On the representation of automation using a work domain analysis

Work domain analysis (WDA) has been applied extensively within cognitive engineering as an analytic framework for the evaluation of complex sociotechnical systems in support of design. However, the WDAs described in the literature have not explored the representation of automated system components, despite the documented problems associated with operator-automation interaction and the requirements for operator support in complex automated systems. The current research examines the application of WDA to model an example automated system – a camera – by representing the camera along with its automated components as separate systems using the abstraction hierarchy (AH). Additionally, we contrasted this modelling approach with the more typical approach of modelling automation within a cognitive work analysis (CWA) by performing a control task analysis using the decision ladder. The results of these analyses suggest that, similar to non-automated systems, considering a separate representation of an automated system within the WDA may provide useful system design guidance in terms of user support and information requirements. The comparison of the AH and the decision ladder (DL) models indicates that the models provide different information about the requirements and support different user needs: the AH provides information about specific subsystems and components of the automation that are used for control and how they support functions and purposes of the automation while the DL shows how the control tasks are achieved interleaving automated actions with those of the user. The information obtained from modelling automation with the AH is different from what would normally be obtained by performing only a control task analysis, yet is necessary for operator support.     

Effects of feedback lag variability on the choice of an automated diagnostic aid: A preliminary predictive model

This paper outlines the Signal Detection Model of Choice (SDMC) that predicts operators' use of automated diagnostic aids based on system feedback lag characteristics. Specifically, the SDMC predicts that users will prefer an aid having variable rather than fixed feedback lag characteristics when the value of correct decisions (hits and correct rejections) are large relative to the negative consequences of incorrect decisions (misses and false alarms). A preference reversal is predicted by the model when the positive consequences of correct decisions are small relative to the negative consequences of wrong decisions. Furthermore, this pattern of choice is predicted even when aids are not equally reliable. Theoretical explanations of the possible cognitive processes that underlie the model, including temporal and reliability distortion theories are presented. Results from recent laboratory experiments that provide preliminary support for the model's predictions and theoretical assumptions are summarized. The bridge that this new model provides between traditional behavioural models of choice and cognitive models of decision-making are also discussed. The hope is that the SDMC will provide fruitful avenues of inquiry into the relatively unexplored effects that automation feedback lag has on choice and decision making processes.     

Integration of dependability in a task allocation problem

The task allocation on various components or processing units composing an automation system needs a design-aided methodology in order to obtain both relevant architecture of this automation system and a sufficiently efficient task allocation. The dependability, mainly illustrated in our approach by the availability of the process and by the reliability that characterizes the risk of incidents or accident occurrences, can be taken into account in the earliest stage of the automation system design. The main interest is that it allows for the definition of reliable operational and functional architectures. To achieve the task allocation, the search method used must integrate a notion of cost that includes both technological and functional aspects and those linked to the dependability. A genetic approach is used for the task allocation, giving a very satisfactory result in a reasonable computational time.     

团队任务反思行为对决策绩效影响的实验研究

团队任务反思行为,是团队主动信息加工方式,影响着人们的判断与选择。因此,以团队任务反思行为理论为基础,提出了团队任务反思行为与决策绩效之间关系作用的研究假设。利用150名MBA学员展开了团队任务反思行为对决策质量、决策满意度和决策一致性影响效应的实验研究。研究结果表明,团队任务反思行为与决策质量有正"U"型相关关系,对决策满意度有显著正向预测效应,与决策一致性的正向相关关系显著。研究结果为决策群体利用团队任务反思提高决策绩效和团队效能有重要的实践意义。     

Advancing the practice of cognitive task analysis: a call for taxonomic research

Cognitive task analysis (CTA) captures unobservable cognitive processes, decisions and judgments of expert performance. Over 100 different CTA methods are identified in prior literature. However, existing classifications typically sort techniques by process rather than outcome, application or causal mechanism. Therefore, techniques can be misapplied and comparative analysis of methods made difficult. Based on the frequency distribution of CTA methods in 1065 studies, a subsample representing 60% of the most frequently published methods was coded based on elicitation and analysis techniques. Consistency of resulting applications was assessed. Inconsistent matching of CTA methods and subsequent applications indicate CTA is currently more craft than technology. Therefore, there is no robust basis for selecting one method over another for research or practice. Specific challenges include comparing the reliability and validity of individual methods and optimising selection of techniques for intended applications. Developing a causal taxonomy may facilitate such advancements.     

A case study evaluating the ergonomic and productivity impacts of partial automation strategies in the electronics industry

A case study is presented that evaluates the impact of partial automation strategies on productivity and ergonomics. A company partly automated its assembly and transportation functions while moving from a parallel-batch to a serial line-based production system. Data obtained from company records and key informants were combined with detailed video analysis, biomechanical modelling data and field observations of the system. The new line system was observed to have 51% higher production volumes with 21% less per product labour input and lower work-in-process levels than the old batch-cart system. Partial automation of assembly operations was seen to reduce the total repetitive assembly work at the system level by 34%. Automation of transportation reduced transport labour by 63%. The strategic decision to implement line-transportation was found to increase movement repetitiveness for operators at manual assembly stations, even though workstations were constructed with consideration to ergonomics. Average shoulder elevation at these stations increased 30% and average shoulder moment increased 14%. It is concluded that strategic decisions made by designers and managers early in the production system design phase have considerable impact on ergonomic conditions in the resulting system. Automation of transport and assembly both lead to increased productivity, but only elements related to the automatic line system also increased mechanical loads on operators and hence increased the risk for work-related disorders. Suggestions for integrating the consideration of ergonomics into production system design are made.     

An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network

The design of instrumentation and control (I&C) systems for nuclear power plants (NPPs) is rapidly moving towards fully digital I&C systems and is trending towards the introduction of modern computer techniques into the design of advanced main control rooms (MCRs) of NPPs. In the design of advanced MCRs, human–machine interfaces have improved and various types of decision support systems have been developed. It is important to design highly reliable decision support systems in order to adapt them in actual NPPs. In addition, to evaluate decision support systems in order to validate their efficiency is as important as to design highly reliable decision support systems. In this paper, an operation advisory system based on the human cognitive process is evaluated in order to estimate its effect. The Bayesian belief network model is used in the evaluation of the target system, and a model is constructed based on human reliability analysis event trees. In the evaluation results, a target system based on the operator's cognitive process showed better performance compared to independent decision support systems.     

Strategic Thrust of Manufacturing Automation Decisions: A Conceptual Framework

American manufacturing firms increasingly consider automation as the means to increase productivity and improve their competitiveness. However, decisions to automate do not always produce the expected results and lead to further frustration. The so called “islands of automation” are often blamed for such failures and other technological alternatives such as computer integrated manufacturing (CIM) are adopted on a piece-meal fashion. This paper examines the adoption of new technology in general, and die decision to automate in particular, from a strategic perspective. In order to deal with the underlying complexities of automation, a conceptual framework is developed that can guide decision makers through a step-by-step process. Within an experimental analysis context, a decision support system is built that uses the “Expert Choice” cell to test the effectiveness of the introduced framework. The results indicate that the study's method can greatly enhance the decision making capabilities of firms contemplating automation     

The integration of manufacturing and cost information into the engineering design process

In manufacturing systems engaged in the batch manufacture of discrete products, critical decisions on materials and processes are made during the design phase, decisions having significant impact on costs of production. A new computer aided design tool has been developed to enable product designers in small to medium size companies to incorporate manufacturability and cost criteria into their decision making. The paper describes the rationale of the system and its mode of operation. Experiments to validate its practicality and usefulness have yielded encouraging results.     

A Decision-Information-Synchronisation perspective on the performance of FMS

The performance of a Flexible Manufacturing System (FMS) largely depends on how the control system can control the flow of entities in the system. The control system takes control decisions based on the information provided as an input to the decision-making process. Therefore, it is important that the decision-making process and information systems operate in a synchronised manner with respect to the FMS characteristics. This can also be referred to as a Decision-Information-Synchronisation (DIS) operating zone implemented in the control system. To study the DIS in the present research, three types of visibility for decision-makers in FMS shop-floor control have been identified: (1) no local visibility, (2) physical local visibility and (3) physical and information local visibility of decision-maker/operator. These alternative visibilities and automation levels of decision and information system provide the hybrid environments of FMSs control. The current paper presents an approach to identify the DIS operating zone of FMS with suitable visibility of decision-maker and automation level. Simulation results show that under non-real-time control (low automation level in decision and information system) with physical local visibility, the FMS system performs comparable with the real-time control (high automation level in decision and information system) when routing flexibility levels are presented. Under the current global competitive environment, this study helps industrial managers determine a suitable level of visibility and automation in planning an FMS control system in order to obtain the desired performance at the lower cost.     

用户认知视角下的产品设计方法研究

目的 为提高用户认知与产品映射关系的明确性与有效性,提升产品使用过程中用户认知的满意度。方法 从用户认知视角出发,结合信息加工模型,集成认知任务分析方法与结构方程模型,解构用户认知与产品体验的映射关系,构建用户认知视角下的产品设计方法流程。结果 以老年代步车作为设计研究对象。首先,通过认知任务分析方法明确产品“认知任务—认知路径—设计要素—产品体验”的设计分析流程;其次,引入结构方程模型以确定代步车设计要素权重,识别不同产品体验中的关键设计要素;最后,结合用户人群需求,进行设计决策和方案细化。结论 该方法可识别用户对产品的关键认知触点,减少用户认知在设计创造过程产生的“黑箱”,帮助设计师确定用户认知与产品体验之间的建构路径,为设计师在具体的实践活动中提供明确的设计依据,丰富了认知心理学在设计领域的实践研究。     

Dimensional analysis for investment selection in industrial robots

Investment evaluation and selection of industrial robots is a complex multicriteria decision-making task. This paper considers the possibility of applying to the robot selection problem a known mathematical method based on Dimensional Analysis (DA) theory. It is shown how it is possible to obtain an easy, efficient and robust decision-making support system which overcomes all attribute dimension problems. In particular, the robustness of the DA approach when compared with judgements made by a group of experts concerning different factors and weights, is evaluated. DA low sensitivity is compared with a weightedpoint decision method found in the literature.     

Using Taguchi design,regression analysis and simulation to study maintenance float systems

This paper proposes a new strategic approach for the maintenance float decision models. This new approach incorporates Taguchi experimental design, Taguchi's ANOVA procedure and regression analysis. Taguchi experimental design is used to generate the input variables into the simulation program. The results are analysed using Taguchi's ANOVA procedure. Input variables found significant are subsequently applied in a regression model. Predictor models for the system utilization are developed and their validity tested. Cost oriented decision models are further developed to show the applicability of our models to decision situations. The major advantage of the strategic approach proposed here is that it saves time and reduces the cost of running simulation. This approach will also offer a decision support and improve the effectiveness of maintenance float decisions.     

认知科学与设计研究

目的阐述设计师应如何看待认知科学。方法结合高端重大装备设计领域的学识和经验,详细解读认知科学。结论认知科学是人工智能的基础,设计师必须具备理解任务内容和解决问题的智慧,也就是“心智”,即人类学习、理解、产生决策的心智能力。人工智能尝试用计算来表达人的理解和心智。心智是认知过程产生结果的“集合”,因此设计师首先要懂得认知科学。     

复杂系统人机交互中的多任务调度策略综述

目的 随着自动化技术的不断发展,系统的复杂性导致多任务成为人机系统交互中常见的场景,多任务呈现出信息模态的复杂化、任务类型多样化、任务中断普遍化等特点,其中多任务的调度策略对系统的运营安全和绩效起着十分重要作用.通过梳理和总结复杂系统人机交互中的多任务调度策略,旨在解决复杂人机系统在设计、建造、维护过程中的问题.方法 通过对国内外相关文献的回顾,以认知心理学的双任务转换生理机制实验研究为起点,从任务调度策略研究逐步分析延展到中断管理和多任务调度决策的发展过程,着重围绕人机交互过程中的多任务调度行为和任务突显性、优先级、参与感、难度、执行时间等不同属性对任务调度决策的影响,进行了详细梳理和总结.结论 在研究综述和相关文献的基础上指出了既有任务调度策略研究中存在的局限性,并从系统交互设计的角度对将来的人机交互多任务管理研究提出了建议.     

Development of a Structured Methodology for Knowledge Elicitation: Applications to Flexible Manufacturing Systems

While automation in the discrete parts manufacturing industry has increased productivity and improved product quality it has also significantly altered the role played by the operator of the system. The operators' role has not only become more critical to the effective functioning of the system but also causes mental overload and imposes greater demands on humans' information processing capabilities. This paper examines methods by which the mental overload experienced by operators can be alleviated while sustaining improvements in productivity and product quality. Additionally, the possibility of reducing mental overload by training and aiding the operator and effecting a more optimal allocation of function using dynamic allocation of function schemes is reviewed. It is concluded that a prerequisite to using the above methods to reduce mental overload is the ability to build appropriate decision support systems. A methodology that allows the development of such decision support systems is described and results of a study to evaluate the methodology are presented.     

Value analysis as a decision support tool in cruise ship design

In the cruise ship industry product development and production activities are really complex and must follow strict rules imposed by naval registries. Designers are frequently required to choose among several alternative solutions (e.g., materials, components, layouts, etc.). Because of time constraints, as a matter of fact, design decisions are made fast and in a reactive way, according to the particular case, without considering decisions made in the past and without using specific decision support tools. The final choice is often left to a single designer's experience, whose selection criteria are unknown and not formalised. As a consequence there is no shared knowledge justifying the reason why a design solution has been chosen and whether it is the best one. We developed and implemented in Fincantieri S.p.A. – a leading company in the cruise ship industry – an original decision support tool, based on value analysis, designers can use to document and formalise their choices. Value analysis is a well known structured method to increase product value and/or cut costs, thus supporting the selection of the most valuable solution by means of objective parameters. We demonstrate that the proposed tool can also facilitate reuse of the available knowledge base on decisional criteria, increase interactions between people (design staff, buyers, shipyard personnel, etc.) involved in different stages of different value analysis projects, and reduce decision time.     

Understanding reliance on automation: effects of error type,error distribution,age and experience

An obstacle detection task supported by ‘imperfect’ automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over-relying on it during non-alarm states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behaviour according to the characteristics of the automation similar to younger adults, although it took them longer to do so. The results of this study suggest that the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human–automation interaction can help designers of automated systems to make predictions about human behaviour and system performance as a function of the characteristics of the automation.     

基于KANO模型的后共享时代单车设计决策研究——从设计师与消费者视角

目的 探究消费者对共享单车的需求偏好,获取用户和设计师对产品的认知差距,并提出相应的设计决策,为共享单车以及两轮车行业的产品创新提供启迪与参考。方法 从设计师思维与消费者偏好的视角出发,对共享单车消费者偏好的各项设计原则(属性)进行细致分类,建立8个评价维度与41个评价特征,采用KANO模型对有效回收样本进行定量统计及定性分析。结果 基于前期调研与KANO模型分析,提出后共享时代单车设计的相关策略。结论 在后共享单车时代下,设计师需要根据用户真实的产品偏好与体验感知进行设计策略的研究,以设计出真正满足用户需求和体验期望的产品。同时也证明KANO模型作为一种阐明用户不同感性需求的方法,有助于设计师进行设计决策的综合判断,提升设计的竞争力。