUptime LossesProcess Stability MeasuresCausesTouches and Downtime

Engineering and Vertical Start-upsEngineering and Vertical Start-ups

Design is a critical component of long-term costs

Data is essential to make wise decisions

Vertical Start-up tools and targets lead to right methodology if used correctly

SummarySummary

Downtime data is not nearly as important as many other data types

Focus data systems to reduce costsGet real-time data to operatorsProcess Stability reduces all lossesDesign and Process Management combine

to produce results at start-up and long-term

Specific RecommendationsSpecific Recommendations

Focus on Quality data to reduce variation and sampling losses

Focus on Stops (especially in unit ops) to improve OEE and productivity

Include productivity considerations and data capture ability in design efforts

Get easy to use data to operators

Feedback?Feedback?

Send Email to Eric.Allen@DataDrivenMfg.com