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Where Does The Time Go?<br />Using Production Downtime to<br />Improve the Success Rate of<br />Continuous Improvement Ini...
Purpose of this Presentation<br />Many Continuous Improvement initiatives fail to reach their expected goals - often estim...
Many CI Programs Fail to Achieve Expected Gains<br />Many CI programs (quality improvement, employee involvement, lean man...
Solving the “Where Do We Start?” Problem<br />One barrier to successful continuous improvement is defining a targets that ...
What is Lost Production Time?<br />The following chart shows the impact of downtime on actual production<br />Planned Prod...
Why Focus on Lost Production Time?<br />The Six Major Losses in Manufacturing -  these six losses address all reasons for ...
Why is it difficult to track lost production time?<br />Traditional accounting and production measurement systems rarely  ...
Why is it difficult to track lost production time?<br />Lean Manufacturing uses Overall Equipment Effectiveness (OEE) to t...
How can we track lost production time?<br />The Work Sampling approach:<br />Based on a number of random observations<br /...
1st Example: Using Downtime to Target Improvements<br />The objective of this study was to find out where the time goes to...
1st Example: Using Downtime to Target Improvements<br />HoursEquivalent Pieces<br />Available hours		15,120			5,670,000<br...
1st Example: Using Downtime to Target Improvements<br />Lessons from this study:<br />Management’s singular focus on labor...
2nd Example: Comparing Two Similar Plants<br />The objective of this study was to show how to plants with similar products...
2nd Example: Comparing Two Similar Plants<br />Plant ABC   	Uptime = 80.1%<br />Based on 1619 observations<br />Plant XYZ	...
2nd Example: What did this Downtime Study show?<br />Lessons from this study:<br />The two plants, despite common division...
Lessons Learned from Downtime Studies<br />This approach for documenting lost production time works and it is relatively q...
How Can We Use Downtime Information to Improve?<br />Improve how we manage the production system<br />Balancing offline su...
Summary<br />Understanding production time lost to equipment, speed, and quality downtime is crucial to achieving higher p...
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Where Does The Time Go?

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Where Does The Time Go?

  1. 1. Where Does The Time Go?<br />Using Production Downtime to<br />Improve the Success Rate of<br />Continuous Improvement Initiatives<br />Jerry Stevick<br />
  2. 2. Purpose of this Presentation<br />Many Continuous Improvement initiatives fail to reach their expected goals - often estimated at an 80% - 90% failure rate.<br />Getting better results requires better definition of targets – targets that provide tangible benefits to the overall business.<br />This presentation shows how improving production uptime drives dollars to the bottom line.<br />This presentation also provides a method to easily set targets and track progress.<br />
  3. 3. Many CI Programs Fail to Achieve Expected Gains<br />Many CI programs (quality improvement, employee involvement, lean manufacturing, etc) fail to achieve expectations or struggle and sputter as they try to gain and sustain momentum. <br />Some firms are paralyzed or don’t start because the target is not clear or they are not convinced the CI method will solve the business problem<br />Some firms have false starts because the early results don’t appear to have significant business impact<br />Some firms wander chasing symptoms such as inventory or labor efficiency because the underlying issues are not identified<br />Some firms select an improvement program without really understanding where the improvements will come or their impact on the business<br />Some firms struggle because they fail to create metrics to drive the improvements<br />How can we improve the early results of these initiatives?<br />
  4. 4. Solving the “Where Do We Start?” Problem<br />One barrier to successful continuous improvement is defining a targets that generate visible gains for the business. Two good options are:<br />Where does the money go?<br />Where does the time go?<br />All production or operating systems have downtime. Maximizing uptime maximizes the productive output of the system.<br />Employees at all levels tend to understand and support business improvements that are clear and productive.<br />Identifying and fixing causes of production downtime generates buy-in and quick returns because it immediately addresses the core purpose of the organization – providing products and services to customers<br />What exactly do we mean by production uptime?<br />
  5. 5. What is Lost Production Time?<br />The following chart shows the impact of downtime on actual production<br />Planned Production Time<br />Quality losses<br />Actual Productive<br />Uptime<br />Equipment losses<br />Speed losses<br />The actual productive output of a complex system is often much less than its managers realize and its traditional metrics show<br />
  6. 6. Why Focus on Lost Production Time?<br />The Six Major Losses in Manufacturing - these six losses address all reasons for lost production, not just equipment<br />Equipment losses<br />Maintenance - breakdowns and planned maintenance<br />Changeover - model changes and adjustments<br />Speed losses<br />Speed - equipment does not run at designed rate<br />Idle time - time lost to behaviors, training, meetings, etc.<br />Quality losses<br />Defects - production defects that is not useable or requires rework<br />Yield - production losses inherent to process<br />Time sets a high standard - it is the one resource we cannot rework or reuse - when it is lost, it is lost forever<br />
  7. 7. Why is it difficult to track lost production time?<br />Traditional accounting and production measurement systems rarely capture the lost time categories<br />Downtime causes are fragmented and often overlooked<br />Responsibility for addressing downtime categories is split<br />Downtime is often understated – limited to maintenance activities<br />Fire-fighting to eliminate the current downtime issue takes precedence over understanding the overall downtime problem<br />
  8. 8. Why is it difficult to track lost production time?<br />Lean Manufacturing uses Overall Equipment Effectiveness (OEE) to track and manage the Six Losses definition of downtime.<br />However, most firms struggle to get good data for measuring OEE. <br />Let’s look for an easier way:<br />Goal: to provide a good estimate of the distribution of work activities that is relatively accurate and easy to implement<br />The Work Sampling Study from Industrial Engineering provides a method for generating a quick snapshot of production downtime.<br />
  9. 9. How can we track lost production time?<br />The Work Sampling approach:<br />Based on a number of random observations<br />Categories can be tailored to the processes being studied<br />Large sample size leads to statistical validity<br />Good for documenting non-repetitive activities<br />Basic steps of a Work Sampling Study:<br />Define the objective and how data will be collected<br />Classify activity into categories appropriate for the process<br />Prepare data sheets, sample method, random times<br />Develop procedure for analyzing the data<br />Collect data by random observations<br />Let’s look at two examples:<br />
  10. 10. 1st Example: Using Downtime to Target Improvements<br />The objective of this study was to find out where the time goes to gain a better understanding of which improvement methods would add the most value<br />Production facility with rubber molding shop (55 tool locations):<br />Management focus on labor efficiency<br />Difficulty scheduling rush orders<br />No target-based improvement program in place<br />Building ahead for large customers hurt remaining customers<br />Capacity “constraints” prevented 100% satisfaction<br />Utilize sampling study of mold shop downtime:<br />Set up data collection sheets unique to this operation<br />Collect data randomly over 4 week period – 2230+ data points<br />Utilize time estimates to demonstrate impact on the number of pieces built and the capacity constraints<br />
  11. 11. 1st Example: Using Downtime to Target Improvements<br />HoursEquivalent Pieces<br />Available hours 15,120 5,670,000<br />Production hours (85%) 12,852 <br />Std Hours Earned (92%) 11,834 4,437,750<br />Downtime Loss (15%) 2,268 850,500<br />Maintenance (5.3%) 300,510<br />Set-up (5.7%) 323,190<br />Not scheduled (1.5%) 85,050<br />Cleaning (1.0%) 56,700<br />Miscellaneous (1.5%) 85,370<br />Efficiency Loss (8.0%) 453,375<br />Scrap / Quality loss (6.3%) 355,020<br /> Plant Effectiveness 72%<br />Early Production loss (15%) 665,662<br /> Actual Plant Effectiveness 59%<br />
  12. 12. 1st Example: Using Downtime to Target Improvements<br />Lessons from this study:<br />Management’s singular focus on labor efficiency is unlikely to solve their production and capacity problems<br />Significant downtime from scrap, changeover time, and maintenance point to the need for a more well rounded improvement program<br />Scheduling improvements were needed to capture scheduling conflicts around tools and unique models<br />The “old school” practice of dropping in orders for big customers robbed a large chunk of capacity from the current month<br />While management worried about it’s 92% labor problem, it was unaware that the production effectiveness of the facility was at 72%<br />When early orders were considered, the shop was only 59% effective at producing current orders<br />
  13. 13. 2nd Example: Comparing Two Similar Plants<br />The objective of this study was to show how to plants with similar products, in the same organization, might have different profiles<br />Comparison of two similar facilities<br />Two automotive control plants compared (similar products)<br />Large plastic molding operations<br />Define targeted and random data collection<br />Data collected over 3 – 4 week period<br />How did the two plants compare?<br />Set up data collection sheets unique to each operation<br />Collect data randomly over 3 week period <br />Utilize time estimates to demonstrate how different processes, people, and business pressures created different improvement opportunities<br />
  14. 14. 2nd Example: Comparing Two Similar Plants<br />Plant ABC Uptime = 80.1%<br />Based on 1619 observations<br />Plant XYZ Uptime = 74.6%<br />Based on 4460 observations<br />
  15. 15. 2nd Example: What did this Downtime Study show?<br />Lessons from this study:<br />The two plants, despite common division management and similar products and processes, had different downtime profiles<br />Plant ABC displayed a significant need to focus on equipment downtime, primarily time lost to maintenance<br />Plant XYZ displayed a large loss of time to changeover, another form of equipment downtime, that was double the same downtime category in their sister plant<br />Both management teams seriously underestimated the time lost to the non-maintenance downtime categories. <br />In both cases, there was no significant attack on maintenance and changeover prior to this study. Losses of close to 20%, if cut in half, would add significant profit dollars to the business<br />
  16. 16. Lessons Learned from Downtime Studies<br />This approach for documenting lost production time works and it is relatively quick and easy to implement<br />The results of most downtime studies “surprise” the managers of the operations being studied.<br />Downtime reduction (greater productive uptime) represents a significant improvement opportunity<br />Every production system is different<br />The production system and its offline support systems (tooling, changeover, maintenance, etc) are closely linked and interdependent<br />Continuous improvement plans can be linked to production system downtime to target improvements with significant payback<br />
  17. 17. How Can We Use Downtime Information to Improve?<br />Improve how we manage the production system<br />Balancing offline support systems to maximize production<br />Increasing capacity by reducing lost production time<br />Targeting the most effective improvements<br />Justify new equipment by considering indirect costs<br />Specify equipment to reduce downtime impact<br />Justify upgrades for monitoring and controlling the process<br />Target continuous Improvement efforts<br />Directly monitor and quantify Continuous Improvement program benefits to create and sustain improvement momentum<br />
  18. 18. Summary<br />Understanding production time lost to equipment, speed, and quality downtime is crucial to achieving higher performance levels<br />Collecting data and monitoring downtime periodically can be relatively easy – a quarterly or monthly snapshot can overcome barriers to measurement<br />Downtime data can help us focus our improvement efforts<br />Downtime represents a significant improvement opportunity in most production systems<br />Improvements in uptime flow directly to the bottom line <br />

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