Six Sigma is a management philosophy with the goal of reducing quality defects in production processes using a broad variety of statistical analysis “tools” and techniques. It is a robust methodology that borrows elements from other manufacturing methodologies, such as Lean, Agile Manufacturing, Total Productive Maintenance (TPM), and the relatively similar (but functionally distinct!) Lean Six Sigma, for a few examples.
There is no single international standard for Six Sigma principles or practices, although there are a variety of instructional materials available, including certifications based on the Judo black-belt system. Certifications can be helpful in implementing Six Sigma methodology, but they are not necessary or required in order to achieve actual results in your business.
Six Sigma is a process control gameplan built on statistical analysis
Two methods: DMAIC and DMADV
Aims for 3.4 DPMO (99.99966% quality control)
Six Sigma received its name from one of the statistical tools that it uses the most: the control chart. In this kind of diagram, output is tracked over time, and any deviations in quality from the average will cause output to stray to either side of the ideal standard. This kind of graph is particularly helpful for tracking differences in output quality over time.
Optimal output is measured in terms of sigma levels, which mark the mathematical distance between expected standard deviation and the specification requirements in place for that process.
In Six Sigma, any potential output created in the manufacturing process is called an “opportunity.” These opportunities are measured by a DPMO rating, which stands for Defects Per Million Opportunities. If implemented in a perfect scenario, a Six Sigma plan should lead to 3.4 DPMO rating, which is equal to a standard of 99.99966% quality output.
The DMAIC (pronounced duh-MAY-ick) Method is used for the improvement of currently existing processes and products. The acronym is as follows:
Define the process boundaries and expectations from customer’s perspective
Measure the actual, quantitative performance of the process/product/service
Analyze the measured data to identify the root cause of issues
Improve the process by developing and testing alternate solutions
Control the maintenance of the updated process using statistical process control (SPC)
Explanations of the Six Sigma approach can cite an overwhelming number of acronyms, so keep in mind that an absence of one or more “tools” in developing a strategy will not overly determine the anticipated results of the Six Sigma process.
The DMADV (pronounced duh-MAD-iv) Method is used for the development of brand new processes or products that have not yet been implemented.
The DMADV approach is very similar to the DMAIC approach, and half of the acronym’s terms are shared between the two. The first three steps, define, measure, and analyze are exactly the same as in the DMAIC method, but with the angle of developing a new, and not established, process:
Define the process' boundaries and expectations; Measure the process' quantitative performance; Analyze the data to find root causes;
The final two terms added to the DMADV Method work to center this process management specifically for developing a new service, product, or process:
Design a new alternative to fill the niche shown by the data analysis; Verify the prototypes through testing and then implement them for longer-term use.
Design for Six Sigma (DSS) is a methodology based on Six Sigma that prioritizes design instead of mere process improvement. This offshoot uses the DMADV approach to identify the customer’s needs and then design a solution. A DSS approach is useful for when a project is so ill-performing that it needs to be completely redesigned rather than merely improved with the current foundation.
Six Sigma is a list of questions that executives can use as a planning outline in developing new or better production processes. It was developed in the 1980s at Motorola as a management tool for reducing statistical variations, or defects, and has become popular ever since for businesses looking to smooth out their production systems.
The steps of Six Sigma are asking increasingly specific questions about ways to solve a problem. Like all problem-solving, the first step is never to jump straight to solutions. The first steps are about defining the situation currently, brainstorming possible approaches, and outlining the resources needed to isolate the potential problems.
EXAMPLE: Carol’s Office Olympics
Carol is having a slow day at the office so she has been tossing balls of paper into a nearby bin as a game. Her aim is poor, with only 1 out of 10 balls hitting the bin. Since she thinks she already has a pretty decent throwing arm, slightly increasing her accuracy will make her the cubicle champion. She takes the DMAIC approach, because she is trying to improve on a current process.
First, Carol defines the area in question as well as some goals. For instance, a point wouldn’t count if the paper ball hits the edge of the bin and then falls in. The athletic Carol is aiming for pure net, and any potential missed opportunities will lower her success rate.
Then, she measures the circumference of her paper balls to make sure they are the same size for consistent throwing. She also measures the distance that she throws the paper balls and takes 50 throws, writing down the distance from the bin for each throw to measure overall accuracy.
Carol analyzes the data from 50 throws in a row and sees that she is most successful when she aims from 4 feet away from the bin and angles the bin slightly so that it faces her. She also realizes she can improve paper ball size consistency by using a single sheet for each ball.
She improves upon her process by standing to get more height, flicking her wrist, and striking a 90-degree angle with her elbow. She records the new dataset and compares it with the old one — success! Using her standardized process, her success rate is up from 1/10 to 4/10 paper balls hitting the bin.
Finally, Carol controls the results of the experiment by duct taping her preferred bin to the floor so that her angle will be similar from day to day. She also sets her email notifications on mute so that nothing will distract her from being the Cubicle Champion of Office Olympics.
Six Sigma overlaps with several other management philosophies, such as Lean and TPS (Toyota Production System), and so there are dozens of different tools you can use to analyze your dataset and frame your experimentation. Here are a few of the most popular charts and diagrams for statistical analysis in Six Sigma:
5 Whys — interrogative technique for identifying causes and effects
Variance, regression, and cost-benefit analyses — statistical modeling used for prediction, forecasting, and machine learning applications
Scatter and correlation diagrams — graphs with many points falling along at least two axes
Axiomatic design — matrix-based systematic design
Business Process Mapping — a check sheet for assigned responsibilities
Ishikawa diagram — a “fishbone” style chart outlining causes & effects
Shewhart chart — a process-behavior chart used to determine control levels
CTQ tree — product performance measurement
Design of experiments/stratification — explores analytical scope, extrapolating from different population sizes
Histograms and Pareto chart — diagrams showing both individual and cumulative results possibilities
Quality Function Deployment (QFD) — Japanese methodology of translating customer needs into engineering specifications
Enterprise Feedback Management (EFM) — central management software
SIPOC analysis (Suppliers, Inputs, Process, Outputs, Customers) — a summary table of process inputs and outputs
Taguchi Loss Function — statistically-based robust design graph
Value Stream Mapping — tracks flow of materials in lean production
Bill Smith is known as the “father of Six Sigma.” He joined Motorola as a quality control consultant in 1986 and used what are now Six Sigma methodologies to improve the quality engineering team. Just two years later, Motorola received the coveted Malcolm Baldrige National Quality Award for performance excellence from the president of the United States.
Considering the breadth and innovation of industrial manufacturing today in Industry 4.0, it is impossible to successfully implement a Six Sigma process plan without proper software tools. There are four general categories of software tools, and some software platforms offer all of the following categories in one:
These categories are fairly broad because depending on the type of project at hand, you may need to mix and match several platforms to assemble a full toolkit. If assessing your software needs is too big a hurdle to start with, try outlining your DMADV or DMAIC approach step by step and then add a software platform such as VKS Enterprise that captures and correlates data from your existing ERP system so that everything works smoothly together without tricky architectural fiddling.
Six Sigma is a very popular management philosophy because of the many statistical tools available for analysis. However, there are several criticisms of the Six Sigma philosophy that hold some weight:
Many companies have benefited from the management philosophy of Six Sigma, but there is no scientific or academic proof that a Six Sigma process is always the perfect solution. Because the Six Sigma philosophy is so broad and involves looking at many different steps, it is not clear that whatever problems exist within the business are teased out specifically because of Six Sigma processes. In other words, a Six Sigma approach is a very thorough, analytical approach, but it is not necessarily THE analytical map that will ensure fewer defects per million opportunities.
Another occasional abuse of a Six Sigma plan occurs when the executive team values the planning process more than the intended result. Because Six Sigma has so many offshoots and there are so many technical levels of understanding, it can be tempting to get backlogged in the beginning of the planning stage. Avoid this error by sticking to a DMADV or DMAIC approach and outlining exact steps with their respective analysis charts. Also, avoid complicated jargon when necessary, so that everyone can understand the game plan.
The last step, whether “control” or “verify”, depending on your Six Sigma method, covers a lot of ground—too much to determine future consistency, some experts say. While Six Sigma may be effective at decreasing the DPMO rate in the short term, there is no evidence that that DPMO rate will remain constant into the future.
Motorola was the inventor of the phrase “Six Sigma” but the methodology as a whole has floated around the industrial and manufacturing world since, and there is no single international standard for specific skills training. The largest system that currently exists sells certifications for Six Sigma based on the Judo ranking of colored belts, and while this can be helpful in identifying Six Sigma experts, it can also be a pricey investment that funnels employees through unnecessary skills training.
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