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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)

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.

This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills in working with line graphs and teaching them how to plot points on a graph. The guide is divided into five sections. The first section contains the following preliminary information: individual assessment sheet, instructor notes, and primary objectives. The second section consists of lessons and worksheets on the following topics: graph-related vocabulary, types of graphs and their purposes, introduction to control charts, and plotting points. The final three sections contain answers to the worksheets, a posttest, and a posttest answer key. (MN)

This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills in working with line graphs and teaching them how to plot points on a graph. The guide is divided into five sections. The first section contains the following preliminary information: individual assessment sheet, instructor notes, and primary objectives. The second section consists of lessons and worksheets on the following topics: graph-related vocabulary, types of graphs and their purposes, introduction to control charts, and plotting points. The final three sections contain answers to the worksheets, a posttest, and a posttest answer key. (MN)

180 pages

180 pages

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.

Different methods are used in an organization to improve productivity, one such method is Statistical process Control(SPC).Statistical process control is a collection of tools, that when used together can result in process stability and variance reduction, thereby leading to a more streamlined production process. This paper presents a case study of SPC to improve the performance of current process by reducing the variability in the dimension of parts produced, there by diminish rejections and improving the process. By carrying out mathematical calculations and using various SPC tools, process capability study was done under existing conditions, some improvements were done in the existing welding fixture used for producing the part to improve their capabilitiy indices. In this study after the application of SPC tools and integrating the suggested changes in existing process, great improvements were seen, as such the capability indices which were 0.1.1&0.38 respectively for the existing process, increased to 1.91&1.50 respectively for the improved process, thereby representing good process performance with higher strength. Bhushan S. Jogi | Lekrajsing R. Gour | Nikhil Turkar"Process Improvement Using Statistical Process Control in a Small Scale Industry" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: http://www.ijtsrd.com/papers/ijtsrd17144.pdf http://www.ijtsrd.com/engineering/industrial-engineering/17144/process-improvement-using-statistical-process-control-in-a-small-scale-industry/bhushan-s-jogi

297 p. 24 cm

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 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 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.

The inverse gaussian distribution can be used to model processes with skewed output. In this thesis, several Shewhard and CUSUM control schemes are developed for the inverse gaussian distribution. The behavior of these schemes is described. A new type of Shewhart chart, a self-starting Shewhart chart, is developed and applied to the inverse gaussian distribution. A second new type of control chart, which controls simultaneously for multiple parameters, is developed and shown to have some useful properties. Predictive Shewhart schemes, based on a diffuse prior, are developed and used for control.

Military commanders determine the appropriate Force Protection measures to protect their units from a wide variety of threats based on their assessment of the enemy threat in the specific situation They currently have no statistical tool from which to base their assessment of the threat, or to recognize changes in the current situation. In Operations Other Than War (OOTW), environments where the enemy is disorganized and incapable of mounting a deception plan, staffs could model hostile events as stochastic events and use statistical methods to detect changes to the process. This thesis developed a statistical tool, based on Cumulative Sum (CUSUM) and Shewhart Charts, that military leaders can use in OOTW environments to recognize statistically significant changes in the situation. The tool applies current univariate control chart methods, as well as an original nonparametric multivariate control scheme developed in this thesis, to North Atlantic Treaty Organization (NATO) Stabilization Force (SFOR) incident data. The tool enables commanders to identify isolated and persistent shifts in the means of the data categories or shifts in the correlation of three data categories. By recognizing changes in the current situation, military leaders have a basis from which to change their force protection measures and better protect their unit.

This instructional guide, one of a series developed by the Technical Education Advancement Modules (TEAM) project, is a 20-hour advanced statistical process control (SPC) and quality improvement course designed to develop the following competencies: (1) understanding quality systems; (2) knowing the process; (3) solving quality problems; and (4) working with SPC. 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 seven sections: (1) introduction to quality in the 1990s; (2) know your process--flow charting; (3) solving quality problems--problem-solving techniques and data collection; (4) data analysis techniques; (5) Statistical Process Control; (6) process capability studies; and (7) nontraditional SPC methods--control charts. Frameworks for various processes are included at the end of this manual. (NLA)

This article is from BMC Medical Research Methodology , volume 12 . Abstract Background: Few studies discuss the indicators used to assess the effect on cost containment in healthcare across hospitals in a single-payer national healthcare system with constrained medical resources. We present the intraclass correlation coefficient (ICC) to assess how well Taiwan constrained hospital-provided medical services in such a system. Methods: A custom Excel-VBA routine to record the distances of standard deviations (SDs) from the central line (the mean over the previous 12 months) of a control chart was used to construct and scale annual medical expenditures sequentially from 2000 to 2009 for 421 hospitals in Taiwan to generate the ICC. The ICC was then used to evaluate Taiwan’s year-based convergent power to remain unchanged in hospital-provided constrained medical services. A bubble chart of SDs for a specific month was generated to present the effects of using control charts in a national healthcare system. Results: ICCs were generated for Taiwan’s year-based convergent power to constrain its medical services from 2000 to 2009. All hospital groups showed a gradually well-controlled supply of services that decreased from 0.772 to 0.415. The bubble chart identified outlier hospitals that required investigation of possible excessive reimbursements in a specific time period. Conclusion: We recommend using the ICC to annually assess a nation’s year-based convergent power to constrain medical services across hospitals. Using sequential control charts to regularly monitor hospital reimbursements is required to achieve financial control in a single-payer nationwide healthcare system.

Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability) although, there are constantly more approaches to non-normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation -S/R) individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution) therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes. / W artykule dotyczącym metod i technik prognozowania wartości kluczowych wskaźników efektywności obsługi (ang. Key Performance Indicators) zdefiniowano oraz sklasyfikowano te wskaźniki. Przedstawiono wymagania oraz sposób doboru wskaźników KPI. Dokonano przeglądu, a także scharakteryzowano metody i techniki prognozowania stanu organizacji utrzymania ruchu. Przedstawiono koncepcję wykorzystania wybranych metod oraz narzędzi gromadzenia oraz przetwarzania danych dla potrzeb prognozowania tego stanu.

Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability) although, there are constantly more approaches to non-normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation -S/R) individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution) therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes. / W artykule dotyczącym metod i technik prognozowania wartości kluczowych wskaźników efektywności obsługi (ang. Key Performance Indicators) zdefiniowano oraz sklasyfikowano te wskaźniki. Przedstawiono wymagania oraz sposób doboru wskaźników KPI. Dokonano przeglądu, a także scharakteryzowano metody i techniki prognozowania stanu organizacji utrzymania ruchu. Przedstawiono koncepcję wykorzystania wybranych metod oraz narzędzi gromadzenia oraz przetwarzania danych dla potrzeb prognozowania tego stanu.

Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability) although, there are constantly more approaches to non-normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation -S/R) individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution) therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes. / W artykule dotyczącym metod i technik prognozowania wartości kluczowych wskaźników efektywności obsługi (ang. Key Performance Indicators) zdefiniowano oraz sklasyfikowano te wskaźniki. Przedstawiono wymagania oraz sposób doboru wskaźników KPI. Dokonano przeglądu, a także scharakteryzowano metody i techniki prognozowania stanu organizacji utrzymania ruchu. Przedstawiono koncepcję wykorzystania wybranych metod oraz narzędzi gromadzenia oraz przetwarzania danych dla potrzeb prognozowania tego stanu.

Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability) although, there are constantly more approaches to non-normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation -S/R) individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution) therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes. / W artykule dotyczącym metod i technik prognozowania wartości kluczowych wskaźników efektywności obsługi (ang. Key Performance Indicators) zdefiniowano oraz sklasyfikowano te wskaźniki. Przedstawiono wymagania oraz sposób doboru wskaźników KPI. Dokonano przeglądu, a także scharakteryzowano metody i techniki prognozowania stanu organizacji utrzymania ruchu. Przedstawiono koncepcję wykorzystania wybranych metod oraz narzędzi gromadzenia oraz przetwarzania danych dla potrzeb prognozowania tego stanu.

Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability) although, there are constantly more approaches to non-normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation -S/R) individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution) therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes. / W artykule dotyczącym metod i technik prognozowania wartości kluczowych wskaźników efektywności obsługi (ang. Key Performance Indicators) zdefiniowano oraz sklasyfikowano te wskaźniki. Przedstawiono wymagania oraz sposób doboru wskaźników KPI. Dokonano przeglądu, a także scharakteryzowano metody i techniki prognozowania stanu organizacji utrzymania ruchu. Przedstawiono koncepcję wykorzystania wybranych metod oraz narzędzi gromadzenia oraz przetwarzania danych dla potrzeb prognozowania tego stanu.

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 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.

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

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.

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)

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.

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.

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.

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)

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).

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.

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.

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 instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills and instructing them in basic calculator operation. The guide is divided into five sections. The first section contains the following preliminary information: individual assessment sheet, instructor notes, and primary objectives. The second section is a course outline, and the third section contains the module lessons and worksheets, which are devoted to the following topics: using a calculator, calculating totals, calculating averages, calculating process averages, rounding off decimals, and calculating ranges. The final two sections consist of answers to the worksheets and pretests and posttests. (MN)

This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills and instructing them in basic calculator operation. The guide is divided into five sections. The first section contains the following preliminary information: individual assessment sheet, instructor notes, and primary objectives. The second section is a course outline, and the third section contains the module lessons and worksheets, which are devoted to the following topics: using a calculator, calculating totals, calculating averages, calculating process averages, rounding off decimals, and calculating ranges. The final two sections consist of answers to the worksheets and pretests and posttests. (MN)

This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills and instructing them in basic calculator operation. The guide is divided into five sections. The first section contains the following preliminary information: individual assessment sheet, instructor notes, and primary objectives. The second section is a course outline, and the third section contains the module lessons and worksheets, which are devoted to the following topics: using a calculator, calculating totals, calculating averages, calculating process averages, rounding off decimals, and calculating ranges. The final two sections consist of answers to the worksheets and pretests and posttests. (MN)

This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills and instructing them in basic calculator operation. The guide is divided into five sections. The first section contains the following preliminary information: individual assessment sheet, instructor notes, and primary objectives. The second section is a course outline, and the third section contains the module lessons and worksheets, which are devoted to the following topics: using a calculator, calculating totals, calculating averages, calculating process averages, rounding off decimals, and calculating ranges. The final two sections consist of answers to the worksheets and pretests and posttests. (MN)

This research effort focuses on applying statistical process control (SPC) techniques to the departure reliability improvement process for Air Mobility Command, Mission Reliability Office. Basic SPC methods, including Pareto analysis, cause and effect diagrams, and control charts are determined to be effective tools for analyzing and assessing departure reliability. In addition, two more alternative measures of effectiveness for departure reliability are evaluated and compared using AMC's data. SPC methods are also shown to be useful in assessing in performance and in determining the reporting frequency for on-time performance information. Additional statistical analyses are conducted, including on-way analyses of variance, hypothesis tests, autocorrelation of time series and normal probability plots.

This paper presents a procedure by which institutional researchers can determine whether gender-salary discrimination exists at an institution of higher education. The procedure utilizes a statistical quality control tool, which is referred to as setting the process aim. This procedure is based on the premise that salaries are determined by a salary system. Since the values produced by any system will exhibit some variation, the value used to measure the difference between the salaries of the female and male faculty, which is generated by multiple regression analysis of the salary data, will vary from year to year. In order for institutional researchers to determine if the salary system has led to gender-salary discrimination, the noise of the system must be separated from a gender salary discrimination signal. Applying the process aim setting technique to the values obtained from the multiple regression analyses of multi-year data will enable researchers to separate a gender salary discrimination signal from the normal variation in those values. A demonstration of this technique, using hypothetical salary data, is included. (Contains 17 references.) (Author/MDM)

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