quality assurance quality management.docx

 

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I. Contents of quality assurance quality management  o- safe -ould you feel going to a hospital for surgery if there -ere no standards dictating the minimum education and e0pertise for surgeons and nurses ould ould you fly confidently on a plane if there -ere no training or even flying e0perience requirements for pilots ould ould you cross a  bridge -ithout -orries if you !ne- that nobody had chec!ed -hether the steel used -as strong enough for that particulardesign In fact, the introduction of regulations and definition d efinition of standards to ensure that -e get a minimum level of confidence -hen using a product is nothing ne-. n e-. lready in the 4iddle ges, guilds of craftsmen determined the minimum quality of products and also the training needed for  membership. 5he advent of mass production and the evermore comple0, e0pensive and ha6ardous endeavours in -hich -e embar!, such as building aircraft, s!yscrapers, nuclear po-er plants, openheart surgery or going to space, ma!es it even more necessary to ensure quality -or!manship,  processes and materials at all levels of any successful organi6ation. organi6ation. Going to space is by its very nature comple0, costly and involves thousands of highly s!illed  professionals -or!ing harmoniously. harmoniously. 5o 5o avoid fla-s and problems that could never be fi0ed once in orbit, it is critical to ensure that even the smallest part is manufactured properly to do its +ob7  in space, you do not n ot get a second chance. chan ce. ctually, ctually, it is not that different to coo!ing a gourmet meal8 you should better chec! that the recipe is follo-ed properly and the ingredients are of good quality or the -hole thing may be spoiled.

 

What is the Quality Management and Assurance domain? 9uality management and assurance is all about abou t ma!ing sure that the team building a satellite or launcher does the -or! as it should be done, that the correct materials are being used and the right steps are follo-ed. or!manship and process standards need to be defined for all activities and products and, in addition, chec!s need to be performed to confirm that these standards are respected by the team. 5he same for materials8 suitable materials have to be identified and

chec!s need to be performed to confirm that these are indeed the materials used. 9uality management and assurance is also involved in handling the inevitable e0ceptions to the rules. hat shall -e do -hen the -or! cannot be performed follo-ing the intended method and so an alternative one has to be introduced &r -hat shall -e do if a material -e -anted to use is not available anymore or does not no t -or! as e0pected and -e need to choose a different one ny  problem or deviation needs to be thought through, other-ise the -hole spacecraft may fail. 5his could mean a large financial loss or even danger to life. 9uality management and assurance has yet another aspect to it. It ma!es sure that evidence e vidence of the quality of the -or! done, the methods and the materials used is collected and available for inspection. 5his is very important to reassure decision ma!ers, government officials and users in general that the satellite or roc!et manufactured can be successfully launched and -ill bring the e0pected return on the investment made. &n one hand, quality qua lity management focuses on the general system s ystem and processes across pro+ects. &n the other, quality assurance focuses on the set of measures to gain confidence on the achievement of the quality of the product.

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III. Quality management tools

1. Check sheet

 

5he chec! sheet is a form :document; used to collect data in real time at the location -here the data is generated. 5he data it captures can be b e quantitative or qualitative. hen the information is quantitative, the chec! sheet is sometimes called a tally sheet. 5he defining characteristic of a chec! sheet is that data are recorded by b y ma!ing mar!s :<chec!s<; on it.  typical chec! sheet is divided into regions, and mar!s made in different regions have different significance. =ata are a re read by observing the location and number of mar!s on the sheet. >hec! sheets typically employ a heading that ans-ers the ?ive s@ •

ho filled out the chec! sheet

•

•

hat -as collected :-hat each chec! represents, an identifying batch or lot number; here the collection too! place :facility, room,

•

apparatus; hen the collection too! place :hour, shift, day of 

•

the -ee!; hy the data -ere collected

2. Control chart

>ontrol charts, also !no-n as %he-hart charts :after alter alter . %he-hart; or processbehavior charts, in statistical process control are tools used to determine if a manufacturing or business  process is in a state of statistical statistical control. If analysis of the control chart indicates that the  process is currently under control :i.e., is stable, stable, -ith variation only coming from sources common to the process;, then no corrections or changes ch anges to  process control parameters are needed or desired.

 

In addition, data from the process can be used to  predict the future performance of the process. If the chart indicates that the monitored process is not in control, analysis of the chart can help determine the sources of variation, as this -ill result in degraded process p rocess performance.A1B   process that is stable but operating outside of desired :specification; limits :e.g., scrap rates may be in statistical control but above desired limits; needs to be improved through a deliberate effort to understand the causes of current  performance and fundamentally improve the  process. 5he control chart is one of the seven basic tools of  quality control.A3B 5ypically control charts are used for timeseries data, though they can be b e used for data that have logical comparability :i.e. you -ant to compare samples that -ere ta!en all at the same time, or the performance of different individuals;, ho-ever the type of chart used to do this requires consideration.

3. Pareto chart

 

 *areto chart, named after Cilfredo *areto, is a type of chart that contains both bars and a line graph, -here individual values are represented in descending order  by bars, and the cumulative total is represented by the line. 5he left vertical a0is is the frequency of occurrence,  but it can alternatively represent cost or another important unit of measure. 5he right vertical a0is is the cumulative percentage of the total number of occurrences, total cost, or total of the particular unit of  measure. Decause the reasons are in decreasing order, the cumulative function is a concave function. 5o ta!e the e0ample above, in order to lo-er the amount of late arrivals by E"F, it is sufficient to solve the first three issues. 5he purpose of the *areto chart is to highlight the most important among a :typically large; set of factors. In quality control, it often represents the most common sources of defects, the highest occurring type t ype of defect, or the most frequent reasons for customer complaints, and so on. il!inson :2''; devised an algorithm for producing statistically based acceptance limits :similar to confidence intervals; for each bar in the *areto chart.

(. Scatter plot Method

 

 scatter plot, scatterplot, or scattergraph is a type of mathematical diagram using >artesian coordinates to display values for t-o variables for a set of data. da ta. 5he data is displayed as a collection of points, each having the value of one variable determining the position on the hori6ontal a0is and the value of the other variable determining the position on the vertical a0is.A2B 5his !ind of plot is also called a scatter chart, scattergram, scatter diagram,A3B or scatter graph.  scatter plot is used -hen a variable e0ists that is under the control of the e0perimenter. If a parameter e0ists that is systematically incremented and/or decremented by the other, it is called the control parameter or independent variable and is customarily plotted along the hori6ontal ho ri6ontal a0is. 5he measured or dependent variable is customarily  plotted along the vertical a0is. If no dependent variable e0ists, either type of variable can be plotted on either a0is and a scatter plot -ill illustrate only the degree of correlation :not causation; bet-een t-o variables.  scatter plot can suggest various !inds of correlations  bet-een variables -ith a certain confidence interval. ?or e0ample, -eight and height, -eight -ould be on 0 a0is and height -ould be on the y a0is. >orrelations may be  positive :rising;, negative :falling;, :falling;, or null :uncorrelated;. If the pattern of dots slopes from lo-er left to upper right, it suggests a positive correlation bet-een the variables  being studied. If the pattern of dots slopes from upper left to lo-er right, it suggests a negative correlation. co rrelation.  line of  best fit :alternatively called GtrendlineG; can be dra-n in order to study the correlation bet-een the variables. n equation for the correlation bet-een the variables can be determined by established bestfit procedures. ?or a linear  correlation, the bestfit procedure is !no-n as linear regression and is guaranteed to generate a correct solution in a finite time. Ho universal bestfit procedure is guaranteed to generate a correct solution for arbitrary relationships.  scatter plot is also very ver y useful -hen -e -ish to see ho- t-o comparable data d ata sets agree -ith each

 

other. In this case, an identity line, i.e., a y0 line, or an 1@1 line, is often dra-n as a reference. 5he more the t-o data sets agree, the more the scatters tend to concentrate in the vicinity of the identity line8 if the t-o data da ta sets are numerically identical, the scatters fall on the identity line e0actly.

5.Ishia!a diagram

Ishi!a-a diagrams :also called fishbone diagrams, herringbone diagrams, causeandeffect diagrams, or ?ishi!a-a; are causal diagrams created by )aoru Ishi!a-a :1$"; that sho- the causes of a specific event. A1BA2B >ommon uses of the Ishi!a-a diagram are product design and quality defect prevention, to identify potential factors causing an overall effect. ach cause or reason for imperfection is a source of variation. >auses are usually grouped into ma+or categories to identify these sources of variation. 5he categories typically include • •

*eople@ nyone involved -ith the process 4ethods@ o- the process is performed and the specific requirements for doing it, such as policies,  procedures, rules, regulations and la-s

•

4achines@ ny equipment, computers, tools, etc.

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required to accomplish the +ob 4aterials@ Ja- materials, parts, pens, paper, etc. used to produce the final product

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4easurements@ =ata generated from the process that are used to evaluate its quality

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nvironment@ 5he conditions, such as location, time, temperature, and culture in -hich the process operates

. istogram method

 

 histogram is a graphical representation of the distribution of data. It is an estimate of the probability distribution of a continuous variable :quantitative variable; and -as first introduced by )arl *earson.A1B *ea rson.A1B 5o construct a histogram, the first step is to <bin< the range of  values  that is, divide the entire range of values into a series of small intervals  and then count ho- many man y values fall into each interval.  rectangle is dra-n -ith height proportional to the count and -idth equal to the bin si6e, so that rectangles abut each other.  histogram histogram may also be normali6ed displaying relative frequencies. It then sho-s the proportion of cases that fall into each of several categories, -ith the sum of the heights equaling equa ling 1. 5he  bins are usually specified as consecutive, nonoverlapping intervals of a variable. 5he bins :intervals; must be ad+acent, and usually equal si6e.A2B 5he rectangles of a histogram are dra-n so that they touch each other to indicate that the original variable is continuous.A3B

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