Applying a coupled expert system to quality control charts

Quality control charts are a common tool used for control of a manufacturing process. Expert systems can serve as a valuable tool to automate the different phases in the use of quality control charts. The authors have developed a coupled expert system to select a proper control chart, optimize the design of the selected control chart, analyze the chart to identify an out-of-control process and suggest the reason(s) for an out-of-control process. The intent of this paper is to discuss the main features of this coupled expert system.

An expert system shell called PCPLUS helps a user select the most appropriate control chart and identify the reason(s) for a process to be out-of-control. FORTRAN was used to implement the modules for design, plotting, and analysis of the selected control chart.     

A new monitoring design for uni-variate statistical quality control charts

In this research, an iterative approach is employed to analyze and classify the states of uni-variate quality control systems. To do this, a measure (called the belief that process is in-control) is first defined and then an equation is developed to update the belief recursively by taking new observations on the quality characteristic under consideration. Finally, the upper and the lower control limits on the belief are derived such that when the updated belief falls outside the control limits an out-of-control alarm is received. In order to understand the proposed methodology and to evaluate its performance, some numerical examples are provided by means of simulation. In these examples, the in and out-of-control average run lengths (ARL) of the proposed method are compared to the corresponding ARL’s of the optimal EWMA, Shewhart EWMA, GEWMA, GLR, and CUSUM[11] methods within different scenarios of the process mean shifts. The simulation results show that the proposed methodology performs better than other charts for all of the examined shift scenarios. In addition, for an autocorrelated AR(1) process, the performance of the proposed control chart compared to the other existing residual-based control charts turns out to be promising.     

Applying quality control charts to the analysis of single-subject data sequences

Techniques from the field of quality control can be used to classify the quality of individual samples of physical or cognitive performance. After stable baselines have been established for an individual, deviations in performance can be evaluated using control charts. The effectiveness of this approach in evaluating cognitive performance was tested using databases collected under a variety of risk factors. The sensitivity and specificity characteristics of Shewhart, cumulative-sum (CUSUM), and exponentially weighted moving average (EWMA) control charts were determined for a total of 174 trials involving 10 participants and 23 cognitive performance assessment measures. The most effective technique in each case was typically a function of the specific performance measure and the type of performance change being evaluated. Sensitivity and specificity for the best techniques were as high as 100%. This study demonstrated the usefulness of quality control charts as a tool to evaluate individual participant performance over time. Actual or potential applications of this research include readiness-to-perform screening of industrial workers in order to improve the health and safety of the workforce.     

Integrating active localization into high-level robot control systems

High-level control systems are designed to enable mobile robots to successfully perform complex missions such as office delivery and survillance tasks. For that purpose they have to control, coordinate, and monitor different kinds of subtasks like navigation, manipulation, and perception. An important aspect of the effectiveness of high-level control systems is the ability to cope with failures that occur during the execution of such subtaks. In this paper we focus on the particular subtask of estimating the position of the robot and show how to achieve its robust integration into the high-level control system. The principle of this integration is to monitor the certainty of the position estimation and to autonomously relocalize the robot whenever the uncertainly grows too large. We present a localization approach which accurately and efficiently keeps track of the robot's position. Furthermore, it provides a measure for detecting localization failures and it is able to autonomously relocalize the robot in such situations. In addition to this, we introduce structured reactive plans, which can be interrupted by such active localization processes at any point in time and allow the robot to complete its mission afterwards. Our method has been implemented and shown to be robust in long-term experiments involving a typical office delivery scenario.     

A proposed method to use electronic spreadsheets to develop quality control charts

The combination of the personal computer and spreadsheet software provide an inexpensive and accurate capability to use control charts for the quality contol average and standard deviation. The popular spreadsheet program, Lotus 17ndash;2–3, is limited to graphing six variables. Eight are needed to graph both the average and standard deviation control charts on a single screen. This article examines several methods to overcome this limitation. All calculation needed are performed and a series of charts are drawn for the readers examination.     

Software quality assurance economics

ContextSoftware companies invest in quality assurance in order to lower software development and maintenance cost, and to increase revenue and profit margins. To contribute to increase of net income, a quality assurance organization has to consider cost and value of the testware involved in assuring quality of software artifacts, such as requirements, specifications, designs, and code.ObjectiveThis paper proposes a set of economic metrics: testware return on investment, inflation, and cost and value sensitivity to artifact changes and time passage. The paper proposes a set of guidelines on lowering testware cost, on increasing value, on maximizing return on investment, and on when to release.MethodThis paper presents an industrial case study data on the relation between test case cost and value, and on cost and value sensitivity to time passage and artifact changes.ResultsThe industrial case study showed return on investment on test cases of up to 200%, deflation of up to −2% per month, undesirable economic effects, such as test case cost outpacing test case value and rapid test case value depreciation based on time passage.ConclusionA viable QA organization should measure and improve test case return on investment, inflation, and cost and value sensitivity to artifact changes and time passage.     

A control point methodology for CUSUM control charts

A control point methodology (CPM) is proposed for implementation of graphical cumulative-sum (CUSUM) control charts on computers. Currently, most computer implementation of CUSUM charts is based on tabular form which loses the distinguished look of CUSUM statistics and V-mask. The more intuitive graphical CUSUM charts are not popular due to the difficulty of computer implementation. CPM removes the need to store all CUSUM points and thus reduces computing time. Examples are given to show that the proposed method can be applied to CUSUM for both means and ranges.     

Process control using VSI cause selecting control charts

The article considers the variable process control scheme for two dependent process steps with incorrect adjustment. Incorrect adjustment of a process may result in shifts in process mean, process variance, or both, ultimately affecting the quality of products. We construct the variable sampling interval (VSI) Z_{[`(X)]</sub>-Z<sub>SX<sup>2</sup></sub>{Z_{\overline{X}}-Z_{S_X^2}} and Z<sub>[`(e)]}-Z_Se²{Z_{\bar{{e}}}-Z_{S_e^2}} control charts to effectively monitor the quality variable produced by the first process step with incorrect adjustment and the quality variable produced by the second process step with incorrect adjustment, respectively. The performance of the proposed VSI control charts is measured by the adjusted average time to signal derived using a Markov chain approach. An example of the cotton yarn producing system shows the application and performance of the proposed joint VSI Z_{[`(X)]</sub> -Z<sub>SX<sup>2</sup></sub> {Z_{\overline{X}} -Z_{S_X^2 }} and Z<sub>[`(e)]} -Z_Se² {Z_{\bar{{e}}} -Z_{S_e^2 }} control charts in detecting shifts in mean and variance for the two dependent process steps with incorrect adjustment. Furthermore, the performance of the VSI Z_{[`(X)]</sub>-Z<sub>SX<sup>2</sup></sub> {Z_{\overline{X}}-Z_{S_X^2 }} and Z<sub>[`(e)]} -Z_Se² {Z_{\bar{{e}}} -Z_{S_e^2 }} control charts and the fixed sampling interval Z_{[`(X)]</sub> -Z<sub>SX<sup>2</sup></sub> {Z_{\overline{X}} -Z_{S_X^2 }} and Z<sub>[`(e)]} -Z_Se² {Z_{\bar{{e}}} -Z_{S_e^2 }} control charts are compared by numerical analysis results. These demonstrate that the former is much faster in detecting small and median shifts in mean and variance. When quality engineers cannot specify the values of variable sampling intervals, the optimum VSI Z_{[`(X)]</sub>-Z<sub>SX<sup>2</sup></sub> {Z_{\overline{X}}-Z_{S_X^2 }} and Z<sub>[`(e)]} -Z_Se² {Z_{\bar{{e}}} -Z_{S_e^2 }} control charts are also proposed by using the Quasi-Newton optimization technique.     

Integrating testability into microsystems

 The integration of sensors and actuators with microelectronics into either compact packages or onto a single silicon die is likely to be of major technological importance over the next decade. These systems are referred to as Microsystems or Micro-Electro-Mechanical-Systems (MEMS). One obstacle to mass-market introduction are difficulties with quality and reliability verification. This paper outlines the difficulties of testing microsystems, shows approaches of test generation and verification transferable from the mixed-signal Integrated-Circuit (IC) domain, and demonstrates an on-line test designed for bridge-type, micromachined accelerometer and pressure sensors [1]. Received: 31 October 1996 / Accepted: 14 November 1996     

Robust control charts for time series data

This article presents a control chart for time series data, based on the one-step-ahead forecast errors of the Holt–Winters forecasting method. We use robust techniques to prevent that outliers affect the estimation of the control limits of the chart. Moreover, robustness is important to maintain the reliability of the control chart after the occurrence of alarm observations. The properties of the new control chart are examined in a simulation study and on a real data example.     

Beta control charts for monitoring fraction data

p-Charts and np-Charts are commonly used in monitoring variables of the fraction type and these charts assume that the monitored variables are binomially distributed. In this paper we propose a new control chart called Beta Charts, for monitoring fraction data (p). The Beta Chart presents the control limits based on the Beta probability distribution. It was applied for monitoring the variables in three real studies, and it was compared to the control limits with three schemes. The comparative analysis showed that: (i) Beta approximation to the Binomial distribution was more appropriate with values confined in the [0, 1]-interval; and (ii) the charts proposed were more sensitive to the average run length (ARL), in both in-control and out-of-control processes monitoring. The Beta Charts outperform the control charts analyzed for monitoring fraction data.     

Q control charts for negative binomial distribution

As we known, Q charts are SPC charts for approximate normal distribution. This paper proposes new kinds of Q charts for negative binomial random variable. First, define two transformations of approximate standard normal distribution for a negative binomial parameter p which it is known or unknown. Then, Q charts are constructed by transformed data, these Q charts are useful for monitoring process in real time from the beginning of sampling, especially, for p unknown in advance. In order to compare the goodness of the Q charts with conventional Shewhart charts with 3-sigma limits, an example is given. The results have shown that these Q charts are more efficient than classical Shewhart charts. Finally, some review are given.     

Behavioral economics in software quality engineering

This article describes empirical research results regarding the “history effect” in software quality evaluation processes. Most software quality models and evaluation processes models assume that software quality may be deterministically evaluated, especially when it is evaluated by experts. Consequently, software developers focus on the technical characteristics of the software product. A similar assumption is common in most engineering disciplines. However, in regard to other kinds of goods, direct violations of the assumption about objective evaluation were shown to be affected by the consequences of cognitive processes limitations. Ongoing discussion in the area of behavioral economics raises the question: are the experts prone to observation biases? If they are, then software quality models overlook an important aspect of software quality evaluation. This article proposes an experiment that aims to trace the influence of users’ knowledge on software quality assessment. Measuring the influence of single variables for the software quality perception process is a complex task. There is no valid quality model for the precise measurement of product quality, and consequently software engineering does not have tools to freely manipulate the quality level for a product. This article proposes a simplified method to manipulate the observed quality level, thereby making it possible to conduct research. The proposed experiment has been conducted among professional software evaluators. The results show the significant negative influence (large effect size) of negative experience of users on final opinion about software quality regardless of its actual level.     

Integrating skills into multi-agent systems

Currently, an important topic of robotic research is the design and development of multi-agent robot systems (MASs). In these a number of autonomous robots cooperate and coordinate themselves in order to pursue given goals. The agents of an MAS not only have to work autonomously or in cooperation with other agents, but in dynamic, relatively unstructured environments. Therefore, the agents require agent-specific but flexible skills to cope with their tasks and the environment's variability. On the other hand, the actions to be performed by agents in an MAS have to meet certain requirements imposed by the MAS's structure. The representation of actions has to support planning, inter-agent communication, task negotiation etc. In this paper, we describe a method of combining the agent-specific nature of skills with the requirements for a general action knowledge representation inherent to MASs, by presenting elementary operations (EOs) that provide an appropriate interface.     

Integrating security into the curriculum

Computer security can be used as a vehicle to achieve accreditation goals for computer science and engineering programs, while at the same time engaging students with relevant, exciting topics. The authors' approach, based on educational outcomes, illustrates that security topics can contribute to an engineering program by fostering all skills required to produce graduates capable of critical thinking     

Integrating systems into the organization

Over the last thirty years, computer technology - hardware and software - has entered every phase of business and government. It has not been an easy or smooth transition, but much has been learned about the success factors of integrating systems into the organization.This paper adresses those factors - other than technical ones - which facilitate successful systems, which are in the nature of organizational attitude, behaviour and style. The roles of various functions vis-à-vis systems management are discussed.The paper concludes with some practical rules which have evolved with experience, intended to insure that systems are indeed useful and effective and therefore judged successful by the users and the developers.     

CUSUM control charts for monitoring optimal portfolio weights

A portfolio investor requires statistical tools for the timely detection of changes in the optimal portfolio composition. Several multivariate cumulative sum (CUSUM) control charts are proposed for the purpose of monitoring optimal portfolio weights. The ability of the CUSUM schemes to detect important types of changes in the optimal portfolio weights is analyzed in an extensive Monte Carlo simulation study. The empirical application of control charts shows that the proposed methodology can provide a significant reduction of the portfolio volatility.     

Optimization designs of the combined Shewhart-CUSUM control charts

This article presents the optimization design of the combined Shewhart chart and CUSUM chart ( chart in short) used in Statistical Process Control (SPC). While the optimization design effectively improves the overall performance of the chart over the entire process shift range, it does not increase difficulties in understanding and implementing this combined chart. A new feature pertaining to an additional charting parameter w (the exponential of the sample mean shift) is also investigated, with the hope of further enhancing the detection effectiveness of the chart. Moreover, this article provides the SPC practitioners with a design table to facilitate the designs of the charts. From this design table, the users can directly find the optimal values of the charting parameters, according to the design specifications. The design table makes the design of an chart as simple as the design of the simplest chart. In general, this article will help to enhance the detection effectiveness of the chart, and facilitate and promote its applications in SPC.