(Illustration) Measure Step-2

Measure step - 2

Professor : In step one of Measure, you determined the specific sub-process that is now the subject of your greenbelt project.
Professor : In step 2, you'll create a standard for the performance of that process. This is the point when you determine the best way to turn what the customer wants into a numeric measurement. This measurement will later be compared to the measurement of your current process in order to see how well you're meeting the customer's need.

Professor : In Step 2, you'll become familiar with the components of a good Performance Standard, including the operational definition, specification limit, target performance, and defect definition.
Professor : You'll also learn about the two types of measurements that you can make-discrete or continuous-and recognize examples of each.
Professor : Once you understand all those concepts, you'll be able to write a performance standard for our Rockledge Plant case.
Professor : Why write a performance standard? We already know that reducing the nut removal time will support meeting the customer's C T Q of increasing plant availability, so why don't we just get started?
Professor : This is where the numbers become important. For one thing, what does "reduce" mean? If we reduced it by twenty seconds would that be good enough, or do we need to reduce it by twenty minutes? The performance standard translates the customer need into a clearly defined, measurable characteristic.

Professor : A good performance standard includes: an operational definition of the process, a target performance, specification limits, and a defect definition.

Professor : Let's start with the Operational Definition. It's purpose is to remove ambiguity so that everyone, including the customer and all G E staff involved, has the same understanding of the process being investigated and agree on how to measure it.First, let's tackle the question, "what is the process?" by looking at an example from the airline industry.
Professor : Airlines know one of their primary customer C T Qs is "on-time flights."Here is a sample of how a customer defines "on-time."
Professor : Here is how the airline defines it. Can you see a problem?
Professor : The customers are concerned with getting in the air, but the airline is only focused on getting them onto the plane. The result is that the airline is advertising ninety-nine percent on-time departures, yet the customers still are unsatisfied because they're sitting on the runway for two hours before the plane takes off! Now you see how important it is to get customer agreement to the definition of a process.
Professor : In this example, we'll adopt the customer's definition of on-time departure.

Professor : Let's start with the Operational Definition. It's purpose is to remove ambiguity so that everyone, including the customer and all G E staff involved, has the same understanding of the process being investigated and agree on how to measure it.First, let's tackle the question, "what is the process?" by looking at an example from the airline industry.
Professor : Airlines know one of their primary customer C T Qs is "on-time flights."Here is a sample of how a customer defines "on-time."
Professor : Here is how the airline defines it. Can you see a problem?
Professor : The customers are concerned with getting in the air, but the airline is only focused on getting them onto the plane. The result is that the airline is advertising ninety-nine percent on-time departures, yet the customers still are unsatisfied because they're sitting on the runway for two hours before the plane takes off! Now you see how important it is to get customer agreement to the definition of a process.
Professor : In this example, we'll adopt the customer's definition of on-time departure.

Professor : So, once you know what it is, the next step is determining "how do I measure it?" Let's begin by talking about data types.
Professor : You need to be aware of two types of data, Discrete and Continuous.

Professor : Discrete values can only vary by a finite amount, which cannot be further subdivided.
Professor : For example, counting the number of people that walk into a room in an hour is collecting discreet data because one is the only unit of measure for a person . A half-person couldn't walk in, right?

Professor : Continuous data, on the other hand, can be refined to any degree of exactness. Time is a common example of continuous data. We often put convenient constraints on time, measuring it in years, months, days, hours, etc. But, in reality, you can refine those measurements to infinity.
Professor : Think of the Olympics where runners win by one thousandth of a second - now that's detailed! And, if you had the right tool to capture the measurement,
Professor : you could refine that number even further. How far we refine a measurement depends on the needs of a given process.Oh, there's the master again.

Professor : The C T Q does not dictate the data type; it is up to you to determine the type of measurement you collect. Here's a table showing some C T Q types and examples of discrete and continuous data for each.
Professor : You should always aim for collecting continuous data because with it you can more accurately assess your process.

Professor : What about our airline example? The goal is to assess the on-time performance of an airline and use the information to seek possible improvement. Which of the following approaches would be better suited for that task?

Professor : So we've talked about how an operational definition answers the questions "What is it?" and "How do I measure it?"
Professor : To determine the other three components of a performance standard, you need to first ask the question, "How much variation in performance will the customer tolerate?" Is a fifteen-minute late departure too late to satisfy their need? The answer to this question will set your specification limits.
Professor : The answer can come from a variety of sources, but should always reflect the voice of the customer. In this case, let's say that a customer survey determined that customers would tolerate a flight leaving the ground up to ten minutes late. Your upper specification limit then becomes the scheduled time plus ten minutes.
Professor : In many cases you will have a lower specification limit that mirrors the upper limit. But in this case, a flight leaving before the scheduled time would not make customers happy because they could miss it, so the lower specification would default to the scheduled departure time.
Professor : The Target Performance is where we will aim our process. In a perfect world there would be no variation in the performance of a process or creation of a product. In other words, it would be done exactly the same way every time.
Professor : So, in that perfect world we could say our target performance for the airline is departure at the scheduled time and we would get that each time.
Professor : But, in the real world, there is variation in performance, sometimes you're a few minutes early, sometimes a few minutes late.
Professor : The goal of six sigma is to reduce that variation in performance so that you are as close to the target performance as possible, thus providing a high degree of customer satisfaction. You'll learn more about the statistical concept of variation in the Analyze section of this course.
Professor : The last component of the performance standard is a defect definition. A defect is any nonconformance or any item outside the specification limit. Another way is to think of a defect as anything that results in customer dissatisfaction.
Professor : In this case, a defect would be any departure time before the scheduled time or more than ten minutes late. In Analyze, you'll hear about Defects per Million Opportunities-or D P M O. Each creation of a product or performance of a task is an opportunity. In this case, each flight that takes off is an opportunity for on-time departure. Whew! I know that was a lot to cover, but I wanted to make sure you understood what a performance standard is all about before we work on master's Rockledge case.

Professor : Based on what we know, what question do we need to answer first to begin writing the performance standard for the Rockledge Plant?

Professor : Coming back to the Rockledge case, we know that the high level goal is to reduce the scheduled maintenance cycle time, so our project goal is reducing nut removal time. For the performance standard, we need to turn that goal into a numeric measurement. Select the best measurement for the Rockledge case.

Professor : Master has reviewed existing GE procedures on this process and talked with Mr. Alberti, Mr. Frank, and some GE Millwrights about the nut removal process. Here is the official GE operational definition, which the customer has also agreed to.
Professor : The nut removal process is the actual time measured from when the millwright places the wrench on the nut, until the nut comes out of the socket. The customers have also provided some other useful information.

Professor : So, here's what we know from the customer. Let's wrap up this performance standard.
Professor : First, I want you to try it yourself. Use the information we've gathered to select the specification limits, target performance, and defect opportunities per year from the drop-down lists.
Professor : These are your answers. Let's talk about each component and you can see how you did.
Professor : The upper specification limit is 30 minutes because after 30 minutes the nuts are being cut off, and that is costing money and impacting the length of the outage.
Professor : The lower specification in this case is not applicable because the faster they get them off, the better.
Professor : That makes a defect any time over 30 minutes.
Professor : You also heard that an expert can do this in 15 minutes, so the customer is telling you that based on historical data of best practice the target should be 15.
Professor : Finally, there are 88 bolts per turbine and you've got 2 turbines in the plant, so that gives you a total of 176 opportunities each maintenance cycle.

Professor : In Step 2, you became familiar with the components of a good Performance Standard, including the operational definition, specification limit, target performance, and defect definition.
Professor : You learned to recognize the two types of measurements that you can make-discrete or continuous-and to aim for continuous data as a measure of performance.
Professor : Once you understood those concepts, we were able to write a performance standard for our Rockledge Plant case.

Professor : So, what we've learned about the nut removal process in step 2 of Measure is this:
Professor : Our operational definition of the process is the actual time measured from the wrench being put on the nut to the removal of the nut.
Professor : And, our standard for performance of this process is a time of 30 minutes or less for removal, with a defect being any time over 30 minutes and an opportunity being each time a nut needs to be removed, and with a target performance of fifteen minutes.

Professor : We're at the end of Step 2 and now we know our project focus and have set a standard for its performance.