How practice produces suboptimal heuristics that render backup instruments ineffective

The operation of machines typically requires attention to instruments that signal the state of the machine. One safeguard against primary instrument malfunction is to provide backup instruments, but this works only if the operators react to malfunction by switching attention to the backups. Little is known about the effect of negative outcomes or feedback on allocation of attention to backup instruments. Four experiments demonstrated that prior practice causes operators of a simulated machine to adapt to instrument malfunction by changing to a suboptimal decision rule rather than by reallocating attention to a different set of instruments. This fallacy appears linked to the operators' failures to notice feedback that they should switch during the simulations and operators' failures to correctly interpret outcome feedback following the simulations. The results raise theoretical questions and warn interface designers not to overrate backup instruments.     

The role of wearable devices in meeting the needs of cloud manufacturing: A case study

Cloud manufacturing is a service-oriented, customer-centric and demand-driven process with well-established industrial automation. Even though, it does not necessarily mean the absence of human beings. Due to products and their corresponding manufacturing processes becoming increasingly complex, operators' daily working lives are also becoming more difficult. Enhanced human–machine interaction is one of the core areas for the success of the next generation of manufacturing. However, the current research only focuses on the automation and flexibility features of cloud manufacturing, the interaction between human and machine and the value co-creation among operators is missing. Therefore, a new method is needed for operators to support their work, with the objective of reducing the time and cost of machine control and maintenance. This paper describes a practical demonstration that uses the technologies of the Internet of things (IoT), wearable technologies, augmented reality, and cloud storage to support operators' activities and communication in discrete factories. This case study exhibits the capabilities and user experience of smart glasses in a cloud manufacturing environment, and shows that smart glasses help users stay productive and engaged.     

Deep learning-based construction equipment operators’ mental fatigue classification using wearable EEG sensor data

Operator attention failure due to mental fatigue during extended equipment operations is a common cause of equipment-related accidents that result in catastrophic injuries and fatalities. As a result, tracking operators' mental fatigue is critical to reducing equipment-related accidents on construction sites. Previously, several strategies aimed at recognizing mental fatigue with adequate accuracy, such as machine learning utilizing EEG-based wearable sensing systems, have been proposed. However, the ability to track operators’ mental fatigue for its implementation on an actual construction site is still an issue. For instance, the mobility and systemic instability of EEG sensors necessitate their application in laboratory settings rather than on actual construction sites. Furthermore, while the machine learning classifiers achieved acceptable accuracy, their input is limited to manually developed EEG features, which may compromise the models’ performance on real construction sites. Accordingly, the current research proposes the viability of a construction site strategy that uses flexible headband-based sensors for acquiring raw EEG data and deep learning networks to recognize operators' mental fatigue. To serve this purpose, a one-hour excavator operation by fifteen operators was conducted on a construction site. The NASA-TLX score was used as the ground truth of mental fatigue, and brain activity patterns were recorded using a wearable EEG sensor. The raw EEG data was then used to develop deep learning-based classification models. Finally, the performance of deep learning models, i.e., long short-term memory, bidirectional LSTM, and one-dimensional convolutional networks, was investigated using accuracy, precision, recall, specificity, and an F1-score. The findings indicate that the Bi-LSTM model outperforms the other deep learning models with a high accuracy of 99.941% and F1-score between 99.917% and 99.993%. These findings demonstrate the feasibility of applying the Bi-LSTM model and contribute to wearable sensor-based mental fatigue recognition and classification, thus enhancing on-site health and safety operations.     

Interaction between an operator and the control desk at the control room of the railway traffic: A Serbian experience

The subject of this paper is the interaction between an operator and the control desk at the Railway Traffic Control Room (RTCR) in Nis, Serbia. The following methods were used for this research: operators' anthropometric measurement; determining of maximum force of the movements of operators' arms; an analysis of workload of the movements of operators' arms, heads and torsos, and an analysis of errors in operators' movements in response to visual cues. The paper presents the following results: static parameter of 20 anthropometric measures of 41 operators' bodies were measured; nine corresponding dimensions of particular body parts for 5th, 50th, and 95th percentile were calculated; 10 characteristic work angles were measured; five corresponding functional body parts were calculated; times and distances covered by operators' arms were measured; maximum forces used for these movements were calculated; positions and number of movements of arms, heads, and torsos of operators were determined, and movement errors and probability of movement errors in choice of direction, arms and cumulative conditional probability were calculated. The research was conducted with the aim of discovering determining factors of mutual synchronization of the operator and desk.     

Alphanumeric and graphic displays for dynamic process monitoring and control

The use of high resolution graphic display technology provides the control system designer with numerous options for displaying process plant information. This research evaluated the effectiveness of alphanumeric and graphic display formats for presenting system information in a dynamic process plant environment Thirty subjects, divided equally into three groups, were tested on three separate display formats: graphical, digital and multiple representations. The operators' task was to optimize the performance of a simulated fluid processing plant and to detect system failures. Results showed that the multiple display resulted in the best optimization performance and minimized the time required to detect failures. In general, the graphic display produced the worst performance with the digital display exhibiting intermediate results. The decision strategies used by the operators were found to have the greatest impact on performance. The results are discussed in terms of the merits of different display formats for representing system information in a manner appropriate to the operator's task.     

Situation awareness measurement of an ecological interface designed to operator support during alarm floods

Alarm summary interfaces are lists of chronologically sorted alarms used in oil producing supervision programs for decades. When a great number of alarms are activated in a small interval of time – that is, an alarm flood – alarm summary ceases to be as useful to understand the process situation. New alarm systems and interfaces are necessary to support operators' decision when dealing with such alarm floods. Situational awareness is an important concept for process operators when making decisions. The application of Ecological Interface Design concepts can lead to better interface designs, especially in unanticipated situations. The aim of this work is to verify the usefulness of a new ecological alarm interface, called Advanced System of Intelligent Alarms (SAAI, the Portuguese acronym). SAAI displays alarms prioritised in real-time with relevant graphical information on process conditions. Professional operators' situational awareness is measured when using either the SAAI interface, or the alarm summary interface, connected to a dynamic simulator running a model of an oil production process. Measurement techniques used include objective and subjective rating approaches, and a proposed technique. Operators' situation awareness for SAAI interface has shown greater values under all techniques used, compared to alarm summary interface. Although the new interface implied that operators would have to look also at an extra monitor, results show that their situation awareness improved on average, and that situation awareness might be less impaired under alarm floods.Relevance to industrySituation awareness plays an important role in operators' decision-making process. Alarm systems are critical in complex process operation, and alarm floods may impair operators' decisions. A new alarm ecological interface designed to maintain operators' situational awareness under alarm floods may mean an improvement in operation safety and efficiency.     

Investigating the validity of subjective workload rating (NASA TLX) and subjective situation awareness rating (SART) for cognitively complex human–machine work

Subjective workload and situation awareness measures, such as the NASA task load index (TLX) and the situational awareness rating technique (SART), are frequently used in human–system evaluation. However, the interpretation of these ratings is debated. In this study, empirical evidence for the measures' theoretical assumptions was investigated by comparing operators' ratings collected immediately after performing a scenario and ratings collected after operators' acquisition through a video review of the scenario, knowledge of actual system states. Eighteen licensed control room operators participated in the simulator study, running 12 relatively challenging scenarios. It was found that the interpretation of TLX items involving introspection remained stable after operators acquired factual scenario knowledge, while the interpretation of items involving the perception of external events, such as situation awareness and performance, depended on the operators' scenario knowledge. The result shows that operators’ ratings could discriminate between mental effort, performance, frustration, and situation awareness. No clear evidence for the SART index as a measure of situation awareness was found. Instead, a subjective situation awareness measure developed for this study was distinct from workload and related to operator performance, showing that this type of measure warrants future investigation of its validity. The study findings help in developing measurement procedures and interpreting subjective measures. Finally, the study reveals that informing operators about the scenario can provide useful subjective ratings of situation awareness and performance. Future research should include procedures for how to inform participants adequately and efficiently in subjective assessments.     

Technological coupling,job characteristics and operators' well-being as moderated by desirability of control

This study proposes that the nature of Automated Manufacturing Technology (AMT)-as reflected in the degree of 'technological coupling' and as perceived by shop floor operators in terms of new job control characteristics (timing and method control, monitoring and problem solving demand, production responsibility)-affects operators' psychological well-being (satisfaction and mental health). The study sample consisted of 216 operators of AMT equipment. Findings indicate that technological coupling is negatively related to the job characteristics of timing and method control, and to psychological well-being variables. Operators' satisfaction is positively related to problem solving, production responsibility and timing and method control. Mental health is negatively related to production responsibility. Implications for job redesign and employees selection to AMT work units are discussed. Yet, results indicate that operators' response to technological coupling is contingent upon their desirability of control (DC). For operators with low DC (as opposed to high DC) coupling conditions did not make any difference in psychological well-being.     

I spy with my AI: The effects of AI-based visual cueing on human operators’ performance and cognitive load in CCTV control rooms

The increased number of security cameras in modern cities has elevated the video-feed monitoring demands of closed-circuit television (CCTV) operators. As a result, new AI-driven support systems that leverage the power of computer vision algorithms have been deployed to facilitate the operators' work. However, to effectively design intuitive, AI-driven interfaces and validate their impact on the operators' performance, extensive user testing is required. To address this, we previously developed and tested a virtual reality (VR) control room that can be used to iteratively evaluate intelligent computer assistants and interfaces while operators are subjected to different cognitive load. In the present study, we use this VR environment and physiological markers (e.g., eye tracking measures) to investigate how AI-based visual cueing (i.e., pushing forward video streams on which detections are highlighted by rectangles drawn around targets) affects operator performance and cognitive load. Results suggest that support systems using such technology in a control room improve operators’ performance and decrease their cognitive load, as reflected by changes in pupil dilation and subjective reports irrespective of induced cognitive load.     

Invisible Work of Telephone Operators: An Ethnocritical Analysis

This paper applies principles derived from ethnocriticism to help explain differential outcomes with different methods used to analyze the work of Directory Assistance telephone operators in a large US telecommunications company. The work of Directory Assistance operators provides a subtle case of computer-supported cooperative work. Collaborative work between operator and customer is supported and shaped by digitized-voice and database technologies. Our work also involved the introduction of additional voice-recognition technologies to this human-to-human collaboration. In a previous paper, we used methods from participatory design to show that knowledge work is a major component of the operators' conversations with customers. By contrast, other research using formal cognitive task analyses had described operators' work as routine and as involving no active problem solving. How had evidence that we had found so compelling been invisible to other analysts? I analyze the concept of “invisible work” as an attribute not of the work, but rather of the perspectives from which that work appeared to be invisible. Ethnocritical heuristics help us to contrast the analytical methods and their outcomes.     

面向OpenStack/Ceph的虚拟机备份系统研究

针对OpenStack面临的虚拟机容灾备份问题,提出了一种基于Ceph存储快照的虚拟机容灾备份系统,备份时对虚拟机存储在Ceph中的磁盘生成快照,再根据备份要求计算有效数据或者变化数据,保存虚拟机的配置信息以及磁盘数据,恢复时自动创建相同配置的虚拟机并将当前快照点的磁盘数据恢复到该虚拟机中.实验表明,该方法比OpenStack的快照备份方法能有效节省备份时间和存储空间,并且可以实现后者不具有的增量备份、多磁盘备份等功能.     

Appropriating artifacts as instruments: when design-for-use meets design-in-use

This article discusses the use of artifacts as an instrument-mediated activity based on a field study in a call center specialized in networks and telecommunications. In this work setting, operators have access to a knowledge-sharing database, which is designed to support the collective elaboration of individual knowledge diffused on hot-lines in an instrument as a means for the collective activity. We characterize this situation along two interrelated analytical dimensions:

• the design-in-use process by analyzing operators' activities: hot-line assistance and knowledge base appropriation;
• the design-for-use process by analyzing the design assumptions inscribed in the artifact developed by designers.

Main results showed that the experts' dialogue-conducting strategies are based on the intrinsic complexity of the questions. The problems are co-elaborated in the course of action by the expert and the caller and constituted as a domain of problems organized by one or more specific problems. This progressive elaboration aims at elucidating the problem situation implicitly contained in the initial request. Two individual instruments were developed within the shared database. Both of them showed transformation of the artifact structure. Moreover, a relation between the organized forms of hot-line assistance activity and the forms and functions of the instruments designed is identified: it may be fully or partially reciprocally congruent. These empirical results are discussed while opposing the ‘design-in-use’ criteria developed by operators to the ‘design-for-use’ criteria built up by the actors of institutional design. In conclusion, we emphasize points to consider in order to support further reflection on relations between use and design in an anthropocentric perspective.     

基于模仿学习的机场停机位再分配决策算法

针对机位再分配算法结果难以满足不同操作人员操作习惯的问题,提出一种符合实际业务人员操作习惯的机位再分配推荐算法。首先以航班特征属性和停机位的资源占用状态构建决策环境空间模型,将人工操作数据转换为多通道时空矩阵,再以卷积神经网络构建的生成对抗网络（generative adversarial network,GAN）拟合其序贯决策操作策略。仿真结果表明,可靠度在90%以上的调整动作占比最高达到84.4%。经过在三个数据集上的测试,模型对不同来源的操作数据具有较好的区分能力。对比不同扰动下的动态调整结果,算法能够得到航班—机位属性特征与原有人工操作属性特征接近的调整方案。     

基于隧道技术的客户端策略路由研究

目前很多校园、小区、企业单位的网络,除了接入一条主干的ISP运营商提供的网络外,还同时接入多个不同的ISP运营商提供的网络.其目的是根据收费情况的不同最大程度地节省开销外,还使得原来比较脆弱的单一出口有了备份,不会因为一个ISP发生故障而中断和因特网的连接.但是,这种多出口网络体系结构必须解决策略路由的配置问题.探讨了如果通过隧道技术实现在客户端进行策略路由的方法.     

Evaluation and prediction mental workload in user interface of maritime operations using eye response

Eye response measurement is one of the objective measure methods and useful for assessing of operators' mental workload (MWL). The main objectives of this paper are to consider the relationship between operators' MWL and eye responses in the task of operating marine engine interface. Also, an artificial neural network (ANN) model was developed to predict the operators' MWL based on integrating eye response data. Eye response indices (pupil dilation, blink rate, fixation rate, and saccadic rate) were recorded, and two subjective rating methods (The National Aeronautics and Space Administration's Task Load Index [NASA-TLX] and subjective workload assessment technique [SWAT]) were used for 27 participants. The results again confirm that the eye response is sensitive to MWL in workload levels of the task when using the interface control. The ANN model developed by measuring these indices can predict the operators' MWL with the determination coefficient (R²) of 0.971, 0.912 and 0.918 for training, validation, and testing, respectively. These results indicated that the ANN approach is quite accurate for the prediction of operators' MWL based on eye response indices.Relevance to industryThe developed model is expected to provide the operator with a reference value of their MWL by evaluating their physiological indices. This result might be applied for developing an intelligent prediction model in the actual work environment to inform or support the operator in a variety of ways. From this, the manager can organize the human resources for each task to sustain the appropriate MWL as well as to improve the work performance.     

数控机床维修与维护技术

随着数控机床在各行业生产中的应用日益广泛,数控机床的维护与维修已成为保障生产、提高效率的关键。本文通过一些具体的故障实例,来介绍在数控机床故障处理方面的一些思路和方法。     

面向流式数据处理系统的高效故障恢复方法

针对流式数据处理系统Flink无法高效处理单点故障的问题,提出了一种基于增量状态和备份的故障容错系统Flink+。首先,提前建立备份算子和数据通路;然后,对数据流图中的输出数据进行缓存,必要时使用磁盘;其次,在系统快照时进行任务状态同步;最后,在系统故障时使用备份任务和缓存的数据恢复计算。在系统实验测试中,Flink+在无故障运行时没有显著增加额外容错开销;而在单机和分布式环境下处理单点故障时,与Flink系统相比,所提系统在单机8任务并行度下故障恢复时间减少了96.98%,在分布式16任务并行度下故障恢复时间减少了88.75%。实验结果表明,增量状态和备份方法一起使用可以有效减少流式系统单点故障的恢复时间,增强系统的鲁棒性。     

Relationships between observed and perceived deviations from normative work procedures

Deviations from anticipated courses of events are often associated with accidents, while the effects of deviations that decrease productivity but do not obviously lead to human injury are less clear. A systemic approach to production and safety is introduced, and it is proposed that production deviations have effects that may lead to safety violations and personal injury. In addition, the relationship between observed and perceived production deviations from 12 senior (60–79 years old) males' routine work using three firewood processing machines is analysed. For simple machine work, perceived deviations were positively related to observed deviations per work cycle and inversely correlated to the perception of work efficiency. For more complex machine work it was more difficult to match observers' and operators' perceptions of deviations. Despite challenges in the production deviation concept, this approach offers a holistic understanding of the performance of human–machine-environment systems and complements assessments of deviations from safe working practice.     

Generating OWA weights using truncated distributions

Ordered weighted averaging (OWA) operators have been widely used in decision making these past few years. An important issue facing the OWA operators' users is the determination of the OWA weights. This paper introduces an OWA determination method based on truncated distributions that enable intuitive generation of OWA weights according to a certain level of risk and trade‐off. These two dimensions are represented by the two first moments of the truncated distribution. We illustrate our approach with the well‐known normal distribution and the definition of a continuous parabolic decision‐strategy space. We finally study the impact of the number of criteria on the results.