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The automated manufacturing systems of the future can only be feasible if they have capabilities to recover automatically from faults and errors effectively and efficiently. Reports on the work carried out looking at error recovery problems in manufacturing cell controllers. Cell control systems also invariably manage and schedule work in an automated cell as well as carrying out the general tasks of communications, sequencing and recording. Presents a model for error recovery capability which uses system information, data and prior knowledge of errors to recover from system errors. Elucidates the structure and operation of the cell controller developed. Work so far has shown promise in achieving automatic recovery capability in cell control systems. Finally identifies further developments for future work.

In this study, the integrated navigation system, consisting of radio and inertial navigation system (INS) altimeters, is presented. INS and the radio altimeter have different benefits and drawbacks. The integration is achieved by using an indirect Kalman filter. Hereby, the error models of the navigators are used by the Kalman filter to estimate vertical channel parameters of the navigation system. In the open loop system, INS is the main source of information, and radio altimeter provides discrete aiding data to support the estimations. At the next step of the study, in case of abrupt faults, the performance of the integrated system is examined. The optimal Kalman filter reacts with abnormal estimates to this situation as expected. To recover such a possible malfunctioning, the robust Kalman filter algorithm is suggested.

Recent reports by the Institute of Medicine (IOM) signal a substantial yet unrealized deficit in patient safety innovation and improvement. With the aim of reducing this dilemma, we provide an introductory account of clinical error resulting from poorly designed systems by reviewing the relevant health care, management, psychology, and organizational accident sciences literature. First, we discuss the concept of health care error and describe two approaches to analyze error proliferation and causation. Next, by applying transdisciplinary evidence and knowledge to health care, we detail the attributes fundamental to constructing safer health care systems as embedded components within the complex adaptive environment. Then, the Health Care Error Proliferation Model explains the sequence of events typically leading to adverse outcomes, emphasizing the role that organizational and external cultures contribute to error identification, prevention, mitigation, and defense construction. Subsequently, we discuss the critical contribution health care leaders can make to address error as they strive to position their institution as a high reliability organization (HRO). Finally, we conclude that the future of patient safety depends on health care leaders adopting a system philosophy of error management, investigation, mitigation, and prevention. This change is accomplished when leaders apply the basic organizational accident and health care safety principles within their respective organizations.

The reliability of accounting internal control systems (AICS) is often viewed as a primary concern of auditors. Over the past three decades, several reliability models have been proposed for internal control. The main goal of these models is to provide an objective approach to evaluate the reliability of internal control systems. In addition, the models seek to assess the degree of audit reliance that can be placed on internal controls. This paper has a two‐fold objective: (1) to present an overview of the descriptive and prescriptive reliability models developed for the design and evaluation of internal control systems, and (2) to discuss the effects of various factors on the reliability assessment. Furthermore, two methods to estimate process reliabilities are presented and several numerical examples are provided to show the detailed calculations of the reliability and economic efficiency of accounting internal control systems.

The purpose of this paper is to present a review of health information system (HIS)-induced errors and its management. This paper concludes that the occurrence of errors is inevitable but it can be minimised with preventive measures. The review of classifications can be used to evaluate medical errors related to HISs using a socio-technical approach. The evaluation could provide an understanding of errors as a learning process in managing medical errors.

A literature review was performed on issues, sources, management and approaches to HISs-induced errors. A critical review of selected models was performed in order to identify medical error dimensions and elements based on human, process, technology and organisation factors.

Various error classifications have resulted in the difficulty to understand the overall error incidents. Most classifications are based on clinical processes and settings. Medical errors are attributed to human, process, technology and organisation factors that influenced and need to be aligned with each other. Although most medical errors are caused by humans, they also originate from other latent factors such as poor system design and training. Existing evaluation models emphasise different aspects of medical errors and could be combined into a comprehensive evaluation model.

Overview of the issues and discourses in HIS-induced errors could divulge its complexity and enable its causal analysis.

This paper helps in understanding various types of HIS-induced errors and promising prevention and management approaches that call for further studies and improvement leading to good practices that help prevent medical errors.

Classification of HIS-induced errors and its management, which incorporates a socio-technical and multi-disciplinary approach, could guide researchers and practitioners to conduct a holistic and systematic evaluation.

This research aims to consider the impact of common inventory system inaccuracies that occur in retail outlets on the inventory levels, fill rate, and service level of those outlets by simulating daily customer demand and random error in the inventory system.

The simulation experiments vary the amount of inventory system error, the frequency of inventory record error correction, the size of the daily demand, the number of days in the replenishment system's review interval, and the replenishment system's customer service level.

Inventory system error and the frequency with which the error is corrected are statistically significant for fill rate and service level. Thus, inaccuracies in inventory levels affect a retail outlet's ability to service its customers, though at the single SKU level, the results do not indicate a practical impact due to countervailing effects.

Retail outlets must be aware that error exists and can influence the behavior of their replenishment systems, but the overall impact may not be as significant as it might appear.

This research extends prior work on the effects of inventory inaccuracies and clarifies the debate pertaining to their ultimate effects on retail performance outcomes.

Medication errors (MEs) are important in terms of their magnitude and severity, and there are numerous systems in place to reduce their occurrence. However, the ideal system has not yet been identified. The authors' institution uses three different medication prescription‐dispensation systems which operate simultaneously. ME rates were compared, overall and by phase (prescription, transcription and administration) and their overall and specific clinical impact.

The administration of medicinal products was observed directly and compared with medical and nursing prescriptions. Errors and adverse events were classified by a consensus of experts.

In the traditional system the error prevalence rate was 13.59 per cent, (99 per cent CI, 12.15‐14.61 per cent), in the single dose system it was 6.43 per cent (99 per cent CI, 5.53‐7.32) and in the electronic prescription system it was 8.86 per cent (99 per cent CI, 7.33‐10.17). The highest error rates in all phases were found in the traditional system. The phase affected by most errors in all three models was transcription, and the least affected was administration, except for the single dose system, in which prescription was the worst. The effects of errors in the administration phase are greater, although less so than with the automated system.

The dispensation phase was not analyzed.

A study of errors will enable us to reduce their occurrence if we know the most frequent types and in which phase they are produced, we will be able to prioritise the areas in which to work and select the necessary preventive measures.

It is possible that automated medication dispensation systems reduce error rates and the severity of their effects.

“Core data” has now been in successful use for some 15 years in the UK and some other countries and is the basis from which a large number of standard data systems have been developed for work as varied as woodworking, electronic and mechanical assembly and the needle trades. More recently, the system documentation and training materials have been updated, tested and improved and submitted to the International MTM Directorate for scrutiny. This article outlines the MTM Core Data system and the methodology and results of validation tests conducted by the United Kingdom MTM Association. After stringent evaluation of the test results and the revised materials, the evaluation of the test results and the revised materials, the International MTM Directorate have granted recognition and approval to MTM Core Data as a properly developed and documented MTM system.

The purpose of this paper is to discuss the adverse impact of management systems on the occurrence of human errors.

Conducted is systemic analysis of scenarios, which are illustrating creation of human errors, caused by functions of management systems. The text refers to a research study on mechanisms of errors committed by employees, conducted by the author in several organizations. In the text a special focus is given to the interaction between error‐generating mechanisms and management systems.

First, there are decisions made in favor of the management systems that increase risk of human errors in processes. The conflict between managers and employees, who are blamed for the errors, may obstruct the elimination of errors and the improvement of management systems. Second, managers are expected to resolve the conflict by establishing and maintaining a policy regarding prevention against system‐specific mechanisms of human error. The involvement of managers in improvement and establishing effective vertical communication in the management system are necessary to successful implementation of the policy. Third, a scheme of analyzing adverse effects of decisions is shown.

The paper focuses on some issues that decide on effectiveness of prevention of human errors. It provides explicit evidence of the necessity of the “management involvement” in the quality management system and respective suggestions for the improvement. The considerations may be useful for organizations that are highly sensitive to human errors such as healthcare institutions.

The purpose of this paper is to present a new methodology, used for dynamic reliability analysis of a gear transmission system (GTS) of wind turbine (WT), which could be used for assembly decision-making of the parts with errors to improve the GTS’s performance.

This paper involves the dynamic and dynamic reliability analysis of a GTS. The history curves of dynamic responses of the parts are obtained with the developed gear-bearing coupling dynamic model considering the random errors, failure dependency and random load. Then, the surrogate models of the mean and standard deviation of responses are presented by statistics, rain flow counting method and corrected-partial least squares regression response surface method. Further, a novel dynamic reliability model based on the maximum extreme theory, a theory of sequential statistics, equivalent principles and the inverse transform theory of random variable sampling, is developed to overcome the limitations of traditional methods.

The dynamic reliability of GTS considering the different impact factors are evaluated. The proposed reliability methodology not only overcomes the limitations associated with traditional approaches but also provides good guidance to assembly the parts in a GTS to its best performance.

Instead of constant errors, this paper considers the randomness of the impact factors to develop the dynamic reliability model. Further, instead of the limitation of the normal distribution of the random parameters in the traditional method, the proposed methodology can deal with the problems with non-normal distribution parameters, which is more suitable for the real engineering problems.