应用统计过程控制监控软件测试过程

统计过程控制(SPC)是通过使用控制图来制定过程决策和预测过程行为的一种质量控制方法.SPC的方法用于软件过程,可以通过描述过程行为来监控过程的稳定性.讨论了将SPC应用于软件测试过程,针对测试过程中所度量的不同分布形式的数据而采用不同计算方式应用SPC的控制图,然后根据控制图判断测试过程是否稳定,并分析可能存在的可归属原因.     

Statistical games and software tools for quality assurance based on statistical process control

This paper proposes two kinds of statistical games constructed to show how to achieve quality assurance system based on SPC(statistical process control) by using simple models and software tools. Proposed games are Coin Shooting Game and Paper Glider Releasing Game. These games can be played on a table using simple materials, and are easy to play. These are described by showing actual data.

Participants of these games get necessary outputs timely by using prepared software tools so that they can execute an effective and efficient decision. These save time and also raise the level of understanding how to achieve quality assurance system based on SPC.     

Statistical process control for software?

Most businesses outside the software-engineering community, like hardware manufacturers and service suppliers, have made statistical process control part of their development regimen. Does this mean we can ultimately expect the technique to penetrate the software world? Although a few pioneers (mostly practitioners) have attempted to use statistical process control in software-engineering applications, the opinion of many academics and practitioners is that it simply doesn't fit in the software world. These objections probably stem from an unfamiliarity with the technique and how to use it to best advantage. Many tend to dismiss it simply on the grounds that software can't be measured, but properly applied, statistical process control can flag potential process problems, even though it cannot supply absolute scores or goodness ratings     

Engineering software under statistical quality control

Eight common misconceptions of software quality are examined and refuted. The concept of cleanroom engineering of software is introduced. Cleanroom engineering achieves intellectual control by applying rigorous, mathematics-based engineering practices, establishes an errors-are-unacceptable attitude and a team responsibility for quality, delegates development and testing responsibilities to separate teams, and certifies the software's mean time to failure through the application of statistical quality-control methods. A typical project is used to explain the concepts and procedures     

An interactive simulator for statistical process control

An interactive program has been developed which simulates several representative industrial processes. Specifically, the program generates product quality characteristic values which are concurrently monitored by standard control charting methods. The program requires the user to specify initial process parameter values and subsequent process adjustments; the latter is necessary in the event the process is deemed to be “out-of-control”. The effectiveness of these decisions are measured by economic criteria. The use of the software promotes a “hands-on” approach, which will better prepare the students to achieve quality improvements in an industrial environment through systematic and scientific evaluation.     

Conceptual model for process control software specification

The paper presents a method for software specification in the domain of industrial process control. As a result of ever more demanding applications, particularly in the area of PLC based control, there is an emerging need for introducing methods that include an appropriate conceptual model and define the specification process. An approach to the method development is presented, based on an architectural extension of the Ward–Mellor structured real time software engineering method. The core of the method is a conceptual model of the equipment control specification, which consists of two essential parts: the first is that of process equipment entities, and the second is the functional part. The former is further decomposed in relation to two aspects of the process equipment entities: the structural aspect and the classification aspect. In order to make the conceptual model more clear some segments of the real process control application dealing with the hydrolysis process in the production of TiO₂ are given.     

Utilization of statistical process control (SPC) in emergent software organizations: Pitfalls and suggestions

Common wisdom in the domain of software engineering tells us that companies should be mature enough to apply Statistical Process Control (SPC) techniques. Since reaching high maturity levels (in CMM or similar models such as ISO 15504) usually takes 5–10 years, should software companies wait years to utilize Statistical Process Control techniques? To answer this question, we performed a case study of the application of SPC techniques using existing measurement data in an emergent software organization. Specifically, defect density, rework percentage and inspection performance metrics are analyzed. This paper provides a practical insight on the usability of SPC for the selected metrics in the specific processes and describes our observations on the difficulties and the benefits of applying SPC to an emergent software organization.     

面向任务的软件过程控制模型

提出了一种面向任务的软件过程控制模型,旨在提高软件过程控制能力、促进CMM/CMMI的实施。该控制模型采用面向任务的调度思想,将软件过程划分为一系列任务。采用有限域约束规划方法建立约束模型,生成任务调度方案。实验验证了该模型的可行性和有效性。     

An intelligent composite system for statistical process control

Combining statistical process control, artificial neural networks and an expert system for the intelligent analysis and control of a plastic extruder facility is described. Statistical methodology is compared and contrasted to the exploratory neural network technique, which learns to relate and classify dependent production variables based on measurements taken on-line during the process. Integrating the neural network analysis into a composite control system using an expert system is presented.     

A requirements engineering process for control engineering software

This paper presents a novel approach for the specification of control engineering software. The proposal is based on software engineering techniques which have improved the performance and quality of software processes. Some of the best practices for the building of software products are included. An example of the proposal is given for the requirements specification of the 1992 ACC robust control benchmark.     

Self-adaptive statistical process control for anomaly detection in time series

Anomaly detection in time series has become a widespread problem in the areas such as intrusion detection and industrial process monitoring. Major challenges in anomaly detection systems include unknown data distribution, control limit determination, multiple parameters, training data and fuzziness of ‘anomaly’. Motivated by these considerations, a novel model is developed, whose salient feature is a synergistic combination of statistical and fuzzy set-based techniques. We view anomaly detection problem as a certain statistical hypothesis testing. Meanwhile, ‘anomaly’ itself includes fuzziness, therefore, can be described with fuzzy sets, which bring a facet of robustness to the overall scheme. Intensive fuzzification is engaged and plays an important role in the successive step of hypothesis testing. Because of intensive fuzzification, the proposed algorithm is distribution-free and self-adaptive, which solves the limitation of control limit and multiple parameters. The framework is realized in an unsupervised mode, leading to great portability and scalability. The performance is assessed in terms of ROC curve on university of California Riverside repository. A series of experiments show that the proposed approach can significantly increase the AUC, while the false alarm rate is improved. In particular, it is capable of detecting anomalies at the earliest possible time.     

项目管理过程域中的统计过程控制研究

本文以CMMI为例,着重讲述对二级不稳定的项目管理过程和三级虽标准过程稳定但项目定义软件过程不稳定时涉及的较低级的七个过程域的统计控制方法,以将八个过程域统一在一个度量模型中进行管理,从而理解过程行为,促进软件过程的稳定性、可预见性和其改进.     

A review of neural networks for statistical process control

This paper aims to take stock of the recent research literature on application of Neural Networks (NNs) to the analysis of Shewhart's traditional Statistical Process Control (SPC) charts. First appearing in the late 1980s, most of the literature claims success, great or small, in applying NNs for SPC (NNSPC). These efforts are viewed in this paper as useful steps towards automatic on-line SPC for continuous improvement of quality and for real-time manufacturing process control. A standard NN approach that can parallel the universality of the traditional Shewhart charts has not yet been developed or adopted, although knowledge in this area is rapidly increasing. This paper attempts to provide a practical insight into the issues involved in application of NNs to SPC with the hope of advancing the use of NN techniques and facilitating their adoption as a new and useful aspect of SPC. First, a brief review of control chart analysis prior to the introduction of NN technology is presented. This is followed by an examination and classification of the NNSPC existing literature. Next, an extensive discussion of implementation issues with reference to significant research papers is presented. Finally, after summarising the survey, a set of general guidelines for future applications of NNs to SPC is outlined.     

A virtual memory organisation for minicomputer process control software

The well known techniques of paged virtual memory provide an attractive base for the organization of process control software because the package can be organized as though a large memory were available but only those pages actually being used at any time need be present in the limited minicomputer memory. Such hardware is not available in minicomputers principally because of their limited word length. A software system for process control applications is implemented which takes advantage of virtual memory but avoids the inefficiency inherent in interpreting every address as a virtual address by partitioning the application programs intomodules which reside on single pages and use normal addresses for intra-module references. External references only are interpreted by the virtual space executive. Experimental results indicate that the system is efficient and attractive for this application.     

Portable software: a new challenge for process control

This paper deals with the relative merit of transportable programming techniques and system modularization. The benefits are discussed broadly in the areas of benefits to managing the sequencing of systems installation, programming effort and touches briefly on the impact of new control equipment from the human aspect.The primary message of the paper is that we should take advantage of the tremendous similarity of system function from process to process and by using extensive applications data structures, capitalize on the similarities to accelerate the project life cycle. This improves the return on investment time, reduces the criticality of number of highly experienced personnel, and offers some suggestions for areas which lend themselves to portable concepts in terms of system function.     

Using Bayesian networks for root cause analysis in statistical process control

Despite their fame and capability in detecting out-of-control conditions, control charts are not effective tools for fault diagnosis. There are other techniques in the literature mainly based on process information and control charts patterns to help control charts for root cause analysis. However these methods are limited in practice due to their dependency on the expertise of practitioners. In this study, we develop a network for capturing the cause and effect relationship among chart patterns, process information and possible root causes/assignable causes. This network is then trained under the framework of Bayesian networks and a suggested data structure using process information and chart patterns. The proposed method provides a real time identification of single and multiple assignable causes of failures as well as false alarms while improving itself performance by learning from mistakes. It also has an acceptable performance on missing data. This is demonstrated by comparing the performance of the proposed method with methods like neural nets and K-Nearest Neighbor under extensive simulation studies.     

Formalization of software design for process control systems in ferrous metallurgy

The operation of control systems in bar-rolling mills is examined and software design tools for such systems are proposed. A system of algorithmic algebras for these design tools is constructed and its capabilities are considered.Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 138–145, September–October, 1991.     

Design of a knowledge-based expert system for statistical process control

A comprehensive expert system design is presented for all problem-solving aspects of statistical process control. Issues concerning the integration of monitoring, interpreting, diagnosing, planning, and statistical consulting for statistical process control are addressed. All aspects of the expert system are discussed. In addition, a new similarity measure useful in a clustering approach to the knowledge organization is proposed. An example session is presented which diagnoses a cyclic pattern in a surface-finishing operation.     

A component-based simulation environment for statistical process control systems analysis

This paper describes a simulation environment, called Prosim, which permits a user to define components, subsystems, and their interconnections to analyse a statistical process control (SPC) system. The components and systems are defined and analysed interactively. A library of standard SPC objects containing models for the Xbar, range, exponential weighted moving average, p-chart and other SPC techniques have been created which help define the control application. The PC-based tool is tested on theoretical, and real data, and is useful for the design and trouble shooting of a manufacturing system. It is also an effective teaching and research tool.