Define, Measure, Analyze, Improve, Control
Originally developed as part of the Six Sigma framework, DMAIC is a proven approach for eliminating defects and improving quality-related business metrics. DMAIC and Lean (the combined methodologies are known as Lean Six Sigma) complement each other and are the foundation for continuous improvement in most companies.
The DMAIC approach is really very simple and practical: Define your problem, Measure where you are and where you want to go, Analyze data to understand the problem, Improve or eliminate the underlying causes, and Control the process for the long run.
The “D” (Define) in DMAIC is focused on selecting high-payback projects and identifying the underlying metric(s) that will reflect project success.
In some cases, the underlying metric will be a performance measure, as in the example to the right, where warranty rates for a specific product line are being addressed.
In other cases, the leadership team may already know that poor performance on a particular CTQ must be addressed, and achieving defect-free performance on that CTQ would be the team’s goal. In cases like this, the sigma level (a measure of process capability, see more below) would likely be the underlying metric.
A common deliverable for the Define phase is a team charter to be reviewed and updated with the leadership team.
The Define phase is arguably the most important since it commits our limited resources.
“M” (Measure) is about documenting the current process, validating how it is measured, and assessing baseline performance. Important tools in this phase often include trend charts, Pareto charts, process flowcharts, Gage R&R, and process capability measurement (sigma level, also referred to as process sigma).
A key deliverable for the Measure phase is the baseline (historical) sigma level.
A process with six sigma capability has a theoretical long-term defect rate of 3 parts per million (considered defect-free in most industries). A sigma conversion chart is a handy reference for relating various sigma levels their corresponding defect rates.
The Analyze phase isolates the top causes behind the metric or CTQ that the team is focused on. In most cases there will be no more than three causes (more likely one or two) that must be controlled in order to achieve success – if too many causes are identified, then the team has either not isolated the primary cause or the project goal is too ambitious to achieve success with a single project.
There are always exceptions, but speed and results are key ingredients to building Six Sigma momentum inside an organization, and projects should be sized to assure team success and project closure inside reasonable time limits.
The Analyze phase deploys a number of tools for collecting team input and conducting objective experiments to identify and confirm top causes.
# 4 Improve
The Improve phase focuses on fully understanding the top causes identified in the Analyze phase, with the intent of either controlling or eliminating those causes to achieve breakthrough performance. The overall theme for the Improve phase is process or product redesign, and the following Six Sigma tools are commonly used in this phase –
- Regression Analysis
- Hypothesis Testing
- Design of Experiments (DOE)
- Analysis of Variance (ANOVA)
The Improve phase often includes a limited production trial (or beta test for non-manufacturing projects) that demonstrates a significantly improved sigma level prior to moving into the Control phase.
DMAIC’s Control phase is about sustaining the changes made in the Improve phase.
The best controls are those that require no monitoring (irreversible product or process changes).
Oftentimes there are process settings, setup procedures, etc., requiring that employees follow specific requirements in daily operations – these items are typically documented in a control plan. In cases like this the team should do everything possible to error-proof the process, and should then add the appropriate checks and balances to the quality system for the long run.
A process improvement team in a furniture manufacturing business was tasked with improving the warranty rate for a product line known as Cedar Essentials. The 2.6% baseline warranty rate for Cedar Essentials was well above the 1.9% average for the overall business, and the team’s goal was to reduce the rate to 1.4%.
The team produced a project charter that summarized the scope, opportunity areas, status, and pending/completed actions –
Note – while it is common to express a failure rate in terms of its corresponding sigma level, high-level metrics like warranty rates are typically not expressed this way, so the baseline and goal performance levels are expressed as simple percentages in the above charter.
In the Measure phase, the team created a historical warranty trend chart for Cedar Essentials, and generated top-level Pareto charts using existing data from the Returns Processing Center.
- The Pareto by Product Family showed that the Adirondack Chair line (AD Chairs) had a very high warranty rate at 5%.
- The Pareto by Sales Location showed that Direct-Ship products (across all product families) had an extremely high warranty rate at 7%.
Knowing that the AD Chair product line would receive plenty of focus, the team put together a process flowchart showing the assembly process. The process flowcharting exercise was very helpful in getting everyone on the same page regarding how the chairs were assembled, inspected, and packaged.
Based on the initial data gathered above, the team decided to conduct a root cause analysis on (1) returned AD Chairs and (2) returned direct-ship products. At this point in the project, the team had to generate their own meaningful data by evaluating customer returns at the Returns Process Center. Knowledgeable R&D team members were included in this exercise.
The field failure analysis produced the following results –
- Shipping damage was the biggest reason for direct-ship returns (and the #2 reason for AD Chair returns), mostly due to corner damage. The packaging was simply not designed to handle the rigors of direct shipping to customers, and the packaging engineer (who was present during the failure analysis session) was ready with a proposed solution.
- Missing hardware was the #2 return reason for both AD Chairs and direct-ship returns.
- The biggest failure mode on the AD Chair line was cracked back-slats, making up 34% of all AD Chair returns. It appeared to the R&D team members that the screws holding the slats in place had been over-torqued in the assembly processes.
At this point in the project, the team began working three improvement projects in parallel, two of which were easily implemented –
- Corner protectors were added to all direct-ship packaging. Before releasing the new corner protectors into production, the packaging engineer conducted extensive use-testing that showed an 83% improvement rate, which turned out to be 92% in reality.
- The hardware packaging operation was improved by changing the standard work method on the assembly line. The new standard work required that all hardware items be loaded into a tray that contained recesses for each piece of hardware. Once the tray was fully loaded, the hardware was then dumped into a plastic bag and sealed for shipment. Again, a validation study was conducted, and the short-term sigma level for missing hardware went from 3.9 (8,198 PPM) to 5.4 (48 PPM) as a result of this change.
The third major failure mode, cracked back-slats on the AD Chair line, became its own Six Sigma project since a solution was not readily apparent. The CTQ for this project was the torque applied to the back-slat screws during the assembly process, and the team was able to achieve six sigma capability on this process by upgrading from a pneumatic screwdriver to an electric screwdriver with closed-loop torque feedback.
The team implemented the following changes in the Control phase:
- A dock-audit inspection point was added to the quality plan, verifying that the corner protectors were in place.
- A process audit inspection point was added to ensure that the standard work for the new hardware packaging method was being followed.
- The new assembly screwdriver was added to the plant’s gage calibration system per the manufacturer’s recommendation, and the standard work was updated to require a calibration on the assembly line at the start of each shift.
Through the above projects and a second round of DMAIC work (and two additional fixes), the team reduced the Cedar Essentials warranty rate to 1.2%, saving just over $250K per year and eliminating the customer dissatisfaction issues associated with shipping damage, cracked back-slats, and missing hardware.
- DMAIC Applied to Risk Reduction: This is a case study/webinar presentation showing how DMAIC and PFMEA tools are combined to measure and reduce risk at a chemical manufacturer.
- Project Charter
- Trend and Pareto Charts
- Flow Chart
- Flow Chart Symbol Definitions
- DMAIC Deliverables – Training File