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I. Contents of quality management document ////////////////// Compliant Quality Management Document Control Systems
0or life sciences organiations and similarly regulated companies, quality management and document control are inetricably lin"ed ith 04, I&', and other guidelines defined by by comparable regulatory entities. Quality management systems must be meticulously managed and proper records must be carefully maintained to comply ith such regulatory requirements. 4 robust, interconnected, and fleible softare application can be the "ey to maintaining cost co st effective quality control systems and maintaining affordable and hassle!free regulatory compliance. The MasterControl Quality Management Document Control Software Solution
+roviding quality management and document control solutions globally since 1%%3, 5aster6ontrol Inc. offers a user!friendly, customiable customiable softare suite that allos companies to efficiently manage quality processes. 5aster6ontrol7s integrated suite of softare solutions is specifically designed to help companies get products to mar"et faster hile maintaining continuous regulatory compliance. &ome of the features and benefits of the 5aster6ontrol quality management and document control system include8
Automated routing, escalation, and approals: 5aster6ontrol7s quality management and document control reduces document cycle time by automating routing and approval procedures and by incorporating escalations for overdue tas"s. 9his automation helps sustain compliance by simplifying and streamlining processes and by maintaining electronic records of such procedures in a secure, centralied repository.
!ncreased isi"ility: 9he 5aster6ontrol softare solution provides advanced analytics and reporting capabilities, including customiable reports and online ch arting. 9hrough the customied or pre!built reports generated by the system managers can have a :real! time: vie of all quality management and document control processes and can be more proactive about ma"ing improvements to the quality system in general.
Connected quality processes: 5aster6ontrol7s solution connects all subsystems to form a cohesive, complete co mplete quality system. 0or instance, any 64+4 that results in a document change can be set to automatically invo"e a training tas" once the change is approved.
#nhanced lifecycles: 5aster6ontrol7s quality management and document control softare allos for multiple lifecycle statuses, timed lifecycle movement, and fleible approval rules. 6ompanies are able to model their product lifecycle ithin the system and simplify routes and or"flos.
Quality Management and Document Control that $oes %eyond Software
5aster6ontrol ta"es pride in being a quality management and document control solution provider that goes :beyond softare.: 5aster6ontrol offers offers not ust a softare system, but products and services that provide actual solutions to critical challenges faced by companies hose products are subect to regulatory requirements. 9he proven 5aster6ontrol softare solution consists of configurable, integrated applications that automate, streamline, and effectively manage quality control processes. 9he ;eb!based ;eb!based 5aster6ontrol system automates all quality and document related processes and connects departments throughout the enterprise to ensure every authoried user has proper system access. 9he 5aster6ontrol quality management and document control suite includes tightly integrated and configurable applications for managing not only documents and forms but also 64+4, change, training, nonconformance, audit, customer complaints, and other aspects of a complete quality system. 9o complement these solutions modules, 5aster6ontrol offers a ide range of implementation, migration, validation, training, and technical support services as ell. //////////////////
III. Quality management tools
1. Check sheet 9he chec" sheet is a form <document= used to collect data in real time at the location here the data is generated. 9he data it captures can be b e quantitative or qualitative. ;hen the information is quantitative, the chec" sheet is sometimes called a tally sheet. 9he defining characteristic of a chec" sheet is that data are recorded by b y ma"ing mar"s <:chec"s:= on it. 4 typical chec" sheet is divided into regions, and mar"s made in different regions have different significance. ata a re read by observing the location and number of mar"s on the sheet. 6hec" sheets typically employ a heading that ansers the 0ive ;s8
;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
6ontrol charts, also "non as &hehart charts <after ;alter ;alter 4. &hehart= 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.>1? 4 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. 9he control chart is one of the seven basic tools of quality control.>3? 9ypically 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=, hoever the type of chart used to do this requires consideration.
&' (areto chart
4 +areto chart, named after @ilfredo +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. 9he left vertical ais is the frequency of occurrence, but it can alternatively represent cost or another important unit of measure. 9he right vertical ais is the cumulative percentage of the total number of occurrences, total cost, or total of the particular unit of measure. Aecause the reasons are in decreasing order, the cumulative function is a concave function. 9o ta"e the eample above, in order to loer the amount of late arrivals by B#C, it is sufficient to solve the first three issues. 9he 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 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
4 scatter plot, scatterplot, or scattergraph is a type of mathematical diagram using 6artesian coordinates to display values for to variables for a set of da ta. 9he data is displayed as a collection of points, each having the value of one variable determining the position on the horiontal ais and the value of the other variable determining the position on the vertical ais.>2? 9his "ind of plot is also called a scatter chart, scattergram, scatter diagram,>3? or scatter graph. 4 scatter plot is used hen a variable eists that is under the control of the eperimenter. If a parameter eists that is systematically incremented andor decremented by the other, it is called the control parameter or independent variable and is customarily plotted along the ho riontal ais. 9he measured or dependent variable is customarily plotted along the vertical ais. If no dependent variable eists, either type of variable can be plotted on either ais and a scatter plot ill illustrate only the degree of correlation <not causation= beteen to variables. 4 scatter plot can suggest various "inds of correlations beteen variables ith a certain confidence interval. 0or eample, eight and height, eight ould be on ais and height ould be on the y ais. 6orrelations may be positive <rising=, negative <falling=, <falling=, or null <uncorrelated=. If the pattern of dots slopes from loer left to upper right, it suggests a positive correlation beteen the variables being studied. If the pattern of dots slopes from upper left to loer right, it suggests a negative co rrelation. 4 line of best fit <alternatively called 7trendline7= can be dran in order to study the correlation beteen the variables. 4n equation for the correlation beteen the variables can be determined by established best!fit procedures. 0or a linear correlation, the best!fit procedure is "non as linear regression and is guaranteed to generate a correct solution in a finite time. Do universal best!fit procedure is guaranteed to generate a correct solution for arbitrary relationships. 4 scatter plot is also ver y useful hen e ish to see ho to comparable data d ata sets agree ith each
other. In this case, an identity line, i.e., a y/ line, or an 181 line, is often dran as a reference. 9he more the to data sets agree, the more the scatters tend to concentrate in the vicinity of the identity lineE if the to da ta sets are numerically identical, the scatters fall on the identity line eactly.
Ishi"aa diagrams <also called fishbone diagrams, herringbone diagrams, cause!and!effect diagrams, or 0ishi"aa= are causal diagrams created by *aoru Ishi"aa <1%-#= that sho the causes of a specific event. >1?>2? 6ommon uses of the Ishi"aa diagram are product design and quality defect prevention, to identify potential factors causing an overall effect. Fach cause or reason for imperfection is a source of variation. 6auses are usually grouped into maor categories to identify these sources of variation. 9he categories typically include • •
+eople8 4nyone involved ith the process 5ethods8 Go the process is performed and the specific requirements for doing it, such as policies, procedures, rules, regulations and las
5achines8 4ny equipment, computers, tools, etc. required to accomplish the ob
5aterials8 Ha materials, parts, pens, paper, etc. used to produce the final product
5easurements8 ata generated from the process that are used to evaluate its quality
Fnvironment8 9he conditions, such as location, time, temperature, and culture in hich the process operates
-. Gistogram method
4 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.>1? +ea rson.>1? 9o 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 man y values fall into each interval. 4 rectangle is dran ith height proportional to the count and idth equal to the bin sie, so that rectangles abut each other. 4 histogram histogram may also be normalied displaying relative frequencies. It then shos the proportion of cases that fall into each of several categories, ith the sum of the heights equa ling 1. 9he bins are usually specified as consecutive, non!overlapping intervals of a variable. 9he bins <intervals= must be adacent, and usually equal sie.>2? 9he rectangles of a histogram are dran so that they touch each other to indicate that the original variable is continuous.>3?
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