The Use of Operational Data to Improve Results

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This presentation was originally developed over 10 years ago to highlight ways to make use of data in manufacturing to improve operational results. Key points include:
Data is an important tool in reducing cost.
We often focus on less important data.
The things we measure for result improvement are the same as those we should measure for start-ups.
Engineering 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.
Written by Eric Allen of Data Driven Manufacturing, this presentation is meant to give an overview to those starting down a path to use data for improving manufacturing results.

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The Use of Operational Data to Improve Results

  1. 1. The Use of Operational Data to Improve ResultsEric AllenData Driven Manufacturing LLCDataDrivenManufacturing.com
  2. 2. Agenda Background on use of data Ranking data by importance How data is used Data, Design, and Start-ups Recommendations
  3. 3. Introduction Data is an important tool in reducing cost We often focus on less important data The things we measure for result improvement are the same as those we should measure for start-ups Engineering 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
  4. 4. The Goal of Data is… ???
  5. 5. Vocabulary Uptime/Downtime Stop MTTR/MTBF Availability OEE
  6. 6. Uptime and Downtime Uptime is the total time the line is running Downtime is the total time the line is down A 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.
  7. 7. MTTR & MTBF Mean time to repair MTTR = downtime / stops ____________________ Mean time between failures MTBF = uptime / stops
  8. 8. Availablity Availability is the percent of time the line is running. Availability = uptime / scheduled time Availability = MTBF / (MTBF + MTTR) OEE = Availability - Uptime Losses
  9. 9. Overall 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.
  10. 10. Traditional OEE Improvement  Track Downtime for R e lia b ilit y L o s s e s P ro d u c t F e e d each unit op Loss = 2%  Pareto Losses U n it O p 1 L in e B L in e C Loss = 5%  Focus on biggest U n it O p 2 Loss = 3% Downtime unit opU n it O p 3 A U n it O p 3 BLoss = 4% Loss = 4%  Go after chunks of U n it O p 4 Loss = 6% 6% Unit Op 4 Unit Op 1 downtime 4% Unit Op 3 U n it O p 5 Unit Op 2  Get operators to fix it Loss = 1% 2% Supply faster (MTTR) Unit Op 5 0%
  11. 11. The Goal of Data is…to ReduceDowntime???
  12. 12. Downtime Losses Breakdowns Minor Stops Planned Maintenance Changeovers Lunches/Breaks/Meetings Material Supply
  13. 13. Downtime Losses Equipment Breakdowns Specific Stops- Minor The rest are Stops associated with the Planned Maintenance whole line. Changeovers Lunches/Breaks/Meetings Material Supply
  14. 14. Downtime Losses Breakdowns Since Minor Stops are shorter in duration than all Minor Stops other stops, reducing the Planned Maintenance number of minors stops will increase MTTR. Changeovers Lunches/Breaks/Meetings Material Supply
  15. 15. Downtime Losses Breakdowns Eliminate with Equipment Minor Stops Design, Prevention, and Planned Maintenance Planning Changeovers Lunches/Breaks/Meetings Material Supply
  16. 16. Downtime Losses Reduce with planning and Breakdowns skills. Of all Minor downtime, only these Stops two are truly speed Planned Maintenance dependent. (With Changeovers proper design, most of this work can be done during Lunches/Breaks/Meetings uptime anyway.) Material Supply
  17. 17. OEE and STOPS OEE SHIFT IN-PROCESS COMPONENTS COMPONENTS MEASURES SENSITIVITY Runtime MTBF (Variable) Availability Stops MTTR (Constant Downtime w/in Range)% OEE % Scrap (Constant ~ 1% ) Rate Loss (Constant except start-up)
  18. 18. OEE and STOPS OEE SHIFT IN-PROCESS COMPONENTS COMPONENTS MEASURES SENSITIVITY Runtime MTBF (Variable) Availability Stops MTTR (Constant Downtime w/in Range) % OEE % Scrap (Constant ~ 1% ) Rate Loss (Constant except start-up)Downtime Focus only addresses part of Reliability
  19. 19. OEE and STOPS OVERALL EQUIPMENT EFFECTIVENESS & STOPS OEE SHIFT IN-PROCESS COMPONENTS COMPONENTS MEASURES SENSITIVITY LEVER Runtime MTBF (Variable) Stop Elimination Availability Stops MTTR (Constant Stop Elimination Downtime w/in Range)% OEE % Scrap (Constant ~ 1% ) Stop Elimination Rate Loss (Constant Stop Elimination except start-up)
  20. 20. OEE and STOPS OVERALL EQUIPMENT EFFECTIVENESS & STOPS OEE SHIFT IN-PROCESS COMPONENTS COMPONENTS MEASURES SENSITIVITY LEVER Runtime MTBF (Variable) Stop Elimination Availability Stops MTTR (Constant Stop Elimination Downtime w/in Range)% OEE % Scrap (Constant ~ 1% ) Stop Elimination Rate Loss (Constant Stop Elimination except start-up) Stop Elimination addresses all components of Reliability
  21. 21. Downtime Reduction, Stop Elimination, What’s the difference? Downtime Stops Focus  Focus on Events on Time Get it back up  Stay down until fixed Repair Skills Focus  Root Cause Elimination
  22. 22. The Goal of Data is…to ReduceDowntimeto EliminateStops???
  23. 23. OEE and STOPS OVERALL EQUIPMENT EFFECTIVENESS & STOPS OEE SHIFT IN-PROCESS COMPONENTS COMPONENTS MEASURES SENSITIVITY LEVER Runtime MTBF (Variable) Stop Elimination Availability Stops MTTR (Constant Stop Elimination Downtime w/in Range)% OEE % Scrap (Constant ~ 1% ) Stop Elimination Rate Loss (Constant Stop Elimination except start-up) Stop Elimination won’t fix uptime losses
  24. 24. Uptime 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)
  25. 25. Quality Samples, DefectiveProduct, and Rate Can BeHidden Losses
  26. 26. Uptime Losses Can be Significant 10.2% 11.5% Dow ntimeSource: CaseStudy- Oct ‘99 Uptime Losses 78.3% Making Good Product (%OEE)
  27. 27. Eliminate Stops & UptimeLosses to Increase PR Uptime Losses, Stops, What Else?
  28. 28. The Goal of Data is…to Reduce to Eliminate OEEDowntime Losses???to EliminateStops???
  29. 29. Show Me the Money!We are in business to make money, not OEE
  30. 30. Our Biggest On-going Cost is... People!
  31. 31. Stops and Touches Tie Operators to Equipment Unit Op A50 stops/shift Unit Op B Unit Op A 75 stops/shift 30 stops/shift Unit Op A 60 stops/shift
  32. 32. Eliminating Stops ImprovesProductivity  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.
  33. 33. Touches Operators often adjust and assist the line to keep it from stopping Often these assists are jam clears Many adjustments can be automated Find ways to detect and count
  34. 34. How Do You Eliminate?Stops AdjustmentsTouches AssistsScrapRate Loss
  35. 35. How Do You Eliminate?Stops AdjustmentsTouches AssistsScrapRate Loss Stabilize the Process
  36. 36. All processes vary- The 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?
  37. 37. What Varies?  Materials  Equipment  Utilities  Control Systems  Environment  Set Points  Operators  Cleanliness
  38. 38. Eliminating 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
  39. 39. Stability 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
  40. 40. Don’t forget Throughput Know your rate limiter(s). OEE List them. Study them. = Stabilize them. Speed them up.Throughput
  41. 41. Cost = Throughput x Productivity Rate  Material Handling Stops  Quality Sampling uptime Losses  Touches  Equipment Geography
  42. 42. The Goal of Data is… to Eliminate OEEto Reduce Losses???Downtimeto Eliminate to ReduceStops??? Cost!
  43. 43. Data Overload!What Data is Most Important?
  44. 44. 1. Quality Without quality, there is no reliability Get quality data easy to access and analyze Automate quality data collection Get in process data to replace destructive finished product sampling Ideally, incorporate quality data into same system as Reliability measures
  45. 45. 2. Count Stops  Line Stops  Unit Op StopsEliminating Stops improves every aspect of OEEStops are the best in-process measure of progress of work
  46. 46. 3. Uptime Losses Track Availability vs. OEE Separate Rate from Scrap Split Quality Sampling Scrap from Quality Defect Scrap
  47. 47. 4. 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 variation Eliminate or use as feedback to other parts of the process to reduce
  48. 48. 5. Causes Stop Causes Reject/Scrap Causes Causes are hard to determine automatically but valuable to know
  49. 49. 6. Other Data Touches Downtime
  50. 50. Ranking of Data Importance Quality Stop Counts Uptime Losses Process Stability Measures Causes Touches and Downtime
  51. 51. Data can be collected and used 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
  52. 52. Data has many sources Counts (stops, starts, products, defects, rejects, cases, touches) Time (uptime, downtime) Variables (pressures, tensions, temperature, speeds, currents) Causes (stops, rejects)
  53. 53. Stops 100 120 140 160 20 40 60 80 0 5/5-Nite 5/12-Day No Data 5/25-Nite to Operator 6/2-Day 6/8-Nite 6/21-Nite 6/28-Nite 7/6-DayDate 7/13-Day Turret Stops 7/19-Nite 7/27-Nite 8/3-Nite Data Broken out Customer is the Operator 8/24-Day 9/15-Day 9/28 Stops-Turret System 10/7
  54. 54. Data 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
  55. 55. Use data averages and trends to develop long term improvements MTBF shows progress and opportunities in stop reduction Scrap rates show uptime losses ? Variation measures show stability opportunities
  56. 56. For Stable OperationsYou need good Design plusgood Process Management vs.
  57. 57. Built in Impacts of Design on Manufacturing Cost Simplicity of Equipment (# of unit ops) Geography- Position of Touch Points Designed in Stops/Touches (material changes, etc.) Data Systems- How much information does the operator have? Ease of Changeover Maintainability- resistance to Breakdowns
  58. 58. Impacts of Process Management Outage Resolution If-Down-Do / Planned Interventions Run to Target
  59. 59. What does this have to do withEngineering 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
  60. 60. Use of Data and Results in Case StudyA multiple unit-operation line used these principles in arigorous method to make substantial improvement. Thefollowing slides show results as measured by the site.
  61. 61. MTBF GOOD Uptim e Results 40.0 39.4 MTBF Goal 35.0 34.2 MTTR 30.7 30.0 26.4 24.9 25.0m inute s 20.0 18.8 17.3 15.4 15.0 13.0 11.0 10.1 10.0 10.4 10.2 9.1 9.5 8.1 8.1 7.8 7.7 6.2 5.0 4.4 3.6 This Month Dec-98 May-99 Sep-99 Aug-99 Feb-99 Mar-99 Jan-99 Apr-99 Jun-99 Jul-99 - m onth
  62. 62. Scrap Results 45.0% 41.0% 40.0% Scrap GOOD Goal 35.0% 30.0% 28.7% 24.8%pe rce nt 25.0% 21.9% 20.9% 20.0% 18.2% 16.7% 15.0% 12.9% 11.0% 11.2% 10.0% 8.9% 5.0% This Month Dec-98 May-99 Sep-99 Aug-99 Feb-99 Mar-99 Apr-99 Jan-99 Jun-99 Jul-99 0.0% m onth
  63. 63. num ber of stops 10 20 30 40 50 60 70 0 5/10-Day 5/24-Nite 6/2-Day 6/9-Nite 6/23-Nite 7/6-DayDate 7/14-Day FFS Stops 7/26-Nite 8/3-Nite 8/25-Day Stops 9/22 6 per. Mov. 10/7 Avg. (Stops)
  64. 64. Month to Date Results Averages Turret 1 Turret 2 Turret 3 Turret 4 Turret 5System MTBF 87.0 49.8 35.4 57.9 45.9Scrap % 0.4% 1.3% 2.4% 0.8% 1.3%Turret Stops/Day 6.1 12.4 17.8 10.4 13.0Bag Stops/Day 2.2 2.0 2.5 2.1 2.7Total Turret Scrap 1.9% This type of data wasMD Phasing Scrap 1.1% posted and reviewedNo Poly Cut Scrap 2.7% daily with operatorsStart-up/Manual Scrap 2.5% to focus their efforts.Sampling/Quality Scrap 4.0% Oct 12, ‘99
  65. 65. Later 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.
  66. 66. Review
  67. 67. Cost = Throughput x Productivity Rate  Material Handling Stops  Quality Sampling uptime Losses  Touches  Equipment Geography
  68. 68. OEE and STOPS OVERALL EQUIPMENT EFFECTIVENESS & STOPS OEE SHIFT IN-PROCESS COMPONENTS COMPONENTS MEASURES SENSITIVITY LEVER Runtime MTBF (Variable) Stop Elimination Availability Stops MTTR (Constant Stop Elimination Downtime w/in Range)% OEE % Scrap (Constant ~ 1% ) Stop Elimination Rate Loss (Constant Stop Elimination except start-up) Stop Elimination addresses all components of Reliability
  69. 69. Stops and Touches Tie Operators to Equipment Unit Op A50 stops/shift Unit Op B Unit Op A 75 stops/shift 30 stops/shift Unit Op A 60 stops/shift
  70. 70. Ranking of Data Importance Quality Stop Counts Uptime Losses Process Stability Measures Causes Touches and Downtime
  71. 71. 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
  72. 72. Summary Downtime data is not nearly as important as many other data types Focus data systems to reduce costs Get real-time data to operators Process Stability reduces all losses Design and Process Management combine to produce results at start-up and long-term
  73. 73. Specific 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
  74. 74. Feedback?Send Email to Eric.Allen@DataDrivenMfg.com

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