Lean Six Sigma and Continuous Improvement

The concept of Lean Six Sigma Continuous Improvement emerged in the post-war era of the late ’50s and is commonly attributed to companies such as Toyota and Motorola. They implemented it on their assembly line to reduce wastage, increase efficiency and enhance the quality of products. A similar concept of Total Quality Management was practiced in the industries even then. Still, it is essential to understand the difference between the two and the unique purpose of each of these methodologies. 

Both Traditional Quality Programs (such as TQM) and Continuous Improvement Six Sigma methods strive to reduce process defects, make the process more efficient, improve customer satisfaction, and increase profits. However, quality programs are designed and implemented to achieve a specific goal. 

They either run forever to achieve a specific target or achieve the target and then reset for a new target. For example, a traditional quality program could reduce oil leakage in the high-pressure pipeline of a 3,000CC IC engine from 1 failure in 1,000 engines to 1 failure in 1,000,000 engines. So, this program will run till this target is achieved, and a new target will be set for another issue, such as defects in the paint shop.

 On the other hand, Lean Six Sigma and Continuous Improvement seek to imbibe a culture of continuous improvement and let organizations enact small and significant enhancements that drastically impact the cost, profits, and efficiencies. Six Sigma does work for milestones of each project, but the projects form a part of the overall culture of improvement. They are never considered ‘complete.’ Six Sigma and continuous improvement methodology create checks and tactics so that controls are installed even after a project is complete to ensure that the improvement continues. It is not possible to return to old ways.

Once specific project parameters are defined, the Six Sigma quality improvement process applies statistical analysis to define, measure, analyze, verify and control functions (called the DMAIC model). The process of DMAIC gives enough inputs to a team for plotting them on a graph we call the Normal Distribution curve. We know that the Normal Distribution curve is just one of the several possible probability distribution models but is the one that follows the Central Limit Theorem and is widely applicable almost everywhere.

Start Your Six Sigma Training

Deming’s PDCA cycle of Six Sigma and Continuous Improvement:  

During the late 60s, two renowned scholars in statistical Six Sigma were Walter Shewhart and W. Edwards Deming. Shewhart’s contributions to quality are many, but the two ideas that brought about drastic and remarkable changes in lean six Sigma and continuous improvement were:

  1. He created a model that could closely relate sigma levels with quality (as shown in the Normal Distribution Curve below). He defined a process in need of correction as performing at a three-sigma level- approximately 68.26%. In the manufacturing industry, this model is widely used to understand the state of the process at any point in time and take actions accordingly. Looking at the shape of the graph, defects and costs increase drastically as the sigma level decreases. 
  1. Shewhart is also considered the father of control charts. Using the model of the distribution curve, he plotted a control chart with two sigmas, four sigmas, and six sigmas of defined control limits above or below which the probability of a process deviating from its mean is so less that it must be implied that the process has deviated and is producing defects. The production managers and development engineers then stop the production and start it only after the root cause of the fault has been found and resolved. A sample of Shewhart’s control chart is present below: 

Deming’s work focuses on the idea of the PDCA cycle and finds application across a wide range of industries, including the service industry, IT, hospitality business, and consulting. That idea is that improvement comes when a team recognizes a need for change and makes a plan to bring about the progress. 

When should the PDCA model of the Six Sigma quality improvement process be used?

  • When starting a new improvement project
  • Developing a new design or editing the existing design of a process, part, or service
  • Defining an already standardized and repetitive process.
  • Implementing any engineering change in the existing product
  • Working for continuous and everlasting improvements

Start Your Six Sigma Training

The Plan-Do-Check-Act procedure

Plan: In this step, the team recognizes an opportunity for improvement and plans an appropriate action for it.

Do: After the plan has been laid down, the second step is to act upon the problem and implement the solution as planned in stage-1

Check: During this phase, the data and results collected from the Do phase are evaluated. This data is then compared with the existing results, and any similarities, differences, or irregularities are marked. The testing procedures are also assessed to ensure that the testing has been carried out with precision and calibration. A good strategy, in this case, would be to test multiple times and then plot them all on a typical graph, and such activity will highlight irregularities and trends with more precision.

Act: Sometimes also termed as ‘Adjust phase,’ this is the phase in which the process is improved. The results from the ‘Do phase’ and the ‘Check phase’ are evaluated and studied to find the root cause of a non-conformity or defect or any other issue because of which the performance of a process is less-than-optimal. Further, improvements are carried out in steps, and their results are rechecked to find whether the process has improved or not.

The PDCA model of continuous improvement has become so widely accepted across all industries that there are jobs for which the essential requirement is a PDCA Six Sigma certification. Arrowhead Six Sigma training & consulting firm in Mumbai, India offers certification programs, and one must go for them.