Intelligent Automatic System Research Articles

Understanding social collaboration between actors and technology in an automated and digitised deep mining environment

The purpose of this article is to develop knowledge and learning on the best way to automate organisational activities in deep mines that could lead to the creation of harmony between the human, technical and the social system, towards increased productivity. The findings showed that though the introduction of high-level technological tools in the work environment disrupted the social relations developed over time amongst the employees in most situations, the technological tools themselves became substitute social collaborative partners to the employees. It is concluded that, in developing a digitised mining production system, knowledge of the social collaboration between the humans (miners) and the technology they use for their work must be developed. By implication, knowledge of the human's subject-oriented and object-oriented activities should be considered as an important integral resource for developing a better technological, organisational and human interactive subsystem when designing the intelligent automation and digitisation systems for deep mines. Statement of Relevance: This study focused on understanding the social collaboration between humans and the technologies they use to work in underground mines. The learning provides an added knowledge in designing technologies and work organisations that could better enhance the human–technology interactive and collaborative system in the automation and digitisation of underground mines.

WebDigital: A Web-based hybrid intelligent knowledge automation system for developing digital marketing strategies

This paper presents a Web-based hybrid knowledge automation system, called WebDigital (created by the first and second named authors), for formulating digital marketing strategies. Within this system, various digital marketing strategy models are computerised, adapted and extended. On-line Monte Carlo simulation is employed to capture the stochastic behaviour of relevant factors or variables influencing digital marketing decision making. Web-based fuzzy logic is applied to model the uncertainty surrounding the input and strategic options. On-line “IF–THEN” rules are created to represent and automate associated planning knowledge and guidelines. Web databases are used to pass data amongst different functional components, and store and retrieve simulation results and user entries. The system has been tested using digital marketing cases with involved managers. Evaluation findings indicate that the Web-enabled knowledge automation system is efficient and effective in improving the digital marketing strategy formulation process and its output.

SCADA 기능과 전기품질 온라인 감시 및 배전설비 열화감시 기능을 갖는 배전지능화 시스템 개발

Intelligent distribution automation system have total monitoring and control capability. The system covers substation, distribution network, distributed generations and customers at HV system. Various intelligent distribution facilities installed at distribution systems have voltage sensor, current sensor, aging monitoring sensor. Intelligent Feeder Remote Terminal Unit (IFRTU) tied to intelligent distribution facilities process information from facilities and it checks information of fault, power quality and aging of distribution facilities. The information is transmitted to master station through communication line. The master station have remote monitoring system covers substation, distribution network, distributed generations and customers. It also have various application programs that maintain optimal network operation by using information from on-site devices.

Industrial Wireless Sensor Networks: Challenges, Design Principles, and Technical Approaches

In today's competitive industry marketplace, the companies face growing demands to improve process efficiencies, comply with environmental regulations, and meet corporate financial objectives. Given the increasing age of many industrial systems and the dynamic industrial manufacturing market, intelligent and low-cost industrial automation systems are required to improve the productivity and efficiency of such systems. The collaborative nature of industrial wireless sensor networks (IWSNs) brings several advantages over traditional wired industrial monitoring and control systems, including self-organization, rapid deployment, flexibility, and inherent intelligent-processing capability. In this regard, IWSN plays a vital role in creating a highly reliable and self-healing industrial system that rapidly responds to real-time events with appropriate actions. In this paper, first, technical challenges and design principles are introduced in terms of hardware development, system architectures and protocols, and software development. Specifically, radio technologies, energy-harvesting techniques, and cross-layer design for IWSNs have been discussed. In addition, IWSN standards are presented for the system owners, who plan to utilize new IWSN technologies for industrial automation applications. In this paper, our aim is to provide a contemporary look at the current state of the art in IWSNs and discuss the still-open research issues in this field and, hence, to make the decision-making process more effective and direct.

광 EtherCAT을 이용한 네트워크 기반 모터 제어기 개발

In this paper, we design, implement and apply network physical layer to 100 BaseFx optical cable interface module based on industrial ethernet protocol which is physical layer of EtherCAT that has ensure its open standard ethernet compatibility which having been provided with real time of control in network of intelligent service robot, can be process numerous data to sensor and motor control system. Through BLDC motor control performance tests, we try to propose suitability as internal network of intelligent service robot and automation system.

Integrated management and optimization of the sanitation cycle using intelligent automation systems and communication networks

The recognition of the importance of our planet's water resources by human society increased significantly during the last decade. With a growing population and environmental degradation, an efficient management of water resources is even more vital to mankind. This article introduces a new systemic proposal for an efficient management of water treatment stations and also the entire sanitation cycle. Maximizing the efficiency of water resource management, as proposed in this article, requires the development and implementation of an automation system based on intelligent systems and communication networks. Therefore, the proposal of integrated management and optimization of the sanitation cycle presented in this article is a contribution to the improvement of sustainability for human evolution.

Modelling Na and Cl concentrations in the recycling nutrient solution of a closed-cycle pepper cultivation

A mass balance model relating the concentrations of Na or Cl in the recycled nutrient solution to the cumulative uptake of water by the plants was calibrated and validated in greenhouse sweet pepper crops grown in closed-cycle cultivation systems. The results indicated that the model allows for simulation of the courses of Na and Cl accumulation in closed-cycle cultivations of pepper, provided that the fluctuations in the volume of drainage solution and the moisture status of the substrate during the cropping period are small. Furthermore, the model predicts a delay in the process of salt accumulation in closed-cycle hydroponic systems when the drainage percentage is relatively high due to enhanced irrigation frequency, in compassion with standard irrigation frequency. The proposed model may be incorporated into intelligent automation systems to automatically adjust the target total salt concentration in the outgoing irrigation solution to levels allowing for a constant nutrient supply, despite the Na and Cl accumulation in the recycled leachate. As a result, the entire amount of drainage solution can be recycled without risking depletion of essential nutrients in the root zone.

Integrated Digital Automation System for Production Optimization in the North San Juan Basin

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 106952, "Successful Application of Integrated Digital Automation System for Production Optimization in the North San Juan Basin," by Peter O. Oyewole, SPE, Michael D. Scull, and Mark S. Downey, BP plc and John B. Herring, SPE, Pure Automation, prepared for the 2007 SPE Digital Energy Conference and Exhibition, Houston, 11–12 April. An integrated digital automation system was used to optimize tubing-flow-control and plunger-lift installations in the north San Juan basin. The intelligent closed-looped automation system increased gas production, improved equipment reliability, and provided an efficient and inexpensive deliquification method with an almost exclusively remote-controlled operation. Introduction Gas-well production tends to decrease over time as a result of depleting reservoir pressure. The liquids associated with the produced gas accumulate in the wellbore. The liquid column creates hydrostatic backpressure on the reservoir, which further reduces the gas flow rate. A minimum gas-flow rate is required to lift the entrained liquid droplets to the surface at a specific wellhead pressure. Several artificial-lift and dewatering methods are available to lift liquid from the bottom of the well to the surface; one is plunger lift. In some marginal gas wells, anticipated production would not justify installing artificial-lift systems such as a sucker-rod pump to dewater wells. In some applications, plunger lift is an economical choice. Plunger lift is an intermittent form of artificial lift that uses the reservoir energy to lift liquids out of the wellbore. Plunger lift has benefited from improved digital technology. The entire system can be completely monitored and optimized. Unlike conventional natural-gas reservoirs in which gas production rates tend to be greatest at the onset, then steadily decline over the life of the well, coalbed methane produced in the north San Juan basin progressively increases to a maximum flow rate several days or years after first production. It is a challenge to match and optimize tubing and casing sizes with the ever-changing production rate. Applying optimized tubing-flow control helps to mitigate these challenges. Integrated Digital Automation Input/output (I/O) abstraction is the function that defines the connection between physical I/O and the applications or process I/O, or between a calculated variable and a consuming program. An example of I/O abstraction would be to assign an analog input as casing pressure. The programmer could assign the physical I/O to the casing pressure at design time so that "Analog X" is always casing pressure. In an abstracted scheme, the analog input is assigned to the casing-pressure variable at run time so that, if needed, the physical input can be assigned to another process variable if the particular installation did not have a casing pressure. An example of a calculated value abstracted and consumed by a program is a critical-flow-rate value placed in a common index or array, and then, by use of mapping, that value is called into a subroutine program-organization unit and used to control a plunger process.

Guest Editorial Introduction to the Focused Section on Advanced Integrated Mechatronics

The 11 regular papers and four short papers in this special section focus on the research issues of advanced integrated mechatronics. The topics include advanced mechatronic sensing, devices and control, biomechatronics for better life, intelligent mechatronic systems, infotronics-enabled mechatronics systems, intelligent automation systems, and innovative applications of mechatronic systems.

Intelligent automation systems for predictive maintenance: A case study

A case study is presented, where a predictive maintenance solution for non-critical machinery (such as elevators and machine tools) was sought. Both cases are different. There is no experience in elevator monitoring and diagnosis, and modeling has been performed using Neural Networks. On the other hand, machine tools were monitored through vibration systems where some experience exists. In this case, Bayesian Networks are the paradigm of choice as it was also recommended to include some ‘adaptation’ mechanism for the knowledge modeled in the network. The final system also includes a sensor processing unit and a remote maintenance module system that provides an automated remote condition monitoring system, for both applications. Results indicate the feasibility of partial solutions in monitoring and diagnosis, though future enhancements are needed to compose a complete solution. This paper explains the characteristics of the Bayesian Network solution finally developed for high-speed machine tools, evaluate their strengths and weaknesses, and indicate the future enhancements.

Intelligent integrated automation and management systems for administration buildings

During the last two decade there is an evident trend towards integrated and intelligent automation systems in the control and management of public domain buildings for various aims and purposes. The fundamentals and advanced developments in such systems have been studied thoroughly and are reviewed. A feasibility study along with a full scale conceptual engineering design for such a systems aimed at automation of a business administration building in Skopje within a worldwide chain of a certain class of buildings has been elaborated, and is about to be fully implemented. The main resulting outcome, however, is a methodology for designing intelligent integrated building automation and management systems for multi-store buildings aimed at business and administration functions. This paper presents its essential features and results.

Searching a Scalable Approach to Cerebellar Based Control

Decades of research into the structure and function of the cerebellum have led to a clear understanding of many of its cells, as well as how learning might take place. Furthermore, there are many theories on what signals the cerebellum operates on, and how it works in concert with other parts of the nervous system. Nevertheless, the application of computational cerebellar models to the control of robot dynamics remains in its infant state. To date, few applications have been realized. The currently emerging family of light-weight robots (Hirzinger, in i>Proc. Second ecpd Int. Conference on Advanced Robotics, Intelligent Automation and Active Systems, 1996) poses a new challenge to robot control: due to their complex dynamics traditional methods, depending on a full analysis of the dynamics of the system, are no longer applicable since the joints influence each other dynamics during movement. Can artificial cerebellar models compete hereq

Developing distributed real-time systems for industrial automation: Method and tool support

This paper presents an object-oriented approach to the development of real-time computer-based systems (i.e. hardware and software) that are embedded in devices used in intelligent industrial automation systems, such as those required for agile manufacturing and multi-agent systems. The approach covers all development phases, ftom requirements engineering, through hardware and sofiware (co-)design, until implementation. The paper discusses strategies and metrics for identifying and structuring sofiware and hardware components of industrial automation applications using 'real-time autonomous objects' Existing tool support is presented.

An Autonomous Objects Architecture for Developing Flexible Industrial Automation and Manufacturing Systems

This paper presents an object-oriented approach to the development of real-time computer-based systems (Le. hardware and software) that are embedded in devices used in intelligent industrial automation systems, such as those required for agile manufacturing and multi-agent systems. The approach covers all development phases, from requirements engineering, through hardware and software (co)design, until implementation. The paper discusses strategies and metrics for identifying and structuring software and hardware components of industrial automation applications using real-time autonomous objects. Such structuring approach allows a representation of the application domain at a very high level of abstraction. It also allows a very flexible structure for implementing adaptive automation strategies, such as those required in intelligent manufacturing systems. The whole system is considered as a set of communicating autonomous objects, where each object has local processing and decision making capabilities. The proposed approach is explained using a case study of a Wine Bottling Production Line Automation.

Cerebellar Control of Robot Arms

Decades of research into the structure and function of the cerebellum have led to a clear understanding of many of its cells, as well as how learning takes place. Furthermore, there are many theories on what signals the cerebellum operates on, and how it works in concert with other parts of the nervous system. Nevertheless, the application of computational cerebellar models to the control of robot dynamics remains in its infant state. To date, a few applications have been realized, but limited to the control of traditional robot structures which, strictly speaking, do not require adaptive control for the tasks that are performed since their dynamic structures are relatively simple. The currently emerging family of light-weight robots (Hirzinger, G. (1996) In Proceedings of the 2nd International Conference on Advanced Robotics, Intelligent Automation, and Active Systems, Vienna, Austria ) poses a new challenge to robot control: owing to their complex dynamics, traditional methods, depending on a full analysis of the dynamics of the system, are no longer applicable since the joints influence each other's dynamics during movement. Can artificial cerebellar models compete here? In this paper, we present a succinct introduction of the cerebellum, and discuss where it could be applied to tackle problems in robotics. Without conclusively answering the above question, an overview of several applications of cerebellar models to robot control is given.

Three‐dimensional vision technology offers real‐time inspection capability

Describes a three‐dimensional machine vision technology for inspecting and measuring on‐line production. States that the 4DI three‐dimensional imager, a new machine vision technology developed by Intelligent Automation Systems, combines speed and accuracy to perform 100 per cent on‐line inspection and measurement of volumes and surfaces in real‐time. Until recently, neither conventional measurement techniques such as co‐ordinate measurement machines nor non‐contact optical technologies could inspect 100 per cent of production on‐line three‐dimensionally, being either too slow or too sensitive to ambient light. The 4DI uses structured laser light, multiple cameras and triangulation to capture moving or stationary objects. States this technology allows objects of different sizes, ranging from several feet to fractions of an inch to be imaged. States the system has no moving parts, it is robust in industrial environments.

Exploiting Prior Knowledge in Fuzzy Model Identification of a Heat Exchanger

Abstract Intelligent automation systems integrate a great variety of methods based on models of the controlled processes, e. g. model-based control or model-based supervision and fault diagnosis. Hence, there emerges a great demand for modeling techniques suitable for the identification of nonlinear dynamic systems. Besides classical approaches, neuro/fuzzy systems appear promising due to their approximation qualities. In this contribution, it is investigated how Takagi-Sugeno type fuzzy systems can be utilized for identification of a cross-flow water/air heat exchanger. On the one hand, these models provide transparency and interpretability which allows to incorporate qualitative and quantitative prior knowledge about the plant. On the other hand, Takagi-Sugeno models can also be identified from measurement data in order to compensate for incomplete system knowledge. Data gathering requires appropriate excitation of the system. It will be shown how elementary prior knowledge can be exploited for the design of identification signals. The concept of error bars is reviewed, and it is used to roughly evaluate the model quality depending on the properties of the excitation signal. For identification from training data the local linear model tree algorithm (LOLIMOT) is applied.

Designing a parts feeding system for maximum flexibility

Looks at short‐run production, frequent product modifications, and pressures to reduce product time to market make flexible manufacturing increasingly desirable. Despite advances in flexible systems, the problem of feeding parts to an assembly line is not fully addressed by conventional methods such as bowl feeders. New technologies such as Intelligent Automation Systems’ FPF2000 Flexible Feeder for Small Parts offer additional versatility for short production cycles with frequent changes, and multiple simultaneous assembly lines.

The interrelationship between surface froth characteristics and industrial flotation performance

This paper discusses the rapid development in computer technology and neural networks that are used to transform recently developed concepts and available technology into a new generation of intelligent automation systems. In this study features extracted from images of froths by an on-line machine vision system in an industrial precious metal flotation plant were used to relate froth characteristics with the performance of the plant by using self-organising and Sammon maps. This intelligent vision system constitutes a powerful tool for the investigation and interpretation of the effect of various flotation parameters. Previous work is extended by relating surface froth characteristics with industrial flotation control and performance variables. This method of system identification represents a significant development towards an automatic control system.

The interpretation of flotation froth surfaces by using digital image analysis and neural networks

The rapid developments in computer vision, computational resources and artificial intelligence, and the integration of these technologies are creating new possibilities in the design and implementation of commercial machine vision systems. In chemical and minerals engineering, numerous opportunities for the application of these systems exist, of which the characterization of flotation froth structures is a good example of the utilization of visual data as a supplement to conventional plant data. In this paper images from pyrite batch flotation tests conducted after a factorial design as well as images from a copper flotation plant were used to understand the relationship between froth characteristics and flotation performance better. The results show that a significant amount of data can be extracted from flotation surface froths. Techniques have been developed to characterize chromatic information, average bubble size, froth texture, froth stability and mobility of surface froths. It has been shown that most of the froth characteristics of this study can be explained in terms of the concentration of solids in the froth and the factors that affect the solids concentration. The techniques developed proved to be useful in investigating the effect of a mixed collector and the addition of copper sulphate. The depressing effect of the copper sulphate and the higher grades and recoveries made possible by the mixed collector under these conditions were explained by analysis of the froth features. Excellent results were obtained in modelling the relation between froth characteristics or froth grade and recovery by using a backpropagation neural network. A sensitivity analysis showed that the most important froth features for the experimental conditions of this study are the froth stability, mobility and average bubble size. This computer vision system constitutes a powerful research tool for the investigation and interpretation of the effect of various flotation parameters. This paper also shows how the rapid development in computer technology and related disciplines can be used to transform recently developed concepts and available technology into a new generation of intelligent automation systems.