Introduction to Six Sigma

Introduction to Six Sigma

• Six Sigma is a methodology for improving quality, based on the concept of a natural curve introduced by Carl Friedrich Gauss (1777-1855).
• Walter Shewhart used this concept in the 1920s to develop quality control charts.
• The Six Sigma approach was initially developed at Motorola in the 1980s, by Bill Smith, responding to product demand.
• The aim of Six Sigma is to reduce variation in product manufacturing to a level where defects or nonconformities are extremely rare (approximately 3.4 defects per million opportunities).
• This approach was further developed with contributions from Shewhart, Juran, Taguchi, Deming, and Ishikawa, focusing on quality control, total quality management, and zero defects.
• It is notable that Motorola's executive officer, Bob Galvin, played a key role in implementing Six Sigma in the United States.
• Six Sigma spread beyond Motorola to encompass various industries, including Allied Signal, General Electric, Ford, Nissan, and Honeywell, and many others today.
• Companies commonly apply the principles of lean production management alongside Six Sigma.

Historical Implementation of Six Sigma

• There are three levels of Six Sigma application:
  • Level 1 aimed at eliminating defects and reducing variation prevalent in the 1980s (Motorola example).
  • Level 2 focused on cost reduction and performance efficiency activities.
  • Level 3 focused on creating value (General Electric example).

Statistical Background

• Process Sigma (σ): The standard deviation of a process, indicating the degree of variation in data around the mean (μ).
• Population Standard Deviation (σ): A parameter calculated from every individual in the population; a fixed value.
• Sample Standard Deviation (σ): A statistic calculated from a sample of individuals from the population.
• A larger standard deviation means a wider dispersion of data points around the mean.
• Six Sigma aims to reduce process variation to achieve a standard deviation that maintains few defects (< 3.4 DPMO).

Process Sigma Level

• Sigma level, or (Z), measures how far a data point is from the mean by the sigma units.
• The higher the Sigma level, the fewer defects a process produces.
• The goal is to have sigma level at 6 in a process.
• A process considered as capable if Upper Specification Limit (USL), Lower Specification Limit (LSL) have a distance of six standard deviations from the mean (μ), allowing for 99.9999998% of the products to be within the specification limits. This corresponds to 0.002 part per million (ppm) defectives.
• This equates to about 3.4 defects per million opportunities (DPMO).

Six Sigma and Quality Control Charts

• Control Charts: Visual tools used to monitor process behavior and identify whether the process is in statistical control, as developed by Shewhart.
• Different control charts are suited for continuous and discrete data (e.g., x-bar and R charts, p-charts).
• Quality control charts plot data points against control limits, centered on the mean.
• Points outside the control limits suggest the process is not in control, indicative of a potential issue needing investigation.

Mapping Critical Customer Needs to the VOC

• Critical to Quality (CTQ): Customer requirements that are measured, in terms of importance.
• The VOC (Voice of the Customer) can be analyzed to define the CTQ (Critical to Quality) breakdown of customer needs.
• The requirements to satisfy these CTQs are mapped to the inputs/output variables (VOP) of any given process.
• This process of mapping helps to align customer needs with the process.

Defects and Opportunities

• Defect: A flaw, imperfection, or error in a product or process.
• Defect Per Unit (DPU): The average number of defects observed for one unit of production.
• Defects Per Million Opportunities (DPMO): The number of defects per million opportunities related to the production.
• The DPU and DPMO are calculated using data collected from process samples or units to get a snapshot of the process performance and identify problematic or error-prone parts in the process.

Six Sigma and Quality Control Charts

• Control Charts: Monitoring process behavior over time for control, using calculated control limits to help identify issues.

Six Sigma Projects

• Typical projects involve improving specific processes to eliminate defects or increase efficiency, like improving system response time, reducing downtime, or eliminating defects in a manufacturing process.

Six Sigma and Lean

• Lean and Six Sigma are complementary philosophies that focus on efficiency and effectiveness.
• Lean focuses on efficiency by eliminating waste, while Six Sigma focuses on effectiveness by reducing defects.
• A combination of Lean and Six Sigma methodologies is commonly used in many businesses.

Six Sigma Organization and Certification

• Motorola developed a Six Sigma structure and certifications, which can be followed by other organizations.
• Different levels of certification are assigned based on the degree of skills/knowledge for the various roles within the program.