Overall Equipment Efficiency (OEE)

Transcription

1 Research on Overall Equipment Efficiency Overall Equipment Efficiency (OEE) Prepared by: ASECO Integrated Systems Office Locations including; Oakville, ON, Canada 905/ Philadelphia, PA, USA 215/ Mountainside, NJ, USA 908/ Report /07/27

2 Table Of Contents 1. Introduction Document Purpose Scope of the Document Document Overview What is OEE? Background Information Introduction How do computers help in OEE? Calculating OEE Input Variables Benefits of OEE OEE at Work Boeing Pratt & Whitney Whirlpool Rockwell Automation Eastman Chemical Company Conclusion... 12

3 1. Introduction 1.1 Document Purpose The purpose of this document is to provide information about Overall Equipment Efficiency or OEE. It was created and organized to give both a general and specific view about OEE. The document describes the aspects of OEE and how it is beneficial to organizations. It also contains the equations for calculating OEE, along with its components and derived equations. 1.2 Scope of the Document The following OEE questions have been researched for this document What is OEE? Why use OEE? What were the results of implementing OEE? How is OEE calculated? 1.3 Document Overview The document has been organized in the following manner: Section 1: This section gives a basic overview of the information presented in subsequent sections. Section 2: This section introduces the concept of OEE and describes how it is calculated. Section 3: This section documents the results of OEE implementations at major companies. Section 4: This section provides some conclusions. 3

4 2. What is OEE? 2.1 Background Information OEE derived from a system of plant management called Total Productive Maintenance (TPM). The key goal of TPM is to help operators and maintenance staff to understand how they can improve the efficiency of the equipment with which they work. TPM challenges the complacent view, to engender a sense of joint responsibility between operators and maintenance workers, not simply to keep machines running smoothly, but also to extend and optimize their performance overall. This larger goal is measured by an Overall Equipment Effectiveness ratio. There are two main thrusts to achieving this goal: Quantitative, emphasizing improvement in total available time and in productivity per period; and Qualitative, emphasizing reduction in the number of defective products and stabilization of quality. Several losses interfere with the overall objective. They can be described as: Breakdown losses: These are losses of quantity via defective products and losses of time due to decreased productivity from equipment and breakdowns. Set-up and adjustment losses: These losses stem from defective units and downtime that may be incurred when equipment is adjusted to shift from producing one kind of product to another. Idling and minor stoppage losses: Typically, these kinds of losses are relatively frequent. They result from brief periods of idleness where between units in a job or when easy-to-clear jams occur. Reduced speed losses: These losses occur when equipment is run at less than that the design speed. Design speed may not be known. Materials or tooling may be off spec and require special treatment. There may be fear of running equipment if it is run too fast. Quality defects and rework: These are product related defects and corrections necessitated by malfunctioning equipment. Start-up losses: These are yield losses incurred during early productions, i.e. from machine start-up to steady state. As of this writing, no official standards exist for the calculation of OEE. The OEE calculation is quite general and can be applied to any manufacturer from semi-conductors to chemicals. Since OEE is derived from the TPM model, businesses sometimes make adjustments to the calculation of OEE for their own use. Since no two businesses are the same, no standard exists for OEE calculation across manufacturing industries. Instead the common OEE calculation of available time times performance efficiency times quality is used and small modifications can be made to this if necessary. An example of a small change that a business would make to the OEE calculation could be the available time. Some machines are designed to run 24 hours a day 7 days a week but are only run 24 hours a day for 5 days. Some companies calculate the available time using the 24/7 as the available time and some use the 24/5. There are differing opinions as to which method is better, using 24/5 gives accurate data for the time frame but could lead management to believe that more equipment is needed to increase production instead of just fully utilizing the available time on a given machine. Although OEE grew out of TPM, OEE does not require a business to use TPM in order to gain its advantages. Any organizational structure can use the OEE calculation to find out how effectively that a plant is running. Once an organization determines the efficiency level of a plant, it is up to them to determine the best course of action to increase their OEE. 4

5 2.2 Introduction To give a static definition of OEE one could say it is a statistical measurement used to determine how efficiently a machine is running. An accurate OEE percentage indicates whether a machine is running at optimum capacity and producing quality output or experiencing unnecessary downtime. Although this definition implies that OEE is the measure of a particular machine, it can also be used to measure efficiency of product lines, sections of a plant, or even the entire plant. With emphasis being placed on reducing downtime and maximizing productivity for manufacturing companies, optimizing processes and machinery performance has become more critical than ever. OEE was developed as a tool to effectively analyze the performance of a machine. If a machine is running at optimum capacity, its actual operating speed is equal to its ideal cycle time (design speed). This comparison is also known as performance efficiency. If all output produced by a machine is acceptable and not defective, the machine s quality rate is 100 percent. A machine without unplanned downtime means its availability is 100 percent. Using the key factors of availability, performance efficiency, and quality yields the OEE of a machine. Analyzing the OEE of a machine will give a percentage, a high value for the OEE indicates that the machine is operating close to its maximum efficiency. Although the OEE does not diagnose a specific reason why a machine is not running as efficiently as possible, it does give some insight into the reason. Since the OEE is comprised of availability, performance, and quality, it is possible to analyze these areas to determine where the lack of efficiency is occurring. For example, if the performance and quality values are both above 85% and the availability is around 50% then it is apparent that unscheduled downtime events are causing the machine to lose its efficiency. It is then necessary to focus on this area and to find a solution to increasing its OEE. How total efficiency is measured: 5

6 2.3 How do computers help in OEE? With the widespread use of computers in manufacturing, it is possible to create software which automatically generates the OEE of machines. Although in the past OEE was calculated by a person actually sitting and watching a machine or a plant line for an entire shift, it is now possible to automate the process, which in turn produces better data. Human error was always a key factor in dismissing the OEE value. It is now possible using computer networks, and databases to log information from a machine. Using a specified time period (one hour polling or end of shift logging), it is possible to calculate the OEE of a machine using data that is widely available. They key inputs required to calculate the OEE should be readily available from any plant floor. The required inputs include the sum of the downtime for a specified time period (time a machine is not running), the quantity of output generated by a machine (measured in any applicable unit) and the number of rejects (includes all product that does not meet quality assurance in the first pass, includes re-work pieces). On top of this information a static value is required by each machine in order to calculate the OEE. This value is the theoretical standard cycle time. It represents the amount of output that should be produced during a certain time frame (unit of time / output). The theoretical standard cycle time must be known for each machine for which an OEE is to be calculated. This includes product lines comprised of multiple machines. There is an incredible amount of data that can be calculated using the components of the OEE. All of these equations rely on the results of other equations. Calculating this information by hand proves both error prone and time consuming. Using computers to automate the process, real time data over specified intervals of time could be provided which would include forecasts of yields. This data could then be graphed and compared historically with old data. Once OEE information starts to be received, management can take steps to try to increase its value. As new strategies are implemented to increase the OEE, the comparison of current to historic OEE data will validate these strategies. This is a major benefit because in the past, initiatives were set to increase performance but without the capability to measure success. This often lead to money being wasted for prolonged periods for initiatives that are not successful. Using the OEE calculation to provide real time data makes it possible to determine very quickly how new initiatives are doing and whether they are worth continuing. This strategy gives organizations the confidence to try new things without wasting a ton of money. Often times it is this confidence that leads a company to increase their yields. 2.4 Calculating OEE OEE is calculated by multiplying a machine s efficiency times its quality, times its availability. In this section the inputs required to determine efficiency, quality, and availability will be discussed. Availability: Availability is calculated by dividing the operating time by the running time. Although these two inputs seem quite similar, there are significant differences between them. Running Time: is calculated by taking the total hours available during a certain time frame, minus the time for scheduled shutdown (planned maintenance, breaks, etc.) Operating Time: is calculated by taking running time minus unscheduled downtime (breakdowns, set-ups) It is easiest to understand the concept of availability using an example: The timeframe of this example is going to be an eight-hour shift (480 minutes). In this example, there is a scheduled lunch break of one hour during which the machine is shut down, and in the eight-hour shift, unscheduled downtime events sum up to two hours. Calculations will be done in minutes. Calculating the Running Time: 6

7 Running Time = total time available time for scheduled shutdowns = = 420 The Running Time of the machine is 420 minutes or 7 hours Calculating the Operating Time: Operating Time = Running Time unscheduled shutdowns = = 300 The Operating Time of the machine is 300 minutes or 5 hours Calculating the Availability of a machine: Availability = Operating Time / Running Time = 300/420 = 0.71 or 71% The machine is available for use 71 % of the time. Performance Efficiency: Performance Efficiency is calculated by multiplying the output during the operating time by the theoretical standard cycle time and then dividing by the operating time. Output during operating time: the amount of output the machine produced during its operating time. Theoretical standard cycle time: is the amount of output that should be produced during a certain time frame (unit of time / output) Operating time: is the time that the machine is available to produce output. It is easiest to understand the concept of performance efficiency by using an example: This example is a continuation of the above example. The output of the machine is units during the operating time. The theoretical standard cycle time is 3000 units an hour or 0.02 minutes per unit (60 min / 3000 units). Calculation will be done in minutes. Performance Efficiency = (output * theoretical standard cycle time) / operating time = (12500 * 0.02) / 300 =.83 or 83% The Performance Efficiency of the machine is 83% of what it should be. Quality: Quality is calculated by subtracting the output during the operating time by rejects and then dividing the output during operating time. Output during operating time: the amount of output the machine produced during its operating time. Rejects: the amount of output discarded due to quality issues. It is easiest to understand the concept of Quality by using an example. This example is a continuation of the above examples. The output of the machine is units during the operating time. The number of rejects was 200 (50 garbage, 150 re-work). Quality = (output rejects) / output = ( ) / = or 98.4% 7

8 The Quality of the machine is 98.4% of what is should be. OEE: OEE is calculated by multiplying the available time, quality and performance efficiency. In this case the OEE would be: OEE = available time * performance efficiency * quality = 0.71 * 0.83 * = 0.58 of 58% The machine has an OEE of 58%. Management should attempt to get this machine up to about 85% OEE in order to maximize its effectiveness. 2.5 Input Variables To use software to calculate the OEE of a machine, it is only necessary to know the time frame within which you wish to measure, and then within that time frame, the sum of the downtime events, the output of the machine and the number of rejects. Today s technologies ease the process for retrieving these values from the plant floor. Downtime events could be logged to the database when they occur with a reason code stating the machine identification. Once an hour or when a shift ends, the output and rejects from a machine could be logged into a database. With this information it would then be possible to give the OEE of any machine for a certain time period. Other valuable information is gained through the use of OEE components. The following is a list of other information that can be derived using OEE and its components. 1. Ideal Cycle Parts (Total Pieces that could have been made if running at Ideal Cycle Time for the entire Net Available Time) 2. Operating Pieces (Total Pieces that could have been made while Operating) 3. Pieces Lost due to Availability Net Operating Pieces (Total Pieces that should have been made based on Availability and Performance) 4. Pieces Lost due to Performance 5. OEE Pieces (Total Good Parts Made) Forecast and Actual 6. Pieces Lost Due to Quality Forecast and Actual 7. OEE Pieces Lost Forecast and Actual The above list is just a sample of the information that can be provided using OEE and its components. Depending on the data that is recorded, many more possibilities for calculating data and locating problems are available. These will be discussed in section Benefits of OEE The benefits of OEE are numerous. Being able to see statistics on how well a plant, line, or machine is running, gives the potential to increase yields. Using OEE as a diagnostic tool allows anyone to target an area that needs 8

9 improvement. Once this area is addressed, techniques can be used to try and remedy the situation and to improve the OEE. Using real-time data, the OEE can be checked to see how well the improvement techniques are working. This can reduce costs by eliminating techniques that are not achieving the desired results. The following example will show how using OEE as a statistical diagnostic tool could produce a better yield. Consider a plant where the overall OEE is 50% and it is producing an output of 100,000 units a week. Using techniques to adjust the OEE, the plant has raised the OEE to 85% thus increasing the output of the plant to around 120,000 a week. That s an additional units a month, or 1,040,000 units a year. If the units sold for just a dollar a piece, it would mean an additional one million dollars a year. Most manufacturers want to increase production but do not know how to start, what areas to focus on, nor how to maintain safety levels. Using OEE allows a manufacturer to focus on an area and then develop a solution. Though OEE by itself cannot fix a problem, it does provide the capability to detect points in a system that are not functioning as efficiently as possible. Often companies invest in assets that are unnecessary or do not perform to expectation. This situation arises because of a lack of visibility of the current performance, and more importantly, the potential performance of their assets. Once this visibility is improved, there are enormous opportunities for increasing return on investment by avoiding unnecessary expenditure and generating more value from new and existing assets. The way to improve this visibility is to employ OEE as a measure of how effectively a plant is running. Before a company decides to invest a large amount of money into buying new machines, they should first determine the OEE of their current machines. The answer to increased production is not always the addition of new machines. If there are five machines each running at 38% OEE and an increase in production is required, it may make more sense to increase the OEE, rather than buying new machines. If the OEE for all five machines increased to a value of 85% not only would that company not have to buy new machines to increase production, but could shut down a machine saving operating costs while still increasing production. A key benefit often overlooked by implementing an OEE system is the increase in company morale. In order to raise the OEE of a plant, total commitment by all employees is necessary. Once techniques are in place to raise the OEE, feedback by the operators throughout the plant is also required. Their participation in the process affects many positive changes in attitudes across the plant floor. The day to day operational knowledge that each operator possesses brings contributions that not only improve the OEE, but do so with minimal effort. OEE has benefits even if a manufacturer does not intend to increase production or make any changes because current productivity levels are found to be acceptable. Using historical OEE will help to detect future problems (such as decreased OEE overtime) and allow proactive corrections. OEE also gives the statistical power to justify future investments. If all the machines are running above 85% OEE and production needs to be increased, the data will prove that new equipment is needed. The number of ways OEE can be used is unlimited. Once the data is collected, it is up to the enterprise to decide how they are going to use this information to their advantage. The resourcefulness of the company is in creating new ideas and techniques will determine the resultant amount of increase in the OEE. 9

10 3. OEE at Work 3.1 Introduction In this section, real examples of major companies will be discussed as to how OEE was used for them. All of these companies have recognized a need for accurate, real-time OEE calculations. These cases are from Engineer s Digest, January, Boeing Boeing identified six areas of loss in efficiency, quality, and equipment availability: machine tool cutting, thermal processes (autoclaves and ovens), chemical processes (tanklines), material handling processes (AGV s, conveyors, etc.), and machine tool presses. The most commonly seen unplanned downtime events relate to personnel and their lack of training on the machines they operate. It s common for operators to shut their machine down in order to help another operator. With this information in hand, Boeing launched a standard work program intended to improve training practices, as well as provide a more logical workflow. The OEE data Boeing obtains on a regular basis helps the company incorporate improvement activities, accelerate capacity planning, and justify capital investments. 3.3 Pratt & Whitney Pratt & Whitney uses OEE data not only to audit is processes, but also to establish benchmarks. The company has established an aggressive program to achieve 85 percent OEE, which requires accounting for every event, planned and unplanned, associated with a process. The company has successfully completed a major effort called the 5S Program, which stands for straighten, sort, standardize, sustain, and shine. Management felt total productive maintenance could not be implemented without the 5S program. Only after 5S was practiced for some time did management focus on autonomous maintenance activities and the OEE. The company s view of TPM includes empowering operators to make decisions based on accurate data collection. Using a data collector, operators are able to obtain real-time feedback and make informed decisions. The data the operators receive from the OEE tests gives them the tools necessary to direct their maintenance focus. OEE at Pratt & Whitney helps to minimize start-up losses while eliminating breakdowns, speed losses, idling, minor stoppages, quality defects, and rework. 3.4 Whirlpool Whirlpool, in its Marion plant, has workers using a press record sheet to record the total time spent running a press and the total time for each occurrence of either planned or unplanned downtime. Scrap defect codes are categorized by material, equipment, tooling, or process. The sheets record descriptions of all events, the amount of time they caused that machine to be down, and a reason code associated with each event. A safety checklist is included to ensure safeguards are in place. Once the data is documented, it is downloaded into a spreadsheet for further analysis. A control chart plots availability, performance efficiency, quality rate and the OEE. These trending charts help Whirlpool determine performance and identify area for improvement. The benefits of OEE and TPM have lead to an increase of production by 21%, without any significant capital gains. 10

11 3.5 Rockwell Automation Rockwell Automation in Twinsburg, focuses TPM not only on employee involvement at the operator level, but also on involvement at the management level. When a machine goes down, an operator inputs a code into the machine s controller signaling the entire management team that a machine is down and why. Plant managers become especially concerned with bottlenecks that affect the entire production process. Events such as setup, adjustment and minor stoppages are noted too. Downtime associated with these events adds up over time, resulting in lost production. The facility also monitors the time it takes to re-work parts. Often a machine produces a part in need of re-work. Rather than stop the run, operators choose a re-work mode within the collector and monitor the time the machine is re-working a part. A data recorder and utility software monitor any bottlenecks that cause work slowdowns and poor quality parts. The flexibility within the software allows company engineers to quickly identify the cause of the downtime. Control charts on the recorder display efficiency, quality, and availability details. Pareto charts for planned and unplanned downtimes help the person monitoring the process understand the severity of these events. 3.6 Eastman Chemical Company Founded in 1920 in Kingsport, Tennessee, as a unit of Eastman Kodak Company, Eastman Chemical Company was spun off in 1994 and is now an independent, publicly held company. Eastman has approximately 5,300 customer s worldwide and posted 1998 sales of $4.48 billion. With corporate headquarters in Kingsport, Eastman employs 16,100 people in the processes industry in more than 30 countries. In the 1980s, Eastman built a strong team-based enterprise that involved all employees in the quality management process. Employees use data to trace their individual and/or team performance. In the late 1980s, Eastman leveraged employees' experience with small group activities to implement TPM, which is still going strong. TPM at Eastman depends upon the support of top management, a well-planned deployment process, statistical data (OEE), and perhaps most importantly, implementation driven by hourly workers. Using OEE statistical data to give management direction in improving the efficiency of their plants, equipment availability improved by over 300,000 hours. It was the use of TPM s OEE that gave the organization the ability to effectively implement new techniques to increase the overall efficiency of the plant. In addition to the improved availability of machines, the cost savings incurred for maintenance totaled $16 million a year. On top of these numbers was how easy it was to initiate the program with an estimate of 90% of Eastman s 6,000 hourly workers participating in the TPM and OEE initiative voluntarily. 11

12 4. Conclusion Many organizations have already seen the benefit of using OEE to increase their production. It gives companies the ability to analyze data quickly using information that is usually already recorded at most manufacturers. Almost every company wishes to increase its yield but does not know how to go about it. Using OEE and component calculations, a company can identify areas that are not running as efficiently as possible. Once these areas are discovered management can try to improve the OEE by introducing new techniques. The OEE value can then be analyzed to determine the resulting impact caused by these techniques. One of the hardest areas for manufacturers to deal with is optimizing the use of data. Data is often collected but not utilized by the organization. Implementing an OEE strategy makes use of information that is likely already being collected. OEE then organizes and presents this information in an easy to understand manner, which can then be used to improve yields. Computers and software are the ideal way to monitor the OEE of a manufacturing plant because they provide quick, reliable access to data. Moving ahead with OEE measurements does not have to be a large-scale investment because the data to calculate it can easily be attained from the plant floor. Also, OEE does not have to be installed throughout an entire plant, but can be focused on individual problem areas. OEE is not the solution to problems in manufacturing. Instead it identifies areas where equipment is not running as effectively as possible. As equipment runs more efficiently output increases which in turn increases profits. 12