Six Sigma Introduction

Introduction:

SIX SIGMA is a type of best management strategy, which is developed by MOTOROLA basically in 1981 USA.It is a problem solving strategy by which we studied about how to increase our maximization  profit with in low capital.

 

Six sigma:

Six sigma is defined as a method for problem solving.

It is perhaps true that the main benefits of six sigma are:

 (1)The method slows people down when they solve problems, preventing them from prematurely jumping to poor recommendations that lose money; and

 (2)Six sigma forces people to evaluate quantitatively and carefully their proposed recommendations. These evaluations can aid by encouraging adoption of project results and in the assignment of credit to participants.

a)      ” Many of these sub-methods fall under the headings “statistical quality control” (SQC) and “design of experiments” (DOE), which, in turn, are associated with systems engineering and statistics.

b)      “Experts” often complain that opportunities to use these methods are being missed.

c)       Former General Electric CEO Jack Welch, e.g., wrote that six sigma is relevant in any type of organization from finance to manufacturing to healthcare.

d)      When there are “routine, relatively simple, repetitive tasks,” six sigma can help improve performance, or if there are “large, complex projects,” six sigma can help them go right the first time (Welch and Welch 2005).

e)      However, it is often easy to apply methods competently, i.e., with an awareness of the intentions of methods’ designers. Also, competent application generally increases the chance of achieving positive outcomes. Wisdom about how to use the methods can prevent over-use, which can occur when people apply methods that will not likely repay the associated investment.

f)       In some cases, the methods are incorrectly used as a substitute for rigorous thinking with subject-matter knowledge, or without properly consulting a subject-matter expert.

g)      These choices can cause the method applications to fail to return on the associated investments.

h)      Several terms are defined in relation to generic systems. These definitions emphasize the diversity of the possible application areas.

 

Systems and Key Input Variables:

a)      We define a “system” as an entity with “input variables” and “output variables.” Also, we use “factors” synonymously with input variables and denote them x₁… xm.

b)      All inputs must conceivably be directly controllable by some potential participant on a project team. We use responses synonymously with output variables and denote them y₁… yq.

a)      Assume that every system of interest is associated with at least one output variable of prime interest to you or your team in relation to the effects of input variable changes. We will call this variable a “key output variable” (KOV). Often, this will be the monetary contribution of the system to some entity’s profits. Other KOV are variables that are believed to have a reasonably strong predictive relationship with at least one other already established KOV. For example, the most important KOV could be an average of other KOVs.

b)      “Key input variables” (KIVs) are directly controllable by team members, and when they are changed, these changes will likely affect at least one key output variable. We omit the word “process” because sometimes the system of interest is a product design and not a process. Therefore, the term “process” can be misleading.