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Public interest in educational outcomes has markedly increased in the most recent decade; however, quality management and statistical process control have not deeply penetrated the management of academic institutions. This paper presents results of an attempt to use Statistical Process Control (SPC) to identify a key impediment to continuous improvement in the academic setting and to facilitate continual improvement of instructional performance. An illustration from an undergraduate degree program in business administration is provided.

Public interest in educational outcomes has markedly increased in the most recent decade; however, quality management and statistical process control have not deeply penetrated the management of academic institutions. This paper presents results of an attempt to use Statistical Process Control (SPC) to identify a key impediment to continuous improvement in the academic setting and to facilitate continual improvement of instructional performance. An illustration from an undergraduate degree program in business administration is provided.

Public interest in educational outcomes has markedly increased in the most recent decade; however, quality management and statistical process control have not deeply penetrated the management of academic institutions. This paper presents results of an attempt to use Statistical Process Control (SPC) to identify a key impediment to continuous improvement in the academic setting and to facilitate continual improvement of instructional performance. An illustration from an undergraduate degree program in business administration is provided.

Public interest in educational outcomes has markedly increased in the most recent decade; however, quality management and statistical process control have not deeply penetrated the management of academic institutions. This paper presents results of an attempt to use Statistical Process Control (SPC) to identify a key impediment to continuous improvement in the academic setting and to facilitate continual improvement of instructional performance. An illustration from an undergraduate degree program in business administration is provided.

This guide, part of a series of workplace-developed materials for retraining factory workers, provides teaching materials for a workplace mathematics course. The course is a review of basic number concepts focused on helping participants to understand the meaning of numbers and arithmetic operations. The introductory materials include a course outline, course objectives, a topical outline, information on course length and continuing education units, and resources. Lesson plans for four sessions are provided on the following topics: adding, subtracting, and multiplying decimals; using the metric system; calculating percents; interpreting control charts; and interpreting histograms. The session materials include objectives, topics, methods, evaluation criteria, a pretest and a posttest, information sheets, and handouts. (KC)

This guide, part of a series of workplace-developed materials for retraining factory workers, provides teaching materials for a workplace mathematics course. The course is a review of basic number concepts focused on helping participants to understand the meaning of numbers and arithmetic operations. The introductory materials include a course outline, course objectives, a topical outline, information on course length and continuing education units, and resources. Lesson plans for four sessions are provided on the following topics: adding, subtracting, and multiplying decimals; using the metric system; calculating percents; interpreting control charts; and interpreting histograms. The session materials include objectives, topics, methods, evaluation criteria, a pretest and a posttest, information sheets, and handouts. (KC)

This guide, part of a series of workplace-developed materials for retraining factory workers, provides teaching materials for a workplace mathematics course. The course is a review of basic number concepts focused on helping participants to understand the meaning of numbers and arithmetic operations. The introductory materials include a course outline, course objectives, a topical outline, information on course length and continuing education units, and resources. Lesson plans for four sessions are provided on the following topics: adding, subtracting, and multiplying decimals; using the metric system; calculating percents; interpreting control charts; and interpreting histograms. The session materials include objectives, topics, methods, evaluation criteria, a pretest and a posttest, information sheets, and handouts. (KC)

This guide, part of a series of workplace-developed materials for retraining factory workers, provides teaching materials for a workplace mathematics course. The course is a review of basic number concepts focused on helping participants to understand the meaning of numbers and arithmetic operations. The introductory materials include a course outline, course objectives, a topical outline, information on course length and continuing education units, and resources. Lesson plans for four sessions are provided on the following topics: adding, subtracting, and multiplying decimals; using the metric system; calculating percents; interpreting control charts; and interpreting histograms. The session materials include objectives, topics, methods, evaluation criteria, a pretest and a posttest, information sheets, and handouts. (KC)

Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.

The problem of classifying pilot mental workload is important to the United States Air Force. Pilots are more subject to errors and G-induced loss of consciousness during periods of mental overload and task saturation. Often the result is the loss of aircraft. and in extreme cases, the loss of the pilot's life. Current research efforts use different psychophysiological features to classify pilot mental workload. These include cardiac, ocular, respiratory, and brain activity measures. The focus of this effort is to apply statistical process control methodology on different psychophysiological features in an attempt to classify pilot mental workload. The control charts track these features throughout the flight, and classify a segment as high workload if the measurements of these feature, are greater than predefined control limits. We find that using certain control charts prove to be effective workload classifiers and maintain high classification accuracies when applied to other flight data.

This research effort concentrated on applying statistical process control techniques to the results of seven years worth of spirometry exams of workers at Wright-Patterson AFB in helping the occupational health squadron identify potential work hazard areas. Each spirometry exam was classified as abnormal or normal based on a comparison with established normals or a significant loss of function from the previous year's exam for the individual. Each test was classified into the work area of the individual and the number of abnormalities per population of the work area was examined.

Traditionally, medical surveillance of liver disease generally involves a battery of tests. This research used multivariate analysis techniques to reduce the number of measures required to identify liver dysfunction and found using a Transferase Index (a combination of three tests; ALT, AST, and GGT) provided the most satisfying assessment, but the single best indicator, ALT, may be sufficient. Transferase Index and ALT criterion were both applied to SPC control charts. Through the use of statistical process control (SPC), this research identified work zones possessing signs of adverse effects to an individual's liver as a possible result of their work environment and demonstrated SPC as an excellent way to conduct medical surveillance. Industry has embraced SPC, and control charts, this research extended their scope and demonstrated their effective use in medical surveillance of the liver. This research showed they provide easy, efficient ways to monitor work environments.

The application of statistical methods to process control provides a better understanding of the behavior of any operation. This understanding is a necessary piece of management information. It is essential for making good decisions about process adjustments and assessing the effect of process improvement actions. The use of statistical methods also makes this understanding available to the employees who are actually working the processes. Fortunately it is not necessary to understand a great deal about the mathematics of statistical theory in order to make full use of statistical methods. The concepts and techniques of a methodology known as statistical process control (SPC) form a repertoire of powerful statistical tools that are effective in bringing about concurrent improvements in both quality and productivity.

The current tools used by squadron supervisors to monitor the bombing performance of aircrews flying F-111E aircraft are monthly reports that have little predictive capability. No real-time methodology exists for monitoring and predicting aircrew bombing performance and preventing bombing problems that might cause an individual to become unqualified. It has been suggested that Statistical process Control (SPC) can be applied to the bombing process to develop tools for managing the process, correcting problems, and improve the bombing performance of a squadron. This study investigates the application of SPC to the bombing process. It examines data taken from an F-111E Fighter Wing during a sixth-month training period. The goal is to develop a control charting scheme that is both useful to squadron supervisors as well as simple to apply by squadron weapons officers. The results indicate that SPC methodologies can have a significant impact on the bombing process. Control carts generated from the data can give insights to the bombing performance and capabilities of individual aircrews. These insights can lead to improvements in the bombing performance of individuals, as well as in the bombing performance of their squadron as a whole. (AN)

This instructional guide, one of a series developed by the Technical Education Advancement Modules (TEAM) project, is a 6-hour introductory module on statistical process control (SPC), designed to develop competencies in the following skill areas: (1) identification of the three classes of SPC use; (2) understanding a process and how it works; (3) tracking the process; and (4) analyzing the process. Project TEAM is intended to upgrade basic technical competencies of unemployed, underemployed, and existing industrial employees. The materials in this module serve as a student outline and an instructor guide. The manual includes six sections: (1) introduction--including course objectives and classes of SPC use; (2) what is a process; (3) how a process works; (4) Dr. W. E. Deming's plan to save America--the assignment of responsibilities and the master plan for process improvement; (5) tracking the process--the average and range chart, and detecting lack of control; and (6) analyzing and removing special causes--individual and team problem solving, simple diagnostic tools, and return to Deming's plan. (NLA)

Statistical process control has been compared with two other approaches (confidence intervals and acceptance testing) to determine the potential for this technology in developing realistic sampling plans that offer equal protection for both consumer and producer. These theories were first assessed from a practical standpoint and then were subjected to experimental manipulation using a computer simulation program. Results showed that the optimal solution is to use a combination of process control (the p-chart method) and acceptance testing (Military Standard 105D) to evaluate service quality. This approach offers realistic output that protects the consumer and producer at a similar level; in addition, process control allows historical data to be used so that a contractor who has performed well in the past can be sampled less stringently. Finally, a major advantage is that overall quality of contract services should improve by implementing this approach because the contractor will receive feedback that identifies inconsistencies in services performed; the faults can then be corrected and, over time, the contractor will learn what needs to be done to provide acceptable performance. A step-by-step implementation plan has been proposed. It is recommended that the Army field- test this approach and develop an automated system for rapid evaluation.

Statistical process control has been compared with two other approaches (confidence intervals and acceptance testing) to determine the potential for this technology in developing realistic sampling plans that offer equal protection for both consumer and producer. These theories were first assessed from a practical standpoint and then were subjected to experimental manipulation using a computer simulation program. Results showed that the optimal solution is to use a combination of process control (the p-chart method) and acceptance testing (Military Standard 105D) to evaluate service quality. This approach offers realistic output that protects the consumer and producer at a similar level; in addition, process control allows historical data to be used so that a contractor who has performed well in the past can be sampled less stringently. Finally, a major advantage is that overall quality of contract services should improve by implementing this approach because the contractor will receive feedback that identifies inconsistencies in services performed; the faults can then be corrected and, over time, the contractor will learn what needs to be done to provide acceptable performance. A step-by-step implementation plan has been proposed. It is recommended that the Army field- test this approach and develop an automated system for rapid evaluation.

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Historically, quality inspection systems focused on out of spec material instead of providing control strategies to prevent defects from occurring. New inspection systems include Contractor Inspection Systems and Statistical Process Control. The overall objective of this Short Term Project was the design, development and demonstration of a plan for automated manufacturing process controls and in-process inspection for the manufacture of combat rations. The Statistical Process Control Plan for CRAMTD was approved by DPSC and a final SPC Manual released. Also developed and released were a cookbook for Beef Chunks and Gravy in Tray-Pack and the on-line quality control procedures. Several new concepts were examined as advanced on-line sensors. Recommendations for expanded work were developed and undertaken by the DOD. It was recommended that qualities relevant to food manufacturing control be quantified (Funded as DAAK60-92-C-0087); that key hardware and computer software to implement SPC at the CRAMTD site be acquired (funded as STP #12); and that the ability of a food manufacturing process to produce products be quantified (funded as STP #20).

Historically, quality inspection systems focused on out of spec material instead of providing control strategies to prevent defects from occurring. New inspection systems include Contractor Inspection Systems and Statistical Process Control. The overall objective of this Short Term Project was the design, development and demonstration of a plan for automated manufacturing process controls and in-process inspection for the manufacture of combat rations. The Statistical Process Control Plan for CRAMTD was approved by DPSC and a final SPC Manual released. Also developed and released were a cookbook for Beef Chunks and Gravy in Tray-Pack and the on-line quality control procedures. Several new concepts were examined as advanced on-line sensors. Recommendations for expanded work were developed and undertaken by the DOD. It was recommended that qualities relevant to food manufacturing control be quantified (Funded as DAAK60-92-C-0087); that key hardware and computer software to implement SPC at the CRAMTD site be acquired (funded as STP #12); and that the ability of a food manufacturing process to produce products be quantified (funded as STP #20).

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180 pages

This article is from Radiation Oncology (London, England) , volume 6 . Abstract Background: This study seeks to increase clinical operational efficiency and accelerator beam consistency by retrospectively investigating the application of statistical process control (SPC) to linear accelerator beam steering parameters to determine the utility of such a methodology in detecting changes prior to equipment failure (interlocks actuated). Methods: Steering coil currents (SCC) for the transverse and radial planes are set such that a reproducibly useful photon or electron beam is available. SCC are sampled and stored in the control console computer each day during the morning warm-up. The transverse and radial - positioning and angle SCC for photon beam energies were evaluated using average and range (Xbar-R) process control charts (PCC). The weekly average and range values (subgroup n = 5) for each steering coil were used to develop the PCC. SCC from September 2009 (annual calibration) until two weeks following a beam steering failure in June 2010 were evaluated. PCC limits were calculated using the first twenty subgroups. Appropriate action limits were developed using conventional SPC guidelines. Results: PCC high-alarm action limit was set at 6 standard deviations from the mean. A value exceeding this limit would require beam scanning and evaluation by the physicist and engineer. Two low alarms were used to indicate negative trends. Alarms received following establishment of limits (week 20) are indicative of a non-random cause for deviation (Xbar chart) and/or an uncontrolled process (R chart). Transverse angle SCC for 6 MV and 15 MV indicated a high-alarm 90 and 108 days prior to equipment failure respectively. A downward trend in this parameter continued, with high-alarm, until failure. Transverse position and radial angle SCC for 6 and 15 MV indicated low-alarms starting as early as 124 and 116 days prior to failure, respectively. Conclusion: Radiotherapy clinical efficiency and accelerator beam consistency may be improved by instituting SPC methods to monitor the beam steering process and detect abnormal changes prior to equipment failure.PACS numbers: 87.55n, 87.55qr, 87.56bd

This article is from Journal of Family & Community Medicine , volume 16 . Abstract Objective:: To use statistical control charts in a series of audits to improve the acceptance and consistant use of guidelines, and reduce the variations in prescription processing in primary health care. Methods:: A series of audits were done at the main satellite of King Saud Housing Family and Community Medicine Center, National Guard Health Affairs, Riyadh, where three general practitioners and six pharmacists provide outpatient care to about 3000 residents. Audits were carried out every fortnight to calculate the proportion of prescriptions that did not conform to the given guidelines of prescribing and dispensing. Simple random samples of thirty were chosen from a sampling frame of all prescriptions given in the two previous weeks. Thirty six audits were carried out from September 2004 to February 2006. P-charts were constructed around a parametric specification of non-conformities not exceeding 25%. Results:: Of the 1081 prescriptions, the most frequent non-conformity was failure to write generic names (35.5%), followed by the failure to record patient's weight (16.4%), pharmacist's name (14.3%), duration of therapy (9.1%), and the use of inappropriate abbreviations (6.0%). Initially, 100% of prescriptions did not conform to the guidelines, but within a period of three months, this came down to 40%. Conclusions:: A process of audits in the context of statistical process control is necessary for any improvement in the implementation of guidelines in primary care. Statistical process control charts are an effective means of visual feedback to the care providers.

This article is from Journal of Family & Community Medicine , volume 16 . Abstract Objective:: To use statistical control charts in a series of audits to improve the acceptance and consistant use of guidelines, and reduce the variations in prescription processing in primary health care. Methods:: A series of audits were done at the main satellite of King Saud Housing Family and Community Medicine Center, National Guard Health Affairs, Riyadh, where three general practitioners and six pharmacists provide outpatient care to about 3000 residents. Audits were carried out every fortnight to calculate the proportion of prescriptions that did not conform to the given guidelines of prescribing and dispensing. Simple random samples of thirty were chosen from a sampling frame of all prescriptions given in the two previous weeks. Thirty six audits were carried out from September 2004 to February 2006. P-charts were constructed around a parametric specification of non-conformities not exceeding 25%. Results:: Of the 1081 prescriptions, the most frequent non-conformity was failure to write generic names (35.5%), followed by the failure to record patient's weight (16.4%), pharmacist's name (14.3%), duration of therapy (9.1%), and the use of inappropriate abbreviations (6.0%). Initially, 100% of prescriptions did not conform to the guidelines, but within a period of three months, this came down to 40%. Conclusions:: A process of audits in the context of statistical process control is necessary for any improvement in the implementation of guidelines in primary care. Statistical process control charts are an effective means of visual feedback to the care providers.

This article is from Journal of Family & Community Medicine , volume 16 . Abstract Objective:: To use statistical control charts in a series of audits to improve the acceptance and consistant use of guidelines, and reduce the variations in prescription processing in primary health care. Methods:: A series of audits were done at the main satellite of King Saud Housing Family and Community Medicine Center, National Guard Health Affairs, Riyadh, where three general practitioners and six pharmacists provide outpatient care to about 3000 residents. Audits were carried out every fortnight to calculate the proportion of prescriptions that did not conform to the given guidelines of prescribing and dispensing. Simple random samples of thirty were chosen from a sampling frame of all prescriptions given in the two previous weeks. Thirty six audits were carried out from September 2004 to February 2006. P-charts were constructed around a parametric specification of non-conformities not exceeding 25%. Results:: Of the 1081 prescriptions, the most frequent non-conformity was failure to write generic names (35.5%), followed by the failure to record patient's weight (16.4%), pharmacist's name (14.3%), duration of therapy (9.1%), and the use of inappropriate abbreviations (6.0%). Initially, 100% of prescriptions did not conform to the guidelines, but within a period of three months, this came down to 40%. Conclusions:: A process of audits in the context of statistical process control is necessary for any improvement in the implementation of guidelines in primary care. Statistical process control charts are an effective means of visual feedback to the care providers.

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A subset of Statistical Process Control (SPC) methodology known as Control Charting is introduced. SPC methodology is a collection of graphical and inferential statistics techniques used to study the progress of phenomena over time. The types of control charts covered are the null X (mean), R (Range), X (individual observations), MR (moving range), p (measure of successes), and U (number of events per unit). Uses of charts in the binomial case and the Poisson case are considered. These charts provide the researcher with a combined graphical and hypothesis testing procedure for assessing the stability of various types of data collected across time. The details of constructing each of these charts and the methods for hypothesis testing are described. Examples drawn from the field of education illustrate chart construction. SPC procedures described are understandable by researchers who are not mathematically oriented; whereas other procedures often recommended in the statistically-oriented literature on single-subject design are not easily understood by these researchers. All of the SPC techniques introduced can be modified to allow the analysis of data from one-way multiple group designs and factorial designs. Although these charts do not represent all the control charting techniques used in process control, they are the ones most applicable to educational research. Five tables present sample data, and seven graphs illustrate SPC charts. (SLD)

This module for a 1-semester Total Quality Management (TQM) course for high school or community college students gives a brief introduction to some statistical tools. It includes a section on process variation that is intended to familiarize students with the causes of variation such as common and special causes. Statistical definitions are given for common statistical terms such as "mean" and "standard deviation," with examples to aid students in understanding the meanings of the terms. Run charts and control charts are described. An eight-step process is defined for the use of control charts, and two examples are provided. An example of a run chart also is provided. A bibliography lists six references. Handouts and transparency masters are included. (KC)

One may receive the most benefit from an evaluation of an educational program or the performance of a teacher if the evaluation process is approached from a Total Quality Management (TQM) point of view. Under the philosophy of TQM, the purpose of any evaluation process is to provide feedback for the continual improvement of the educational process that is being evaluated. In the process of obtaining this feedback, the evaluator must be cognizant of two concepts that are basic to the TQM philosophy. First, an educational program or the work of a teacher can be viewed as a system. Second, since every system is impacted by numerous factors, any outcome variable of the system will experience variation. The implication of these two concepts is that an educational evaluator must be able to separate the impact of a change in an educational system from the noise of that system. This paper discusses how an evaluator can increase the ability of an individual values chart to separate a signal in an outcome variable, a signal caused by a change in the educational program or in the teacher's pedagogical practices, from the normal variation found in that variable when the chart is used in conjunction with the Western Electric Zone tests. In an individual values chart, the outcome variable is plotted on a chart in which the time factor and the outcome variable are placed on the X axis and Y axis respectively. The Western Electric Company has proposed four statistical control detection tests to be used in conjunction with control charts to increase the chances of detecting such a signal. (Contains two tables, three figures, and nine references.) (Author/SLD)

The 1996 Summer Faculty Fellowship Program and Kennedy Space Center (KSC) served as the basis for a research effort into statistical process control for KSC processing. The effort entailed several tasks and goals. The first was to develop a customized statistical process control (SPC) course for the Safety and Mission Assurance Trends Analysis Group. The actual teaching of this course took place over several weeks. In addition, an Internet version of the same course complete with animation and video excerpts from the course when it was taught at KSC was developed. The application of SPC to shuttle processing took up the rest of the summer research project. This effort entailed the evaluation of SPC use at KSC, both present and potential, due to the change in roles for NASA and the Single Flight Operations Contractor (SFOC). Individual consulting on SPC use was accomplished as well as an evaluation of SPC software for KSC use in the future. A final accomplishment of the orientation of the author to NASA changes, terminology, data format, and new NASA task definitions will allow future consultation when the needs arise.

The research was conducted to determine if the study program of the career of industrial processes Technological University of Chihuahua, 1 year after that it was certified by CACEI, continues achieving the established indicators and ISO 9001: 2008, implementing quality tools, monitoring of essential indicators are determined, flow charts are developed and introduced to strengthen the quality management system, the website was designed to systematize finally implemented for each requirement primary control indicator and their respective metric to measure performance and determined that 17 indicators are being met extensively, five indicators were moderately satisfied and 3 indicators are not met, it has a 12% failure of the primary indicators measured during the study period 2014-2015.

The research was conducted to determine if the study program of the career of industrial processes Technological University of Chihuahua, 1 year after that it was certified by CACEI, continues achieving the established indicators and ISO 9001: 2008, implementing quality tools, monitoring of essential indicators are determined, flow charts are developed and introduced to strengthen the quality management system, the website was designed to systematize finally implemented for each requirement primary control indicator and their respective metric to measure performance and determined that 17 indicators are being met extensively, five indicators were moderately satisfied and 3 indicators are not met, it has a 12% failure of the primary indicators measured during the study period 2014-2015.

Efforts to prevent psychopathology from an early stage are likely most effective when targeted at the right moment in time. Just-in-time adaptive interventions (JITAIs) are personalized smartphone interventions that aim to target these moments by monitoring people in their daily lives. An interesting target for such moments of vulnerability is the transdiagnostic process of delayed recovery of affect following daily life stress, which has been shown to play a role in the development of mental illness. However, the exact point at which the recovery begins to put an individual at risk is not yet established. The current study aims to define thresholds for delayed affective recovery that are associated with increased risk for the development of mental illness. We use the experience sampling method (ESM) to investigate affective recovery following daily life stressors. We use statistical process control (SPC) to establish norms of affective stress recovery duration and slopes using general population data and subsequently use these to create control limits (thresholds) for healthy recoveries. We can then apply this control limit to individual recoveries from various populations, and test whether they can accurately distinguish between healthy and at-risk individuals. Our results will reveal whether control limits derived from SPC can be used to assess if an individual is at risk for psychopathology. Identifying thresholds for delayed affective recovery from daily-life stress may provide a very concrete timing for JITAI interventions for individuals at risk for the development of psychopathology.

In recent years there has been a push within NASA to use statistical techniques to improve the quality of production. Two areas where statistics are used are in establishing product and process quality control of flight hardware and in evaluating the uncertainty of calibration of instruments. The Flight Systems Quality Engineering branch is responsible for developing and assuring the quality of all flight hardware; the statistical process control methods employed are reviewed and evaluated. The Measurement Standards and Calibration Laboratory performs the calibration of all instruments used on-site at JSC as well as those used by all off-site contractors. These calibrations must be performed in such a way as to be traceable to national standards maintained by the National Institute of Standards and Technology, and they must meet a four-to-one ratio of the instrument specifications to calibrating standard uncertainty. In some instances this ratio is not met, and in these cases it is desirable to compute the exact uncertainty of the calibration and determine ways of reducing it. A particular example where this problem is encountered is with a machine which does automatic calibrations of force. The process of force calibration using the United Force Machine is described in detail. The sources of error are identified and quantified when possible. Suggestions for improvement are made.

In recent years there has been a push within NASA to use statistical techniques to improve the quality of production. Two areas where statistics are used are in establishing product and process quality control of flight hardware and in evaluating the uncertainty of calibration of instruments. The Flight Systems Quality Engineering branch is responsible for developing and assuring the quality of all flight hardware; the statistical process control methods employed are reviewed and evaluated. The Measurement Standards and Calibration Laboratory performs the calibration of all instruments used on-site at JSC as well as those used by all off-site contractors. These calibrations must be performed in such a way as to be traceable to national standards maintained by the National Institute of Standards and Technology, and they must meet a four-to-one ratio of the instrument specifications to calibrating standard uncertainty. In some instances this ratio is not met, and in these cases it is desirable to compute the exact uncertainty of the calibration and determine ways of reducing it. A particular example where this problem is encountered is with a machine which does automatic calibrations of force. The process of force calibration using the United Force Machine is described in detail. The sources of error are identified and quantified when possible. Suggestions for improvement are made.

In recent years there has been a push within NASA to use statistical techniques to improve the quality of production. Two areas where statistics are used are in establishing product and process quality control of flight hardware and in evaluating the uncertainty of calibration of instruments. The Flight Systems Quality Engineering branch is responsible for developing and assuring the quality of all flight hardware; the statistical process control methods employed are reviewed and evaluated. The Measurement Standards and Calibration Laboratory performs the calibration of all instruments used on-site at JSC as well as those used by all off-site contractors. These calibrations must be performed in such a way as to be traceable to national standards maintained by the National Institute of Standards and Technology, and they must meet a four-to-one ratio of the instrument specifications to calibrating standard uncertainty. In some instances this ratio is not met, and in these cases it is desirable to compute the exact uncertainty of the calibration and determine ways of reducing it. A particular example where this problem is encountered is with a machine which does automatic calibrations of force. The process of force calibration using the United Force Machine is described in detail. The sources of error are identified and quantified when possible. Suggestions for improvement are made.

In this study a cumulative-sum (CUSUM) procedure from the theory of Statistical Process Control was modified and applied in the context of person-fit analysis in a computerized adaptive testing (CAT) environment. Six person-fit statistics were proposed using the CUSUM procedure, and three of them could be used to investigate the CAT in online test taking. The usefulness of these statistics was explored in a small simulation study. In most CUSUM procedures standard normally distributed statistics are used. Based on this normality, boundaries can be determined to decide when a process is out of control. The statistics proposed in this study, however, are not standard normally distributed, and therefore, in this study, boundaries were determined using simulated data. The study investigated whether the numerical values of the upper and lower threshold were dependent on the latent trait, theta. Results show that the upper and lower bound were rather stable across theta-levels. However, the height of the boundaries was dependent on the particular statistic chosen. (Contains 12 figures and 14 references.) (Author/SLD)

In this study a cumulative-sum (CUSUM) procedure from the theory of Statistical Process Control was modified and applied in the context of person-fit analysis in a computerized adaptive testing (CAT) environment. Six person-fit statistics were proposed using the CUSUM procedure, and three of them could be used to investigate the CAT in online test taking. The usefulness of these statistics was explored in a small simulation study. In most CUSUM procedures standard normally distributed statistics are used. Based on this normality, boundaries can be determined to decide when a process is out of control. The statistics proposed in this study, however, are not standard normally distributed, and therefore, in this study, boundaries were determined using simulated data. The study investigated whether the numerical values of the upper and lower threshold were dependent on the latent trait, theta. Results show that the upper and lower bound were rather stable across theta-levels. However, the height of the boundaries was dependent on the particular statistic chosen. (Contains 12 figures and 14 references.) (Author/SLD)

In this study a cumulative-sum (CUSUM) procedure from the theory of Statistical Process Control was modified and applied in the context of person-fit analysis in a computerized adaptive testing (CAT) environment. Six person-fit statistics were proposed using the CUSUM procedure, and three of them could be used to investigate the CAT in online test taking. The usefulness of these statistics was explored in a small simulation study. In most CUSUM procedures standard normally distributed statistics are used. Based on this normality, boundaries can be determined to decide when a process is out of control. The statistics proposed in this study, however, are not standard normally distributed, and therefore, in this study, boundaries were determined using simulated data. The study investigated whether the numerical values of the upper and lower threshold were dependent on the latent trait, theta. Results show that the upper and lower bound were rather stable across theta-levels. However, the height of the boundaries was dependent on the particular statistic chosen. (Contains 12 figures and 14 references.) (Author/SLD)

In this study a cumulative-sum (CUSUM) procedure from the theory of Statistical Process Control was modified and applied in the context of person-fit analysis in a computerized adaptive testing (CAT) environment. Six person-fit statistics were proposed using the CUSUM procedure, and three of them could be used to investigate the CAT in online test taking. The usefulness of these statistics was explored in a small simulation study. In most CUSUM procedures standard normally distributed statistics are used. Based on this normality, boundaries can be determined to decide when a process is out of control. The statistics proposed in this study, however, are not standard normally distributed, and therefore, in this study, boundaries were determined using simulated data. The study investigated whether the numerical values of the upper and lower threshold were dependent on the latent trait, theta. Results show that the upper and lower bound were rather stable across theta-levels. However, the height of the boundaries was dependent on the particular statistic chosen. (Contains 12 figures and 14 references.) (Author/SLD)

In this study a cumulative-sum (CUSUM) procedure from the theory of Statistical Process Control was modified and applied in the context of person-fit analysis in a computerized adaptive testing (CAT) environment. Six person-fit statistics were proposed using the CUSUM procedure, and three of them could be used to investigate the CAT in online test taking. The usefulness of these statistics was explored in a small simulation study. In most CUSUM procedures standard normally distributed statistics are used. Based on this normality, boundaries can be determined to decide when a process is out of control. The statistics proposed in this study, however, are not standard normally distributed, and therefore, in this study, boundaries were determined using simulated data. The study investigated whether the numerical values of the upper and lower threshold were dependent on the latent trait, theta. Results show that the upper and lower bound were rather stable across theta-levels. However, the height of the boundaries was dependent on the particular statistic chosen. (Contains 12 figures and 14 references.) (Author/SLD)

Successful ground processing at KSC requires that flight hardware and ground support equipment conform to specifications at tens of thousands of checkpoints. Knowledge of conformance is an essential requirement for launch. That knowledge of conformance at every requisite point does not, however, enable identification of past problems with equipment, or potential problem areas. This paper describes how the introduction of Statistical Process Control and Process Capability Analysis identification procedures into existing shuttle processing procedures can enable identification of potential problem areas and candidates for improvements to increase processing performance measures. Results of a case study describing application of the analysis procedures to Thermal Protection System processing are used to illustrate the benefits of the approaches described in the paper.

The U.S. Navy is concerned with receiving high quality hybrid microelectronic circuits. The Navy recognizes that in order to obtain high quality circuits a manufacturer must have an effective statistical process control (SPC) program implemented. The implementation of effective SPC programs is an objective of the military hybrid microelectronics industry. Often the smaller sized manufacturers in the industry have little SPC implementation, while the larger manufacturers have practices originally developed for the control of other product lines outside the hybrid technology area. The industry recognizes that SPC programs will result in high quality hybrid microcircuits which the U.S. Navy requires. In the past, the goal of the industry had not been to put in effective process control methods, but to merely meet the government military standards on the quality of the hybrids they produce. This practice, at best, resulted in a 'hit or miss' situation when it comes to hybrid microcircuit assemblies meeting military standards. The U.S. Navy through its MicroCIM program has been challenging and working with the industry in the area of SPC practice methods. The major limitations so far have been a lack of available sensors for the real time collection of effective SPC data on the factory floor. This paper will discuss the Navy's efforts in bringing about effective SPC programs in the military hybrid manufacturing industry.