The Use of Operational The Use of Operational Data to Improve Results Data to Improve Results Eric Allen Data Driven Manufacturing LLC DataDrivenManufacturing.c om
May 24, 2015
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
100
120
140
160
5/5
-Nite
5/1
2-D
ay
5/2
5-N
ite
6/2
-Day
6/8
-Nite
6/2
1-N
ite
6/2
8-N
ite
7/6
-Day
7/1
3-D
ay
7/1
9-N
ite
7/2
7-N
ite
8/3
-Nite
8/2
4-D
ay
9/1
5-D
ay
9/2
8
10/7
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
4.4
6.2
3.6
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5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
De
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is M
on
th
month
min
utes
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%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
De
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perc
en
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Scrap
Goal
GOOD
FFS Stops
0
10
20
30
40
50
60
70
5/10
-Day
5/24
-Nite
6/2-
Day
6/9-
Nite
6/23
-Nite
7/6-
Day
7/14
-Day
7/26
-Nite
8/3-
Nite
8/25
-Day
9/22
10/7
Date
nu
mb
er o
f st
op
s
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?
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