Hosny Abbas

Hosny A. Abbas

Computer-based supervisory control and data acquisition (SCADA) systems have evolved over the past four decades, from standalone, compartmentalized operations into networked architectures that communicate across large distances. There is an emerging trend comprising SCADA and conventional IT units toward consolidating some overlapping activities. This trend is motivated by cost savings achieved by consolidating disparate platforms, networks, software, and maintenance tools. For reasons of efficiency, maintenance, economics, data acquisition, control platforms have migrated from isolated in-plant networks using proprietary hardware and software to PC-based systems using standard software, network protocols, and the Internet. In this thesis, we present an approach for web-based SCADA systems that adapt to the behavior of the target application. In addition, we take into account the real time constraints that imposed by the nature of the problem. We show that our approach is more efficient than other approaches in terms of consuming as little as possible of the available resources (computational power and network bandwidth).

Hosny Abbas

Automation is at the core of modern industry. It aims to increase production rates, decrease production costs, and reduce human intervention in order to avoid human mistakes and time delays during manufacturing. On the other hand, human assistance is usually required to customize products and reconfigure control systems through a special process interface called Human Machine Interface (HMI). Machine Learning (ML) algorithms can effectively be used to resolve this tradeoff between full automation and human assistance.This paper provides an example of the industrial application of ML algorithms to help human operators save their mental effort and avoid time delays and unintended mistakes for the sake of high production rates. Based on real-time sensor measurements, several ML algorithms have been tried to classify paper rolls according to paper grammage in a white paper mill. The performance evaluation shows that the AdaBoost algorithm is the best ML algorithm for this application with classification accuracy (CA), precision, and recall of 97.1%. The generalization of the proposed approach for achieving cost-effective mills construction will be the subject of our future research.

Hosny Abbas, Samir Shaheen, Mohammed Amin

Modern supervisory control and data acquisition (SCADA) systems comprise variety of industrial equipment such as physical control processes, logical control systems, communication networks, computers, and communication protocols. They are concerned with control and supervision of production control processes. Modern SCADA networks contain highly distributed information, control, and location. Moreover, they contain large number of heterogeneous components situated in highly changing and uncertain environments. As a result, engineering modern SCADA is a challenging issue and conventional engineering approaches are no longer suitable for them because of their increasing complexity and highly distribution. In this research, Multi-Agent Systems (MAS) are used to enable building adaptive agent-based SCADA system by modeling system components as agents in the micro level and as organizations or societies of agents in the macro level. A prototype has been implemented and evaluated within a simulation environment for demonstrating the adaptive behavior of the system-to-be, which results in continuous improvement of system performance.

Hosny A. Abbas, Samir I. Shaheen, Mohammed H. Amin

SCADA (Supervisory Control and Data Acquisition) is concerned with gathering process information from industrial control processes found in utilities such as power grids, water networks, transportation, manufacturing, etc., to provide the human operators with the required real-time access to industrial processes to be monitored and controlled either locally (on-site)or remotely (i.e., through Internet). Conventional solutions such as custom SCADA packages, custom communication protocols, and centralized architectures are no longer appropriate for engineering this type of systems because of their highly distribution and their uncertain continuously changing working environments. Multi-agent systems (MAS) appeared as a new architectural style for engineering complex and highly dynamic applications such as SCADA systems. In this paper, we propose an approach for simply developing flexible and interoperable SCADA systems based on the integration of MAS and OPC process protocol. The proposed SCADA system has the following advantages: 1) simple (easier to be implemented); 2) flexible (able to adapt to its environment dynamic changes); and 3) interoperable (relative to the underlying control systems, which belongs to diverse of vendors). The applicability of the proposed approach is demonstrated by a real case study example carried out in a paper mill.

Hosny A. Abbas, Samir I. Shaheen, Mohammed H. Amin

Multi-Agent Systems (MAS) are adopted and tested with many complex and critical industrial applications, which are required to be adaptive, scalable, context-aware, and include real-time constraints. Industrial Control Networks (ICN) are examples of these applications. An ICN is considered a system that contains a variety of interconnected industrial equipments, such as physical control processes, control systems, computers, and communication networks. It is built to supervise and control industrial processes. This paper presents a development case study on building a multi-layered agent-based ICN in which agents cooperate to provide an effective supervision and control of a set of control processes, basically controlled by a set of legacy control systems with limited computing capabilities. The proposed ICN is designed to add an intelligent layer on top of legacy control systems to compensate their limited capabilities using a cost-effective agent-based approach, and also to provide global synchronization and safety plans. It is tested and evaluated within a simulation environment. The main conclusion of this research is that agents and MAS can provide an effective, flexible, and cost-effective solution to handle the emerged limitations of legacy control systems if they are properly integrated with these systems.