The Six Sigma Handbook for the Modern Engineer

Six sigma is one of the best known data-driven methodologies to eliminate defects in manufacturing. Learn the entire process through our comprehensive handbook.
Trevor English

Six Sigma methodologies can profoundly impact how we engineer, but what is involved in this innovation-advancing method?

Why and where it all began

Competition and professional pressures consistently drive us as engineers to streamline our processes, optimize our designs, and improve product quality. To meet our needs in the drive towards optimization, it is important to choose a work path that is bolstered by past success. It is in this need for a clear direction, the Six Sigma methodology becomes important for the modern engineer.

Whether you are an engineer, a process manager, or a manufacturer, proper utilization of the Six Sigma organizational structure will provide benefits beyond your current abilities. This process began as a tool for engineers, formulated by engineers, and today it continues to provide an effective means for advancement.

The Six Sigma Handbook for the Modern Engineer
Source: Cmglee/Wikimedia Commons

In reality, most Six Sigma plans are 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, an engineer, through the beginning and inner workings of Six Sigma, while providing a perspective of the bigger picture. If you take the time to really embrace this process, there are significant opportunities for career advancement and engineering innovations contained in the Six Sigma methodology.

Philosophy for improvement

Whether you know very little about Six Sigma methodology, or consider yourself a “black belt” in its usage, understanding the way these techniques can improve the quality of output is the first step in applying Six Sigma to engineering.

The technique was originally developed at Motorola in the 1980s. At its core is a philosophy based on the constant improvement in the quality of a product or design. This task is accomplished by removing the root causes of defects in products and minimizing variability in manufacturing and business architecture. This seemingly simple philosophy of removing the root causes of errors, and implementing a consistent structure, is the key to how Six Sigma techniques improve our engineering process.

Our desire for measurement

As engineers, we naturally favor the quantifiable and understandable. Abstract design constraints are often a source of frustration during a design process, especially when balanced against the 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 name of this technique is in the statistical modeling of manufacturing processes. The maturity of any manufacturing process is measured by its sigma rating, which is a direct correlation to the quality of its output. A manufacturing process with a perfect sigma rating would produce parts with zero defects in a completely optimized process. Obviously, this is practically impossible, but it is kept as an understandably unreachable goal in the Six Sigma workflow.


Aside from a set of techniques, Six Sigma is also a measurement system. If we undergo optimization under these techniques, the result should be a manufacturing process where 99.99966% of all outputs are defect-free. When a technique results in this - only 3.4 defective features to 1 million outputs, then it is a Six Sigma process. Digging further, we can find the sigma statistics the methodology is based on.

Analytical Sigma statistics

The entire Six Sigma Process is based on the idea of being able to measure the output of a manufacturing process through mathematical models. We hinted at this at the beginning of this e-book, but now that we have the necessary structural background on how Six Sigma works, we can dive into the math.

The basic idea of Six Sigma is 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 of deviation away from the upper and lower tolerances of a design. This, in turn, makes the process highly unlikely to produce a product outside of the tolerances.

The other key aspect of the Six Sigma statistical model is the 1.5 sigma shift, denoted by the two bell curves outside of the center diagramed above. This shift is based on the knowledge that process efficiencies tend to degrade in the long term, even if short-term performance is optimal. Machines tend to wear and get less efficient, injection molds tend to develop cracks and lose details over time, etc. This can all be accounted for through the 1.5 sigma shift.

Why 1.5? Study of 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 with 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 the mathematical models Six Sigma is based on in practice is typically done company-wide, rather than on a single project. 

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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 an analytical explanation for 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 using solid developmental techniques leaves us in a far better end state than the freeform design process that we often like to participate in.

The doctrines of Six Sigma necessitated definable processes, predictable process results without variation, 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 benefits upper management. However, arguably the most impactful aspect of Six Sigma is when it is used on a micro-level. When we take Six Sigma to heart in engineering, we stand to benefit in our individual work as much as the entire project stands to benefit collectively.

Innovation analysis

Before we delve into the exact application of Six Sigma, we need to lay a little more groundwork in our understanding of innovation. When properly applied, these techniques provide analytical tools which can be used to measure innovation. These tools also help to eliminate waste and provide standard methods for what was previously unstandardized.

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 specifications. If manufacturing operates with Six Sigma quality in a short-term design flow, improvements in long-term production will reflect this. 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 goal of 3.4 defects per million outputs with each innovation, but we will get close.

Each engineer and each organization will have to weigh the appropriate scope for improvement in 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 more than 30 years now, and its innovative capability has been proven by nearly every leader in manufacturing. It saved Motorola 17 billion dollars after it was first implemented, and today nearly all Fortune 500 manufacturing companies use the technique. The method 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 effectively implement it.


At the core of the technique are two methodologies, defined as DMAIC and DMADV. DMAIC is used for improving the 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 of pre-existing processes. The process goes as follows:

The Six Sigma Handbook for the Modern Engineer
Source: CarsonWyatt/Pixabay

DEFINE systems, voices, requirements, and goals. In this first step, we lay the foundation for what it is that needs to be improved upon. 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 actual data that we can improve upon. We gather key aspects of the current process 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 tells us how much improvement is needed to meet our goals. 

ANALYZE the data. This is arguably the most important step of the DMAIC process. After collecting the data, we need to analyze it to establish cause-effect relationships. Using a technique such as a root cause analysis allows us to ensure our analysis is accurate. We must determine relationships and ensure that every factor in the operation of a process has been considered.

IMPROVE the current process based on data, using new techniques. This step turns the corner from understanding to innovation. Here we will engineer and design a new process, or aspect of a process, based on the cause-effect, data, and relational analysis.

To accomplish this, we can use techniques integral to Six Sigma, like designing experiments, mistake proofing, and standardizing 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 are monitored. Finally, we need to implement controls, such as statistical process control, production boards, and visual controls, that will help us monitor our new process.

Alternate: You can also choose to add a RECOGNIZE step to the beginning of this workflow, which 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 a project from formulation to actualization, giving it the best potential for success. DMADV is sometimes referred to as DFSS, or Design for Six Sigma, because it applies the Six Sigma process 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 those which align with the company or personal design strategy. In some senses, this defines a box, inside of which the innovations needed 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, its absence would result in an undesirable product. This step does not so much measure pre-existing systems but rather 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 bulk of work on the new process or product design is done here. We must take all of the analysis done in the previous steps 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 verifies your new design. We can do this by setting up pilot runs or implementing the production process. 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 a general way can be simple, but bridging the gap to actually implementing it in a company, team, or even in your individual 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 the leadership roles.

Roles in the Six Sigma Implementation Process

There are five different roles in the Six Sigma toolset that facilitate growth. These are: 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 consist of the CEO, and Green Belts may be the design engineers. However, this isn’t the only case. We can also implement Six Sigma on specific design projects. In this instance, We might find ourselves, as engineers, functioning as the Project Leadership, the Champion, and maybe even the Master Black Belt as well. Taking it even further, if we want to apply Six Sigma to a design or process involving only ourselves, then we can do so by 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 driven from the top down. Rather, it can be molded, used in applications both large and small, and made to fit our workflow in whatever way we need it.

All of these roles are great in theory, but without some form of objective measurement of an individual'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 help you become certified in any of the roles of Six Sigma.

If you’re an engineer looking for a leg up into 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. By taking initiative, you can end up filling 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 and defined ways to implement them. In essence, DMAIC and DMADV are only theories, unless we put them into practical use by bridging the gap between design conception and design implementation.

There are a huge number of tools available to facilitate quality management and allow set standards of improvement. Implementing any one of the following tools will help to access and deliver 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 tools most utilized and applicable to Six Sigma and give overviews of each.

5 Whys

This method provides us, as engineers and managers, an iterative technique for understanding cause and effect relationships. 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 face to face with 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 points out 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 in an organized way, and determine causal factors behind every event until the final root cause is found.

Cost-benefit analysis

This method provides a systematic approach to determining the respective weaknesses and strengths of a product, in order 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, we design tasks that aim to explain the variation of data or outcomes in a process, in order to affirm a hypothesis about these outcomes. In a basic way, we get to play scientist. This technique allows us to test methods and problems, with the end goal of finding the root cause of a problem or providing a better analysis of a system. Each experiment should directly affect the variation being tested and provide an outcome that is analyzable.

Mistake proofing

Mistake proofing is simple. It creates a device or method, either actual or theoretical, 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 provide monitoring or improvements.

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 the 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, 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 at the beginning has the potential to make the rest of our innovation efforts useless.

Finally, our goal 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 saying, “What I’m doing right now is working well, why spend so much effort to make minor improvements?” This is natural and is a byproduct of being trained to optimize how we use our time – we shouldn’t waste it. However, Six Sigma matters because it succeeds in doing many things for the modern engineer:

It gives us a quantifiable measure of our skills. By measuring and analyzing data throughout the product improvement process, we can better see innovation and directly correlate its impact.

It demands better performance. Implementing Six Sigma, while it may have some bumps along the road, 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 the competition and properly manage our assets in the drive towards innovation.


Six Sigma has been at 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 become 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 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 theories mentioned here with some success. For projects of larger size, you will want to investigate the relevant techniques further and determine which ones best apply to your project.

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