Showing papers on "Process modeling published in 1994"

Modeling of combined discrete/continuous processes

Abstract: The dynamic behavior of processing systems exhibits both continuous and significant discrete aspects. Process simulation is therefore a combined discrete/continuous simulation problem. In addition, there is a critical need for a declarative process modeling environment to encompass the entire range of processing system operation, from purely continuous to batch. These issues are addressed by this article. A new formal mathematical description of the combined discrete/continuous simulation problem is introduced to enhance the understanding of the fundamental discrete changes required to model processing systems. The modeling task is decomposed into two distinct activities: modeling fundamental physical behavior, and modeling the external actions imposed on this physical system. Both require significant discrete components. Important contributions include a powerful representation for discontinuities in physical behavior, and the first detailed consideration of how complex sequences of control actions may be modeled in a general manner.

A process study of new technology adoption in smaller manufacturing firms

Abstract: Based on longitudinal case studies of new technology adoption in five smaller Canadian manufacturing firms, this article develops an inductive process model that views the technology adoption process as a partially nested set of three parallel and interacting sub-processes that are different in nature: the strategic commitment process, the technology choice process and the financial justification process. These processes are themselves intertwined with other strategic decision processes in the firm, and influenced by a dynamic set of contextual elements that interact with one another over time. the study underlines the problems associated with a narrow conception of technology adoption as a ‘decision’while showing how various process models from the literature are useful in understanding different parts of the overall process of adoption

Goal decomposition and scenario analysis in business process reengineering

Abstract: This paper presents experiences in applying the goal decomposition and scenario analysis model in the context of Business Process Reengineering (BPR). The relationships of goals, scenarios, as well as the understanding and description of business processes are discussed. Different methods of goal refinement, and the application of scenarios to support this process of refining goals and roles are reviewed. A case study is presented which serves to exemplify and validate the process of using scenarios in refining business process descriptions. We tried deriving full scenarios for business processes, but obtaining them from the organization's prescriptive goals was difficult. Explanatory scenarios that justify descriptive goals are easier to obtain but are fragmentary. We conclude that both types of scenario and goal analysis are necessary for effective BPR. The need for technology support for this process is discussed and attention is given to future anticipated research in this area.

A methodology for business process redesign: experiences and issues

Abstract: Business process redesign (BPR) refers to the endeavour to augment organizational performance by improving the efficiency, effectiveness and adaptability of key business processes This article describes a flexible and extensible methodological framework (called PADM) for BPR which has been developed on the firm basis of several years of practical experience PADM is an eclectic methodology It has been strongly influenced by a number of methodological approaches, most notably soft systems methodology and sociotechnical systems design This article outlines the main features of PADM and describes three recent case studies which show the range and variety of BPR initiatives A number of issues are taken up in the discussion The need for a flexible and adaptable methodology is stressed given the broad spread of studies subsumed under the BPR rubric The dangers of process automation are illustrated and the need for a sociotechnical perspective is underlined Business process redesign entails organization change Many of our case studies fell short of their anticipated impact; various explanations are discussed (politics, culture, information technology inertia) The paper concludes by outlining several fruitful areas for further research and describes a number of aspects of our current work

Training recurrent neural networks: why and how? An illustration in dynamical process modeling

Abstract: The paper first summarizes a general approach to the training of recurrent neural networks by gradient-based algorithms, which leads to the introduction of four families of training algorithms. Because of the variety of possibilities thus available to the "neural network designer," the choice of the appropriate algorithm to solve a given problem becomes critical. We show that, in the case of process modeling, this choice depends on how noise interferes with the process to be modeled; this is evidenced by three examples of modeling of dynamical processes, where the detrimental effect of inappropriate training algorithms on the prediction error made by the network is clearly demonstrated. >

Business Process Reengineering.

Abstract: Re-engineering is a relativity young art that examines the change and reorganization existing business processes in the organization to change the present, be desired situation and the achievement of radical approvement process organization.For very important significance to have these processes in the overall work of the organization, in this paper first define reengineering process.Then explains the process of implementation the BPR by explaining the link between BPR and managers, employees, consumers and application of information technology. On the other side, the re-engineering processes helping them to managers in the selection process and the decision about what actually needs to introduced to the organization.

A paradigm for decentralized process modeling and its realization in the Oz environment

Abstract: We present a model for decentralized Process Centered Environments (PCEs), which support concerted efforts among geographically-dispersed teams - each local team with its own autonomous process - and emphasize flexibility in the tradeoff between collaboration vs. autonomy. We consider both decentralized process modeling and decentralized process enaction. We describe a realization in the OZ decentralized PCE, which employs a rule-based formalism, and also investigate the application to PCEs based on Petri-nets. >

Hybrid modelling of yeast production processes – combination of a priori knowledge on different levels of sophistication

Abstract: Process models are used to formulate knowledge about process behaviour. They are applied, e.g., to predict the process' future behaviour and for state estimation when reliable on-line measuring techniques to monitor the key variables of the process are not available. There are different sources of information available for modelling, which provide process knowledge in different representations. Some elements or aspects may be described by physically based mathematical models and others by heuristically obtained rules of thumb, while some information may still be hidden in the process data recorded during previous runs of the process. Heuristic rules are conveniently processed with fuzzy expert systems, while artificial neural networks present themselves as a powerful tool for uncovering the information within the process data without the need to transform the information into one of the other representations. Artificial neural networks and fuzzy technology are increasingly being employed for modelling biotechnological processes, thus extending the traditional way of process modelling by mathematical equations. However, a sufficiently comprehensive combination of all these techniques has not yet been put forward. Here, we present a simple way of combining all the available knowledge relating to a given process. In a case study, we demonstrate the development of a hybrid model for state estimation and prediction on the example of a yeast production process. The model was validated during a cultivation performed in a standard pilot-scale fermenter.

Artificial Neural Networks - Studies in-Process Modeling and Control

Abstract: In the mid 1980s wide spread interest in Artificial Neural Network research re-emerged following a period of reduced research funding. The much wider availability and power of computing systems, together with new research studies, resulted in a far greater market for the technology. The seeds were sown for claims by some that the technique provided much sought after pragmatic solutions, and by others that it provided a panacea to all complex modelling problems. Unlike ARMA, NARMA and multivariate statistical modelling approaches the methodology has been attributed the potential of accurately describing the behaviour of extremely complex systems. But is the approach so different? Should we not consider the concept of Neural Networks as being an integral part of system representation, modelling and identification? In this respect perhaps we really do have an established, but still developing, theory and technology represented within a new framework. Indeed, selling the technology in anything but this manner might discredit what could well prove to be a valuable engineering tool. We examine the contribution that various network methodologies can make to the process modelling and control toolbox. Feedforward networks with sigmoidal activation functions, radial basis function networks and autoassociative networks are reviewed and studied using data from industrial processes. Finally, the concept of dynamic networks is introduced with an example of nonlinear predictive control

Modeling business processes with simulation tools

Abstract: Provides an overview of business process modeling tools for business process re-engineering (BPR), demonstrates the suitability of simulation for BPR and highlights the modeling considerations. A simulation exercise is presented to illustrate how ServiceModel, a popular modeling tool, may be used to simulate the financial, human resources and production elements of a business. The model is aimed at returning the simulated business to profitability by smoothing out the work backlog, maximizing resource utilization and reducing expenses.

An architecture for the virtual enterprise

Abstract: This paper presents an architecture for the virtual enterprise based upon an object oriented business process modeling approach. The paper proposes that business processes naturally fall into three categories: 1) processes transform external constraints into an internal constraint structure that might be expressed at a system of objectives, policies, and procedures; 2) processes acquire and make ready resources used by the enterprise; and 3) processes (design, marketing, manufacturing, distribution) transform the family of inputs into the desired enterprise results or outputs (i.e. products). The business processes are in turn organized into an enterprise. The paper suggests that the virtual enterprise consists of a set of business processes from category (1) which are collectively owned by the virtual enterprise and a set of business processes from all three categories (1,2,3) which are owned by two or more individual enterprises, but used by both the individual enterprise and the agile or virtual enterprise. The agile enterprise temporarily disturbs but does not consume the individual enterprise. >

Business Process Modelling in the Workflow-Management Environment Leu

Abstract: Most of todays approaches to business process engineering (also called business process management) start from an activity-centered perspective. They describe activities to be carried out within a business process and their relationships, but they usually pay little attention to the objects manipulated within processes. In this article we discuss an approach to business process management which is based on modeling data-related, activity-related, and organizational aspects of business processes. In fact, the Leu approach to business process management considers data models (describing types of objects to be manipulated in a business process and their relationships), activity models (describing activities to be carried out in a business process), and organization models (describing organizational entities involved in a business process) as separate, but equally important, facets of business processes.

Phenomenological Modeling of Fusion Welding Processes

Abstract: Welding is utilized in 50% of the industrial, commercial, and consumer products that make up the U.S. gross national product. In the construction of buildings, bridges, ships, and submarines, and in the aerospace, automotive, and electronic industries, welding is an essential activity. In the last few decades, welding has evolved from an empirical art to a more scientifically based activity requiring synthesis of knowledge from various disciplines. Defects in welds, or poor performance of welds, can lead to catastrophic failures with costly consequences, including loss of property and life.Figure 1 is a schematic diagram of the welding process showing the interaction between the heat source and the base metal. During the interaction of the heat source with the material, several critical events occur: melting, vaporization, solidification, and solid-state transformations. The weldment is divided into three distinct regions: the fusion zone (FZ), which undergoes melting and solidification; the heat-affected zone (HAZ) adjacent to the FZ, that may experience solid-state phase changes but no melting; and the unaffected base metal (BM).Creating the extensive experimental data base required to adequately characterize the highly complex fusion welding process is expensive and time consuming, if not impractical. One recourse is to simulate welding processes either mathematically or physically in order to develop a phenomenological understanding of the process. In mathematical modeling, a set of algebraic or differential equations are solved to obtain detailed insight of the process. In physical modeling, understanding of a component of the welding process is achieved through experiments designed to avoid complexities that are unrelated to the component investigated.In recent years, process modeling has grown to be a powerful tool for understanding the welding process. Using computational modeling, significant progress has been made in evaluating how the physical processes in the weld pool influence the development of the weld pool and the macrostructures and microstructures of the weld.

A‐pool: An agent‐oriented open system shell for distributed decision process modeling

Abstract: An agent‐oriented open system shell, A‐Pool, for distributed decision process modeling in the Internet domain is presented. Unlike most decision support systems, A‐Pool provides a testbed for modeling and understanding the cognitive aspects of distributed decision processes themselves rather than for domain‐specific problem solving. This is achieved with a pool of virtual agents and a pool of cognitive maps of the agents at each A‐Pool node. The virtual agent scheme extends object‐oriented programming to the Internet domain and supports different communication and collaboration protocols with virtual communities, virtual sessions, and virtual conferences. The cognitive map scheme supports perspective sharing and various conflict integration and resolution strategies through cognitive map composition, derivation, and focus generation. Thus each A‐Pool node provides an architecture for modeling interdependencies and for ensuring global coherence; in addition, the communication is asynchronous and the contro...

An approach to integrate workflow modeling and organization modeling in an enterprise

Abstract: In this paper we introduce a framework for enterprise modeling. We specifically introduce the tasks process modeling (workflow modeling) and organization modeling. Processes describe the activities which have to be performed in an enterprise; an organization describes the people and organizational structure of an enterprise. Although these two tasks are independent in principle, they have to be integrated eventually in order to assign organizational elements (e.g. people) to processes. This paper presents a general model for process and organization modeling and shows a script language of a prototype system. The architecture of that prototype is briefly discussed. >

Modeling with a group modeling tool: group support, model quality, and validation

Abstract: During business process re-engineering, business activities are modelled and analyzed. Redefined models become the blueprints for improved business activities. The cost to produce models of the organization is high and model accuracy is important. How do models help support understanding of business processes? Should functional business personnel or systems analysts create business models for the organization? How are models validated? From their experience with applying EMS technology and re-engineering techniques with actual organizations, the authors discuss benefits of broad involvement during modeling and improvement idea generation. They discuss their experiences using group technology to support groups during the modeling of business activities using the IDEF modeling method, and discuss aspects of broad involvement that influence the quality of the resulting models. >

Analyzing and re-engineering business processes using simulation

Abstract: Increasingly, companies around the world are re-engineering their core business processes to be more profitable and to improve customer satisfaction. Modeling and analysis are two critical steps in any process redesign effort. In this paper, we discuss the need for simulation tools that can be used effectively to model, document and analyze business processes. We also present the design of a hierarchical simulation tool called BPMAT (Business Process Modeling and Analysis Tool), and discuss its implementation.

Elicit: a method for eliciting process models

Abstract: Eliciting process models from software projects is a first significant step towards process improvement. In this paper, we present a method, called Elicit, for eliciting software process models from industrial software environments. What is significant about this method is that it has evolved from an intuitive state-the state that defines the immaturity of current elicitation methods-to a formally defined, repeatable, effective and quantified state. Over the last two years of its usage, the method has been used to elicit models from three industrial-scale processes: preliminary analysis, requirements engineering, and product planning and dependency management. The example given in the paper focuses on the requirements engineering process. >

Application of run by run controller to the chemical-mechanical planarization process. II

Abstract: The chemical-mechanical planarization (CMP) process has demonstrated planarization capabilities beyond other current technologies, and is considered a strategically important process for next generation multilevel metal interconnect devices. The Run by Run (RbR) controller is applied to CMP. The application of the RbR controller is to reduce the drifts and shifts in the average removal rate and nonuniformity in the CMP process. The RbR controller is a model-based process control system which combines the advantages of both statistical process control (SPC) and feedback control to provide accuracy and flexibility that cannot be achieved by using either method alone. In characterizing the CMP process for the models, there are a transition effect and a memory effect. In this paper, we report further experiments and the results of process modeling. Included in the process models are the pad age effect and the pad rebound effect, which we have characterized to increase the accuracy and effectiveness of the process models. The predicted average removal rate including all these effects matches the process data very well over hundreds of wafers, with only 5 adjustable parameters. >

Experience-based method evaluation and improvement: A process modelling approach

Abstract: Little is known about the actual usage and evaluation of methods especially in the early phases of information systems engineering. This paper therefore advocates an experience-based approach in which methods and tools can be defined, applied, evaluated, and gradually improved. We argue that this requires three ingredients: • a process meta model which can deal with many different situations in a flexible, decision-oriented manner; • a process repository that links process and product traces, guidance, and improvement through carefully defined concept mappings; • a tool interoperability concept in which tool behavior adapts to the present process definition and situation, and where tools automatically trace their own behavior. The interplay of these ingredients is demonstrated in the NATURE requirements engineering environment .

Toward metrics for process validation

Abstract: To a great extent, the usefulness of a formal model of a software process lies in its ability to accurately predict the behavior of the executing process. Similarly, the usefulness of an executing process lies largely in its ability to fulfil the requirements embodied in a formal model of the process. When process models and process executions diverge, something significant is happening. We are developing techniques for uncovering discrepancies between models and executions under the rubric of process validation. Further, we are developing metrics for process validation that give engineers a feel for the severity of the discrepancy. We view the metrics presented here as a first step toward a suite of useful metrics for process validation. >

Database Evolution: the DB-Main Approach

Abstract: The paper analyses some of the practical problems that arise when the requirements of an information system evolve, and when the database and its application programs are to be modified accordingly. It presents four important strategies to cope with this evolution, namely forward maintenance, backward maintenance, reverse engineering and anticipating design. A common, generic, framework that can support these strategies is described. It is based on a generic data structure model, on a transformational approach to database engineering, and on a design process model. The paper discusses how this framework allows formalizing these evolution strategies, and describes a generic CASE tool that supports database applications maintenance.

Policies and mechanisms to support process evolution in PSEEs

Abstract: This paper discusses the characteristics that should be offered by PSEEs (process-centered software engineering environments) to support the evolution of the software process. A PSEE is a software engineering environment based on the explicit representation of the software process (the process model). Processes and process models are dynamic entities that need to evolve. Existing PSEEs offer limited capabilities to support process evolution. To address this issue, it is necessary to extend PSEEs with features that enable the process manager to effectively and consistently change the process. The design of these functionalities must be guided by a clear characterization of the evolution problem. In particular, it is necessary to understand what kinds of services a PSEE should offer as built-in mechanisms, and what kinds of functionalities have to be implemented by the process modeler as process-specific policies. >

OO MODELING OF BUSINESS PROCESSES Object-Oriented Systems Analysis

Abstract: Business reengineering requires new systems analysis tools for process modeling. An object-oriented (OO) approach may be better than the traditional data flow diagram method in modeling business processes. This article explains the development of an OO tool that may potentially benefit IS in reengineering business processes.

The SMART approach for software process engineering

Abstract: Describes a methodology for software process engineering and an environment, SMART, that supports it. SMART supports a process life-cycle that includes the modeling, analysis, and execution of software processes. SMART's process monitoring capabilities can be used to provide feedback from the process execution to the process model. SMART represents the integration of three separately developed process mechanisms, and it uses two modeling formalisms (object-oriented data representation and imperative-style programming language) to bridge the gap between process modeling, analysis, and execution. SMART demonstrates the meta-environment concept, using a process modeling formalism as input specification to a generator that produces process-centered software engineering environments (PSEEs). Furthermore, SMART supports a team-oriented approach for process modeling, analysis, and execution. >

Improving software maintenance at Martin Marietta

Abstract: Using data collected throughout a major project, the authors apply common statistical methods to quantitatively assess and evaluate improvements in a large contractor's software-maintenance process. Results show where improvements are needed; examining the change in statistical results lets you quantitatively evaluate the effectiveness of the improvements. We selected a process-assessment methodology developed by J.E. Henry (1993) that follows Total Quality Management principles and is based on Watts Humphrey's Process Maturity Framework. It lets you use a process modeling technique based on control-flow diagrams to define an organization's maintenance process. After collecting process and product data throughout the maintenance process, you analyze it using parametric and nonparametric statistical techniques. The statistical-analysis results and the process model help you assess and guide improvements in the organization's maintenance process. The method uses common statistical tests to quantify relationships among maintenance activities and process and product characteristics. The relationships, in turn, tell you more about the maintenance process and how requirements changes affect the product. >