Successful Simulations Using Six Sigma Methodologies

Together, simulation and Six Sigma are a powerful combination to help process improvers to make informed decisions.

Simulation is an ideal tool for Six Sigma projects, enabling realistic representations of systems to be easily created and tested, ensuring improvement ideas will eliminate defects, reduce costs and increase profit.

What is Six Sigma?
Six Sigma is a disciplined, data-driven approach and methodology for eliminating defects in any process – from manufacturing to transactional and from product to service.
The central idea behind Six Sigma is that if you can measure where "defects" (anything that results in customer dissatisfaction) occur in a process, you can systematically understand how to eliminate them and, through a process of continuous improvement, get as close to "zero defects" as possible.
Six Sigma seeks to improve the quality of the output of a process by minimizing variability in manufacturing and business processes. It uses a set of quality management methods, mainly empirical, statistical methods, and creates a special infrastructure of people within the organization who are experts in these methods e.g. Six Sigma Black Belt.
Each Six Sigma project an organization undertakes will follow a defined sequence of steps and has specific value targets, for example to reduce cycle time, decrease costs, improve customer satisfaction, and increase profit.
Six Sigma is divided into two methodologies, DMAIC and DFSS:
  •  DMAIC (Define, Measure, Analyze, Improve, Control) focuses on improving existing processes and performance

  • Design for Six Sigma (DFSS) focuses on generating new processes, products, and services to meet customer needs (CTQ) at the Six Sigma level 

How can simulation support Six Sigma projects?

For a more powerful study and insightful results than static analysis or a mathematical equation, process improvers utilize discrete event simulation (DES).

The statistical rigor available through valid, verifiable simulation and the synergy and capability of simulation software is an ideal fit with both DMAIC and DFSS methodologies.

For example, simulation allows users to compare defects in a Six Sigma analysis process, and even predict six sigma tolerances. Simulation is also capable of measuring financial, operational and customer satisfaction indicators in the same analysis.
Turning static data into a dynamic simulation can help you find the answers to your ‘what if’ scenarios in the planning stage so you can be confident that you are implementing the right process first time.
The dynamic analysis capability of discrete event simulation tools can capture the stochastic behavior of any system. Simulatiom software provides the basic entities and logic to create realistic simulations of any process or manufacturing facility. These core building blocks within process simulation software are known as: Start Point, Queue, Activity, Conveyor, Resource, and End Point.
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