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Six Sigma

Six Sigma
The common Six Sigma symbol Six Sigma is a set of techniques and tools for process improvement. It was developed by Motorola in 1986.[1][2] Jack Welch made it central to his business strategy at General Electric in 1995.[3] Today, it is used in many industrial sectors.[4] Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and 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 ("Champions", "Black Belts", "Green Belts", "Yellow Belts", etc.) who are experts in these methods. Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified value targets, for example: reduce process cycle time, reduce pollution, reduce costs, increase customer satisfaction, and increase profits. Doctrine[edit] Methodologies[edit]

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Lean manufacturing Overview[edit] The difference between these two approaches is not the goal itself, but rather the prime approach to achieving it. The implementation of smooth flow exposes quality problems that already existed, and thus waste reduction naturally happens as a consequence. The advantage claimed for this approach is that it naturally takes a system-wide perspective, whereas a waste focus sometimes wrongly assumes this perspective. Both lean and TPS can be seen as a loosely connected set of potentially competing principles whose goal is cost reduction by the elimination of waste.[5] These principles include: Pull processing, Perfect first-time quality, Waste minimization, Continuous improvement, Flexibility, Building and maintaining a long term relationship with suppliers, Autonomation, Load leveling and Production flow and Visual control.

Ishikawa diagram Ishikawa diagrams (also called fishbone diagrams, herringbone diagrams, cause-and-effect diagrams, or Fishikawa) are causal diagrams created by Kaoru Ishikawa (1968) that show the causes of a specific event.[1][2] Common uses of the Ishikawa diagram are product design and quality defect prevention, to identify potential factors causing an overall effect. Each cause or reason for imperfection is a source of variation. Causes are usually grouped into major categories to identify these sources of variation. The categories typically include: Overview[edit] Ishikawa diagram, in fishbone shape, showing factors of Equipment, Process, People, Materials, Environment and Management, all affecting the overall problem.

The Mojo Collaborative Complex Challenges – Community Co-creation - Everyday Leadership & Teamwork Agile embodies a simple yet incredibly powerful set of principles and practices that help teams collaborative effectively and deliver successfully on complex projects. Progress is delivered in short cycles, enabling fast feedback, continual improvement, and rapid adaptation to change. As the leading Agile development framework, Scrum has predominantly been used for software development, but it is also proving to be effective in efforts far beyond (Source: Scrum Alliance) Agile beyond Software: Mojo Collaborative is busting these awesome practices out of the silo of software development and into a bigger world: Communities, classrooms, governments, and all areas of our workplaces where we can benefit from empowered teams, clear goals, adaptability, and effective and transparent teamwork!

Binomial Distribution To understand binomial distributions and binomial probability, it helps to understand binomial experiments and some associated notation; so we cover those topics first. Binomial Experiment A binomial experiment (also known as a Bernoulli trial) is a statistical experiment that has the following properties: The experiment consists of n repeated trials.

Minitab Minitab is a statistics package developed at the Pennsylvania State University by researchers Barbara F. Ryan, Thomas A. Ryan, Jr., and Brian L. Joiner in 1972. Minitab began as a light version of OMNITAB, a statistical analysis program by NIST; the documentation for OMNITAB was published 1986, and there has been no significant development since then.[2] Minitab is distributed by Minitab Inc, a privately owned company headquartered in State College, Pennsylvania, with subsidiaries in Coventry, England (Minitab Ltd.), Paris, France (Minitab SARL) and Sydney, Australia (Minitab Pty.). Total quality management Total quality management (TQM) consists of organization-wide efforts to install and make permanent a climate in which an organization continuously improves its ability to deliver high-quality products and services to customers. While there is no widely agreed-upon approach, TQM efforts typically draw heavily on the previously-developed tools and techniques of quality control. TQM enjoyed widespread attention during the late 1980s and early 1990s before being overshadowed by ISO 9000, Lean manufacturing, and Six Sigma. History[edit] In the late 1970s and early 1980s, the developed countries of North America and Western Europe suffered economically in the face of stiff competition from Japan's ability to produce high-quality goods at competitive cost.

Customer lifetime value In marketing, customer lifetime value (CLV) (or often CLTV), lifetime customer value (LCV), or user lifetime value (LTV) is a prediction of the net profit attributed to the entire future relationship with a customer. The prediction model can have varying levels of sophistication and accuracy, ranging from a crude heuristic to the use of complex predictive analytics techniques. One of the first accounts of the term Customer Lifetime Value is in the 1988 book Database Marketing, which includes detailed worked examples.[2] Purpose[edit]

WATERFALL vs. AGILE METHODOLOGY « Agile Introduction For Dummies There is no IT meeting that does not talk and debate endlessly about Waterfall vs. Agile development methodologies. Feelings run strong on the subject with many considering Agile ‘so of the moment’, just so right, while Waterfall is thought to be passé! But, before deciding which is more appropriate, it is essentially important to provide a little background on both. Waterfall A classically linear and sequential approach to software design and systems development, each waterfall stage is assigned to a separate team to ensure greater project and deadline control, important for on-time project delivery. Sampling Distribution Suppose that we draw all possible samples of size n from a given population. Suppose further that we compute a statistic (e.g., a mean, proportion, standard deviation) for each sample. The probability distribution of this statistic is called a sampling distribution. Variability of a Sampling Distribution

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