Hierarchical Decision Making in Stochastic Manufacturing Systems

A function modeling methodology was used to analyze and graphically describe the activities and work products of an industrial Human Factors Engineering (HFE) group. A model was constructed representing the HFE functions and describing the information that interrelates them. Data was collected to estimate the amount of staff effort devoted to each of the functions. The model: (a) identifies where actual practice departs from desired practice; (b) pinpoints where and how critical project deliverables are generated, (c) provides the basis for a standardized approach to the conduct of HFE; and (d) serves as a training vehicle for new staff members. The results of the data collection showed that 83% of HFE activities are devoted directly to performing technical functions. These efforts reflect a “classical” Human Engineering approach which emphasizes human-machine system analysis, design and evaluation. Less staff effort is devoted to the larger Human Factors domain which is concerned, per se, with personnel subsystem issues.

As the brain of Nuclear Power Plant (NPP), Main Control Room (MCR) is an integrated system which comprises varieties of Human System Interfaces (HSIs), procedures, operators and environment. HSI is the medium that the operators monitor and control the Nuclear Power Plant. To improve the operating performance and avoid human errors, Human Factor Engineering (HFE) is required to be implemented in the new plant HSI design for plant safety. HPR1000 has followed the NUREG-0711 as the guidelines of HFE program, in which 12 elements are included. Task Analysis (TA) and Human Factor Verification & Validation (HF V&V) are two important elements for the HSI design. For task analysis, the design engineers could analyze the human actions (HAs) to identify the tasks that the operators must perform to accomplish the plant functions. Task analysis identifies not only the specific tasks needed to accomplish HAs but also the information, and controls required to complete those tasks which are considered as important input for the MCR HSI design. HF V&V is one of the final stages of the Human Factors Services as included in NUREG-0711. The HF V&V objective is to evaluate that the HSI design conforms to HFE design principles and that the adequacy of the interfaces enable plant personnel to successfully perform their tasks and other operational goals, assuring plant safety. The V&V element consists of four major activities: Sampling of Operational Conditions, Design Verification, Integrated System Validation, and HED Resolution. For different targets, Design Verification could be separated into two kinds of activities: HSI Task Support Verification (TSV) and HFE Design Verification (DV). TSV is an evaluation to verify that the HSI supports the requirements of personnel tasks, as defined by task analyses. The HAs, controls and information identified in task analysis could be used as the basic input for HSI TSV. To provide adequate input for the HSI design and TSV, the operational conditions of task analysis should be sampled as many as possible to cover all the typical conditions, which include normal conditions, transients, Design Based Accidents (DBA), Beyond Design Based accidents (BDBA), even severe accidents. The sampled conditions for task analysis would be available for the task support verification of the related HSIs. In conclusion, the task analysis could be used as the design input for HSI, while the task support verification could review the designed HSI with the output information from TA. This paper addresses the research and engineering implementation methodologies for task analysis and HSI task support verification. As the first reactor of HPR1000, HFE program have been carried out in Fuqing 5&6 MCR from preliminary design to final test. The Fuqing 5&6 TA and TSV achievements for MCR HSIs design are summarized in the paper.

Nuclear power plants design is moving toward a wider use of digital computers, especially microprocessors, in information and control systems. The amount of automation and the role of the operator are under discussion in many countries. The view of the operator’s role presently varies. The main opinions can be summarized as follows: 1. Move toward a high degree of automation, fostering the machine role. 2. Use of computer-generated procedures providing information to skilled operators for them to make the final decision. 3. Use of digital systems to help the operator identify problems, decide on the appropriate corrective actions and aid in the execution of those actions. Tecnatom, S.A. has developed an integrated Human Factor Engineering (HFE) methodology, based on international regulations and experience obtained from several national and international projects, combining technology, organization and human elements to generate a Human-Centered Design. Human Factor Engineering (HFE) is the application of the knowledge of human capabilities and characteristics to develop equipment, facilities and systems. With the application of this knowledge, human performance, and therefore system performance, can be dramatically improved. Man/machine systems designed with the human as a key element are inherently safer and more reliable than those that are not. Until recently, design of these human-equipment interfaces has been secondary to “pure hardware” design; that is, equipment and facilities were designed without formal consideration of the implications for operators. Our approach is to systematically apply an HFE methodology that will produce: a) Human-System Interfaces that are easy, friendly to and consistent for the operators. b) Simulator-Assisted Engineering platforms for validation activities in the logic, control and human-system interface areas. c) Training Programs based on the systematic analysis of job and task requirements. d) Procedures derived from the same design process and analyses as the Human-System Interface and Training. Application of good HFE methodology during system development, implementation and operation is, from our point of view, vital for optimal system performance regarding operation activities. “A disciplined approach to HFE helps ensure that humans are considered integral system components, requiring careful consideration of how they will interact with their equipment.”

We explain the main ingredients of the Abstract State Machines (ASM) method for high-level system design and analysis and survey some of its application highlights in industrial software-based system engineering. We illustrate the method by defining models for three simple control systems (sluice gate, traffic light, package router) and by characterising Event-B machines as a specific class of ASMs.We point to directions for future research and applications of the method in other areas than software engineering.

An approach to improve human reliability is introduced in this chapter. Major methods to analyze human reliability have been reviewed in Chapter 7. Chapter 8 presents human factors-related activities to design a human-machine interface (HMI), especially for nuclear power plant (NPP) applications. Human factors engineering (HFE) is strictly applied in the nuclear industry. Designing a good HMI enhances human reliability and prevents human errors, as well as helping with training and proceduralization. An HFE process to design an HMI for a safety critical system that requires high reliability for operators consists of three steps: analysis, design, and verification & validation (V&V).

This paper conducts an in - depth exploration of the application of industrial engineering in the Chinese prickly ash industry. Through a systematic analysis of the planting, processing, and logistics aspects of Chinese prickly ash, it elaborates on how the concepts, methods, and technologies of industrial engineering can enhance the overall efficiency of the industry. By using methods such as literature research and field investigations, and integrating theories like human factors engineering, facility planning, and logistics analysis in industrial engineering, this study analyzes the current situation of the industry and proposes improvement strategies, aiming to promote the modernization of the Chinese prickly ash industry and provide theoretical support and practical guidance for its upgrading.

The Deepwater Channel Phase III Regulation Project of Yangtze Estuary was completed and approved in March 2010, and deepwater channel has been extended to Dangxikou of Taicang City at the end of 2010. According to the national plan, in order to give full play to the benefits of the Yangtze river golden channel, the 12.5m deepwater channel will be extended to reach Nanjing Harbor, thus about 400km long 12.5m deepwater channel will be constructed. Therefore, deepwater channel of Nanjing downstream project is carried out by Ministry of Transportation and Communication and Jiangsu Province Government. The project is another major water transportation engineering following the Yangtze estuary deepwater channel regulation project. The project will be implemented in two phases, in which phase I is located in Taicang～Nantong reach of Yangtze River, immediately following the completed Yangtze Estuary 12.5m deepwater channel. There are two major navigation-obstructing channels in this reach —— Tongzhou Shoal channel and Baimao Shoal channel. Based on preliminary works of riverbed evolution analysis, mathematical model calculation and other researches, depended on existing large-scale and wide-range Yangtze River estuary model, fixed and movable bed physical model tests were used to study the comparable feasibility scheme and optimization scheme. Through analysis, four fixed bed model and three movable bed model representative hydrodynamic conditions were considered, channel regulation effects, beach protection effects, and influences on river regime, flood control and nearby regions after implementing the two engineering schemes were all comparatively analyzed from water level, velocity, flow direction, braided channel diversion ratio, riverbed erosion and deposition and other aspects. Studies suggest that: after implementing the two engineering schemes, the planned 12.5m channel is continuous, the 500m×12.5m requirement is satisfied with slight dredging; compared with the feasibility scheme, beach protection effects of optimization scheme for Tongzhou Shoal is roughly equal with the feasibility scheme, while for Baimao Shoal, the optimization scheme is better; in optimization scheme, the head of tooth dikes are extended forward, the velocity of shallow areas increased slightly, channel depth improvement effect is better; Langshan Shoal tail submerged dike of optimization scheme can increases the stability of Langshan Shoal tail, and local scouring is decreased. In general, optimization scheme can be the recommend scheme, regulation effects of it are better than feasibility scheme. The relevant results have been used in channel engineering design and decision making.

Operators of critical processes, such as nuclear power production, must contend with highly complex systems, procedures, and regulations. Developing human-machine interfaces (HMIs) that better support operators is a high priority for ensuring the safe and reliable operation of critical processes. Human factors engineering (HFE) provides a rich and mature set of tools for evaluating the performance of HMIs, but the set of tools for developing and designing HMIs is still in its infancy. Here we propose that Microsoft Windows Presentation Foundation (WPF) is well suited for many roles in the research and development of HMIs for process control.

The purpose of the study is to analyze the social environment of Ukraine in order to identify its impact on the parameters of formation and implementation of human capital to substantiate the conclusions for public policy in terms of effective measures for its development. In the course of the research general scientific and special methods of synthesis and system analysis were used (to substantiate the characteristics of human capital); system analysis and theoretical generalization (to assess the state of formation and use of human capital in Ukraine); statistical analysis (to assess the factors influencing the human capital of the country); logical analysis, strategic management (to substantiate the instruments of state policy to improve the human capital of the state); system and comparative analysis (taking into account the peculiarities of human capital formation in Ukraine). The urgency of the problem of analyzing the social environment of the country in the context of tracking its impact on various aspects of the formation and implementation of human capital. The practical significance of the research results is that the indicators of employment and income of the population of Ukraine are analyzed. Negative preconditions for the formation of human capital related to the problems of the labor market and employment have been identified. The characteristic of indicators of social security in Ukraine is given. The growth of state expenditures on social assistance, the development of social infrastructure, which ambiguously affects the strengthening of human capital of the state. The analysis of parameters of social tension in Ukraine is carried out. It is established that high levels of unemployment, crime, and morbidity are problematic aspects (in the context of human capital). Indicators of provision of the population of Ukraine with social infrastructure are analyzed. It is shown that its specific indicators are deteriorating and this is a negative factor in the context of preserving the country's human capital. Conclusions are made regarding the negative preconditions for the impact of the state of the social sphere on the formation, as well as instruments of state policy to improve human capital in Ukraine. The scientific novelty of the research results is the development of methodological support - SWOT-analysis of advantages and disadvantages, tools for improving human capital in the country.

Oral absorption of chemicals can be influenced significantly by the administration vehicle or diluent. It has been observed that the oral absorption of carbon tetrachloride (CCl4) and other volatile organic chemicals is markedly affected by the dosing vehicle, with administration in oils producing erratic blood concentration-time profiles with multiple peaks. Analysis of this type of data by a compartmental modeling approach can be difficult, and requires numerous assumptions about the absorption processes. Alternatively, a system analysis method with few assumptions may provide a more accurate description of the observed data. In the current investigations, a nonlinear system analysis approach was applied to blood CCl4 concentration-time data obtained following iv and oral administration. The oral regimens consisted of 25 mg CCl4/kg body wt given as an aqueous emulsion, in water, as pure chemicals, and in corn oil. The system analysis procedure, based upon a disposition decomposition method, provided an absorption input rate function, F, for each regimen. A physiological pharmacokinetic model, based primarily on parameters available in the literature, and the F input functions, formed a hybrid model that adequately described the observed blood CCl4 concentration-time data. The same physiological pharmacokinetic model, employing conventional first-order absorption input schemes, did not predict the data as well. Overall, the system analysis approach allowed the oral absorption of CCl4 to be characterized accurately, regardless of the vehicle. Though system analysis is based on general mathematical properties of a system's behavior rather than on its causal mechanisms, this work demonstrates that it can be a useful adjunct to physiological pharmacokinetic models.

The quality of man-machine interface (MMI) directly affects efficiency, safety and comfort of the man-machine system. Therefore, it is significant to study an appropriate evaluation technology for MMI. The method of grey relational analysis based on interval numbers is put forward in the field of MMI evaluation in this paper, based on human thinking having the grey and fuzzy characteristic. In this method, interval numbers are employed as a mean to reflect the rating of indexes instead of real numbers, which offer uncertain information. By judging the correlative degree between the evaluation criterion and the design schemes, the optimal scheme can be found. Based on the proposed method, a novel subjective evaluation model of MMI is set up and applied in the subjective evaluation on the digital control system console of the power plant. Results of the evaluation example prove that the proposed method for MMI evaluation is reasonable and applicable.

Chemseddine Mansouri1 and Nasser H. Kashou2,3,4 1CRAN UMR 7039 CNRS-UHP-INPL, Nancy University Vandoeuvre-les-Nancy, 2Department of Radiology, Children’s Radiological Institute, Nationwide Children’s Hospital 3Department of Radiology, Department of Ophthalmology, The Ohio State University Medical Center 4Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, 1France 2,3,4USA

Background: the Skill, Rule, and Knowledge (S-R-K) model is a framework used to describe and analyze human behaviour and decision-making in complex environments based on the nature of the task and kind of cognitive control required. The S-R-K model is particularly useful in fields like human factor engineering, system design, and safety-critical industries because it helps to understand human errors and how they relate to different levels of cognitive control. However, the S-R-K model is still qualitative and lacks specific and quantifiable metrics for determining what kind of cognitive control a person is using at any given time. This aspect makes difficult to directly measure and compare performance across the three levels. This study aimed therefore to characterize the S-R-K model from a neurophysiological perspective by analyzing the operator’s cerebral cortical activity. Methods: in this study, participants carried out experimental tasks able to replicate the Skill (tracking task), Rule (rule-based navigation) and Knowledge conditions (unfamiliar situations). Results: participants’ Electroencephalogram (EEG) was recorded during tasks execution and then Global Field Power (GFP) was estimated in the different EEG frequency bands. Brodmann areas (BAs) and EEG features were then used to characterize the S-R-K pattern over the cerebral cortex and as inputs to build up the machine learning-based model to estimate participants’ cognitive control behaviours while dealing with tasks. Conclusions: the results demonstrate the possibility of objectively measuring the different S, R and K levels in terms of brain activations. Furthermore, such evidence is consistent with the scientific literature in terms of cognitive functions corresponding to the different levels of cognitive control.

First, we present a large expert system. Advice, that has been built to help evaluate the study plans of Systems and Industrial Engineering graduate students. We explain system requirement, program architecture, technical characteristics, and system evaluation. Advice has four components: a knowledge base, an inference engine, a database and an external Interface file. A novel feature of Advice is its use of a DECtalk voice synthesizer that talks to the user. External functions allow M.1 to communicate with this voice syn- thesizer as well as with dBASE II files where the attributes of each course are stored. Although checking study plans may seem like a forward chaining problem, we used M.1 because of its user friendliness and Its convenient support of external functions. Verification and validation was performed to ensure the accuracy and reliability of the system. Advice saved time for both the students and the professors. and provided more accurate and more comprehensive advice for the students. Finally we present a statistical analysis of 25 smal expert systems that were written by undergraduate and graduate students in Systems and Industrial Engineering at the University of Arizona in partial fulfillment of the requirements of a one semester course in Expert Systems From this analysis we conclude that novice knowledge engineers require three to four hours for each kilo byte of knowledge base.

Expert System for the Selection of the Rational Method for Collecting and Processing Information During Russian Census Based on Geographical and Socio-Economic Characteristics of Regions