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According to regulations, aircraft must be in an airworthy condition before they can be operated. To ensure airworthiness, they must be maintained by an approved component maintenance organisation. This study is aimed to identify potential errors that may arise during the final inspection and certification process of aircraft components, categorise them, determine their consequences and quantify the associated risks. Any removed aircraft components must be sent to an approved aircraft component maintenance organisation for further maintenance and issuance of European Union Aviation Safety Agency (EASA) Form 1. Thereafter, a final inspection and certification process must be conducted by certifying staff to receive an EASA Form 1. This process is crucial because any errors during this stage can result in the installation of unsafe components in an aircraft.

The Systematic Human Error Reduction and Prediction Approach (SHERPA) method was used to identify potential errors. This method involved a review of the procedures of three maintenance organisations, individual interviews with ten subject matter experts and a consensus group of 14 certifying staff from different maintenance organisations to achieve the desired results.

In this study, 39 potential errors were identified during the final inspection and certification process. Furthermore, analysis revealed that 48.7% of these issues were attributed to checking errors, making it the most common type of error observed.

This study pinpoints the potential errors in the final inspection and certification of aircraft components. It offers maintenance organisations a roadmap to assess procedures, implement preventive measures and reduce the likelihood of these errors.

In the era of the service economy, the personalized needs of customers are increasing rapidly. It often occurs that front-line employees bend organizational rules to help customers. The study sought to explore the influence mechanism of servant leadership on specific dimensions of customer-oriented deviance from the manager’s perspective, examine the mediating role of psychological security, and the moderating role of error management climate in the process.

We conducted an online survey study in China from April 10 to 29, 2023. We use online survey questionnaire technique and random sampling method for data collection. The authors collected 385 questionnaires from China and tested the model by SPSS 26.0 and AMOS 24.0.

The results show that servant leadership significantly promotes employees' deviant customer-oriented behaviors, psychological security plays a mediating role between servant leadership and deviant customer-oriented behaviors, and error management climate has a positive moderating effect between servant leadership and deviant customer-oriented behaviors.

This study explores the influence mechanism of servant leadership on deviant customer-oriented behaviors. The results of this study not only enrich the theoretical research on the formation mechanism of deviant customer-oriented behaviors but also provide a reference for leaders to correctly view and effectively manage employees' deviant customer-oriented behaviors.

A great deal of time and effort is invested by personnel managers and researchers in minimising performance appraisal errors. Until recently, these efforts concentrated on improving the design, implementation and the monitoring of appraisal instruments, producing only minimal improvement in the accuracy of performance appraisal. The amount and type of impact that leadership style and other rater characteristics have on appraisal errors are investigated.

The concepts of solution error and optimal mesh in adaptive finite element analysis are revisited. It is shown that the correct evaluation of the convergence rate of the error norms involved in the error measure and the optimal mesh criteria chosen are essential to avoid oscillations in the refinement process. Two mesh optimality criteria based on: (a) the equal distribution of global error, and (b) the specific error over the elements are studied and compared in detail through some examples of application.

Localization accuracy is a key concern in the design of a fixture to specify a locating scheme and tolerance allocation. This paper presents an analysis describing the impact of localization source errors on the potential datum‐related geometric errors of machined features. The analysis reveals the error sensitivity and error characteristics of critical points of multiple manufacturing features. It shows the importance to consider the overall error among the multiple critical points in fixture layout design. This paper also suggests an optimal approach to the locator configuration design for reducing geometric variations at the critical points of machined features.

The Uganda Makerere University provides clinical laboratory support to over 70 clients in Uganda. With increased volume, manual data entry errors have steadily increased, prompting laboratory managers to employ the Six Sigma method to evaluate and reduce their problems. The purpose of this paper is to describe how laboratory data entry quality was improved by using Six Sigma.

The Six Sigma Quality Improvement (QI) project team followed a sequence of steps, starting with defining project goals, measuring data entry errors to assess current performance, analyzing data and determining data‐entry error root causes. Finally the team implemented changes and control measures to address the root causes and to maintain improvements. Establishing the Six Sigma project required considerable resources and maintaining the gains requires additional personnel time and dedicated resources.

After initiating the Six Sigma project, there was a 60.5 percent reduction in data entry errors from 423 errors a month (i.e. 4.34 Six Sigma) in the first month, down to an average 166 errors/month (i.e. 4.65 Six Sigma) over 12 months. The team estimated the average cost of identifying and fixing a data entry error to be $16.25 per error. Thus, reducing errors by an average of 257 errors per month over one year has saved the laboratory an estimated $50,115 a year.

The Six Sigma QI project provides a replicable framework for Ugandan laboratory staff and other resource‐limited organizations to promote quality environment. Laboratory staff can deliver excellent care at a lower cost, by applying QI principles.

This innovative QI method of reducing data entry errors in medical laboratories may improve the clinical workflow processes and make cost savings across the health care continuum.

This study aims to provide healthcare managers with a meaningful synthesis of state of the art knowledge on error proofing strategies. The purpose is to provide a foundation for understanding medical error prevention, to support the strategic deployment of error proofing strategies, and facilitate the development and implementation of new error proofing strategies.

A diverse panel of 40 healthcare professionals evaluated the 150 error proofing strategies presented in the AHRQ research monograph using classification systems developed by earlier researchers. Error proofing strategies were ranked based on effectiveness, cost, and ease of implementation as well as based on their aim/purpose, i.e. elimination, replacement, facilitation, detection, or mitigation of errors.

The findings of this study include prioritized lists of error proofing strategies from the AHRQ manual based on the preferred characteristics (i.e. effectiveness, cost, ease of implementation) and underlying principles (i.e. elimination, replacement, facilitation, detections mitigation of errors) associated with each strategy.

The results of this study should be considered in light of certain limitations. The sample size of 40 panelists from hospitals, medical practices, and other healthcare related companies in the Gulf Coast region of the USA prevents a stronger generalization of the findings to other groups or settings. Future studies that replicate this approach, but employ larger samples, are appropriate. Through the use of public forums and expanded sampling, it may be possible to further validate research findings in this paper and to expand and build on the results obtained in this study.

Using the error‐proofing strategies identified provides a starting point for researchers seeking to better understand the impact of error proofing on healthcare services, the quality of those services and the potential financial ramifications. Further, the results presented enhance the strategic deployment of error proofing strategies by bringing to light some of the important factors that healthcare managers should consider when implementing error proofing solutions. Most notably, healthcare managers are encouraged to implement effective solutions, rather than those that are merely inexpensive and/or easy to implement, which is more often the case.

This study provides a much‐needed forum for sharing error‐proofing strategies, their effectiveness, and their implementation.

The purpose of this paper is to evaluate accuracy of macro fiscal forecasts done by Government of Zimbabwe and the spillover effects of forecasting errors over the period 2010-2015.

In line with the study objectives, the study employed the root mean square error methodology to measure the accuracy of macro fiscal forecasts, borrowing from the work of Calitz et al. (2013). The spillover effects were assessed through running simple regression in Eviews programme. The data used in the analysis are based on annual national budget forecasts presented to the Parliament by the Minister of Finance. Actual data come from the Ministry of Finance budget outturns and Zimbabwe Statistical Agency published national accounts.

The results of the root mean square error revealed relatively high levels of macro-fiscal forecasting errors, with revenue recording the highest. The forecasting errors display a tendency of under predicting the strength of economic recovery during boom and over predicting its strength during periods of weakness. The study although found significant evidence of GDP forecasting errors translating into revenue forecasting inaccuracies, the GDP forecasting errors fail to fully account for the revenue errors. Revenue errors were, however, found to be positive and significant in explaining the budget balance errors.

In other jurisdictions, particularly developed countries, they undertake regular evaluation of their forecasts in order to improve their forecasting procedures, which translate into quality public service delivery. The situation is lagging in Zimbabwe. Given the poor performance in public service delivery in Zimbabwe, this study contributes in dissecting the sources of the challenge by providing a comprehensive review of macro fiscal forecasts.

The purpose of this paper is to analyse the conception of the positioning system of fused deposition modeling (FDM) machines, optimising design parameter and components accuracy to decrease mechanical errors of equipment, which, consequently, results in the increase of parts accuracy. This paper also reports studies related to analytical estimation of machine errors, describing a theoretical model which was used for the multivariable study. Additionally, an alternative conception is proposed, according with the result of this study.

For elaboration of the numerical model of equipment, the authors have focused on conception of first generation of FDM, specifying as design parameters, timing belt stiffness, linear bearing clearance, and accuracy grade of ball screw housing, support and pulley. In order to identify the main effect of each design parameter for the final error of machine, the authors have applied a multivariable method in addition to identifying the error budget of model. Also indicated are the two factors that promote more errors, undergoing a proposal of conception which consists in replacing one component of machine.

With reference to the evaluation of the numerical model, equivalency was found between the resultant error of model and the current FDM accuracy. The result of multivariable study identified the main causes of errors in machine, implying on an optimized solution which decreases the initial error in 69 μm. Similarly, the evaluation of the proposed conception resulted in the reduction of general error in almost 20 μm, even though the worst case was studied for this comparison.

Although the number of applications for additive manufacturing has been growing in recent years, implying an increase of demand for high precision parts, there are still several challenges to be overcome, such as the improvement of equipment. For that reason, the motivation of this work concerns the contribution for development of new equipment, as well the improvement of current technologies. Furthermore, the authors' focus was the reduction of mechanical errors through an analytical approach.

The investigation of the influence of the modeling error on the solution of the inverse problem given uncertain measured data in electrical capacitance tomography (ECT).

The solution of the nonlinear inverse problem in ECT and hence, the obtainable accuracy of the reconstruction result, highly depends on the numerical modeling of the forward map and on the required regularization. The inherent discretization error propagates through the forward map, the solution of the inverse problem, the subsequent calculation of process parameters and properties and may lead to a substantial estimation error. Within this work different finite element meshes are compared in terms of obtainable reconstruction accuracy. In order to characterize the reconstruction results, two error measures are introduced, a relative integral error and the relative error in material fraction. In addition, the influence of the measurement noise given different meshes is investigated from the statistical point of view using repeated measurements.

The modeling error, the degree of regularization, and measurement uncertainties are the determining and limiting factors for the obtainable reconstruction accuracy of electrical tomography systems. The impact of these key influence factors on the calculation of process properties given both synthetic as well as measured data is quantified. Practical implications – The obtained results show that especially for measured data, the variability in calculated parameters strongly depends on the efforts put on the forward modeling, i.e. on an appropriate finite element mesh size. Hence, an investigation of the modeling error is highly recommended when real‐world tomography problems have to be solved.

The results presented in this work clearly show how the modeling error as well as inherent measurement uncertainties influence the solution of the inverse problem and the posterior calculation of certain parameters like void fraction in process tomography.