Statistic Methods: Utilizing Six Sigma

The term Six Sigma (6σ) was initially used as a measure of operational evaluation or quality. In Six Sigma, the process goal is set at 1 part per million (PPM) in each part of the manufacturing process. Beginning with that source, Six Sigma has now evolved into a program that enhances organizational capabilities and efficiency, focusing on productivity, price declines and quality. Six Sigma employs a rigorous data-driven approach to eliminate defects in all business areas while managing management, service delivery, design, manufacturing, and customer satisfaction while emphasizing breakthrough work Fixed and quantifiable management discipline to use.

Six Sigma is a statistical tool and technology system focused on eliminating defects and reducing process changes. The Six Sigma process includes measurement, improvement and verification activities. The name or name of Six Sigma relates to the relationship between the number of defects per million opportunities and the standard deviation number found in process specifications. In statistics, Sigma is a reference to the section below the normal or "Gaussian" curve. Each interval is equal to one standard deviation or sigma. Therefore, Six Sigma means the positive and negative 3 sigma of the mean value of the data under the curve. For a normal distribution, 68.26% of the data points are within the range of the average positive and negative sigma, 95.46% are within 2 sigma and 99.73% are within 3 sigma. Process variations above ± 3 sigma should be improved

If you are looking for new technology, please do not mind. The magic of Six Sigma is not the glare of statistics or high technology. Six Sigma relies on a proven genuine way that has existed for decades. In fact, Six Sigma abandoned the complexity of Total Quality Management (TQM). According to expert statistics, there are over 400 TQM tools and technologies. Six Sigma employs several methods trained to apply a small group of internal technology leaders called Six Sigma Black Belt with advanced technology, but these tools have a simple performance as DMAIC or definition Applied to improved models - Measurement - Analysis - Improvement - Control. The DMAIC can be explained as follows.

Six Sigma: Many people say TQM has evolved into Six Sigma. The intention of Six Sigma is a business process without errors. Six Sigma is a data driven approach that focuses on reducing variability to eliminate defects within the process. Like BPR, Six Sigma does not need to question the current way of working. However, Six Sigma uses the "adjustment and maintenance" five-step approach to identify the root cause and does not completely redesign the process like BPR. Lean: Lean is also based on the idea of ​​eliminating waste. Lean organizations can eliminate additional management and bring everyone closer to the process. In addition, lean has analytical instructions, each step is fully evaluated. We keep only the value added step. Lean is similar to BPR, but it can achieve results very quickly. They are very different, but lean does not start from the beginning like BPR.