Model-based Reasoning Approach Research Articles

Analyzing goal variability in cyber-physical system networks

Networks of collaborative cyber-physical systems can achieve goals individual systems are incapable of achieving on their own. However, which goals such a network can achieve depends, in part, on the networks current configuration, i.e. its composition of partaking individual systems. As networks of collaborative cyber-physical systems are of a dynamic nature, the composition of such a network can change during runtime, leading to a plethora of often similar, albeit slightly different configurations. Due to the huge number of possible configurations and their various dependencies to the different goals of the network, it is infeasible to handle this amount of information manually. Hence, to provide support for reasoning about dependencies between different configurations and the goals they can achieve, this paper contributes an automated model-based reasoning approach using view generations. Our approach allows for exploring which goals can be fulfilled by which configurations and which goals cannot be fulfilled by these configurations. We evaluated the approach using an industrial case study which shows the applicability of the approach and a controlled experiment which shows the benefits of the approach.

Model-based Reasoning Approach for Automated Failure Analysis: An Industrial Gas Turbine Application


 
 
 Keeping up with the technological advances, turbo- machinery industry aspires to integrate manufacturing, servicing and maintenance of their plants. Typically, these objectives may be accomplished by adoption of condition monitoring services and diagnostic solutions, resulting in improved plant operations, lower maintenance cost, and impart safety and reliability. Specifically, failure analysis, within systematic diagnostics, is a fundamental feature of design and maintenance phase, as it allows fault identification, and its causes and effects that propagate at different system levels. With the large number of subsystems and process flows, failure analysis for industrial gas turbines is non-trivial, and requires expertise of system mechanics, aerodynamics, thermodynamics, etc. Consequently, in order to realize an efficient system analysis, we device an automated model-based approach to failure analysis for industrial gas turbine applications. This paper presents context-independent qualitative models of key turbine components, which are most error-prone, together with their potential failure mode descriptions, and their impact at different system levels. Using an existing reasoning engine, we present behavior models and results for two most vulnerable turbine subsystems i.e. Lubrication Oil System and the Core Gas Turbine Engine. Finally, we evaluate the practical use-cases of this model-based solution implemented for diagnostic services at Siemens AG.
 
 

Computational Idealizations in Software Intensive Science: a Comment on Symons’ and Horner’s paper

This commentary on John Symons’ and Jack Horner’s paper, besides sharing its main argument, challenges the authors’ statement that there is no effective method to evaluate software-intensive systems as a distinguishing feature of software intensive science. It is underlined here how analogous methodological limitations characterise the evaluations of empirical systems in non-software intensive sciences. The authors’ claim that formal methods establish the correctness of computational models rather than of the represented programme is here compared with the empirical adequacy problem typifying the model-based reasoning approach in physics, and the remark that testing all the paths of a software-intensive system is unfeasible is related to the enumerative induction problem in the justification of empirical law-like hypotheses in non-software intensive sciences.

Commentary on the Special Issue

At the outset, I must confess to being very enthusiastic about the line of research being presented. On a larger scale, I am very pleased to see experimental psychology as conducted by applied cognitive scientists focusing on principles of learning, memory, and cognition that have implications for classroom practice. At the same time, these principles, generally speaking, have been available to classroom teachers in one form or another for some time. The question that I keep asking myself is “what didn’t work before, what went wrong?” Why has there been no wide spread adoption of these learning principles by educational professionals? Prior to specific comments about individual contributions, I am going to take the liberty of engaging in some philosophical thoughts. First, I will comment on a couple of metaphors frequently employed by educators when making meaning about educational progress and reform. Second, I will recommend the consideration of “the correspondence principle” as described by Gibson (1994) as a means of facilitating communication among researchers and practitioners. Following comments on individual articles, I suggest the development of a model-based reasoning approach (Mislevy 2009), that should not only enhance the construct validity of the arguments presented, but enhance communication between basic researchers and educational professionals. Models, like metaphors, provide a common referent for communication and are a critical component in the conventionalization process.

Configuration of progressive dies

The computer-assisted configuration of progressive die is a computationally mixed problem. This paper describes the progressive die design problem and reviews some existing research related to the configuration of progressive dies. It explains the model-based reasoning approach used to configure the intermediate and final solutions to the design problem. In particular, the various shape representation and spatial reasoning techniques are presented. Finally, a computer software architecture for the die design system is presented.

Automatic communication from a neutral object model of mechanism to mechanism analysis programs based on a finite element approach in a software environment for CADCAM of mechanisms

The development of an intelligent graphical user-interface system for mechanism analysis and design suggests a neutral object model of mechanisms. This has raised an issue called automatic communication of the neutral object model of mechanism with programs for mechanism analysis and design. In this paper, we particularly address our developed system called GMMFEM which performs the automatic communication of a neutral object model of mechanisms, reported elsewhere, with the finite element program systems for mechanism analysis and design, developed at Delft University of Technology. The finite element approach to mechanism analysis and design has many advantages over others, which makes the current work significant. In addition, because the finite element theory has unanimously been used in analysis and design for flexible mechanisms, the discussion makes sense of generality. An approach called model-based reasoning, is clarified and four features or ingredients of this approach are concluded. We illustrate the appropriateness of the approach to our problem and recognize the need of a Finite Element Mechanism Model (FEMM) in the GMMFEM system. FEMM is built by using a semantic data modelling approach to make the model more generic and extendable. The reasoning strategy and reasoning in the GMMFEM system to perform the automatical communication via FEMM are presented. The model-based reasoning approach to the GMMFEM system is applicable to other Computer Aided Engineering (CAE) systems.

COMET: An Application of Model-Based Reasoning to Accounting Systems

An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that process millions of transactions to produce the numbers summarized in a company's financial statements. Accounting sys-ems contain internal controls, procedures designed to detect and correct errors and irregularities that can occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur and evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. To cope with this complexity and variability, the COMET system applies a model-based reasoning approach to the analysis of accounting systems and their controls. An auditor uses COMET to create a hierarchical flowchart model that describes the intended processing of business transactions by an accounting system and the operation of its controls. COMET uses the constructed model to automatically analyze the effectiveness of the controls in detecting potential errors. Price Waterhouse auditors have used COMET on a variety of real audits in several countries around the world.

A general methodology for developing intelligent CAE systems — a model-based reasoning approach

A general methodology for developing intelligent CAE systems is presented, which is based on a so-called Model Based Reasoning Approach (MBRA) in knowledge engineering. Generic features of CAE systems are described, and a generic model for the architecture of CAE systems with these generic features is then presented. A model-based reasoning approach is modified for implementing the generic model. A case for developing a computer system for the mechanism design based on a specific finite element theory is used to explain the methodology.

Aircraft warning systems: application of model-based reasoning techniques

The warning systems fitted to the current generation of civil air transport aircraft represent a significant advance on earlier technologies. One important outcome of this development has been the centralized alerting and monitoring systems that present information directly to pilots via multifunction displays. Despite these advances, there are still areas where substantial improvements might be made on current systems. In this paper a brief review is provided of the design issues associated with current aircraft warning systems, and the potential benefits of an 'intelligent' warning system are identified. This system would be capable of monitoring and interpreting data from aircraft systems and flight operational conditions, and in the event of failures and abnormal conditions, would provide the crew with a high-level interpretation of the malfunction. In addition, it would generate appropriate crew actions and prediction of future trends. The use of a model-based reasoning approach to this task is outli...

An engineering approach to model-based troubleshooting in communication networks

A model-based reasoning approach called model refinement, which has been used in an experiment to reason about faults on trunks, is presented. In the model-refinement approach, heuristics are used to generate an appropriate level of description, depending upon symptoms. Related-issues on developing a model-based expert system are also discussed, namely, translating models into rules for efficiency, and user interface requirements for system explanations. Some of the unresolved problems with model-based reasoning are examined, with emphasis on the deficiencies of the model-refinement technique.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>