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In order to improve working methods, this study proposes a method for the analysis of medication incidents and the systematic planning of error‐proofing (EP) countermeasures, in the hope that it might contribute to a reduction in medication incidents.

In order to simplify the process of planning EP countermeasures, the following approaches are employed in this study. Improvement elements are extracted in order to plan EP countermeasures. The improvement elements that caused the error‐factor are called improvement objects, and the authors designed the extraction set of improvement objects. The authors correlated the improvement objects with recommended EP solutions. Finally, these parameters are collated. Moreover, these tools are summarized as a procedure for analysis of such incidents and for the creation of appropriate EP countermeasures.

Using this approach, this paper suggests four steps to reduce medical incidents. The proposed procedure can facilitate the planning of EP countermeasures and can reduce the rate of medical incidents.

It can be surmised that the proposed method can serve as a useful means for planning EP countermeasures and reducing the number of medication incidents. On the other hand, there are various countermeasures which can be planned for one incident by applying the proposed method.

The relationship between Error factors and improvement objects were then clarified through utilizing maps. Furthermore, a list that clearly indicates which EP solutions should be adopted for the improvement objects were suggested. There is, therefore, a significant difference between the proposed and the conventional method, and this makes it possible to plan the EP countermeasures easily.

Laboratory calibration methods are time-consuming and require accurate devices to find the error coefficients of the low-cost microelectromechanical system (MEMS) accelerometer. Besides, low-cost MEMS sensors highly depend on temperature because of their silicon property and the effect of temperature on error coefficients should also be considered for compensation. This paper aims to present a field calibration method in which the accelerometer is placed in different positions without any accurate equipment in a few minutes and its temperature is changed by a simple device like a hairdryer.

In this paper, a non-linear cost function is defined based on this rule that the magnitude of the acceleration measured by the accelerometer in static mode is equal to the gravity plus error factors. Also, the dependency of error coefficients of the accelerometer is presented as a second-order polynomial in this cost function. By minimizing the cost function, the accelerometer error coefficients include bias, scale factor and non-orthogonality and their temperature dependency are obtained simultaneously.

Simulation results in MATLAB and empirical results of a MPU6050 accelerometer verify the good performance of the proposed calibration method.

Finding a fast and simple field calibration method to calibrate a low-cost MEMS accelerometer and compensate for the temperature dependency without using accurate laboratory equipment can help a wide range of industries that use advanced and expensive sensors or use expensive laboratory equipment to calibrate their sensors, to decrease their costs.

The purpose of this study is to propose an automatic leveling method for a printing platform based on a three-point coordinate feedback. The proposed method is used in fused deposition modeling additive manufacturing systems. The coordinate error of the leveled plane is constrained to within  ± 0.2 mm, which is less than the printed layer thickness.

First, the model of the forward and inverse solutions of the parallel arm is obtained based on the principles of vector algebra. Second, the automatic leveling mechanism for collecting the z-coordinate is designed. The best position of the virtual origin plane is obtained by comparing the z-coordinates of the test points. Finally, after making multiple adjustments through a closed-loop z-coordinate feedback, the parallelism of the printing plane and the virtual origin plane is limited to an effective range.

The experimental results show that after three leveling attempts, the z-coordinate of the test points can be constrained to within  ± 0.2 mm, which shows that this method can effectively achieve automatic leveling in a delta three-dimensional (3D) printer.

This study presents a novel and distinctive delta 3D printer leveling system by designing a leveling mechanism and a leveling algorithm. The method uses a closed-loop feedback mode to make the leveling process simple, convenient and efficient without requiring major changes to the printer. The error after leveling is less than the printed layer thickness, which fully guarantees the accuracy of the leveling process.

This paper aims to explore true technical efficiency in order to select the most competitive manufacturing industries in China. And the paper intends to discuss how environmental variables measured by energy consumption affect performance in different industrial sectors under the restriction of low-carbon economy.

In order to measure the calculated efficiency of industrial sectors more accurately, Three-stage DEA model is presented in the empirical analysis using data from 2007 to 2010 covering 29 manufacturing industries in China. The advantage of using this method is enabling us to separate the managerial factor from external environmental factors and random errors factors on the technical efficiency.

The results using this Three-stage DEA model show that textile manufacturing sector has the highest technical efficiency, and when environment variables are not considered, efficiencies in machinery and electronics manufacturing industries have a significant increase. Moreover, this empirical model enables us to evaluate the technical performance in various manufacturing sectors more accurately.

This study provides a useful efficiency measurement tool (Three-stage DEA model) to calculate technical efficiency among different industrial sectors. Technical efficiency plays a key role in building the competitiveness of manufacturing industry. Based on the objective efficiency evaluation, the paper can make a better selection of the most competitive industries.

The paper contributes to the existing literature by developing a Three-stage DEA to examine the technical efficiency and competitive power of manufacturing sectors in China. This study has great policy implications for the research of China's manufacturing in both ideas and methodology.

Outlines the current scenario regarding work‐related injuries and states that most company policies are built on the occupational safety and health administration programmes. Considers the need for additional administrative controls, together with brief examples from industry. Discusses the human error factor and provides examples of sources of problems caused by poorly designed human factors and their solutions. Presents a framework for a behaviour base of safety in an effort to discover underlying reasons.

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.

Ineffective communication consequences can be life-threatening and drastic. Communication misunderstandings are frequently reported in incidents, accidents and occurrences. This research paper aims to evaluate operator communication load in highly automated systems; distinguish and highlight the communication error factors during flight operations from different perspectives; and provide suggestions to operators to decrease the rate of misunderstandings in aviation communication.

This study is based on a questionnaire that investigated the critical communication load, including aviation training, standard phraseology, operators’ native language and cultural background. In addition to the effect of using controller–pilot data link communications will be discussed widely. In this research, 110 responses were obtained from pilots and air traffic controller (ATCOs) that vary in 44 countries; approximately 20% were ATCOs, and 75% were pilots.

This study was designed to assess the level of aviation operators communication load in highly automated systems, identify and illustrate the factors that contribute to communication errors during flight operations from multiple viewpoints, and offer recommendations to operators to minimize the rate of misunderstandings in aviation communication.

This research deals with evaluating the operators’ communication load, which is crucial for the air traffic safety and efficiency.

Contemporary management and strategy mean optimization of ingredient factors such as human factors, systems, operations and equipment. With system approach in management and strategy, human risk factor as input has considerable potential to change results as airworthiness in aviation management. The managers of aviation business also optimize their functions to act safe while making contribution to development in triple of sustainability as economic development and its sustainability; social development and its sustainability; and environmental development and its sustainability. Corporate sustainability can be accomplished via supporting workforce which is the human risk factor. To support (empowerment) workforce, researchers should identify human risk or error factors which are important to this research. The purpose of this study is to suggest holistic framework for working environment system of aircraft maintenance technicians (AMTs) within two respects such as human performance (ergonomics) and corporate performance (sustainability). The secondary purpose of this system is to develop human risk taxonomy by determining the factors affecting both human and work by taking ergonomic aspects in aviation.

In this study, a taxonomy of human risk factors for AMTs is developed. These human factors divided into groups and subfactors are obtained from an extensive literature review and experts’ opinions in the field of human performance in aviation. Taxonomy developed will be useful to both sharing and using corporate sources in sustainable way.

Human risk factors can be considered or accepted as factors that cause human error. This may result in the optimum way to managing human risk factor via minimizing human-based error. Personality, hazardous attitudes, individual characteristics, physical/psychological condition of AMTs and corporate social responsibility factors are human-related risk variables in this study. The risks and error can be reduced by recognizing these factors and revealing their relation to ergonomic design.

The results of this study are intended to constitute a guide for managers to manage risk factors and to take corrective and preventive actions for their maintenance operations. It is believed that this study is highly important for the aviation sector in terms of raising awareness or providing awareness for similar practices. As taxonomy of the risk factors contributes to the managing human error, corrective actions related to these factors must be taken by managers.

Large size of aircraft assembly tooling structure and complex measurement environment exist. The laid enhanced reference points (ERS) are subject to a combination of nonuniform temperature fields and measurement errors, resulting in increased measurement registration errors. In view of the nonuniform temperature field and measurement errors affecting the ERS point registration problem, the purpose of this paper is to propose a neural network-based ERS point registration compensation method for large-size measurement fields under a nonuniform temperature field.

The approach is to collect ERS point information and temperature data, normalize the collected data to complete the data structure design and complete the construction of the neural network prediction model by data training. The data learning is performed to complete the prediction model construction, and the prediction model is used to complete the compensation analysis of ERS points. Finally, the algorithm is verified through experiments and engineering practice.

Experimental results show that the proposed neural network-based ERS point prediction and compensation method for nonuniform temperature fields effectively predicts ERS point deformation under nonuniform temperature fields compared with the conventional method. After the compensation analysis, the registration error is effectively reduced to improve registration accuracy. Reducing the combined effect of environmental nonuniform temperature field and measurement error has apparent advantages.

The method reduces the registration error caused by combining a nonuniform temperature field and measurement error. It can be used for aircraft assembly site prediction and registration error compensation analysis, which is essential to improve measurement accuracy further.

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.