Formal Process Model Research Articles

Armadale: A Case-Study in Environmental Epidemiology

SUMMARY A variety of statistical techniques are suggested for the analysis of data where the incidence of respiratory cancer is thought to be related to a putative pollution source. Nonparametric kernel regression techniques and more formal point process models are considered. Parameter estimation based on maximum likelihood is discussed. Extensions to an existing model are proposed, and a new hybrid model is also fitted.

Formal process modelling

As the use of formal methods for computer systems development is now widely taught and commonly practised, their use for business process modelling is now considered. In the same way that formal system models are used to rationalize the implementations of complex computer systems, formal process models may be used to rationalize system requirements of complex business processes. The paper examines this thesis by way of a case study in the use of formal modelling to analyse systems requirements for an order fulfilment process.

Standardized Data Exchange between CACSD Systems

With the increasing number of CACSD program packages the number of different data formats increases, which are used to store measurement data and design results in form of process models, control systems and simulation data. In order to exchange such data between different program packages, the ≪VDI/GMA Committee 5.6 CACSD Tools≫ has proposed a guideline, which describes a standard data format for CACSD data objects. The purpose of this paper is the presentation of this proposal. It comprises the discussion of the data objects within several object classes, the syntactical formulation according to DIN 66280 and application examples.

Process Fault Diagnosis Based on Process Model Knowledge: Part I—Principles for Fault Diagnosis With Parameter Estimation

A computer assisted fault diagnosis system (CAFD) is considered which allows the early detection and localization of process faults during normal operation or on request. It is based on an on-line engineering expert system and consists of an analytic problem solution, a process knowledge base, a knowledge acquisition component and an inference mechanism. The analytic problem solution uses a process parameter estimation, and the detection of process coefficient changes, which are symptoms of process faults. The process knowledge base is comprised of analytical knowledge in the form of process models and heuristic knowledge in the form of fault trees and fault statistics. In the phase of knowledge acquisition the process specific knowledge like theoretical process models, the normal behavior and fault trees, is compiled. The inference mechanism performs the fault diagnosis, based on the observed symptoms, the fault trees, fault probabilities and the process history. This is described in Part I. In Part II case study experiments with a d.c. motor, centrifugal pump, a heat exchanger, and an industrial robot show practical results of the model based fault diagnosis.

Process Fault Diagnosis Based on Process Model Knowledge: Part II—Case Study Experiments

A computer assisted fault diagnosis system (CAFD) is considered which allows the early detection and localization of process faults during normal operation or on request. It is based on an on-line engineering expert system and consists of an analytical problem solution, a process knowledge base, a knowledge acquisition component and an inference mechanism. The analytic problem solution uses a process parameter estimation, and the detection of process coefficient changes, which are symptoms of process faults. The process knowledge base is comprised of analytical knowledge in the form of process models and heuristic knowledge in the form of fault trees and fault statistics. In the phase of knowledge acquisition the process specific knowledge like theoretical process models, the normal behavior and fault trees is compiled. The inference mechanism performs the fault diagnosis, based on the observed symptoms, the fault trees, fault probabilities and the process history. This is described in Part I. In Part II, case study experiments with a d.c. motor, centrifugal pump, a heat exchanger and an industrial robot show practical results of the model based fault diagnosis.

Toward formal models of software engineering processes

In this paper, a Petri net-based formal specification method for distributed systems is applied to the domain of software process modeling. We introduce domain-specific concepts stressing the distributed and dynamic nature of software processes. Development states are viewed as distributed entities. Development activities are characterized by their effects on software objects, pertinent information exchange with human or technical participants involved, and local changes to development states. These dynamic aspects of software processes are represented as labeled Petri nets. Structuring mechanisms are sketched which support hierarchical decomposition and systematic combinations of separate views of a software engineering process.

Implementation of hill orthotropic criterion in finite strain elastoplasticity for sheet metal forming

In order to develop a three dimensional finite element computer program related to the sheet metal forming process modeling for car industry, we are currently implementing an adapted finite elastoplastic strain module. Our aim is then to progress in representing the deep drawing steel behaviour, especially to describe a wide range of complex strain paths. This module is based on a large strain membrane formulation using a set of curvilinear coordinates and the classical Hill orthotropic criterion with non-associated (or associated) plastic flow rule and mixed (isotropic and/or kinematics) hardening. Experimental/numerical comparisons on testing cups have been carried out and discussed to select the suitable hypotheses.

Implementation of hill orthotropic criterion in finite strain elastoplasticity for sheet metal forming

In order to develop a three dimensional finite element computer program related to the sheet metal forming process modeling for car industry, we are currently implementing an adapted finite elastoplastic strain module. Our aim is then to progress in representing the deep drawing steel behaviour, especially to describe a wide range of complex strain paths. This module is based on a large strain membrane formulation using a set of curvilinear coordinates and the classical Hill orthotropic criterion with non-associated (or associated) plastic flow rule and mixed (isotropic and/or kinematics) hardening. Experimental/numerical comparisons on testing cups have been carried out and discussed to select the suitable hypotheses.

Process Fault Diagnosis Based on Process Model Knowledge

A computer assisted fault diagnosis system (CAFD) is considered which allows the early detect ion and localization of process faults during normal operation or on request. It is based on an on-line engineering-based expert system and consists of an analytic problem solution, a process knowledge base, a knowledge acquisition component and an inference mechanism. The analytic problem solution uses a process parameter estimation, and the detection of process coefficient changes, which are symptoms of process faults. The process knowledge base comprises analytical knowledge in form of process models and heuristic knowledge in form of fault trees and fault statistics. In the phase of knowledge acquisition the process specific knowledge like theoretical process models, the normal behaviour and fault trees, is compiled. The inference mechanism performs the fault diagnosis, based on the observed symptoms, the fault trees, fault probabilities and the process history. Case study experiments with a d.c.-motor, centrifugal pump, a heat exchanger and a grinding machine show practical results of the model based fault diagnosis

Process Fault Diagnosis Based on Process Model Knowledge

A computer assisted fault diagnosis system (CAFD) is considered which allows the early detection and localization of process faults during normal operation or on request. Tt forms an on-line expert system, which consists in an analytic problem solution, a process knowledge base, a knowledge aquisition part and an inference mechanism. The analytic problem solution is based on process parameter estimation, and on the detection of process coefficient changes, which are symptoms of process faults. The process knowledge base comprises analytical knowledge in form of process models and heuristic knowledge in form of fault trees and fault statistics. In the phase of knowledge acquisition the process specific knowledge like theoretical process models, the normal behaviour and fault trees, is compiled. The inference mechanism performs the fault diagnosis, based on the observed symptoms, the fault trees, fault probabilities and the process history. Case study experiments with a d.c.-motor, centrifugal pump and an heat exchanger show the performance of the model based fault diagnosis.

A conceptual model and empirical analysis of children's acquisition of spatial knowledge

How adults and children come to understand, represent and behave within their spatial environment are topics of great interest to geographers, psychologists, environmental planners and laypeople. Considerable research and theory has been published on these and related topics. In this paper, we will review some of what is known and theorized about spatial cognition and then consider elements of our research program on the acquisition of spatial knowledge. We focus on two intimately related topics. The first is the development of a conceptual model of the knowledge structures and processes associated with acquiring, representing and accessing knowledge of a given environment. The conceptual model forms the basis for a formal computational process model intended as a simulation of actual knowledge and performance in way finding tasks. The second emphasis is an in-depth case study of the acquisition of spatial knowledge. The case study focuses on a single child acquiring knowledge of a lengthy route through an unfamiliar suburban neighborhood. It is presented as an empirical test of certain assumptions embodied within the conceptual model. Before introducing the conceptual model and the case study, we first review the state of current theory and data on spatial cognition and identify four central issues confronting researchers in this field. This review provides a necessary context for describing and evaluating our program of research. The second section of this paper discusses elements of the conceptual model and its relationship to other formal computational models. The third section considers specific hypotheses about the acquisition and representation of spatial knowledge and tests of these hypotheses from the single in-depth case study. The final discussion section of this paper is a reconsideration of the four issues raised in the first section and necessary and proposed extensions of the current research.

A review on the finite-element method and metal forming process modeling

Recent developments in the application of the finite element method to metal forming process modeling are reviewed. Various finite element approaches, namely, elastoplastic, rigid-plastic, and viscoplastic analyses are presented, including the coupled analysis of heat transfer and metal flow. In concluding the role of finite element analysis in future metalworking technology is indicated.

Formal Models in Political Science

In recent years the journals have published an increasing number of articles which present or utilize formal models of political behavior and political processes. At present, however, this research probably reaches only a small audience. In an effort to broaden that audience this paper attempts (1) to describe and illustrate the use of formal models, (2) to explain why some believe that the construction of models is a useful research method, (3) to identify subfields in which models exist and suggest others where models should exist, (4) to discuss various types of existing models, (5) to offer some basic critical standards according to which research which involves models can be judged.

Integration Of F.ME.A And SA-RT: A WayTo Enhance Dependability Characteristics OfCritical Systems?

This paper investigates critical systems from the software engineering perspective. It particularly focuses on analysing the system'models building activities defined as Software Process Modeling and tries to lead to a response to problems such as: Is it possible to enhance the dependability characteristics of the system by using a development environment where constraints about the development activities can be expressed and enacted? Which operation could be automated in a critical system development environment leading to a better dependability. Early activities in the system life cycle related to dependability (such as preliminary hasard analysis) are carried on by methods that exhibit two inconveniences: informality and lack of integration. For exemple, in the Failure Modes and Effects Analysis (F.M.E.A) this drawbacks are present: The formalism of F.M.E.A is limited to a tabular representation of the results from the analysis proess and how the method relates to other activities of the life cycle is not clear. We show that the use of a software process modeling formalism to describe the methods can alleviate at least part of these disadvantages. For this, we present the models for SART and FMEA methods, using the MASP/DL software process modeling formalism, which has been developped in the ALF project. Then merging of the two models achieves the integration between methods; this consists of identifying the links between the objects of the two models, establishing the global orderings of operations to maintain the coherence of artefacts and identifying the causes to effects relationships between operations and modeling them through control mechanisms

Process models and stochastic theories of simple concept formation

A class of information-processing models, stated in computer programming language, is constructed for a concept attainment experiment previously studied by Bower and Trabasso. The stochastic theory of Bower and Trabasso can be derived formally from the process models, but the process models, with fewer degrees of freedom, make more specific predictions over a wider range of experiments than the stochastic theory—hence are more universal, precise, and parsimonious in the sense of Popper. The formal process models are shown to be useful in discovering inconsistencies and unstated assumptions in informal descriptions of the psychological processes underlying the stochastic theory. The fit of the “fine-grain” statistics of the stochastic theory to the data is shown to be independent of the psychological content of the theory.