Proceedings
of the Fourth International
Workshop on Functional Modeling
of Complex Technical Systems
(ISSN 1089-7372) (ISBN
0-9652669-3-1) (Total 216 Pages)
Fourth
International Workshop
Athens, Greece
June 20-21,
1996
Edited by:
Mohammad
Modarres
Center for Reliability Engineering
University of Maryland
2100E Marie Mount Hall
College Park, Maryland 20742-2115,
USA
Modeling complex technical systems is highly desirable but very challenging. Many modeling techniques have been developed and used in scientific disciplines, such as Artificial Intelligence, Risk Assessment, Reliability Engineering and Cognitive Sciences. Each of these techniques are dedicated to a specific aspect of complex systems, and most utilize a structural/behavioural modeling approach to describe the system. For example, in risk assessment, fault tree and event tree models are used to model structural behavioral aspects of nuclear and complex chemical plants. The relative new approach of Functional Modeling is becoming a leading modeling approach for complex physical plants.
The objective of this workshop series is to provide an opportunity to present and discuss various methods and experiences with the functional modeling of complex technical systems. The workshop brings together the world's leading experts in the area of functional modeling from diverse fields (Artificial Intelligence, Risk and Reliability, Safety Critical Computing Systems, Control Engineering and Cognitive Science) to present and discuss:
While all papers propose a functional technique and provide their applications, papers by Atoosa Jalashgar; Mohammad Modarres; Hella Poulsen; and Lefteri H. Tsoukalas, Liang Xinqing and Robert E. Uhrig discuss fundamental issues in functional modeling paradigms. For example, the paper by Hella Poulsen discusses the concept of "actants" and extends the use of this concept in MFM approach.
Additional information on functional modeling, people, IFMAA organization, and future meetings and Workshop may be obtained from the following Web address:
Abstract: This paper describes the selection of functional model type for the design work and outlines the first version of the Goal Tree-Success Tree (GO-ST) model for an autonomous submarine.
Abstract: This paper discusses the application of the Dynamic Flowgraph Methodology (DFM) technique in the context of a mini-benchmark exercise conducted as part of the 1996 Annual Workshop on Functional Modeling and Analysis. The objective of the exercise was to model, analyze and verify the design and the functional behavior of a software-controlled real-time system. The benchmark case study is used to illustrate the basic DFM concept its application in the functional analysis of dynamically controlled engineering systems. Other completed and ongoing applications, relative to NASA space systems and to nuclear power plant systems, are thereafter presented and briefly discussed. The paper also introduces the principal features of the workstation software tool developed to implement DFM.
Abstract: This paper illustrates how Chittaro's methods of modeling functions and goals can be applied to a reliability procedure known as Failure Modes and Effects. The use of functional models links structure to purpose and the central theme of this paper is to show how the design objectives of a system can be linked to the structure using functional models as an intermediary. The models are demonstrated using the agreed example of a Water Supply Process Control System.
Abstract: This paper deals with central issues involved in modeling the hierarchy of basic ingredients of human made systems, that can be identified as the goals, the functions, the behaviors, the potentials, the physics and the physical structure. In that respects, several types of modeling approaches such as structure modeling, physics modeling, event based modeling, and goal and function centered modeling are described, and it is discussed what parts of the system each corresponding model aims to represent. The concepts of goal, function, behavior and potential in connection with human made systems are elaborated in some extents in order to highlight the importance of distinguishing and including them in the system model. Finally, the role of representing goals and functions in improving structure and specially physics modeling approaches is argued.
Abstract: The aim of this paper is to apply firstly two interesting functional analysis techniques for the design of supervision systems for complex processes, and secondly to discuss the strength and the weaknesses of each of them. Two functional analysis techniques are applied: SADT (Structured Analysis Design Technique) and FAST (Functional Analysis System Technique) on the process commonly treated by the group participating to the fourth international Workshop on functional analysis, an example of a Water Supply Process Control (WSPC) system. These techniques allow a functional description of industrial processes. The paper briefly discuss the functionalities of a supervision system and some advantages of the application of functional analysis for the design of a "human" centered supervision system design. Then the basic principles of the two techniques which applies to the WSPC system is presented. Finally, the paper is concluded by making a comparison between the different results obtained from the two techniques.
Abstract: A framework describing the properties of complex physical systems composed of human-software-hardware interactions in terms of their functions is described. It is argued that such a framework is domain-general, so that functional primitives present a language that is more general than most other modeling methods such as mathematical simulation. The characteristics and types of functional models are described. Examples of uses of the framework in modeling physical systems composed of human-software-hardware (hereby we refer to them as only physical systems) are presented. It is concluded that a function-centered model of a physical system provides a capability for generating a high-level simulation of the system for intelligent diagnostic, control or other similar applications.
Abstract: This paper presents the latest progress made in the development of the STARS software environment and of its supporting methodology for modeling complex industrial systems. It introduces the notion of Safety Management information system as a method and a tool to handle all information related to the safety of an industrial system. The Safety Management Information System is based on an objective description of reality where objects have multiple relationships with each other. Different models of a same industrial system correspond to specific perspectives of the network of objects. This object representation is illustrated by a number of examples related to safety and reliability.
Abstract: Facing a growing complexity of industrial plants we recognize the need for qualitative modelling methods capturing functional and causal complexity in a human-centered way. This paper presents Actant Modelling as a functional modelling method rooted in linguistics and semiotics. Actant Modelling combines actant models from linguistics with Multilevel Flow Modelling. Thus the semantics of MFM functions is developed further and given an interpretation in terms of actant functions. A present challenge is to provide coherence between seemingly different categories of knowledge. Yet the gap between functional and causal modelling methods can be bridged. Actant Modeling provides an open and provisional but in no way exhaustive or final answer to how the teleological concepts like goals and functions relate to causal concepts. As the main focus of the paper an actant model of an extraction plant is presented. It is shown how the actant model merges functional and causal knowledge in a natural way.
Abstract: Anticipatory control refers to system regulation based on information about present as well as anticipated future states. Advancements in neurofuzzy soft computing methodologies support the development of anticipatory control where planning and control sequencing functions are integrated with feedback control algorithms. We present a neurofuzzy approach for plant anticipatory control where the predictions are based on neural models of processes and demonstrate it through nuclear reactor regulation. The control method does not require knowledge of plant parameters or structure. It is model-independent, and this may be applied to other nonlinear time-varying dynamic systems. Simulation results show that the approach presented improves tracking performance and smoothness and may be quite insensitive to noise.
Abstract: This paper presents a reference model architecture which is believed to be particularly useful to support reuse-based design of industrial control systems. This architecture, called the GFM Reference Model Architecture, relies upon the concepts of goal, function, behaviour, and structure, thus addressing international as well as causal aspects of a control system. Apparently, this basis seems to be effective for formalization and organization of design information, which is one among many preconditions to achieve efficient reuse of complex design constraints.
The work presented is part of a more comprehensive
approach towards definition of a framework of methods and tools for systematic,
large-scale reuse of design information, supported by the European Commission
under the ESPRIT-3 programme.
