Overview/Description Mapping and measuring your current processes, especially those that are most critical to customers, are important steps in improving them. Mapping a process helps you visualize it - enhancing your understanding of the variables that make it work. The map you create can then be used to measure different parts of the process, assessing their efficiency. This course describes the tools you need to map and measure processes effectively. It demonstrates how to create a process map and outlines steps for measuring your current processes. Target Audience Supervisors, team...

Overview/Description "Measure what is measurable, and make measurable what is not so" said Galileo Galilei, the famous Italian physicist, mathematician, astronomer, and philosopher. Measuring the key characteristics in your current processes is a very significant step in any Six Sigma improvement journey. As such, sample data from existing processes needs to be identified, collected, presented, and analyzed. Collecting data that is correct and useful is one of the first steps in the measurement process. Various types of data exist, and they all need appropriate treatment during the collection...

Overview/Description Design for Six Sigma (DFSS) is often called the future of Six Sigma, as it is emerging as a strategy that better serves the current innovation initiatives of many industries. DFSS uses a "pay me now or pay me later" approach by spending more effort and time on process or product design up front to avoid spending time and effort in those areas later. Whereas Six Sigma just focuses on improving existing designs at a later stage, DFSS focuses on creating new and better products and processes from scratch. It designs virtually error-free products and services from the very...

Overview/Description Six Sigma teams concluding the Analyze phase with a well-understood problem strive in the Improve phase to generate a well-designed solution. Design of experiments (DOE) is a controlled approach to experimentation that enables teams to systematically change the level of one or more input factors and observe the effects on the targeted response. If teams exercise care in choosing the right design – including suitable factors, levels, and responses – their experiments can reveal the precise combination of factors that will optimize the response. Later, that combination...