Modeling the Open Source Software Development Processes Using Idef3 Standard
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Modelling, Analysis and Design of Computer Integrated Manueactur1ng Systems
MODELLING, ANALYSIS AND DESIGN OF COMPUTER INTEGRATED MANUEACTUR1NG SYSTEMS Volume I of II ABDULRAHMAN MUSLLABAB ABDULLAH AL-AILMARJ October-1998 A thesis submitted for the DEGREE OP DOCTOR OF.PHILOSOPHY MECHANICAL ENGINEERING DEPARTMENT, THE UNIVERSITY OF SHEFFIELD 3n ti]S 5íamc of Allai]. ¿Hoot (gractouo. iHHoßt ¿Merciful. ACKNOWLEDGEMENTS I would like to express my appreciation and thanks to my supervisor Professor Keith Ridgway for devoting freely of his time to read, discuss, and guide this research, and for his assistance in selecting the research topic, obtaining special reference materials, and contacting industrial collaborations. His advice has been much appreciated and I am very grateful. I would like to thank Mr Bruce Lake at Brook Hansen Motors who has patiently answered my questions during the case study. Finally, I would like to thank my family for their constant understanding, support and patience. l To my parents, my wife and my son. ABSTRACT In the present climate of global competition, manufacturing organisations consider and seek strategies, means and tools to assist them to stay competitive. Computer Integrated Manufacturing (CIM) offers a number of potential opportunities for improving manufacturing systems. However, a number of researchers have reported the difficulties which arise during the analysis, design and implementation of CIM due to a lack of effective modelling methodologies and techniques and the complexity of the systems. The work reported in this thesis is related to the development of an integrated modelling method to support the analysis and design of advanced manufacturing systems. A survey of various modelling methods and techniques is carried out. The methods SSADM, IDEFO, IDEF1X, IDEF3, IDEF4, OOM, SADT, GRAI, PN, 10A MERISE, GIM and SIMULATION are reviewed. -
H)EF3 Technical Report Version 1.0 Chard J. Mayer Christopher P
L. H)EF3 Technical Report Version 1.0 _| i L, _chard J. Mayer Christopher P. Menzel : i_:_pa_la S.D. Mayer Know!edge Based Systems Laboratory L Depar tment- 0 fin-dustrial Engineering Texas A&M University College Station TX 77843 Reviewed by Michad-K, Painter, Capt, USAF Armstrong Laboratory Logistics Research Division Wright-Patterson =Air Force Base, Ohio 45433-6503 :_ _=_January 1991 i _: ?_ | - , i (NASA-CR-I90279) {RESEARCH ACCOMPLISHED AT N92-26587 THE KNOWLEDGE BASED SYSTEMS LAB: IDEF3, VERSION 1.0] (Texas A&M Univ.) 56 p Unclag G]/_I 0086873 L == ; IDEF3 Technical Report Version 1.0 Richard J. Mayer Christopher P. Menzel Paula S.D. Mayer Knowledge Based Systems Laboratory Department of Industrial Engineering Texas A&M University College Station TX 77843 Reviewed by Michael K. Painter, Capt, USAF Armstrong Laboratory Logistics Research Division Wright-Patterson Air Force Base, Ohio 45433-6503 January 1991 umd w _- :7. m w Preface This paper describes the research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University. Funding for the Laboratory's research in Integrated Information System Development Methods and Tools has been provided by the Air Force Armstrong Laboratory, Logistics Research Division, AFWAL/LRL, Wright-Patterson Air Force Base, Ohio 45433, under the technical direction of USAF Captain Michael K. Painter, under subcontract through the NASA RICIS Program at the University of Houston. The authors and the design team wish to acknowledge the technical insights and ideas provided by Captain Painter in the performance of this research as well as his assistance in the preparation of this report. -
The IDEF Family of Languages
CHAPTER 10 The IDEF Family of Languages Christopher Menzel, Richard J. Mayer The purpose of this contribution is to serve as a clear introduction to the modeling languages of the three most widely used IDEF methods: IDEFO, IDEFIX, and IDEF3. Each language is presented in turn, beginning with a discussion of the underlying "ontology" the language purports to describe, followed by presentations of the syntax of the language - particularly the notion of a model for the language - and the semantical rules that determine how models are to be interpreted. The level of detail should be sufficient to enable the reader both to understand the intended areas of application of the languages and to read and construct simple models of each of the three types. 1 Introduction A modeling method comprises a specialized modeling language for represent ing a certain class of information, and a modeling methodology for collecting, maintaining, and using the information so represented. The focus of this paper will be on the languages of the three most widely used IDEF methods: The IDEFO business function modeling method, the IDEFIX data modeling method, and the IDEF3 process modeling method. Any usable modeling language has both a syntax and a semantics: a set of rules (often implicit) that determines the legitimate syntactic constructs of the language, and a set of rules (often implicit) the determines the meanings of those constructs. It is not the purpose of this paper is to serve as an exhaus tive reference manual for the three IDEF languages at issue. Nor will it dis cuss the methodologies that underlie the applications of the languages. -
Structured Models and Dynamic Systems Analysis: the Integration of the Idef0/Idef3 Modeling Methods and Discrete Event Simulation
STRUCTURED MODELS AND DYNAMIC SYSTEMS ANALYSIS: THE INTEGRATION OF THE IDEF0/IDEF3 MODELING METHODS AND DISCRETE EVENT SIMULATION Larry Whitman Adrien Presley Brian Huff Automation & Robotics Research Institute Division of Business and Accountancy The University of Texas at Arlington Truman State University 7300 Jack Newell Boulevard South 100 East Normal Fort Worth, Texas 76118, U.S.A. Kirksville, Missouri 63501, U.S.A. · To analyze and design the enterprise and its ABSTRACT processes prior to implementation · To help reduce complexity The role of modeling and simulation is receiving much · To communicate a common understanding of the press of late. However, the lack of practice in employing system a link between the two is alarming. A static model is · To gain stakeholder buy-in used to understand an enterprise or a system, and · To act as a documentation tool for ISO 9000, TQM, simulation is used for dynamic analysis. Generally, most Concurrent Engineering, and other efforts. models are considered static, whereas simulation is really A primary thrust of this research is to determine the a dynamic model. Static models are useful in achieving feasibility of using a single master static model of the understanding of the enterprise. Simulations are useful in enterprise for multiple purposes. Previous research has analyzing the behavior of the enterprise. presented a single suite perspective (Lingineni, Caraway Most enterprises develop and even maintain multiple et al. 1996) and uses custom developed software (Harrell types of models for different purposes. If a single model and Field 1996). This research uses commercial products can be used to drive other modeling purposes, then exclusively. -
993314 02.Pdf (5.272Mb)
COGNITIVE SKILLS IN MODELING AND SIMULATION Volume II A Dissertation by RICHARD J. MAYER Submitted to the Graduate College of Texas A&M University partial fulfillment of the requirement for the degree DOCTOR OF PHILOSOPHY December 1988 Major Subject: Industrial Engineering RICHARD J. MAYER ALL RIGHTS RESERVED COGNITIVE SKILLS IN MODELING AND SIMULATION Volume II A Dissertation by RICHARD J. MAYER Approved as to style and content by: Don T. Phillips (Chair of Committee) Leland T. Blank Peter J. Sharpe (Member) (Member) •i. 7 c* . " u '.1 v-v Donald K. Friesen Guy H. Bailey7 (Member) (Member) G. Kemblef^ennett (Head of Department) December 1988 Ill TABLE OF CONTENTS Page Volume I 1 INTRODUCTION AND RESEARCH OBJECTIVES 1 1.1 Research Goals 1 1.2 Research Objectives 2 1.3 Background 2 1.3.1 New Paradigms for Simulation 5 1.3.2 Summary of Previous Research 8 1.4 Statement of Major Hypotheses 13 1.4.1 Methodological (Conceptual) Contributions to AI Foundations 16 1.4.2 AI Hypothesis Testing 16 1.5 Approach and Products 17 1.5.1 Research Products 18 1.6 Organization of the Dissertation 20 1.6.1 Summary of Section Contents 20 2 CHARACTERIZATION OF COGNITIVE PROCESSES 22 2.1 Overview of the Process 22 2.2 Perception of Systems 25 2.2.1 Formulating System Descriptions 25 2.2.2 Planning and Understanding 32 2.2.2.1 Goal Detection 34 2.2.2.2 Plan Proposing 35 2.2.2.3 Plan Projection 36 2.2.3 Reasoning With Common Sense Theories of System Dynamics 37 2.3 Identification of Symptoms and Concerns 39 IV TABLE OF CONTENTS (Continued) Page 2.4 Performing Problem Analysis 40 2.5 Problem Solving 42 2.5.1 Characteristic Driven Design 43 2.5.2 External Constraint Driven Design 43 2.5.3 Element Driven Design 44 2.5.4 Formulation of Analysis Goals and Model Require¬ ments ... -
Introduction to IDEF0/3 for Business Process Modelling. Contents Tables & Figures
Introduction to IDEF0/3 for Business Process Modelling. Contents Introduction ............................................................................................................................................ 2 Introduction to IDEF0 and IDEF3: ....................................................................................................... 2 Parent and Child Maps ........................................................................................................................ 2 Tunnelling ........................................................................................................................................ 3 Construction of IDEF Maps ................................................................................................................. 3 Branches and Joins .......................................................................................................................... 3 Starting an IDEF0 Map ............................................................................................................................ 4 Root definition .................................................................................................................................... 4 The IDEF0 Numbering Convention ...................................................................................................... 5 Creating a model ..................................................................................................................................... 5 Decomposition ............................................................................................................................... -
Business Modelling: UML Vs. IDEF
Griffith University School of Computing and Information Technology Domain: Advanced Object Oriented Concepts Business Modelling: UML vs. IDEF available electronically at: http://www.cit.gu.edu.au/~noran © Ovidiu S. Noran Table of Contents. 1 Introduction....................................................................................................1 1.1 The objectives of this paper..............................................................................1 1.2 Motivation.........................................................................................................1 1.3 Some Important Terms.....................................................................................2 1.3.1 Models. .............................................................................................................. 2 1.3.2 Business Process Models.................................................................................. 2 1.3.3 Information Systems Support. ........................................................................... 3 1.3.3.1 The Business Model as a Base for Information Systems.......................... 3 1.3.3.2 'Legacy' Systems....................................................................................... 4 1.3.4 Business Improvement vs. Innovation............................................................... 4 1.4 Business Concepts...........................................................................................4 1.4.1 Business Architecture. ...................................................................................... -
Tools Used in Modeling of the Economic Processes Marian Pompiliu Cristescu
EBEEC 2019 Economies of the Balkan and Eastern European Countries Volume 2019 Conference Paper Tools Used in Modeling of the Economic Processes Marian Pompiliu Cristescu Abstract The paper aims at identifying the economic process modeling languages, starting from the premise that the main beneficiaries of the resulting models are economists or decision-makers, respectively economic researchers. There are a large number of languages that have been developed with different objectives, but they have all been used to describe business processes. Languages have studied different aspects of business processes (dynamic, functional, organizational, informational) and may be more or less formal, depending on the intended use and audience. There is no easy way to classify these languages along a single dimension. However, the languages fall into four groups, clearly defined scientifically or professionally: traditional process modeling languages, object-oriented languages, dynamic process modeling Corresponding Author: languages, and the integration of languages. Economic processes are generally very Marian Pompiliu Cristescu complex and, therefore, different points can be formulated about their modeling. [email protected] Keywords: Formal language, model, simulation, algorithm, business processes. Received: 17 November 2019 Accepted: 6 January 2019 Published: 12 January 2020 Publishing services provided by Knowledge E Marian Pompiliu 1. Introduction Cristescu. This article is distributed under the terms of Business units are complex organizational forms that involve customers, business units, the Creative Commons Attribution License, which resources, and even systems. They extend over many different processes that interact in permits unrestricted use and a seemingly chaotic way. When trying to change business processes in an organization, redistribution provided that the original author and source are change is confronted and confused with great complexity. -
Information Integration for Concurrent Engineering (Iice) Idef3 Process Description Capture Method Report
AL-TR-1995-XXXX INFORMATION INTEGRATION FOR CONCURRENT ENGINEERING (IICE) IDEF3 PROCESS DESCRIPTION CAPTURE METHOD REPORT Richard J. Mayer, Ph.D. Christopher P. Menzel, Ph.D. Michael K. Painter Paula S. deWitte, Ph.D. Thomas Blinn Benjamin Perakath, Ph.D. KNOWLEDGE BASED SYSTEMS, INCORPORATED ONE KBSI PLACE 1500 UNIVERSITY DRIVE EAST COLLEGE STATION, TEXAS 77840-2335 HUMAN RESOURCES DIRECTORATE LOGISTICS RESEARCH DIVISION SEPTEMBER 1995 INTERIM TECHNICAL REPORT FOR PERIOD APRIL 1992 - SEPTEMBER 1995 Approved for public release; distribution is unlimited. September 1995 Interim - February 1991 to September 1995 IDEF3 Process Description Capture Method Report Richard J. Mayer, Ph.D. Michael K. Painter Christopher P. Menzel, Ph.D. Benjamin Perakath, Ph.D Paula S. deWitte, Ph.D. Thomas Blinn Knowledge Based Systems, Inc. One KBSI Place, 1500 University Drive East College Station, TX 77845 KBSI-IICE-90-STR-01-0592-02 Armstrong Laboratory Human Resources Directorate Logistics Research Division Wright-Patterson AFB, OH 45433 AL-TR-1995-XXXX Approved for Public Release; distribution is unlimited A This document provides a method overview, practice and use description, and language reference for the Integration Definition (IDEF) method for Process Description Capture (IDEF3). IDEF3 is designed to help document and analyze the processes of an existing or proposed system. Proven guidelines and a language for information capture help users capture and organize process information for multiple downstream uses. IDEF3 supports both process-centered and object-centered knowledge acquisition strategies enabling users to capture assertions about real-world processes and events in ways paralleling common forms of human expression. IDEF3 includes the ability to capture and structure descriptions of how a system works from multiple viewpoints. -
Business Modelling: UML Vs. IDEF
Griffith University School of Computing and Information Technology Domain: Modelling Languages Business Modelling: UML vs. IDEF available electronically at: http://www.cit.gu.edu.au/~noran © Ovidiu S. Noran 2000 © Ovidiu S. Noran Use of this document is permitted subject to proper reference to the author. Table of Contents. 1 Introduction....................................................................................................1 1.1 The objectives of this paper...............................................................................1 1.2 Motivation...........................................................................................................1 1.3 Some Important Terms. .....................................................................................2 1.3.1 Models. .............................................................................................................. 2 1.3.2 Business Process Models.................................................................................. 2 1.3.3 Information Systems Support. ........................................................................... 3 1.3.3.1 The Business Model as a Base for Information Systems.......................... 3 1.3.3.2 'Legacy' Systems....................................................................................... 4 1.3.4 Business Improvement vs. Innovation............................................................... 4 1.4 Business Concepts. ...........................................................................................4 -
System Reliability and Risk Assessment: a Quantitative Extension of IDEF Methodologies
From: AAAI Technical Report SS-94-04. Compilation copyright © 1994, AAAI (www.aaai.org). All rights reserved. System Reliability and Risk Assessment: A Quantitative Extension of IDEF Methodologies AndrewKusiak, Intelligent Systems Laboratory, Departmentof Industrial Engineering Nick Larson, Intelligent SystemsLaboratory, Deparlmentof Industrial Engineering The University of Iowa, Iowa City, Iowa 52242-1527 1. Introduction for information analysis (IDEF1), dynamic analysis Evaluating system reliability requires modeling the (IDEF2), and process modeling (IDEF3). interaction of resources, information, and material within This paper presents procedures for integrating system the system. Such a model must consider quantitative data reliability and risk assessment techniques with IDEF0and describing the reliability of each element of the system, as IDEF~modeling. The paper is motivated by the need to well as logical data describing the relationship between increase the value of IDEF0 and IDEF3 models by individual components. For example, a manufacturing incorporating quantitative data, thus, extending model use system may assemble products X, Y, and Z, on machines to applications such as risk assessment. By extending the M1, M2, and M3, respectively, and package the products power of existing IDEF models, process modeling will on a fourth machine, M4. Therefore, three different become more attractive to managementand evolve as a relationships exist between the componentsof the system, powerful tool for reengineering design and manufacturing one for each product. If the reliability of each machine systems. differs, the system reliability will differ dependingon the product. Similarly, the reliability of the system as a whole 2. Definitions of System Reliability and Risk will be affected by the production levels of products X, Y, Assessment and Z. -
IDEF5 Ontology Description Cap Ture Me Tho D TECHNICAL REPORT
0 u_ _,_ c_ I U cO IDEF5 Ontology Description o Z 0 Cap ture Me tho d Concept Paper _D Christopher P. Menzel E Richard J. Mayer _-. 3) CL,F._. 4,. ¢_'L>,. V', _' _.J U_ C Knowledge Based Systems Laboratory (.._ C Texas A&M University E ,..jolt,. CU-_ 0 1990 __] 0. ,.-, CC_ ¢ _) ._ Cooperative Agreement NCC 9-16 Research Activity No. IM.06: LJ Methodologies for Integrated Information Management Systems e_. NASA Johnson Space Center Information Systems Directorate Information Technology Division Research Institute for Computing and Information Systems University of Houston-C/ear Lake TECHNICAL REPORT The RICIS Concept I The University of liouston-Clear Lake established the Research Institute for Computing and InformaUon Systems (RICIS) in 1986 to encourage the NASA Johnson Space Center (JSC] and local industry to actively support research in the computing and information sciences, As part of this endeavor, UHCL proposed a partnership with JSC to Jointly define and manage an integrated program of research in advanced data processing technology needed forJSC's main missions, including administrative, engineering and science responsi- biliUes. JSC agreed and entered into a continuing cooperative agreement with UHCL beginning in May 1986, to Jointly plan and execute such research through RIC[S. Addltionally, under CooperaUve Agreement NCC 9-16, computing and educational faciliUes arc shared by the two insUtutlons to conduct the research. The UHCL/RICIS mission is to conduct, coordinate, and disseminate research and professional level education in computing and information systems to serve the needs of the government, industry, community and academia.