iSixSigma-Editorial

Six Sigma Qualtec Introduces SixNet Version 2.7; Intelligence System Gives Users Unprecedented Flexibility In Tracking Progress, Results

GE Healthcare And Virtua Health Collaborate To Redefine 21st Century Patient Care Delivery

North Shore-Long Island Jewish Health System Gaining Ground Through Partnership With GE Healthcare At Two-Year Mark, Achievements are Multiplying Across the Enterprise

Is Six Sigma just a fad – another flavor-of-the-month initiative that will blow over in a few years? Without proper leadership, what is labeled Six Sigma in some organizations may indeed fall by the wayside. However, done right, the tools, methods and culture that are true Six Sigma will be here for decades to come. And […]

Up Close and Personal With Six Sigma

iSixSigma’s 2004 Salary Survey for Six Sigma Professionals has two unique perspectives. First, the survey provides a global view. Second, unlike other quality salary surveys, this one is focused as specifically as possible on Six Sigma professionals. By Matthew LeVeque, iSixSigma Senior Contributing Writer During the past 10 years Six Sigma has become one of […]

Ultimately, the result of using Lean Six Sigma is improved efficiency within the company and a higher quality product or service for the customer. But there are some additional ways your company can benefit.

Control Chart Wizard – p-Chart: Control charts dealing with the proportion or fraction of defective product are called p charts (for proportion). There is a difference between a defect and defective, as there is between a nonconformity and nonconforming unit. The p-chart control chart is used with discrete/attribute defective data when the sample size is greater than 50. The sample size may vary.

Steps in Constructing an np-Chart: The np Chart can be used for the special case when the subgroups are of equal size. Then it is not necessary to convert nonconforming counts into the proportions phat(i). Rather, one can directly plot the counts x(i) versus the subgroup number i.

Control Chart Wizard – np-Chart: The np control chart are used to monitor the number of nonconforming units in samples of inspected units. A nonconforming unit is a product which fails to meet at least one specified requirement. There is a difference between a defect and defective, as there is between a nonconformity and nonconforming unit. The np-chart control chart is used with discrete/attribute defective data when the sample size is greater than 50. The sample size must be constant; this control chart is only valid if data is collected in same-size subgroups.

Control Chart Wizard – Discrete Defective Data: How large is your discrete/attribute defective data sample size?

Control Chart Wizard – Discrete Defective Data: How large is your discrete/attribute defective data sample size?

Steps in Constructing a u-Chart: The u Chart is used when it is not possible to have an inspection unit of a fixed size (e.g., 12 defects counted in one square foot), rather the number of nonconformities is per inspection unit where the inspection unit may not be exactly one square foot…it may be an intact panel or other object, different in sizethan exactly one square foot. When it is converted into a ratio per square foot, or some other measure, it may be controlled with a u chart. Notice that the number no longer has to be integer as with the c chart.

Control Chart Wizard – u-Chart: Control charts dealing with the number of defects or nonconformities over time are called u charts. There is a difference between a defect and defective, as there is between a nonconformity and nonconforming unit. The u-chart control chart is used with discrete/attribute defect data when the sample size varies.

Steps in Constructing a c-Chart: The c Chart measures the number of nonconformities per “unit” and is denoted by c. This “unit” is commonly referred to as an inspection unit and may be “per day” or “per square foot” of some other predetermined sensible rate.

Control Chart Wizard – c-Chart: Control charts dealing with the number of defects or nonconformities are called c charts (for count). There is a difference between a defect and defective, as there is between a nonconformity and nonconforming unit. The c-chart control chart is used with discrete/attribute defect data when c-Bar is greater than 5.

Control Chart Wizard – Discrete Defect Data: How large is your discrete/attribute defect data sample size?

Control Chart Wizard – Discrete Data: What type of discrete/attribute data do you have?

Steps in Constructing an X-Bar and s Control Chart: This document contains the step-by-step instructions to construct an X-Bar and s control chart. First the s chart is constructed. If the s chart validates that the process variation is in statistical control, the XBAR chart is constructed.

Control Chart Wizard – Average And Standard Deviation: This document contains the step-by-step instructions to construct an Average And Standard Deviation control chart.

Steps In Constructing An Exponentially Weighted Moving Average (EWMA) Chart: This document contains the step-by-step instructions to construct an Exponentially Weighted Moving Average (EWMA) control chart.

Steps In Constructing An Individuals And Moving Range Control Chart: This document contains the step-by-step instructions to construct an Individuals And Moving Range control chart.

Steps in Constructing a Median And Range Control Chart: This document contains the step-by-step instructions to construct a Median And Range control chart. The primary reason for using medians is that it is easier to do on the shop floor because no arithmetic must be done. The person doing the charting can simply order the data and pick the center element.

Control Chart Wizard – Median And Range: If the sample size is relatively small (e.g., less than 10-15) and the median is known, we can display how well a process is centered using the median or middle value. In contrast to the X-Bar and R control chart, this chart is useful when you would like to see less influence by data outliers. This can be an advantage or a disadvantage depending on your objective. The range of a sample is simply the difference between the largest and smallest observation. The Median and R control chart is used with continuous/variable data when subgroup or sample size is between 2 and 15.