Simulation and Six Sigma are a powerful combination to help process improvers to make informed decisions.
Simulation enables realistic representations of systems to be easily created and tested in a risk-free environment to ensure improvement ideas will eliminate defects, reduce costs and increase profitability.
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:
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.
The dynamic analysis capability of discrete event simulation tools, like SIMUL8, can capture the stochastic behavior of any system. SIMUL8 provides the basic entities and logic to create realistic simulations of any process or manufacturing facility. These core building blocks within SIMUL8 are known as: Start Point, Queue, Activity, Conveyor, Resource, and End Point.
These 6 core building blocks, combined with attributes (Labels) and Logic (Visual Logic) are all that is required for simulating even the most complex of systems. The significant aspects of parts traversing through a facility utilizing machines, resources and material handling systems can all be captured using SIMUL8’s diverse results functionality.
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.
"SIMUL8 has been a valuable application for expanding our range and depth of analytical abilities. It should be considered an important tool in the design of every robust performance improvement program."
Todd S. Roberts MBA, System Director of Operations Improvement, Memorial Health System
This paper explores the success of having managers and key simulation engineers trained with Six Sigma Methodologies to lead the team, keep them focused on the key input factors and reduce the time to reach answers through a ‘Less is More’ approach.
No two days are the same at an airport. Passenger numbers fluctuate, flights get delayed, there's seasonal variation and each airline has its own schedules and policies. Gatwick Airport shortened the check-in process, reduced queue times and improved airline efficiency.
Brian Harrington, a Six Sigma Black Belt with 20 years operations research and simulation experience at Ford Motor Company, discusses why simulation is such a useful tool to ensure the success of a project when time, cost and quality are all competing objectives.