Six Sigma methodologies can profoundly impact how we engineer, but what all is involved in this innovation advancing method?
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Why and Where it All Began
Competition and professional pressures consistently drive us as engineers to improve our processes, optimize our designs, and improve product quality. To meet our needs in these endeavors towards optimization, we must utilize a work path that is bolstered by past success. It is in this need for direction that the usage of Six Sigma methodology becomes unyieldingly important to the modern engineer.
Whether you are an engineer, a process manager, a manufacturer, proper utilization of the Six Sigma organization structure will present you with benefits beyond your current abilities. This process began as a tool for engineers formulated by engineers and today it continues to provide means for advancement.
In reality, most Six Sigma plans get implemented as a company-wide directive and if you’re an engineer reading this, you might be trying to figure out what lies ahead. This handbook will guide you as an engineer through the beginnings and inner workings of six sigma, all the while providing perspective into the bigger picture. If you take time and really embrace it, there are significant opportunities for career advancement engineering innovation contained in the six sigma handbook.
Philosophy for Improvement
Whether you know very little about Six Sigma methodology or consider yourself a “black belt” in its usage, understanding our need for these techniques to improve our quality output is the first step in applying Six Sigma to engineering.
At the core of this technique developed in the 1980s at Motorola is a philosophy based on constant innovation of our product’s or design’s quality. We can accomplish this task by removing the root causes of defects in products and minimizing variability in our manufacturing and business architecture. This simple philosophy of removal of root causes and implementing consistent structure is overarching in how Six Sigma techniques improve upon our engineering.
Our Desire for Measurement
As engineers, we naturally favor the quantifiable and understandable. Abstract design constraints are often the sole source of frustration during a design process. We have a need for measurement and a desire to easily quantify improvements against past designs. This is where Six Sigma shines.
The origin of the Sigma in the namesake of this technique finds home in the statistical modeling of manufacturing processes. The maturity of any manufacturing process is measured by the sigma rating, which is a direct correlation to the quality of its output. A manufacturing process with a perfect sigma rating would output parts with zero defects in a completely optimized process. Obviously, this is practically impossible, but it can be kept as the understandably unreachable goal in Six Sigma workflow.
Aside from Six Sigma being a set of techniques, it is also a measurement system. If we undergo optimization under these techniques, we should result in a manufacturing process that results in 99.99966% of all outputs being defect free. When a technique results in this, only 3.4 defective feature to 1 million opportunities, then it is a Six Sigma process. Digging further into this seemingly incomprehensible math, we can find the sigma statistics the methodology is based on.
Analytical Sigma Statistics
The entire Six Sigma Process is one based on the idea of being able to measure the output of a manufacturing process through mathematical models. We hinted at this in the beginning of this e-book, but only now that we have the necessary structural background to how Six Sigma works can we dive into the math.
The basic idea of Six Sigma means that if you have six standard deviations between the mean of a manufacturing process and the nearest specification limit, then no product will fail to meet the final specifications. This may sound complicated, but it all has to do with the interactions of bell curves. Sigmas (σ) are used as mathematical units demonstrating a distance of standard deviation. The mean output of a Six Sigma Process should fall exactly Six Sigma values away from the Upper and Lower tolerances of a design. This, in turn, makes any process highly unlikely of producing a product outside of tolerance.
The other aspect of the Six Sigma statistical model is the 1.5 Sigma shift, denoted by the 2 bell curves outside of the center diagramed above. This shift is based on the methodology that process efficiencies tend to degrade in the long term, even if short-term performance is optimum. Machines tend to wear and get less efficient, injection molds tend to develop cracks and lose details over time. This can all be accounted for through a 1.5 Sigma shift.
Why 1.5? Study over processes has found that a 1.5 sigma shift accounts for most deterioration in a process over time. When you factor in the expected 1.5 sigma shift in any direction for a manufacturing process, you are left with 3.4 deviations per million opportunities. This number should be ringing some bells to what we mentioned in the beginning of this e-book. Understanding how to apply all of these complex statistical models is beyond the scope of this handbook, and for many, beyond the scope of their project. Actually utilizing these mathematical models Six Sigma is based on in practice is typically only for company-wide refinement to determine the overall focus of a Six Sigma innovation.
The goal of Six Sigma is to create a process that is as perfect as possible, in other words, to produce a process that has a mean as close in the middle of our upper and lower tolerance levels as possible. These statistical models bolster the effectiveness of the practical steps laid out in Six Sigma. They provide analytical means to the somewhat abstract methods Six Sigma gives us. As engineers, it’s nice to know that our methods are based on concrete mathematics.
Develop a Production Plan
Naturally, any engineer is only as good as their plan. This plan can stretch from initial design to final manufacturing. Regardless of its application, developing a plan with a developmental techniques leaves us in a far better end state than freeform design that we often like to participate in.
The doctrines of Six Sigma necessitate predictable process results without variation, definable processes, and sustained quality innovation, with a clear focus on quantifiable results management. All of this may sound “managerial,” but this couldn’t be further from the truth.
Applying Six Sigma in our development of products certainly works in an overarching managerial state – upper management stands to benefit. However, arguably the most impactful aspect of Six Sigma usage is when it is used on a micro-level to accomplish the overarching goal. When we take Six Sigma to heart in engineering, we stand to benefit in our designs as much as the entire project stands to benefit collectively.
Before we delve into the exact application of Six Sigma, we need to lay a little more groundwork into our understanding of innovation. When we properly apply these techniques, we are met with analytical tools to measure innovation. We are left with eliminated wasted and standards for what was previously unstandard engineering.
Eliminating Waste and Setting Standards
Six Sigma was designed to improve output and increase useable yield. It referred to the capability of manufacturing to produce high output within design specification. If manufacturing operates with Six Sigma quality in a short-term design flow, long-term production will reflect it. The very implicit goal of this technique is to innovate our processes and give us methods to quantify that innovation. We won’t necessarily reach the Six Sigma 3.4 defects per million opportunities level with each innovation, but we will get close.
Each engineer and each organization will have to weigh the appropriate levels for improvement of each process. We recognize that we don’t have the time or money to make everything perfect, so we have to pick and choose what we want to improve and by how much.
Six Sigma has been around for over 30 years now, and its innovative capability has been proven by nearly every leader in manufacturing. It saved Motorola 17 billion dollars after they first implemented it and nearly all Fortune 500 manufacturing companies use the technique today. This method for innovation analysis is proven, so now, we need to understand how to apply it.
How Does It Work?
Implementing Six Sigma is simple in practice, but we have to take some time to understand the techniques that drive it before we can ever effectively implement it.
At the core of the technique are two methodologies, defined as DMAIC and DMADV. DMAIC is used for improving business process and DMADV is used for creating new process and design.
DMAIC: Define Measure Analyze Improve Control
As we mentioned just above, DMAIC is used for improving existing projects and systems already set in place. Utilizing this workflow technique sets up standards for effective innovation on pre-existing processes. The process goes as follows:
DEFINE systems, voices, requirements, and goals. In this first step, we lay the foundation for what it is that needs to be improved up. We define the systems or processes already set in place, the voices that may influence these processes, such as customers or managers, the requirements of the processes, such as outputs, and finally the project goals. The goals mentioned here should involve the desired outcome of using Six Sigma on a pre-existing model.
MEASURE key aspects, relevant data, and process capability. Measuring gives us the groundwork for actual data that we can improve upon. We gather key aspects of the current process in place and collect data about its performance. For example, we may find that an injection mold and machine process produces flow lines or sink marks on 10 out of every 1000 products. This gives us data to improve upon.
ANALYZE the data. We are at arguably the most important step of the DMAIC process here. After collecting the data, we need to analyze it to establish cause-effect relationships. Using a technique such as root cause analysis allows us to accurately trust this step. We must determine relationships and ensure that every factor has been considered in a processes’ operation.
IMPROVE the current process based on data through new techniques. This step turns the corner from understanding down the path of innovation. Here we will engineer and design a new process or aspect of a process based on the cause-effect and relational analysis gathered. We can use techniques integral to Six Sigma-like Design of Experiments, Mistake Proofing and standard work, which will be discussed in the next section, to facilitate innovation for the improved process. Finally, we take these improvements and apply them to the process through a test batch, eventually expanding the application to the entire process.
CONTROL the improved process. After the process has been redesigned and implemented, we want to make sure any deviations from such are monitored. Finally, we need to implement controls such as statistical process control, production boards, and visual workplaces that will help us monitor our new process.
Alternate: You can also choose to add a RECOGNIZE step to the beginning of this workflow that will help determine the right problem you should focus on.
DMADV: Define Measure Analyze Design Verify
This workflow is central to creating products or new process designs. We will use this technique to bring innovation from formulation into actualization, giving it the best potential for success. DMADV is sometimes referred to as DFSS, or Design for Six Sigma because it keeps Six Sigma in mind from the inception of a new product. The DMADV workflow is as follows:
DEFINE design goals. In this first step, we lay the groundwork for the entire process. We want to identify design goals that meet the requirements set in place by customer demands as well as align with a company or personal design strategy. In some senses, this defines the box inside of which innovation for a new process can occur.
MEASURE characteristics of quality, capabilities, and risk. This step identifies characteristics that are critical to quality. When something is critical to quality, absence therein would result in an undesirable product. This step does not as much measure pre-existing systems, rather it sets in place what needs to be measured and what the desired end goals are.
ANALYZE measurements to develop design alternatives. Analyzing at this step provides us a means of determining if the original product or process design was optimum. We want to stretch ourselves to develop alternatives to designs that may seem set in stone to allow the most optimal of innovation paths to prevail.
DESIGN improved alternatives. The brunt work of the new process or product design is done here. We must take all of the analysis done in the previous step and transform it from theoretical into actualized innovation. The end result should be a design that is best suited for our goals and desired outcomes.
VERIFY the design and test. The final step simply verifies your new design. We can do this by setting up pilot runs or implementing the production process into our engineering. In some circumstances, it can even be appropriate to hand over the new design to the customer or process owner at this point.
Applications for Engineers
Understanding how Six Sigma works in generality can be simple, but bridging the gap to actually implementing it in a team or even to your own workflow can be difficult without guidance. For this reason, we need to lay out the typical Six Sigma work structure so that it can be effectively applied in engineering applications. We also need to give the entire technique some relevance through closer examination of the statistical models that it is based on. First, let’s lay out leadership roles.
Roles in the Six Sigma Implementation Process
There are five different roles in the Six Sigma toolset that facilitate growth. These being Executive Leadership, Champions, Master Black Belts, Black Belts, and Green Belts.
Leadership sets up the vision. Champions take responsibility for effective implementation. Master Black Belts act as coaches and drivers for Six Sigma usage. Black Belts apply methodology to specific products. Finally, Green Belts are those who take up Six Sigma implementation along with their other responsibilities.
If a company seeks to implement Six Sigma methodology as a standard, then Leadership may be the CEO and Green Belts may be the design engineers. However, this isn’t the only case. We can implement Six Sigma on our specific design project. In this instance, We might find ourselves as engineers functioning as the Project Leadership, the Champion, and maybe even the Master Black Belt. Taking it even further, if we want to apply Six Sigma to a design or process involving only ourselves, then we can do so my segmenting our goals into each of these five roles, working down as we go.
The point being that Six Sigma doesn’t have to be a toolset direction from the actual top of a company. Rather, it can be molded and used in applications large and small in made to fit our workflow in however we need it.
All of these roles are great in theory, but without some form of objective measurement of someone’s skill, it can be hard to formulate who goes where. This is where six sigma certification comes into play. There are multiple six sigma certification courses available online that can get you certified in any of the roles of six sigma. If you’re an engineer looking for a leg up or a bee-line to management, proving that you’re certified in six sigma might just give it to you. When a company looks to implement six sigma, the first step is identifying who will fill what role. If we take initiative, we can take our engineering skills and fill those new roles.
Management Tools and Methods
All of the information presented above on different workflows and process creation methods means nothing if we don’t have practical defined ways to implement them. In essence, DMAIC and DMADV are only theory if we cannot bridge the gap between design conception and design implementation.
There are boundless tools available that facilitate quality management and allow for set standards of improvement. Implementing any one of the following tools will help in a variety of ways along the DMAIC or DMADV workflow for a given project. Many of these tools are complex in their own right and are independent of Six Sigma. With that said, we will focus on the most utilized and applicable techniques to Six Sigma utilized in industry today and give overviews of each.
This method provides us as engineers and managers an iterative technique for understanding cause and effect relationship. Our goal in using this technique is to determine the root causes of a defect or problem in a process. In practice and theory this tool is simple, whenever we come to a problem or even a simple occurrence, we ask the question, “why?” We continue this until there are no more answers to the question. It is called 5 Whys because this is the anecdotal number of times needed to get to the bottom of the cause-effect chain.
Root Cause Analysis
Root Cause Analysis is similar to the 5 Whys method in that it outlines a way to reach the root cause of a problem. It identifies that failure to find the root cause does not allow for sustained improvement, only temporary success. This technique allows us to walk through a problem and determine causal factors behind every event until the final root cause is found through a constructed pattern.
This method provides a systematic approach to eliminating and determining the weaknesses or strengths respectively of a product to provide the best design. It can be used both anecdotally or systematically to provide either an overview of improvements or a numerical analysis of costs that will factor into a decision. In summary, it allows us to determine whether a design is sound and it gives us a basis for comparing processes.
Design of Experiments
If we utilize the Design of Experiments technique, tasks are designed that aim to explain the variation of data or outcomes in a process to affirm our hypothesis. In a basic understanding, we get to play scientist here. It allows us to test methods and problems with the end goal of finding the root cause or analyzing a system better. Each experiment designed should directly affect the variation being tested and provide an outcome that is analyzable.
Mistake proofing is simple, it creates a device, actual or theoretical in nature that makes an error or problem impossible to occur or makes the error obvious once it has occurred. We can use this method to prevent human error from occurring, to prevent cascading errors through a process, or to prevent costly errors. This method is typically implemented along with a new or improved process design to monitor or improve if necessary.
Value Stream Mapping
VSM is a lean management tool that lets us analyze the current state of a process and design for a future state with a series of events in mind. By stream mapping, we identify what is needed to take a product from beginning to customer. By doing so, we set in place a “process box” that keeps our designs essential to the end product, maximizing time and innovative capability.
Leveraging Improved Skills
Through this handbook so far, we have been able to understand and grasp the basics of Six Sigma and understand its effectiveness. Now, it is crucial that we understand how to set up the model and then determine the final importance of our newfound Six Sigma skill set.
Setting Up the Model
Our intentions behind Six Sigma should almost entirely be customer focused. We may want to create a better product, but innovation is worthless if it doesn’t meet the needs of a customer. This doesn’t always mean that we should only create improvements that directly benefit the customer, but rather that our focus on engineering improvement needs to have an end benefactor. Perhaps we innovate on a certain molding clamp so that the mold maker has an easier workflow, thus improving the process. The point is this, when we go to set up our model and implement our workflows, we need to stay focused on the benefits of our efforts. We don’t want to engineer just for the sake of it, we want to strive towards useful innovation.
We also need to identify what needs to be produced. You’ll find this as the first step of the DMAIC and DMADV processes, and it goes hand in hand with our customer-centric intentions. Improper identification of our end goal from the beginning has the potential to make the rest of our innovation efforts useless.
Finally, our goal in this should be to optimize. Odds are, if you decided to give this e-book a read, you felt that it could help you optimize your work and or workflow. It’s easy to start off with the goal of optimizing and lose focus. With all of this said, we must:
- Be Customer Focused
- Properly Identify Our End Product
- Strive Towards Innovation
Why It Matters
To some, all of this effort towards Six Sigma optimization may not seem worth it. It’s easy to fall into the trap of our engineering minds and say, “What I’m doing right now is working well, why spend so much effort to make minor improvements?” This is natural and a byproduct of being trained to optimize how we use our time – we shouldn’t waste it. However, Six Sigma matters because it succeeds to do many things for the modern engineer.
It gives us a quantifiable measure on our skills. By measuring and analyzing data throughout the product improvement process, we can see innovation and directly correlate its impact.
It demands better performance. Implementing Six Sigma, while it may have some road bumps, demands and nearly always guarantees better process/product performance. It has been proven time and time again to be trustworthy.
It creates value through innovation. This process allows us to improve upon the value of pre-existing processes and create value in new processes. The Six Sigma methodology helps us as engineers to beat competition and properly manage our assets in the drive toward innovation.
Six Sigma has been on the leading edge of engineering innovation since its creation in the late 1980s. It provides us with a means to an end in our efforts to optimize our engineering processes. As you likely already realize, it isn’t a cure-all to every engineering challenge, but when applied correctly to the correct challenges, it can function as an incredibly impactful approach.
This handbook certainly doesn’t function as an all-encompassing guide to implementing Six Sigma methodologies. However, it should set you on your way to becoming a Six Sigma equipped modern engineer. If your company is looking at implementing six sigma or already has, now is the time to embrace it and get certified. Thinking ahead and readying yourself for the changes coming can profoundly impact your career. Aside from career advancement, the other benefits of early adoption should be clear from the innovation that six sigma brings.
In the terms of your skill level with Six Sigma now, the information presented in this handbook will bring most modern engineers up to the Green Belt and early Black Belt stage of understanding. For small projects, you can likely apply the theory mentioned here and succeed. For projects of larger size, you will want to investigate the relevant techniques and determine which one applies to your project, expanding therein