Leveraging DMAIC for Manufacturing Success

I have been in manufacturing since 1989 after earning my Chemical Engineering Degree. Prior to starting my career with Milliken, I had various jobs and with each job there were opportunities that needed to be addressed. Some were simple issues that required little effort or thought to resolve – it was a ‘just do it’ approach. Some required more thought and other resources to help “figure out” how to resolve the issue. A lot of times the problem was addressed and then re-surfaced, or the solution didn’t work so another solution was tried until the desired result was achieved.

In all my years prior to utilizing DMAIC, there were many commonalities in the approach:

1. No standard approach to solving the problem
2. No metric to determine success of the solution
3. Analysis of the opportunity was relevant to the knowledge and skills of those addressing the opportunity thus leading us to “try things” and see if we were right.
4. No analytical tools were utilized
5. There was never a discussion on how to prevent the opportunity from reoccurring.

We knew we were going to see this failure again, but we were ready for it because we learned how to fix it.  Thus, we lived in a world of perpetual opportunities, repeating the same failures over and over, but we were faster at resolving them. Unfortunately, a business cannot survive with perpetual failures: it must pursue a culture change toward continuous process improvement.

What is DMAIC?

DMAIC is an acronym for Define, Measure, Analyze, Improve and Control. The DMAIC process is structured to methodically step a team through a problem to the true root causes, ideal solution or improvement and create a process to control or prevent reoccurrence of the problem. Using DMAIC in manufacturing allows manufacturing teams to focus on the next problem knowing the failure will not return, getting them closer to operational excellence. The prevention of reoccurrence is the keystone to a successful continuous improvement culture and in seeing a significant increase in business performance. Let’s take a look at each step in the process.

Define

Define is the first step of the entire process. The problem or opportunity that may be causing poor performance is defined by the data. Statistical Process Control trends can indicate an opportunity; loss analysis and stratification of data can direct an operation to a large problem, analysis of cost data can indicate excessive spending, in most or all cases there are repeating occurrences because cause and solution are unknown.  When the problem is defined, the boundary areas and scope of work for the team are established.  Team members are selected, and meeting mechanics created.

Measure

Two things happen in the measure phase:

1. Metrics for the project are established using baseline data and targets are set for the project metrics. Setting a target depends on scope of work and the expectations to affect the overall critical operational metrics.    Let’s say a manufacturing plant has a goal of reducing machine breakdowns by 25%. This is considered a large scope of work challenge. This can be a huge expectation if the plant has many breakdowns. To get to a 25% reduction, every historical breakdown can’t be addressed with an expectation to reduce each occurrence by 25%.  The team must find manageable projects based on the data and keep the scope small enough to complete a project within 90 days. With this approach to mathematically hit the plant target of reduction; the projects will need aggressive targets and should be determined based on the project plans to hit the plant target. The team may need 8 projects that have targets of 80% improvement and if these project targets are met the plant target can be met.
2. Additional data may be needed to better understand the problem. This will require a process for data collection involving people and equipment. Both need to be calibrated. People need to understand the expectation and align on clearly written operational definitions. Equipment will need to be calibrated to ensure the data is accurate.
   
   

Analyze

We analyze the data to tell us where to focus.  When the product or equipment doesn’t perform one of the 6Ms; huMan, Method, Machine, Measure, Mother Nature and Material, are. In the analyze step, we will identify the issues that “drive the problem”.

Problem: Drive Belt is wearing faster than its historical life. There can be multiple drivers to this problem and they can be within any of the 6M’s.

Possible Drivers to this problem include:

• Method – Inadequate procedure to teach alignment.
• Machine – Bent shaft, Worn Drive pulley, etc.
• Material – Belt Material is inadequate
  
  

These must be prioritized and focus on eliminating them as drivers. If you find a driver needs focus, then begin the root cause analysis. This provides the greatest opportunity for improvements in a timely manner providing a positive benefit versus effort balance.  For example, if you find a bent shaft – why is the shaft bent? How can this happen? It takes a great force to bend a shaft – what is the cause? With the true root cause identified, the team will determine the ideal countermeasure.

Improve

When the true root cause is identified, the team must determine the appropriate countermeasures or solutions to eliminate the Issue. Sometimes the countermeasures are as simple as improving a procedure, adding an inspection to a Preventative Maintenance check, or implementing an operator check to ensure compliance to the expected condition of the equipment or process. Other times an equipment redesign is needed.   When a countermeasure is implemented everyone must be trained and educated to ensure understanding and adherence.

Control

Control is the keystone to preventing re-occurrence of the problem.  This requires discipline and a change in the way people manage. Checks must be put in place to ensure the equipment or process stays within the new operating requirements delivering the improvement. Teams verify measurable improvement and determine if the improvements implemented have achieved the project goals. Standard Work documentation must be updated and integrate the lessons that have been learned.

The DMAIC methodology is a five-step process that focuses on improving quality while minimizing defects in a process. It provides a standardized process that delivers effective results and providing manufacturing success. This tool can and should be taught to everyone within a manufacturing plant to turn all employees into systematic problem-solvers that eliminate issues and deliver results.