In quality control, multi-vari charts are a visual way of presenting variability through a series of charts. The content and format of the charts has evolved over time.
Quality control (QC) is a process by which entities review the quality of all factors involved in production. ISO 9000 defines quality control as "A part of quality management focused on fulfilling quality requirements".
Multi-vari charts were first described by Leonard Seder in 1950, [1] [2] though they were developed independently by multiple sources. They were inspired by the stock market candlestick charts or open-high-low-close charts. [3]
A candlestick chart is a style of financial chart used to describe price movements of a security, derivative, or currency. Each "candlestick" typically shows one day, thus a one-month chart may show the 20 trading days as 20 "candlesticks". Shorter intervals than one day are common on computer charts, longer are possible.
An open-high-low-close chart is a type of chart typically used to illustrate movements in the price of a financial instrument over time. Each vertical line on the chart shows the price range over one unit of time, e.g., one day or one hour. Tick marks project from each side of the line indicating the opening price on the left, and the closing price for that time period on the right. The bars may be shown in different hues depending on whether prices rose or fell in that period.
As originally conceived, the multi-vari chart resembles a Shewhart individuals control chart with the following differences:
In statistical quality control, the individual/moving-range chart is a type of control chart used to monitor variables data from a business or industrial process for which it is impractical to use rational subgroups.
A specification often refers to a set of documented requirements to be satisfied by a material, design, product, or service. A specification is often a type of technical standard.
Control limits, also known as natural process limits, are horizontal lines drawn on a statistical process control chart, usually at a distance of ±3 standard deviations of the plotted statistic from the statistic's mean.
The three panels are interpreted as follows: [4]
| Panel | Condition | Corrective action |
|---|---|---|
| Variability on a single piece | Lengths of the vertical lines (i.e., the range) exceed one-half the specifications (or more) | Repair or realignment of tool |
| Piece-to-piece variability | Excessive scatter | Examine process inputs for excessive variability—lengths of the vertical lines are estimates of process capability |
| Time-to-time variability | Appearance of a non-stationary process | Examine process inputs or steps for evidence of shifts or drifts |
More recently, the term "multi-vari chart" has been used to describe a visual way to display analysis of variance data (typically be expressed in tabular format). [5] It consists of a series of panels which portray minimum, mean, and maximum responses for each treatment combination of interest rather than for periods of time.
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures used to analyze the differences among group means in a sample. ANOVA was developed by statistician and evolutionary biologist Ronald Fisher. In the ANOVA setting, the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether the population means of several groups are equal, and therefore generalizes the t-test to more than two groups. ANOVA is useful for comparing (testing) three or more group means for statistical significance. It is conceptually similar to multiple two-sample t-tests, but is more conservative, resulting in fewer type I errors, and is therefore suited to a wide range of practical problems.
Because it is a two-dimensional representation of multiple dimensions (one for each factor in the ANOVA), the multi-vari chart is only useful for comparing the variability among at most four factors.
The chart consists of the following:
Control charts, also known as Shewhart charts or process-behavior charts, are a statistical process control tool used to determine if a manufacturing or business process is in a state of control.
Taguchi methods are statistical methods, or sometimes called robust design methods, developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to engineering,biotechnology, marketing and advertising. Professional statisticians have welcomed the goals and improvements brought about by Taguchi methods, particularly by Taguchi's development of designs for studying variation, but have criticized the inefficiency of some of Taguchi's proposals.
In the statistical theory of the design of experiments, blocking is the arranging of experimental units in groups (blocks) that are similar to one another.
In statistical quality control, the and R chart is a type of control chart used to monitor variables data when samples are collected at regular intervals from a business or industrial process.
A Shock Response Spectrum (SRS) is a graphical representation of a shock, or any other transient acceleration input, in terms of how a Single Degree Of Freedom (SDOF) system would respond to that input. The horizontal axis shows the natural frequency of a hypothetical SDOF, and the vertical axis shows the peak acceleration which this SDOF would undergo as a consequence of the shock input.
In process improvement efforts, the process capability index or process capability ratio is a statistical measure of process capability: the ability of a process to produce output within specification limits. The concept of process capability only holds meaning for processes that are in a state of statistical control. Process capability indices measure how much "natural variation" a process experiences relative to its specification limits and allows different processes to be compared with respect to how well an organization controls them.
A Pareto chart, named after Vilfredo Pareto, is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the cumulative total is represented by the line.
Business process mapping refers to activities involved in defining what a business entity does, who is responsible, to what standard a business process should be completed, and how the success of a business process can be determined.
A run chart, also known as a run-sequence plot is a graph that displays observed data in a time sequence. Often, the data displayed represent some aspect of the output or performance of a manufacturing or other business process. It is therefore a form of line chart.
River regime can describe one of two characteristics of a reach of an alluvial river:
Joseph Moses Juran was a Romanian-born American engineer and management consultant. He was an evangelist for quality and quality management, having written several books on those subjects. He was the brother of Academy Award winner Nathan H. Juran.
An oscilloscope, previously called an oscillograph, and informally known as a scope or o-scope, CRO, or DSO, is a type of electronic test instrument that graphically displays varying signal voltages, usually as a two-dimensional plot of one or more signals as a function of time. Other signals can be converted to voltages and displayed.
Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.
In statistical quality control, the and s chart is a type of control chart used to monitor variables data when samples are collected at regular intervals from a business or industrial process.
Laboratory quality control is designed to detect, reduce, and correct deficiencies in a laboratory's internal analytical process prior to the release of patient results, in order to improve the quality of the results reported by the laboratory. Quality control is a measure of precision, or how well the measurement system reproduces the same result over time and under varying operating conditions. Laboratory quality control material is usually run at the beginning of each shift, after an instrument is serviced, when reagent lots are changed, after calibration, and whenever patient results seem inappropriate. Quality control material should approximate the same matrix as patient specimens, taking into account properties such as viscosity, turbidity, composition, and color. It should be simple to use, with minimal vial to vial variability, because variability could be misinterpreted as systematic error in the method or instrument. It should be stable for long periods of time, and available in large enough quantities for a single batch to last at least one year. Liquid controls are more convenient than lyophilized controls because they do not have to be reconstituted minimizing pipetting error.
Dorian Shainin was an American quality consultant, aeronautics engineer, author, and college professor most notable for his contributions in the fields of industrial problem solving, product reliability, and quality engineering, particularly the creation and development of the "Red X" concept.
Maximum elevation figure or MEF is a type of VFR altitude which indicates the height of the highest feature within a quadrangle area. It is of interest to pilots, who want to be aware of the highest mountain peaks and tall towers nearby, so that they can fly above them to avoid controlled flight into terrain. In a VFR context, this altitude is commonly referred to as a "quadrantal altitude"
Quality by Design (QbD) is a concept first outlined by quality expert Joseph M. Juran in publications, most notably Juran on Quality by Design. Designing for quality and innovation is one of the three universal processes of the Juran Trilogy, in which Juran describes what is required to achieve breakthroughs in new products, services, and processes. Juran believed that quality could be planned, and that most quality crises and problems relate to the way in which quality was planned.
The minimum control speed (VMC) of an aircraft is a V-speed that specifies the calibrated airspeed below which directional or lateral control of the aircraft can no longer be maintained, after the failure of one or more engines. The VMC only applies if at least one engine is still operative, and will depend on the stage of flight. Indeed, multiple VMCs have to be calculated for landing, air travel, and ground travel, and there are more still for aircraft with four or more engines. These are all included in the aircraft flight manual of all multi-engine aircraft. When design engineers are sizing an airplane's vertical tail and flight control surfaces, they have to take into account the effect this will have on the airplane's minimum control speeds.