Six Sigma

Six Sigma

Basics: Six Sigma is a business management strategy originally developed by Motorola, USA in 1981. As of 2010 it is widely used in many sectors of industry Basics A new way of doing business Wise application of statistical tools within a structured methodology . Six Sigma originated as a set of practices designed to improve manufacturing processes and eliminate defects.

Six sigma quality:-A high level of quality associated with approximately 3.4 defective parts per million

Consider a 99% quality level: Consider a 99% quality level 5000 incorrect surgical operations per week! 200,000 wrong drug prescriptions per year! 2 crash landings at most major airports each day! 20,000 lost articles of mail per hour!

Improvement cycle :

Improvement cycle PDCA cycle Plan Do Check Act

Six Sigma Stages:

Executive Leadership:- includes the CEO and other members of top management. They are responsible for setting up a vision for Six Sigma implementation. They also empower the other role holders with the freedom and resources to explore new ideas for breakthrough improvements.

Champions :-take responsibility for Six Sigma implementation across the organization in an integrated manner.

Master Black Belts:-identified by champions, act as in-house .

Black Belts :-operate under Master Black Belts to apply Six Sigma methodology to specific projects.

Green Belts:- are the employees who take up Six Sigma implementation along with their other job responsibilities, operating under the guidance of Black Belts.

Statistical Process Control

Capability analysis

What is the currently "inherent" capability of my process when

it is "in control"?

Conformance analysis

SPC charts identify when control has likely been lost and

assignable cause  variation has occurred

Investigate for assignable cause

Find Root Cause(s) of Potential Loss of Statistical Control

Eliminate or replicate assignable cause

Need Corrective Action To Move Forward

For example, if a product must have a thickness between 10.32 and 10.38 inches to meet customer requirements, then the process mean should be around 10.35, with a standard deviation less than 0.005 (10.38 would be 6 standard deviations away from 10.35), assuming a normal distribution.

Six Sigma can also be thought of as a measure of process performance, with Six Sigma being the goal, based on the defects per million. Once the current performance of the process is measured, the goal is to continually improve the sigma level striving towards 6 sigma. Even if the improvements do not reach 6 sigma, the improvements made from 3 sigma to 4 sigma to 5 sigma will still reduce costs and increase customer satisfaction.

Robust design include umbrella fabric that will not deteriorate when exposed to varying environments (external variation), food products that have long shelf lives (internal variation), and replacement parts that will fit properly (unit to unit variation).

Robust design has many advantages. For one, the effect of robustness on quality is great. Robustness reduces variation in parts by reducing the effects of uncontrollable variation. More consistent parts equals better quality.

Another advantage is that lower quality parts or parts with higher tolerances can be used and a quality product can still be made. This saves the company money, because the less variable the parts can be the more they cost.

A third advantage is that the product will have more appeal to the customer. Customers demand a robust product that won't be as vulnerable to deterioration and can be used in a variety of situations.

This method is also good, because you are designing the robustness into the product and process instead of trying to fix variation problem after they occur.

Robust Design method, also called the Taguchi Method, pioneered by Dr. Genichi Taguchi, greatly improves engineering productivity. ... Robust Design focuses on improving the fundamental function of the product or process, thus facilitating flexible designs and concurrent engineering.

In statistics, the term robust or robustness refers to the strength of a statistical model, tests, and procedures according to the specific conditions of the statistical analysis a study hopes to achieve. ... In other words, a robust statistic is resistant to errors in the results.

In Dynamic problems, the optimization is achieved by using 2 Signal-to-Noise ratios - Slope and Linearity. Taguchi Method is a process/product optimization method that is based on 8-steps of planning, conducting and evaluating results of matrix experiments to determine the best levels of control factors.