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ОглавлениеUNDERSTANDING THE POWER OF OVERALL EQUIPMENT EFFECTIVENESS (OEE)
This book is the culmination of the many years of experience I have inside a large Fortune 100 company. It is offered as a “how to improve” guide for many of the issues that exist in manufacturing work centers (factories or refineries) of all sizes and types. We will look at the key parameters for the success of manufacturing communities, then link those parameters to the financial business metrics that are vital to your company’s success. We will also look at the practical application of theories that are commonly spoken, but seldom accepted on the factory shop floor.
Aspects of this book are appropriate for everyone involved in or supporting a manufacturing process. The book provides all work centers with techniques and measures for greater throughput that requires little or no capital spending. Over the years, I have been successful in five different types of manufacturing processes. Based on that experience, I offer recommendations regarding what does and does not work to improve productivity and reliability-maintainability in both the short term and the long term. I hope you will use this book proactively to drive improvements in your area.
1.1 Factories: Effective Producers of Good Goods
Every factory* attempts to be an effective, low-cost producer. This effort is required in today’s challenging environment when customers demand quality product at the best value. Few factories attain and maintain high level productivity and low costs. Many of these use a disciplined approach to identify the best improvements to make. They use teams to eliminate the root problems that otherwise keep the factory from driving toward continuously higher levels of effectiveness. In short, they have found the power of OEE: Overall Equipment Effectiveness.1 By recognizing the ‘hidden factory’ within, they have made improvements that contribute directly to the bottom line.
World-class manufacturing areas share two common characteristics. They are data driven and they are led by synergistic multi-function leadership teams. Accurately measuring and driving key success parameters contributes to higher productivity for both the area and the plant. A method called Overall Equipment Effectiveness, or OEE, can help you better understand how well a manufacturing area is performing, and identify what is limiting higher effectiveness.
Manufacturing systems are composed of equipment and machinery that combine to transform materials and sub-assemblies into products that are either parts for the next step of manufacturing or finished goods. A significant amount of capital is often invested to design, build, and implement a system so that product can be made uniformly at a high rate with minimal waste. The factory should effectively deliver the product at less cost than would be needed to produce it individually. Every business plan should include projections about the effectiveness of the proposed system and how well it will contribute to the bottom line. The company should also be aware of the degree to which it is at risk if the expected effectiveness is not attained and sustained.
Continuous and discrete processes of transforming materials and parts into products can be complex and unique; the system is often quite technical and elaborate. In many instances, a standard product is manufactured in many different formats and variations. The system, therefore, splinters into multiple processes, yet they use shared resources. Some of the cases in this book come from the author’s personal experience in a setting where over thirty process setups were used to produce variations of seventy different products from four different product families. The capital investment was well over $100 million. Thus, the operating cost to product was significant; the effectiveness of the operation had a major influence on the company’s bottom line.
Nearly every industry has multiple manufacturers, each competing for its share of the market. Even a company with the best product may not stay in business if its expense for getting the product to the customer is excessive. Fierce competition usually exists. Companies with the most effective factories will have the staying power to be the long-term survivors, assuming that the need for the product is continuous. This “staying power” provides a significant advantage over time. For example, in the paper clip industry, one of three U.S. manufacturers has equipment over 50 years old, still producing high quality clips2. Sound investments over half a century ago, and on-going maintenance, has provided a long-term business advantage to the company.
In short, factories are at the core of any manufacturing company. Staying in business requires building and maintaining effective factories.
1.2 Factory Dynamics
At any given factory, a vast number of events occur simultaneously every workday. The tasks of producing goods and maintaining equipment usually hold the central focus. However, take a moment to think about all the activities that go on and how and when they impact the manufacturing process.
Decisions made in purchasing today set in motion a timeline for each item ordered and used. How well a piece of equipment is repaired today will influence some future runtime. In the spare parts warehouse, if a bearing is accidentally dropped on the floor today, and re-shelved for later use, the piece of equipment that eventually uses it may have a shortened life. Approval or rejection of various projects can affect overall operations for years to come. Hiring and training decisions by human resources set the stage for subsequent events.
In short, all the pieces of a factory interlock. One event eventually affects all. Left on their own, all these elements can create a chaotic, reactive environment full of surprises, a home for “Murphy,” the demon that brings bad luck. Actually, with all that can potentially go wrong in a factory, it is amazing that factories do as well as they do.
And yet, what makes the difference between world-class manufacturers and the rest of the pack? World-class organizations have evolved from a factory of individuals to a factory of coordinated teams working together with a common purpose. All areas have win-win relationships with their interdependent areas. They make certain that decisions are made correctly the first time. They balance production and production capability appropriately. They are in control of “the big picture;” they have engaged everyone’s support in working toward a high level of excellence and sustaining that position. The bottom line: they know where they are and where they are going.
World-class companies do not create their environment overnight. They may need three to five years to achieve most of their gains. They then start a long journey of continuous improvement. Much of the work is educating all employees about doing their business with others in mind. People may still work independently, but they also understand their relationship with the whole. All employees understand the objectives and strategies of the company. I would rank ‘can do’ people as the most important element of the factory.
At one plant where I worked, every department had submitted its minimum operating budget for the following year. Our corporate headquarters did not accept our proposed budget. We were challenged with a goal of reducing our plant costs by an additional $12 million from the submitted budget. We held many meetings to develop a plan that could produce the results or, as an alternative, plan for inevitable downsizing. Our management team for the plant did not see how we could possibly meet the challenge. We were prepared for the worst.
Finally, one manager suggested that we turn the problem over to the plant community, offering a reward or gain-sharing plan if the plant were to meet or exceed the budget challenge. This strategy was approved and communicated to all the workers. Almost immediately, everyone in every area of the plant began to do all the little things that contributed to our beating the goal. The result was an outstanding performance for the year, surpassing the once-impossible goal by a significant amount. Everyone was amazed at how powerful this dedicated and engaged community was in making the right things happen, once a common cause was accepted.
1.3 Balancing the Business
The last section considered the big picture within the factory, the interdependence of areas and people within a plant. Similarly, the factory is one component within the overall business. It is not enough for you to understand the dynamics within your factory. You must also develop an appreciation for the importance of productivity throughout all parts of the company.
Many different components are needed to make a business successful. The dynamics of these components are often even more dramatic than the dynamics within the factory. In smaller companies, managers must often juggle many different facets of their business at once. Not only do they oversee factory operations, they are also concerned with sales and marketing, accounting and finance, and human resources for the company. Because large organizations are often organized functionally, managers often focus only on their aspect of the business. Yet within that area of focus, they are also often concerned with other areas. In all cases, you should understand how your area of responsibility fits into the larger picture.
You can develop skills and a sense of understanding about managing the overall business in many ways. Traditional academic courses in business, whether at undergraduate, graduate, or vocational schools, are a common approach. At some companies, you may be given a series of three-to-six month assignments that take you from one functional area to another. These assignments help you develop an overall understanding for the company. I encourage you to proactively seek various positions in different departments and areas your factory or different factories. Do this with the intent to learn new processes and perspectives each time too gain experience and skills. Cooperative diversity is a strength in factory teams.
Sometimes a faster way of getting exposure to a company’s complex dynamics is to participate in a simulation. Many business simulations are available. Sometimes you attend a seminar away from the company. These seminars may involve groups of employees from your company or employees from many different companies. In other cases, the person running the simulation may set up an in-house program.
Decide II: A Simulation Experience
A few years ago, I participated in a helpful simulation exercise run over four days. The seminar, Decide II, was developed by Dr. Thomas Pray, Professor of Decision Science at Rochester Institute of Technology, Rochester, NY. The seminar consisted of several simulation exercises, alternating with short lectures and workshop activities. The class provided an excellent framework for cross-functional thinking and team building with several of my company associates. Among the results was a better understanding of many business reports and marketing approaches.
Within the simulation, a class of up to two dozen participants is divided into three- or four-person teams. Each team forms a company and starts with the same information and resources. All the companies make an imaginary common product and compete for the same general market. Teams must set company objectives, implement strategies, and compete against each other.
Teams select their own strategies. For example, one team may decide that its company will produce high volume/low price and pursue a large share of the market. Another team may decide to develop specialty items at high prices, securing a profitable market niche. The teams develop strategies for how their companies will manufacture and sell their products.
Decide II uses a menu-driven Visual Basic decision-support software package. Teams enter their decisions into the Decide II software. Each team then receives immediate feedback on profits, cash flow, quality, and other measures of the effectiveness of their decisions. This feedback is based not only on the decisions made by the team itself, but also on the other teams’ decisions.
Over the course of the simulation, teams enter a series of eight sets of decisions, with ongoing results provided each time. Thus, the second set of decisions is based on the results and new market environment from the first set of decisions. The team’s overall score is provided by the stock price, which varies relative to each company’s overall health. According to Decide II, your company is rewarded for “creating economic value by implementing a solid and ‘balanced’ business plan that generates free cash (i.e. cash from operations), economic profit, and earnings from operations.”3
As part of the Decide II simulation, each team must make decisions covering the full range of functions, including:
Marketing: Price, Promotion, R&D-Process, R&D-Product, Service, Customer surveys.
Operations: Production, Labor Scheduled/Overtime, Maintenance, Material Purchases
Finances: Capital Investment, Dividends, Securities, Market Research
Human Resources: Headcount Plans, Training Budgets, Pay & Compensation, Employee Surveys
The simulation also works in many of the key issues facing industry today, including:
Total Quality Management and Customer Satisfaction
Total Quality Costs: Prevention, Appraisal and Failure costs
Competitive Benchmarking
Customer and Employee satisfaction surveys and impacts
Commitment to customer service
Headcount Planning Linked to Production and Capital Plans
Pay and Compensation Issues
Personnel Training and Development elements
Within each round of decision making, the teams use information from a variety of reports generated as part of the simulation, including:
Operating Income Statements
Balance Sheets
Manufacturing Reports
Total Quality Reports
Cash Flow Reports
Economic Forecasts
Market Research Reports
Stock Market Reports
Participants in the simulation quickly build an appreciation of how complex individual businesses can be. They also see the importance of balancing the use of resources, assets, information, inventories, prices, and sales in order to generate net profit. Because the simulation involves several rounds in a competitive setting, participants also see how one set of decisions affects another set of decisions and results later in the process.
For our particular team, the biggest lesson was to realize the importance of maximizing factory output without the use of overtime. That efficiency, combined with an appropriate market price, helped us develop a healthy business. In our simulation, labor was a very large part of the manufacturing cost. Therefore, minimizing overtime was of vital importance. In other settings, the primary cost may be in automating a process, with labor a minor cost factor. In this case, maximizing the equipment use, even if overtime is necessary, may well be the better choice.
The simulation reinforced the sense that the size of the opportunities for business improvement varies proportionately with the level of information sharing throughout the company. For the best decisions that lead to profitable results, decision makers in the company need information, for example, not only the cost of manufacturing each product, but also margins, compensation and reward policies.
I once worked in a factory area where assets were used to make difficult-to-manufacture products at slower speeds. The level of output ran counter to local expectations of productivity, and the morale of the workers was low. However, once the information was shared that these products provided much greater net profit than standard goods produced elsewhere, morale improved. This understanding helped the group accept the challenge of making these difficult products effectively and overall effectiveness increased. Also, the reward system for the factory could be adjusted accordingly. Remember, what is measured is extremely important. Just measuring barrels/hr or widgets/shift does not measure the business results because profit margins vary with different products.
1.4 Leadership for Teams
Effective factories usually have coordinated teams that work synergistically with a common purpose. The teams, which are from all areas of the factory, have win-win relationships with their interdependent areas and services.
According to a panel of five reliability consultants at the year 2000 annual conference of the Society of Maintenance Reliability Professionals (SMRP), successful initiatives and programs are primarily driven from the top down rather than from the bottom up. In fact when asked, the panel couldn’t relate a single successful experience with a bottom up initiative unless it was first communicated to and accepted by the area leadership.
My own experience supports the concept that successful programs can be implemented at the level of the ‘Champion’ on down. This can be seen where successful programs develop in one work center without ever transferring to other factory areas. When the person who championed the program leaves or transfers, all too often the work center does not sustain the high performance. However, the champions are able to generate new initiatives in other areas once they establish a rapport with the new community.
Management support and area leadership significantly influences the success of initiatives. To sustain a level of excellence, the total community--management, the line organization, and support groups--has to be of one mind. High performance work groups bridge the ‘top down’ syndrome by acceptance of synergistic team leadership.
Nearly everyone comes to work with a desire to do a good job and to be part of a successful unit. Your job and the security of your business depend on strong productivity and top effectiveness. Frustration comes when priorities are not clear and reinforcement is awarded inconsistently. Thus, a single metric--measuring the community as a whole--can be powerful in bringing everyone together.
Let’s look at an example. I once facilitated a workshop activity aimed at improving the changeover time between orders for a packaging operation. This area had four similar flow-lines working around the clock seven days a week. The area had four shifts with four crews per shift, or a total of sixteen crews. Because each flow-line had two to ten changeovers per day, reducing the changeover time for the work area would greatly improve effectiveness. A workshop for developing quick changeovers using a methodology called Single Minute Exchange of Die (SMED)4 was selected for this task. SMED or quick changeover is covered in section 8.3 of this book.
The operations manager decided to have one crew be the pilot crew that would go through the workshop and develop a best practice methodology. This approach proved to be more complex than expected. The area worked with approximately 130 different products, using 35 different processes. Many crews worked with more of one combination than another. Therefore, a typical changeover really did not exist.
In the workshop, the pilot crew categorized changeovers. They initiated improvements that reduced the majority of their changeover times by 40 percent. At the end of the pilot period they presented the results to the product line superintendent. Although they were proud to receive the superintendent’s congratulations, they were shocked when he directed them to teach their methods to the other crews. They had not anticipated this directive, and felt that their reward was more work, beyond the original scope of the workshop. As a pilot crew, they synergistically made improvements, however other crews did not readily accept ‘outside’ ideas and passively committed to new methods. Thus, the improvement methods took much longer to be accepted by the other crews.
What actions would have been better? Proactive leadership would have led to faster results. When the operations manager initiated the request for improvement, he should have confirmed the efforts were supported by the superintendent and then communicated this to all crews. The overall objective should have been outlined with the strategy of how a pilot crew would be selected from volunteers, that this crew would make recommendations for best practices, and that all crews were expected to adapt these methods into their changeovers. If the results of the improvement were visible to the crews, and a system was developed to reward the community when the average changeover improved, then the methods would have been implemented quickly. The superintendent should have invested three or four hours of proactive leadership, earning the support of all the crews. By clearly communicating the desired goal and the expectation that everyone will help implement improved work practices, proactive leadership would provide the community with a common vision. This style of leadership and communication open the way for rapid implementation and sustain improved practices.
Proactive leadership is a vital part of developing work place improvements. It can start at any level of the organization. As objectives are selected, approval should be solicited from the area leadership team to clear the way for rapid success. This book should provide the tools to generate compelling programs for higher effectiveness
1.5 Moving the Community to Improved Performance
Having an effective factory is not the only requirement of a successful business. Many other factors are also important. Which way is the economy going to move? Will the competition cut prices? Is the product in demand? Will the product evolve into another? What are the distribution channels for the product? Should the source of supply be in one place or several? World-class companies continually address these and other questions as they shape and modify their business plans.
World-class companies are known for another attribute. They are built around the concept that an effective factory producing “good goods” as needed to meet market demands is a valuable asset for any company to have. This attribute is maintained both short and long term. One of the main metrics used to identify world-class companies addresses how effectively factories run their processes when scheduled to run. OEE is designed to provide this number. Yet most factories do not compute OEE or use it to set and maintain their priorities. OEE is the product of availability (actual run time vs. scheduled time) times speed rate (actual rate vs. ideal speed rate) times quality rate (good product vs. total product). These parameters are defined in section 2.1. A second metric examines how effectively do factories run their processes relative to the total calendar time. This metric, Total Effectiveness Equipment Performance or TEEP, will be discussed in section 1.6.
All manufacturing processes have some kind of constraint. Factories often subdivide product manufacturing into several steps, using inventories or queues between steps. When factory resources are shared, or used in multiple ways, the manufacturing process grows in complexity. The constraint for one product is often different than for other products. The Constraint Management Handbook6 is a good reference for understanding and operating the vital steps of manufacturing lines and multiple product orders.
OEE should first be applied to the bottlenecks that affect throughput or any other critical and costly areas of a manufacturing line. These areas, so vital in making a plant effective, make a significant difference to the company when driven successfully. OEE is beneficial for every step of the process, however, non-bottleneck steps should be subordinated to bottleneck steps.
Effectively moving a community toward an OEE mindset starts with a company-wide education program that is driven top down. The plant management team must first identify the hierarchy of bottlenecks. Then setting expectations and communicating them to the plant employees launches the initiative for a successful change. OEE should work synergistically with the financial information for each product. When OEE is used by management as the key metric for a factory’s vital points, and each person’s performance appraisal is linked to improving the metric, an effective factory evolves quickly.
True OEE multiplies factors that represent availability, speed, and quality. The result can be expressed as a percentage of effectiveness that directly correlates with actual factory floor output, and can be reconciled 100 percent. This will be demonstrated in the Case Study that follows.
Understanding the correlation concept is key to having a single metric that has credibility with the production, maintenance, engineering, management, and financial areas.
OEE can be generated easily and accurately; it can quickly demonstrate the size of the hidden factory in your specific area. In turn, the plant leadership team can apply people and resources to the proper locations for the fastest improvement.
Chapter 2 will provide a practice example including recommended definitions, a sample production period, and a total range of incidents. In developing the OEE formulas, it will demonstrate that the three different approaches provide exactly the same OEE. Even areas without detailed data collection can still use the simplest method to calculate an accurate OEE.
All manufacturing areas should be able to answer the following questions for each product:
1.How many units that meet specifications were made and transferred to the next step?
2.How much time was scheduled for production of that product?
3.What is the ideal or best theoretical cycle time or throughput for units of that product? (If this were unknown, a rough approximation would be to use the speed value generated by the best 4 hours of the last 400 hours.)
With this information, the simplified calculation shown in section 2.5 can generate an accurate OEE for each product. Prorating the individual product’s OEE can generate a combined OEE for the area. I recommend prorating by the percentage of production schedule time used to make specific products. Even areas with good data collection should reconcile OEE by using the simplified method. All methods should reconcile. If they do not, assume the lowest value is correct and that the other methods have overlooked an area of opportunity. Remember, true OEE directly correlates to area output.
After analyzing all major processes and important equipment systems for each plant site, summarize the results from each area as follows:
< 65% Unacceptable. Hidden dollars are slipping away. Get help now.
65-75% Passable, only if quarterly trends are improving.
75-85% Pretty Good. However, do not stand still; continue to drive to a world-class level. (>85% for batch type processes and > 90% for continuous discrete processes. Continuous on stream process industries should have OEE values of 95% or better.)
Ron Moore of the RMGroup Inc. related to me his best OEE experience was a client with a verified on-stream OEE of 98% over a two-year period.
Using OEE metrics and establishing a disciplined equipment performance reporting system will help any manufacturing area to focus on the parameters critical to its success. Analyzing OEE categories can reveal the greatest limits to success. Forming cross-functional teams to solve these root problems will drive the greatest improvement and generate real bottom-line earnings.
The vast majority of these improvements usually come from non-capital projects. Changes to basic procedures often reduce bottlenecks. Changing supply or distribution policies can help manage bottlenecks. Significant equipment reliability improvement may result by changing maintenance methods or substituting different materials. Focused projects, such as Reliability-centered Maintenance5, can provide major increases in uptime. Improving performance through OEE involves several steps:
1.Calculate the OEE value for current performance (see method 3 in section 2.5).
2.Use discipline and be honest with the results. Compute the financial opportunities of improved throughput (use the model provided in chapter 3). Generate a realistic business plan of closing the OEE gap to world-class levels for your type of industry. At this point, accept the assumption that improvement programs will consist primarily of education efforts and focus teams collecting/analyzing data for root causes. Minimal capital is required and existing resources are usually adequate. Training time and participative education on improvement methods contained in this book are often 90% of the investment.
3.Assuming that the size of the opportunity is significant, commit to a pro-active agenda. Define the hierarchy of critical processes and bottlenecks. Set expectations for plant goals and rewards. (This step may require changing existing measures and reward systems.) Once the key bottlenecks are identified, they must be tackled. OEE and Constraint Management methods should work in synergy.
4.Once the goals are defined, and a plan for addressing the bottle necks is established, share this vision with the workers. Communicate the significance of the improvement and give the community a compelling reason to make the changes. At this time, identify the reward structure.
5.Educate all members of the community about OEE measures and how to collect and reconcile the information. For example, counters, time clocks and chart recorders may be needed on key equipment systems. Reports may need to be modified to categorize downtimes. Everyone should have a major portion of their performance appraisal and compensation linked to achieving the OEE goals. By understanding the categories for data collection and how losses impact OEE, synergistic teams will form. These teams can quickly eliminate root problems. Associated departments can support additional improvements.
6.Generate the resources (e.g., money, people, time, and training) to make the changes happen. Introduce new techniques and programs, as appropriate, including condition-based, predictive maintenance and reliability programs, Total Productive Manufacturing and Best Practices techniques, Statistical Process Control, mistake proof and fail safe techniques, supplier quality requirements and follow up, and quick changeover techniques for operations and maintenance repetitive tasks.
7.Use the OEE metrics at all levels of the plant. Share the results with all parts of the plant community. With good data collection, each improvement project should demonstrate the projected increase in OEE. By frequently posting OEE metrics, any distur bances to high productivity will surface and can be quickly investigated.
A Case Study Using OEE Metrics
In 1996,I was assigned to a highly automated film finishing work center staffed with about 140 people. It was organized into high performance work teams manning four similar equipment flowlines, 7 days a week, 24 hours a day. The area was lead by a cross-functional business team and was data driven. This area finished many different sizes and formats of product and was challenged with many ‘new’ formats and products, as well as methods of operation to improve inventories. Daily meetings were held to review ongoing performance of the “factory”, which included the output quantity, flow line availability, and equipment reliability expressed as an index of the four lines. Meeting the projected production schedules was critical for just-in-time delivery and avoiding overtime in related work centers.
Figure 1-1 Equipment Index versus Output Index
One advantage for the area was an automated Equipment Performance System (EPS) to gather information. The EPS system provided all of the information suggested for categories to compute a detailed OEE, including frequencies of events. However, in early 1996, OEE was computed only monthly and submitted to plant management. It was not being actively used as an online guiding metric.
New levels of output had been achieved at the end of 1995 and carried into week one of 1996. See week one of figure 1-1. Output projections for 1996 were even higher. This was because prototype equipment improvement projects appeared to be successful. Early in 1996, the equipment improvement upgrades were migrated over all four flowlines.
Although the impact of shutdowns on operating schedules was minimal, the equipment changes required procedure changes and retraining for operators and mechanics.
Figure 1-2 Operational MTTR
Almost from week one, 1996, the output began to decline from expected levels. The second quarter results were very serious with an under production of 10 percent. By week sixteen of 1996 the investigating team had reached a conclusion.
In general, the feeling was that equipment reliability was not good. It was reported that the modifications were causing more problems, and couldn’t reliably handle new products.
With this information, the technical community worked hard to make sure processes and systems were working properly. With intense focus, the equipment reliability index improved over the second quarter by approximately 10 percent. See the increase in the equipment index following week sixteen in figure 1-1 Equipment Index vs. Output per Day Index.
Yet, factory output was still going down.
A more thorough investigation followed.
In review of all parameters, the root cause was found to be operational downtime. However, a study of this category did not reveal any unique or significant single items of downtime, by machine section, crew or product.
Only after plotting Operational Mean Time To Restore (MTTR) did the understanding that the many little events, which used to take 0.8 minutes to restore, were now taking 1.1 minutes.
Over time, poor habits and interruption of concentration had diverted the attention from “making product”. See figure 1-2 Operational MTTR. This underscores the importance of being able to collect time and frequencies of category events.
Week twenty eight of 1996 was the specific “intervention” date when the results of the detailed investigation were shared with each crew. That date is noted in figures 1-1 and 1-2.
Once the community was presented with the information and convinced that they really could influence the outcome by re-focusing their attention to detail, the output per day began to recover. In fact, output did reach the higher levels as predicted with the equipment modification project.
This understanding lead to a review of the OEE metric and revealed that existing online measures could be used to compute OEE. Online OEE does correlate very well with actual pack output for this work center. See figure 1-3 Case Study showing Actual Output and OEE Computed Output in 1997. By instituting online OEE measurement, this area has a powerful tool to monitor the on-going health of their production process.
The work center now makes OEE available each shift and plots the metric weekly. The metric is being used for a portion of everyone’s annual performance rating.
1.6 Total Effectiveness Equipment Performance (TEEP)
Whereas OEE measures the effectiveness of planned production schedules, Total Effectiveness Equipment Performance (TEEP) measures the overall equipment effectiveness relative to every minute of the clock, or calendar time. In many settings, management is especially interested in how well a factory’s key assets are used relative to total calendar time. TEEP is the metric that indicates opportunities that might exist between current operations and world-class levels. It reveals the hidden factory that can and should be leveraged to make the company more competitive. Like OEE, TEEP must be used in combination with financial information.
Figure 1-3 Case Study showing Actual Output and OEE Computed Output in 1997 Correlation is >.9
TEEP numbers can be used to speculate on the potential capacity of an existing plant. The last increments of reaching total capacity usually have higher unit manufacturing costs especially if labor overtime is involved. The final increments need to be evaluated from business and OEE perspectives. With focused improvement projects for OEE and TEEP which makes every hour of operation more effective, it is quite possible that future capacities with overtime will be manufactured at less than current (before OEE) standard unit costs without overtime.
The strategy at many companies is to run their factories 24/7 – 24 hours a day, 7 days a week – and to produce the maximum amount of product possible. These companies often can sell everything they can make; they may also be the lowest cost producer. In some cases, the capital investment in equipment and facilities is quite large; and using the asset around the clock maximizes return on investment. In other cases, the process is continuous and, therefore, expensive or difficult to shut down and start up. A 24/7 strategy may also be appropriate for a portion of the year to meet seasonal demands. Understanding the total size of the hidden factory becomes important. For factories that are already running 24/7, the hidden factory represents an opportunity for increased capacity.
Because TEEP categorizes all events around the clock, it is the metric that should be used when you develop a business case for more capacity or capital expansion. TEEP can be a good indicator of the capacity that is still available within an existing asset. Developing this hidden factory is beneficial because it is cost effective. Other advantages would be the hidden factory could be developed sooner. It also comes with fewer risks than new or modified equipment and systems.
According to a presentation at the 1999 Society of Maintenance Reliability Professionals conference, Rohm and Haas Corporation determined that developing hidden capacity of existing factories was ten times less expensive than building new capacity. Consider how favorable this savings is to return on assets.
Even areas that are not yet filled to capacity can benefit significantly by improving the effectiveness of non-production activities. One such benefit is the ability to respond immediately to unexpected increases in production schedules.
An important operating strategy for all companies is to maintain the balance between production and production capability over both the short and long term. Maintaining this balance helps a company sustain strong net profits on a consistent basis. To maintain this balance between production and production capability, companies must effectively manage required off-line activities; they must not delay or cancel required work. Section 6.1 provides a case study of how managing shutdown and maintenance work provided ten additional production days per year for a plant. Frequently, decisions by management to delay equipment shutdown and maintenance work in favor of generating more product for current orders, can lead to a poor performance that jeopardizes current and future orders.
OEE ignores planned downtime whereas TEEP brings into focus the necessary activities required when not planning to make product. These activities include equipment shutdowns and planned maintenance stops, experiments, new product development, meetings, training, and planning for staff needs, shift schedules, and manufacturing strategies. TEEP also records all online rework that affects the key equipment.
Companies must make good business decisions regarding how they allocate time for the various activities that impact the key assets. If all activities are highly effective, then planning and scheduling become straightforward and less reactive. Non-production tasks should take place as scheduled; they should deliver the anticipated results (expected throughput) with high reliability (quality). Opportunities to leverage part of the hidden factory can come from targeted improvements on non-production tasks. Examples include:
Reduce planned maintenance downtime (see section 6.1 for a case study).
Use pre-assembled equipment modules to “swap out,” reducing replacement time.
Execute only statistically designed experiments (minimize guessing).
Staff work areas appropriately to cover lunches, breaks, week ends, and holidays.
Train and educate workers off-line.
Hold multiple meetings to communicate with employees before or after shifts. This avoids work stoppage for full community meetings.
Improve reliability of delivery.
Improve transitions to new equipment modifications (see section 9.1).
When proactive leadership drives improvements in both production and non-production activities, the increased effectiveness from the entire work community improves the bottom line. When the focus is only on production, and non-production activities are ignored or undervalued, poor work practices develop in off-line work that eventually impacts OEE.
1.7 The Bottom Line: Good Goods at Lowest Cost—Now!
The dynamics of the world, both internal and external to the factory, generate great uncertainty about what the future will be for any one course of action taken today. This uncertainty, often the source of “analysis paralysis,” can cause corrective actions to be delayed day after day. Because of global competition, every company must strive to be the best it can be at delivering quality goods, on time, at attractive prices, today. Highly effective factories are certainly advantageous. They increase your company’s ability to leverage stronger financial benefits and sustain more favorable positions relative to its competition.
In many cases, the threat of plant shutdowns and job losses occur before the workforce accepts change. This scenario doesn’t have to happen! Instead, management must determine the true size of the hidden factory and proactively set a course of action that leads the company to world-class numbers.
Where does this leadership start? It starts at every level of the factory. Promoting change should be like discovering gold and then communicating to the rest of the organization about the potential treasure. Once the organization grasps the size of the hidden factory, it has a compelling reason to begin its own gold rush.
For change to take place, everyone in the work community must recognize the consequences of the current path. Without improvement, a serious crash will happen. And in today’s competitive environment, everything happens faster. Everyone must recognize the difference between “continuing as is” (the base case) and “what could be” if high OEE and TEEP levels existed,.
The next two chapters explain how the definitions categorize every minute of calendar time, how the three methods of computing true OEE reconcile, and how true OEE correlates to Operating Income (Earnings Before Interest and Taxes, EBIT) and Return On Assets (ROA). After understanding that each method reconciles to the same OEE, and that the hidden factory can be identified easily, your next step is to determine the size of the opportunity for your plant or work area. Even a small increase in OEE leverages a bigger increase in operating income.
A detailed analysis will bring into focus the areas where opportunities for major improvement exist. At that point, a broad range of tools and methods can be applied to these clearly defined targets. Be creative in developing solutions. Do not limit your vision to only internal resources. Think about bringing in people from other departments and disciplines as well as outside resources. In all cases, be sure to work from good data. Verify your actions with statistically designed experiments. The most important aspect is to get started now. Improved benefits will only be realized after changes are implemented. Every day counts.
Companies and factories often approach new processes by identifying a pilot area. In the selected area, they test and develop methods before applying the process to other areas or plants. This approach has a number of pitfalls relative to an aggressive OEE strategy. Most change involves educating the specific work center about the metric, collecting and analyzing information, and forming cross-functional teams to work on the major limiters. The experience of the pilot group is not easily transferred to other areas. Furthermore, if the pilot area is not of key importance to the plant or overall process, it may not get the resources and attention it needs to be completely successful.
Aggressive OEE strategy should be launched in conjunction with the five steps of constraint management methodology described by Eliyahu Goldratt in Critical Chain7.
1.The strategy should be implemented as a plant or factory objective using the prioritized list of bottleneck assets (Identify).
2.The strategy should focus the resources and the initial program on the top ranked bottleneck (Exploit).
3.All other areas of the plant should not only be informed of the key equipment OEE goals. They should also be supportive of the prioritized list and serve the key assets accordingly (Subordinate).
4.The selected bottleneck area should incorporate all necessary changes for high OEE (Elevate).
5.When this area is successful, the next prioritized key asset should implement the new methods, insuring that the greatest benefits are achieved quickly (Go Back).
Many companies have achieved tremendous improvement by launching such a strategy, including Reynolds Metals Company, as outlined in the June 1998 issue of Reliability magazine8. Reynolds Metals embraced a new process it called “Total Productive Manufacturing.” This process refocused its manufacturing at the plant level, from “Mission/Vision” all the way to best practices on the shop floor. Measuring its own progress was a vital part of the process of change. The backbone of these measures was OEE improvement.
*The word ‘factory’ can be replaced by ‘refinery’ throughout this book.
References:
1. Nakajima, Seiichi. Introduction to TPM: Total Productive Maintenance. Cambridge, Massachusetts: Productivity Press, 1988.
2. Allen, F. “How Do You Make Paper Clips?.” American Heritage of Invention & Technology, Volume 14/number 1, (1998): page 6.
3. Pray, Tom. “Decide II Simulation: A Full-enterprise Business Simulation.Tom Pray,” Rochester Institute of Technology, New York (1999).
4. Shingo, Shigeo. A Revolution in Manufacturing: The SMED System, Cambridge, Massachusetts: Productivity Press, 1985.
5. Moubray, John. Reliability-centered Maintenance. 2nd Edition, New York, New York: Industrial Press, 1997.
6. Cox III, J., Spencer, M. The Constraints Management Handbook. Boca Raton, Florida: The St. Lucie Press, 1998.
7. Goldratt, Eli. Critical Chain. Great Barrington, Massachusetts: The North River Press, 1997.
8. Holt, F., E. Myers, R. Underwood, and others. “Building and Sustaining Total Productive Manufacturing At Reynolds Metals Company.” Reliability Magazine Volume 5 Issue 2, (June 1998): pages 4-12.
