Everything we measure generates variation, especially when there are multiple hands involved. To be honest even with just one person performing the same function, there will be some variation. Variation is not the enemy, uncontrolled variation is our nemesis!
When creating a Measurement System Analysis (MSA) there are 3 characteristics that you should focus on before you try any of the bells and whistles.
Is it accurate?
You need to know how accurate your measurement system is. If you can’t correctly count the number of variations happening can you really call them variations? Your measurement system is only as good as your accuracy, so it makes sense to spend a fair amount of time ensuring that not only are you counting defects, but you are counting the correct defects. This goes back to knowing why you want to measure something. If you want to find out why your shipments are late, measuring the number of birds around your facility won’t help. So accuracy needs two things: measuring the right data and ensuring the data is being measured in a way that answers your question.
Is it precise?
We’ve talked about precision and for a refresher precision is the reduction in variation. When you have identified your improvement area in the process, you are now ready for precision. So you are going to take one process, completed by the same person, in the same order every single time. Once you have identified this, you can began to reduce the variation and create precision.
Can you reproduce it?
The thought behind automating any process is ultimately making it scaleable, that is can you repeat the success? This is what determines a successful process from a failed one. Any process is good in theory, but where you get a great process is when you find one that can be repeated with the same amount of variation no matter who does it. That’s your end goal folks.
So we’ve covered the 3 basic characteristics of a Measurement System Analysis, so have a conversation with your belt and figure out your current state and your future. Your MSA will heavily influence your future, so take this conversation seriously. If you need more help, give us a call and let us help.
I am always an advocate of finding the right tool for your specific project, so I propose that you get to know MSA. It’s a great foundational tool and a great way to start building in the practice of good measurement within your organization. There are a few things you need to know when looking at your measurement system, let’s start with these.
What is a measurement system?
However your organization measures data, in Six Sigma we define your measurement system as ‘your complete process used to measure data’. The thing to know about measurement systems is the more moving parts you have, the more potential sources of errors you have.
What effects measurements?
Measurements are effected by a variety of factors, but some of the usual suspects are:
Accuracy-The numerical difference between what you think and what actually is.
Linearity-The change in the operating system of your measuring system. Think about when you have a different operating system on your laptop. Screens are viewed and you may have some errors. Same principal.
Stability-Something about your measurement system is inconsistent. It may be the way you intake data or the way your process it, but something is not consistent.
Precision-This is all about how much variation occurs in whatever it is you are measuring.
What are the red flags?
If your measurement system give you a reason to pause before you do anything, take a look at the repeatability and reproducibility of your measurement system. When you are looking for repeatability, you are looking for the variation that occurs when you measure the same piece of data using the same measurement method. For repeatability you are looking for the variation that occurs when different people measure the same thing using the same methods. To be fair there will always be some variation when multiple people are involved, but you want to get your measurement system as close to no variation as possible.
In creating your ideal situation, you may have to critical eye on your measurement system. It’s hard, but it is worth it. We will pick up on this subject next week and continue to fine tune your measurement systems!
As we cover Six Sigma Statistics, I want to make sure that I go over the illustrative part of the statistics. We know Six Sigma is technical but the key to making it stick, is to make it simple and understood by the non-technical people using it. So let’s talk about the Box Plot or the Whisker Plot. A key thing to remember in Six Sigma is that everyone using different terminology, so ask questions and make sure you are speaking the same language.
What is a Box Plot?
Simply put a box plot helps to put a picture to the data showing you where most of the data falls, how the data is distributed and where the outliers are. So it basically shows you what you’ve got, how it looks and what is unusual about it.
What does it measure?
Say you have a process that has multiple variables affecting it and you want to know what is what. If you have a delivery truck with 4 alternative routes a box plot can show you which ones, according to the data, are the most problematic. Additionally a box plot will tell you how symmetrical your data is. Knowing if your data is skewed or not can affect how you interpret your data. In a box plot, if the data is mostly symmetrical the median will appear in the middle of the box and the whiskers will appear to be mostly the same length. IF the data is skewed to one direction, the median will not be in the middle and the whiskers will be different sizes.
How does it work?
Box plot measurements are based on quartiles and the distributions are shown within the graphic. Think back to your SAT’s or ACT’s. Remember how they told you that you scored in the 25th percentile? Well that’s a box plot. You will have an upper limit and a lower limit and those limits will be determined by your organization’s goals. The outliers will be the extreme values, values that are so far outside of the normal distribution that it is unlikely they will be reproduced.
Interpreting your data is just as important as gathering it, so choose carefully and with purpose. Talk to your belt and use that advice to help you find the best method for your organization.
In Six Sigma we are always collecting data, generally we are collecting data to address a current problem in our operations or services. The wonderful thing about Six Sigma is that we are also able to collect passive data. The usefulness of passive data is that it provides us with the ability to identify patterns, the catch to visualizing these patterns is in selecting the right graph to view the data.
Why use a graph?
The first benefit that comes to mind is the ability to see the error trends from a visual perspective. The other reasons graphs are a great tool are:
- Alongside identifying trends, they also help you see potential variable relationships. When you have a situation that could have multiple culprits, a graph can help you see which ones are a real potential.
- They can help you identify the risks that your customers will determine critical. This move allows your customer to be proactive instead of reactive, a much more desirable trait.
- It allows you to systematically dismiss variables and determine which one’s control other ones.
- It shows you the results of the passive data you’ve collected.
Where do I get the information for a graph?
Data is everywhere right? Yes and No. Your graph is only as good as your data, so we don’t want questionable data. The integrity of your data will be defined by your individual organization, but if you stick to these three questions you should be fine:
- What do you need the data to tell you?
- How often do you need to collect it?
- How do you need to collect it?
Next week we will get into the types of graphs and what times of data are appropriate for them. Until then happy hunting!
This week we will continue our discussion on process mapping, I promise it will not go on forever, but it does have a lot of intricacies. Many people think that process mapping is just putting some shapes on a diagram, but it means much more than that. There are 3 levels of process mapping that are commonly accepted among the 6Sigma crowd.
Level 1 –The Macro Process Map
This is typically how management views the processes of the organization; it’s a big picture, future strategy kind of view. It also creates the ability for management to see how to position the organization or resources in a way that complements the product/service being created. This is a high-level map which generally includes:
- Activities that relate to one major process step
- How the process fits into the big picture
- Little specific detail
- Visualizes only major process steps
- Can be used with only a general understanding of the purpose of the process and its steps.
Level 2-Process Map
This is the worker bee process map, where the people who have specific knowledge of the process come in. This is the map that is used to identify all the major steps a worker takes to complete a process. Within Level 2, there are 4 types of process maps:
- Linear Flow- A straight line from beginning to end.
- Swim Lane-shows you who is responsible for what task.
- SIPOC-a little more complicated. It takes five areas: your suppliers, your inputs, your process, your outputs and your customers.
- Value Stream-a specific map that helps to visualize and understand the metrics for the performance of major steps.
Level 3-Process Flow Diagram
Level 3 is not a must because this is a micro process map. It is where you zero in on a specific area and focus on the steps in the process that are causing whatever challenge you are having. When beginning this level you need to ask the following questions:
- Which steps contributed to the problem?
- Where would the problem most likely have occurred?
- Are there elements to the product/service that lend itself to the problem?
These questions help you find the focus that you decided in your problem statement. For this to work you will have to break each step in the process down, most easily using SIPOC. Remember a Level 3 map should include:
- All process flows
- Any set points
- Any standard or automated procedures
- Inputs and outputs (specify if the are controllable or non-controllable)
- Defects per unit
- Yield and rolled throughput yield
- Value and non value added activities
It’s a lot of information, but mapping a process is a fundamental step in your improvement project. It is absolutely critical that you get it right. For more help or more information, give us a call and we will be happy to get you started.