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Topic: Statistical process control

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	STATISTICAL PROCESS CONTROL
		SPC techniques need not be restricted to the present, i.e., planning for the insertion of new technology later in the life cycle should also plan for the use of SPC to ensure that processes are controlled and reliability of the resulting software artifacts is optimized.
		Statistical Process Control (SPC) is used to identify and remove variations in processes that exceed the variation to be expected from natural causes.
		When the process is stabilized within acceptable limits, the project’s defined software process, the associated measurements, and the acceptable limits for the measurements are established as a baseline and used to control process performance quantitatively.” [Paulk, et.
	www.goldpractices.com /practices/spc/index.php (4166 words)

	statistical process control
		According to Shewhart, acknowledged father of control charts: "A phenomenon will be said to be controlled, when through the use of past experience, we can predict, at least within limits, how the phenomenon may be expected to behave in the future." Statistical process control (spc) is concerned with operating on target with minimum variance.
		In statistical process control (spc) there are a number of different control charts each of which performs best for a particular kind of data.
		Design of experiments can often speed the improvement or optimization process in major steps while statistical process control (spc) and control charts assure that the gains that have be made are not lost while continuing incremental improvement.
	www.adamssixsigma.com /statistical_process_control_spc.htm (271 words)

	Statistical Process Control - SPC
		The fundamentals of Statistical Process Control (though that was not what it was called at the time) and the associated tool of the Control Chart were developed by Dr Walter A Shewhart in the mid-1920’s.
		The crucial difference between Shewhart’s work and the inappropriately-perceived purpose of SPC that emerged, that typically involved mathematical distortion and tampering, is that his developments were in context, and with the purpose, of process improvement, as opposed to mere process monitoring.
		What inspired Shewhart’s development of the statistical control of processes was his observation that the variability which he saw in manufacturing processes often differed in behaviour from that which he saw in so-called “natural” processes – by which he seems to have meant such phenomena as molecular motions.
	www.managers-net.com /statistical_process_control.html (1117 words)

	Statistical Process Control - Control Charts (Site not responding. Last check: 2007-10-04)
		Control limits lines help to visualize the behavior of the characteristics monitored by the chart; if the characteristics are kept within the limits, the process continues under control state; if however there are bias, occurred changes that must be corrected so the process may return to the stability state.
		The control limits are located on the chart in such way that the probability of a subgroup average falling outside the control limits is 1%.
		The control charts indicate that the process is stable, however the results in the table above show that the natural process limits are much higher than the specification limits (figura 5-28); under these conditions the process is ‘not capable’ and a great percentage of products will be ‘out of specs’.
	www.geocities.com /Eureka/Plaza/6813/cep_us/cep_grctr_us.html (3555 words)

	Statistical process control - Wikipedia, the free encyclopedia
		It is a set of methods using statistical tools such as mean, variance and others, to detect whether the process observed is under control.
		Statistical process control was pioneered by Walter A. Shewhart and taken up by W.
		An example of such a statistical tool would be the Shewhart control chart, and the operator in the aforementioned example plotting the net weight in the Shewhart chart.
	en.wikipedia.org /wiki/Statistical_process_control (693 words)

	Statistical Process Control (SPC) Publications (Site not responding. Last check: 2007-10-04)
		The SPC algorithms are therefore equally applicable to the measurement process.
		This paper describes the role of statistical process control in the maintenance of differential pressure transfer standards in a flow calibration laboratory.
		Statistical process control is an important element in a complete measurement assurance program.
	www.ceesi.com /pubs_spc.aspx (918 words)

	SPCView Statistical Process Control Analysis Software Features
		The Process Control Chart Screen displays a plot of each control point in the process history with optional one-sigma upper and lower uncertainty limits.
		The SPC Interval Worksheet can be used to compute a recommended test or calibration interval commensurate with a desired confidence level or reliability target.
		The SPC Interval Worksheet also shows the drift rate for the process, project intercept of the curve fit, and the intercepts of the upper and lower projection limits with the UCL and LCL.
	www.isgmax.com /spc_features.htm (635 words)

	Statistical Process Control (SPC)
		SPC is one of the basic tools in quality management and as such has been used for a long time.
		SPC can only be successful if the organization is willing to react immediately to signals from the control chart.
		SPC is fully preventive if process parameters are followed and controlled with control charts (integrate with DOE – Design Of Experiments).
	www.qsconsult.be /ESTSPC.htm (315 words)

	Statistical Process Control Overview (Site not responding. Last check: 2007-10-04)
		Statistical process control was not well received by U.S. manufactures, so Dr. Shewhart first applied his theories in Japan.
		The concept is to be able to control your processes by monitoring changes in the process, environment, or labor, using control charts.
		The observation is important because it is the basis for the factor table you use to establish control limits.
	www.sixsigmaspc.com /spc/statistical_process_control.html (962 words)

	NWA - Implementing Statistical Process Control
		Control charts or graphical trend analysis are used to understand changes in the process mean and process standard deviation.
		SPC is based on statistical theory, process control theory and the proper application of the theory to the manufacturing environment.
		Thus, if a company makes this process more difficult by hand charting, this may be one more reason for line associates not to comply with the process of SPC implementation.
	www.nwasoft.com /appnotes/impspc.htm (1687 words)

	SPC - statistical process control
		Statistical process control by a simple control chart of a process variable, is based on the assumption that the process variable is an independent identically distributed random variable.
		The objective of time series model based statistical process control is to separate the process variable into two components namely the systematic variation due to common cause (contained in the fitted values) and the purely random variation (contained in the residuals).
		The process can then be controlled by 1) identifying and removing the source of common cause effects and 2) correcting the cause of special effects observed as outliers on a control chart of the residuals.
	www.fourcast.net /spc.htm (1800 words)

	Statistical Process Control: Process and Quality Views
		Process control engineers use SPC to monitor a process's stability, consistency and overall performance.
		For example, if you had an upper quality control limit of 100, the upper process control limit in a 6-sigma system would be 50 while a 3-sigma system may have an upper process control limit of around 90.
		After the process improvements, the data suggests that the process is in control and all four criteria for control are being met.
	www.cheresources.com /spczz.shtml (1967 words)

	Simplified Statistical Process Control (SPC) Method Tutorial (Site not responding. Last check: 2007-10-04)
		The process must be automatic, or at least semi-automatic, such that the human component has little or no effect on the outcome we are going to address.
		If the resulting "capability factor" is less than 1.0, the process is not capable of statistical control, and either the process needs to be overhauled to reduce variation, or (if feasible) the specified tolerance should be changed.
		As experience is gained with corrective actions for various processes and control chart patterns, a logical path to analysis and corrective action may emerge.
	www.1stnclass.com /spc_tutorial.htm (2536 words)

	Quality Theories (Site not responding. Last check: 2007-10-04)
		Determine for an individual outside of statistical control parameters on the “good” side, if there is reason for study – such as unique personal operating methods or motions that others could learn and use to improve their performance.
		The processes involved in document translation begin with the preparation and quality of the source document and optimally continue through the statistical tracking and review of the outcomes of each translation and publishing process along the way.
		Statistical tracking logically implies that various metrics have been established by which the outcomes of a process can be reviewed for quality and productivity.
	www.omnilingua.com /omnicenter/qualitytheories.aspx (2310 words)

	Statistical Process Control
		Statistical Process Control (SPC) is a diagnostic tool that allows you to determine “special” versus “common” causes of variation.
		SPC allows you to identify when these special causes occur so that you can eliminate them and bring predictability, or “control” to a process without overreacting to normal variability.
		By using a control chart you can graphically monitor a process variable and continuously perform a statistical test to determine if the mean has shifted, an indication that the process has changed.
	www.lwintl.com /html/explainSPC.html (314 words)

	Generating and Using Control Charts
		Convert the run chart to a control chart by adding three additional lines to the graph: the average (mean) line and the three standard deviation upper and lower control limits.
		In some cases, individual point(s) may be so close to the control limits that if they were removed from the average and control limit calculations, these point(s) would become outside the control limits.
		Statistical Process Control can be thought of as a formal "test" for the existence of significant change(s).
	www.hanford.gov /safety/vpp/spc.htm (3066 words)

	Multivariate Statistical Process Control
		This particular pattern shows that the process is in-control for each individual variable since the data points fall within the control rectangle [Mastrangelo et al., 1996; Tracy et al., 1992].
		Using multivariate control charts, it is possible to maintain a specific error rate, while taking advantage of cross correlation between the variables, and the process can be analyzed for its stability without the complication of maintaining many control charts at once.
		It is inherently more complex than univariate SPC, but it may be a more realistic representation of the data since in the real world processes do not usually have only one variable that is measured independent of all other variables in a system.
	www.sys.virginia.edu /mqc (570 words)

	Statistical Process Control SPC
		Statistical process control is the application of statistical methods to identify and control the special cause of variation in a process.
		Statistical Process Control (SPC) is the equivalent of a histogram plotted on it's side over time.
		SPC separates special cause from common cause variation in a process at the confidence level built into the rules being followed (typically 99.73% or 3 sigma).
	www.isixsigma.com /dictionary/Statistical_Process_Control_SPC-344.htm (261 words)

	Statistical Process Control (Site not responding. Last check: 2007-10-04)
		Process stability begins with understanding that producing the highest quality at the lowest cost means constantly striving to reduce variation.
		They'll be ready to work on an SPC team to rid their process of special cause variation and to avoid unnecessary adjustment.
		Process stability begins when people realize some variation is natural in every process — and understand that producing the highest quality at the lowest cost comes from constantly striving to reduce it.
	www.thequalitygroup.net /SPC/002.asp (906 words)

	Statistical Process Control
		The seven basic tools of SPC are taught in the context of a problem solving process.
		The learning process is hands-on with a catapult, bead bowl and process simulator (quincunx) used to generate data.
		Control charts for short runs, or process industries can be covered in optional modules.
	www.mesacg.com /spc1.htm (166 words)

	Statistical Process Control (Site not responding. Last check: 2007-10-04)
		Statistical Process Control (SPC) is a method of monitoring, controlling and, ideally, improving a process through statistical analysis.
		Its four basic steps include measuring the process, eliminating variances in the process to make it consistent, monitoring the process, and improving the process to its best target value.
		A common obstacle to successful use of SPC is getting bogged down with charts (fishbone, pareto, etc.), forgetting that visual representation of data is but a tool, not an end in itself.
	www.hq.nasa.gov /office/hqlibrary/ppm/ppm31.htm (442 words)

	Applying Statistical Process Control: New (Site not responding. Last check: 2007-10-04)
		Automated processes, high-volume data collection and storage, ever-increasing computational capability, powerful and user-friendly statistical software, and increased off-shore manufacturing are now the norm.
		Indeed, the core principles underlying the birth of SPC - the measurement and reduction of variability - are as valid today as they were seventy years ago.
		By the end of the seminar participants will be ready to properly implement SPC in their own work environment.
	cpd.ogi.edu /courseSpecific.asp?pam=848 (654 words)

	Statistical Process Control (SPC) Software
		Most SPC software programs have proven to be very difficult to use due to complexity of architecture which requires many steps to do an analysis.
		The Average (X bar) and Range control chart developed by Walter Shewhart in 1931 is still the most popular chart in use today, due to its simplicity and effectiveness.
		Inertial elements in the process frequently cause the observations to become positively autocorrelated; that is, if X(t) is positive, it is likely that X(t+1) will also be positive.
	www.qualitran.com /SPC_Software/body_spc_software.html (1082 words)

	Implementing Statistical Process Control
		The key to success with SPC is in knowing when, where, and how it should be used.
		Implementing Statistical Process Control is an in-depth seminar program covering all of the basic tools and techniques of SPC.
		Implementing Statistical Process Control is divided into four major sections and requires approximately 32 hours for presentation.
	www.iplusnet.com /ispc.htm (262 words)

	Control Charts / Statistical Process Control (SPC)
		The tedious task of analyzing control charts for validity of the limits can be eliminated and the resulting report can be used as a tool to keep the process of continuous improvement on track.
		When special control strategies are applied to typical process data, the observed relationship between Z(short-term) and Z(long-term) is reproduced, and a relationship to estimate Z(short-term) from Z(long-term, discrete) from defect counts is derived.
		Process stability is one of the most important concepts of any quality improvement methodology.
	www.isixsigma.com /st/control_charts (719 words)

	SPC \| Statistical Process Control by Global Quality Systems
		This Statistical Process Control seminar will teach the technical staff how to select the best control chart for any given process and data type and how to most effectively deploy it.
		This detailed procedure requires some effort to complete but is designed to assure that all aspects of control procedure location, selection, and deployment are seamless and that the results will conform to expectations.
		The class is designed to provide basic knowledge and understanding of control charting, the assumptions that underlie control charts, and how to effectively use them.
	www.gqs-inc.com /SPC.htm (403 words)

	InControl Technologies, Inc. (Site not responding. Last check: 2007-10-04)
		We provide statistical services to the chemical and petrochemical facilities, oil refineries, power generation facilities, and waste water treatment plants - just to name a few.
		Multivariate SPC includes an introduction to multivariate signal detection and interpretation and detailed discussion of the multivariate control chart.
		Statistical Model Building includes a detailed look at the construction and interpretation of multivariate statistical process models.
	www.incontroltech.com /spc (292 words)

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