The Six Sigma DMAIC method (define, measure, analyse, improve, and control) is a data-driven quality improvement strategy. It is a critical component of a Six Sigma project, but it can also be used as a stand-alone quality improvement technique or as part of other process improvement projects like lean.
5S: The Five S’s of lean is a concept that helps eliminate waste and increase by establishing a clean, uncluttered, safe, and well-lit workplace, you can increase productivity. It’s intended to aid in the creation of a healthy and productive work environment. Any work area that may benefit from visual control and lean production can benefit from the 5S philosophy.
There are seven types of garbage: Overproduction ahead of demand; waiting for the following process, worker, material, or equipment; unnecessary transport of materials; over-processing of parts due to poor tool and product design; inventories greater than the bare minimum; excessive movement by employees during their work; and production of defective parts are all examples of waste.
Value stream mapping (VSM) is a two-stage tool that involves pencil and paper. First, trace a product’s production path from start to finish, drawing a visual depiction of each material and information flow process. Second, make a map of how value should move in the future. The map of the future state is the most significant.
Six Sigma Method-Flow: Flow is the continuous completion of tasks along the value stream, ensuring that a product moves from design to launch, order to delivery, and raw to finished materials in the hands of the customer with no delays, scrap, or backflows.
A visual workplace comprises technologies that visually share information about organisational processes to make human and machine performance safer, more precise, repeatable, and reliable.
Six Sigma Method-Customer voice:
Quality function deployment (QFD) begins with a thorough examination and understanding of customer requirements. The initial stage is to record the customer’s agent (VOC), followed by creating a customer voice table (VOCT). Sales and technical trip reports, warranty claims, user support forums or helplines, and social media are all familiar places to look for information.
Project management tools like Gantt charts, as well as team engagement methods like brainstorming and nominal group approach, are used by Six Sigma team leaders.
However, most organisations that adopted TQM (or CQI) by the mid-1990s had run out of “low hanging fruit.” The problems that needed attention didn’t lend themselves to simple data analysis and required more resources and time than what was considered reasonable participation in TQM (or CQI) process improvement initiatives. As a result, TQM (or CQI) projects could no longer deliver significant business returns, and organisational commitment to these initiatives waned.
Meanwhile, the Six Sigma management system grew and thrived, from its inception by Motorola in the mid-1980s to its publicly publicised adoption by GE in 1992 and subsequent adoption by a slew of other major firms. The Six Sigma technique appeared to be the natural next step. It addressed the shortcomings of TQM (or CQI) by adding financial results in measurements, employing more advanced data analysis tools, and employing project selection, evaluation, and related project management methodology and tools.
The quantified financial results secured senior executives’ continued commitment to the effort. In addition to the essential analytical tools of TQM (or CQI), sophisticated data analysis methods, Quality function deployment (QFD), design of experiments (DOE), and failure mechanism and effect analysis are just a few examples (FMEA),
and regression analysis focused on customer issues.
To ensure adequately analysed problems.
Six Sigma projects: are completed thanks to the project-driven organisational structure and the application of tools for project selection, evaluation, and management.
As a result, the Six Sigma management method is as follows:
TQM (or CQI) + Customer Focus + Additional Data Analysis Tools + Financial Results + Project Management = Six Sigma.
German mathematician Carl Friedrich Gauss (1777–1855). This pattern got discovered to apply to a wide range of physical and process features. As a result, it’s a common underlying assumption for measurements of various approaches.
The Normal Distribution shows that a process has a lot of observations near its mean (average) and fewer observations as we travel further away from it. It means that about 68 per cent of statements in a process are within one standard deviation (one sigma) of the mean in each direction. Approximately 95% per cent are within two standard deviations (two sigmas) in each order from the norm. About 99.7% are within three standard deviations (thee sigma) in each direction from the mean (Exhibit 1).
Dr Walter A. Shewhart of Bell Labs created the Statistical Quality Control Theory. He wrote Economic Control of Quality of Manufactured Product, published in 1931. He expanded on it in his book Statistical Method from the Viewpoint of Quality Control, published in 1939, with W. Edwards Deming’s editorial aid.
Dr W. A. Shewhart developed quality control charts to show how a process characteristic changes over time. On the graph, observations, or sample means, are plotted. The data’s mean is the chart’s Centerline (CL), three standard deviations above the mean is the Upper Control Limit (UCL), and three standard deviations below the mean are the Lower Control Limit (LCL). JK Michaels Institute offers Lean Six Sigma Certification Course like IASSC Lean Six Sigma Black Belt and IASSC Lean Six Sigma Green Belt.