Using System Archetypes to Identify Failure Patterns in Acquisition
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Existing Cybernetics Foundations - B
SYSTEMS SCIENCE AND CYBERNETICS – Vol. III - Existing Cybernetics Foundations - B. M. Vladimirski EXISTING CYBERNETICS FOUNDATIONS B. M. Vladimirski Rostov State University, Russia Keywords: Cybernetics, system, control, black box, entropy, information theory, mathematical modeling, feedback, homeostasis, hierarchy. Contents 1. Introduction 2. Organization 2.1 Systems and Complexity 2.2 Organizability 2.3 Black Box 3. Modeling 4. Information 4.1 Notion of Information 4.2 Generalized Communication System 4.3 Information Theory 4.4 Principle of Necessary Variety 5. Control 5.1 Essence of Control 5.2 Structure and Functions of a Control System 5.3 Feedback and Homeostasis 6. Conclusions Glossary Bibliography Biographical Sketch Summary Cybernetics is a science that studies systems of any nature that are capable of perceiving, storing, and processing information, as well as of using it for control and regulation. UNESCO – EOLSS The second title of the Norbert Wiener’s book “Cybernetics” reads “Control and Communication in the Animal and the Machine”. However, it is not recognition of the external similaritySAMPLE between the functions of animalsCHAPTERS and machines that Norbert Wiener is credited with. That had been done well before and can be traced back to La Mettrie and Descartes. Nor is it his contribution that he introduced the notion of feedback; that has been known since the times of the creation of the first irrigation systems in ancient Babylon. His distinctive contribution lies in demonstrating that both animals and machines can be combined into a new, wider class of objects which is characterized by the presence of control systems; furthermore, living organisms, including humans and machines, can be talked about in the same language that is suitable for a description of any teleological (goal-directed) systems. -
Introduction to Cybernetics and the Design of Systems
Introduction to Cybernetics and the Design of Systems © Hugh Dubberly & Paul Pangaro 2004 Cybernetics named From Greek ‘kubernetes’ — same root as ‘steering’ — becomes ‘governor’ in Latin Steering wind or tide course set Steering wind or tide course set Steering wind or tide course set Steering wind or tide course set correction of error Steering wind or tide course set correction of error Steering wind or tide course set correction of error correction of error Steering wind or tide course set correction of error correction of error Steering wind or tide course set correction of error correction of error Cybernetics named From Greek ‘kubernetes’ — same root as ‘steering’ — becomes ‘governor’ in Latin Cybernetic point-of-view - system has goal - system acts, aims toward the goal - environment affects aim - information returns to system — ‘feedback’ - system measures difference between state and goal — detects ‘error’ - system corrects action to aim toward goal - repeat Steering as a feedback loop compares heading with goal of reaching port adjusts rudder to correct heading ship’s heading Steering as a feedback loop detection of error compares heading with goal of reaching port adjusts rudder feedback to correct heading correction of error ship’s heading Automation of feedback thermostat heater temperature of room air Automation of feedback thermostat compares to setpoint and, if below, activates measured by heater raises temperature of room air The feedback loop ‘Cybernetics introduces for the first time — and not only by saying it, but -
What's in a Mental Model of a Dynamic System? Conceptual Structure and Model Comparison
What’s in a mental model of a dynamic system? Conceptual structure and model comparison Martin Schaffernicht Facultad de Ciencias Empresariales Universidad de Talca Avenida Lircay s/n 3460000 Talca, CHILE [email protected] Stefan N. Groesser University of St. Gallen Institute of Management System Dynamics Group Dufourstrasse 40a CH - 9000 St. Gallen, Switzerland Tel: +41 71 224 23 82 / Fax: +41 71 224 23 55 [email protected] Contribution to the International System Dynamics Conference 2009 Albuquerque, NM, U.S.A. Abstract This paper deals with the representation of mental models of dynamic systems (MMDS). Improving ’mental models’ has always been fundamental in the field of system dynamics. Even though a specific definition exists, no conceptual model of the structure of a MMDS has been offered so far. Previous research about the learning effects of system dynamics interventions have used two methods to represent and analyze mental models. To what extend is the result of these methods comparable? Can they be used to account for a MMDS which is suitable for the system dynamics methodology? Two exemplary MMDSs are compared with both methods. We have found that the procedures and results differ significantly . In addition, neither of the methods can account for the concept of feedback loops. Based on this finding, we propose a conceptual model for the structure of a MMDS, a method to compare them, and a revised definition of MMDS. The paper concludes with a call for more substantive research. Keywords : Mental models, dynamic systems, mental model comparison, graph theory, mental model measurement Introduction Mental models have been a key concept in system dynamics from the beginning of the field (Forrester, 1961). -
Guide to the Systems Engineering Body of Knowledge (Sebok) Version 1.3
Guide to the Systems Engineering Body of Knowledge (SEBoK) version 1.3 Released May 30, 2014 Part 2: Systems Please note that this is a PDF extraction of the content from www.sebokwiki.org Copyright and Licensing A compilation copyright to the SEBoK is held by The Trustees of the Stevens Institute of Technology ©2014 (“Stevens”) and copyright to most of the content within the SEBoK is also held by Stevens. Prominently noted throughout the SEBoK are other items of content for which the copyright is held by a third party. These items consist mainly of tables and figures. In each case of third party content, such content is used by Stevens with permission and its use by third parties is limited. Stevens is publishing those portions of the SEBoK to which it holds copyright under a Creative Commons Attribution-NonCommercial ShareAlike 3.0 Unported License. See http://creativecommons.org/licenses/by-nc-sa/3.0/deed.en_US for details about what this license allows. This license does not permit use of third party material but gives rights to the systems engineering community to freely use the remainder of the SEBoK within the terms of the license. Stevens is publishing the SEBoK as a compilation including the third party material under the terms of a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0). See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details about what this license allows. This license will permit very limited noncommercial use of the third party content included within the SEBoK and only as part of the SEBoK compilation. -
System Archetypes As a Learning Aid Within a Tourism Business Planning Software Tool
System Archetypes as a Learning Aid Within a Tourism Business Planning Software Tool G. Michael McGrath Centre for Hospitality and Tourism Research, Victoria University, Melbourne Email: [email protected] ABSTRACT Various studies have identified a need for improved business planning among Small-to-Medium Tourism Enterprise (SMTE) operators. The tourism sector is characterized by complexity, rapid change and interactions between many competing and cooperating sub-systems. System dynamics (SD) has proven itself to be an excellent discipline for capturing and modelling precisely this type of domain. In this paper, we report on an SD-based Tourism Enterprise Planning Simulator (TEPS) and its use as a learning aid within a business planning context. Particular emphasis is focussed on system archetypes. Keywords: tourism, business planning software, system dynamics. 1. Introduction In a recent study conducted for the Australian Sustainable Tourism Cooperative Research Centre (STCRC), improved business planning was identified as one of the most pressing needs of Small-to- Medium Tourism Enterprise (SMTE) operators (McGrath, 2005). A further significant problem confronting these businesses was coping with rapid change: including technological change, major changes in the external business environment, and changes that are having substantial impacts at every point of the tourism supply chain (and at every level – from international to regional and local levels). As a result of these findings, the STCRC provided funding and support for a follow-up research project aimed at producing a Tourism Enterprise Planning Simulator (TEPS). Distinguishing features of TEPS are: • Extensive use is made of system dynamics (SD) modelling technologies and tools (for capturing and simulating key aspects of change). -
Collection System Manager
CITY OF DALY CITY JOB SPECIFICATION EXEMPT POSITION COLLECTION SYSTEM MANAGER DEFINITION Under the general direction of the Director of Water and Wastewater Resources or authorized representative, supervises all activities of the Collection System Maintenance Division, including wastewater collection and recycled water systems, and performs other duties as assigned. EXAMPLES OF DUTIES Manage, supervise, schedule, and review the work of maintenance personnel in the maintenance, inspection and repair of wastewater collection and recycled water distribution systems in the Collection System Maintenance Division of the Department of Water and Wastewater Resources; ensure safe, efficient and effective compliance with local, state and federal laws, rules and regulations, and industrial practices. Implement City, Department and Division Rules and Regulations, policies, procedures and practices. Ensure that required records are accurately maintained. Oversee a comprehensive preventive maintenance program of facilities. Ensure that supervisors conduct regular safety training and maintain a safe work environment. Develop and maintain training programs for employees; ensure that employees maintain required certification. Formally evaluate or ensure the evaluation and satisfactory job performance of assigned employees. Manage crews in support of City departments in maintenance operations, such as the storm drain collection system maintenance and construction program. Work to complete Department and Division goals and objectives. Prepare and manage the Division budget; propose, develop and manage capital projects and manage contracts for the Division. Prepare reports, and make presentations to the City Manager, City Council or others as required. When required, maintain 24-hour availability to address Division emergencies. Develop and maintain good working relationships with supervisors, coworkers, elected officials, professional peer groups and the public. -
Rocket D3 Database Management System
datasheet Rocket® D3 Database Management System Delivering Proven Multidimensional Technology to the Evolving Enterprise Ecient Performance: C#, and C++. In addition, Java developers can access Delivers high performance via Proven Technology the D3 data files using its Java API. The MVS Toolkit ecient le management For over 30 years, the Pick Universal Data Model (Pick provides access to data and business processes via that requires minimal system UDM) has been synonymous with performance and and memory resources both SOAP and RESTful Web Services. reliability; providing the flexible multidimensional Scalability and Flexibility: database infrastructure to develop critical transac- Scales with your enterprise, tional and analytical business applications. Based on from one to thousands of Why Developers the Pick UDM, the Rocket® D3 Database Manage- users ment System offers enterprise-level scalability and Choose D3 D3 is the choice of more than a thousand applica- Seamless Interoperability: efficiency to support the dynamic growth of any tion developers world-wide—serving top industries Interoperates with varied organization. databases and host including manufacturing, distribution, healthcare, environments through government, retail, and other vertical markets. connectivity tools Rapid application development and application Rocket D3 database-centric development environ- customization requires an underlying data structure Data Security: ment provides software developers with all the that can respond effectively to ever-changing Provides secure, simultaneous necessary tools to quickly adapt to changes and access to the database from business requirements. Rocket D3 is simplistic in its build critical business applications in a fraction of the remote or disparate locations structure, yet allows for complex definitions of data time as compared to other databases; without worldwide structures and program logic. -
Thinking by Ian Bradbury
Downloaded from the Curious Cat Management Improvement Library: http://www.curiouscat.net/library/ So, what's System[s] Thinking by Ian Bradbury System[s] thinking is an area that has attracted quite a lot of attention in recent years. This brief article seeks to introduce the first of two key ideas in system[s] thinking, relate it to popular writings on the subject and illustrate the concept. (the second part, originally published as a second article, is included below) Interdependence Ludwig von Bertalanffy said that in dealing with complexes of elements, three different kinds of distinction may be made: 1) According to their number, 2) According to their species and 3) According to the relations of elements. 1. vs. 2. vs. 3. vs. In cases 1 and 2, the complex may be understood as the sum of elements considered in isolation. In case 3, not only the elements, but also the relationships between them need to be known for the complex to be understood. Characteristics of the first kind are called summative, of the second kind constitutive. Complexes that are constitutive in nature are what is meant by the old phrase "The whole is more than the sum of the parts." An example of cases 1 and 2 might be the value of the change in your pocket. The value of the change taken altogether is obtained by simply summing up the values of the individual coins taken separately. An example of case 3, used frequently by Russell Ackoff to illustrate a constitutive complex, is a car [or truck if preferred]. -
Success in Acquisition: Using Archetypes to Beat the Odds
Success in Acquisition: Using Archetypes to Beat the Odds William E. Novak Linda Levine September 2010 TECHNICAL REPORT CMU/SEI-2010-TR-016 ESC-TR-2010-016 Acquisition Support Program Unlimited distribution subject to the copyright. http://www.sei.cmu.edu This report was prepared for the SEI Administrative Agent ESC/XPK 5 Eglin Street Hanscom AFB, MA 01731-2100 The ideas and findings in this report should not be construed as an official DoD position. It is published in the interest of scientific and technical information exchange. This work is sponsored by the U.S. Department of Defense. The Software Engineering Institute is a federally funded research and development center sponsored by the U.S. Department of Defense. Copyright 2010 Carnegie Mellon University. NO WARRANTY THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN “AS-IS” BASIS. CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO, WARRANTY OF FITNESS FOR PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL. CARNEGIE MELLON UNIVERSITY DOES NOT MAKE ANY WARRANTY OF ANY KIND WITH RESPECT TO FREEDOM FROM PATENT, TRADEMARK, OR COPYRIGHT INFRINGEMENT. Use of any trademarks in this report is not intended in any way to infringe on the rights of the trademark holder. Internal use. Permission to reproduce this document and to prepare derivative works from this document for inter- nal use is granted, provided the copyright and “No Warranty” statements are included with all reproductions and derivative works. External use. -
Embedding Learning Aids in System Archetypes
Embedding Learning Aids in System Archetypes Veerendra K Rai * and Dong-Hwan Kim+ * Systems Research Laboratory, Tata Consultancy Services 54B, Hadapsar Industrial Estate, Pune- 411 013, India, [email protected] + Chung –Ang University, School of Public Affairs, Kyunggi-Do, Ansung-Si, Naeri, 456-756, South Korea, [email protected] Abstract: This paper revisits the systems archetypes proposed in The Fifth Discipline. Authors believe there exists a framework, which explains how these archetypes arise. Besides, the framework helps integrate the archetypes and infer principles of organizational learning. It takes the system archetypes as problem archetypes and endeavors to suggest solution by embedding simple learning aids in the archetypes. Authors believe problem in the systems do not arise due to the failure of a single paramount decision-maker. More often than not the problems are manifestations of cumulative and compound failures of all players in the system. Since system dynamics does not account for the behavior of individual actors in the system and it accounts for the individual behavior only by aggregation the only way it can hope to improve the behavior of individual actors is by taking system thinking to their doorsteps. Key words: System archetypes, organizational learning, learning principles, 1. Introduction The old model, “the top thinks and local acts” must now give way to integrating thinking and acting at all levels, thus remarked Peter Senge in the article ‘Leader’s New Work’ (Senge, 1990). Entire universe participates in any given event and thus entire universe is the cause of the event (Maharaj, 1973). However, we must place a boundary to carve out our system in focus in order to understand and solve a ‘problem’ whatever it means. -
ESD.00 Introduction to Systems Engineering, Lecture 3 Notes
Introduction to Engineering Systems, ESD.00 System Dynamics Lecture 3 Dr. Afreen Siddiqi From Last Time: Systems Thinking • “we can’t do just one thing” – things are interconnected and our actions have Decisions numerous effects that we often do not anticipate or realize. Goals • Many times our policies and efforts aimed towards some objective fail to produce the desired outcomes, rather we often make Environment matters worse Image by MIT OpenCourseWare. Ref: Figure 1-4, J. Sterman, Business Dynamics: Systems • Systems Thinking involves holistic Thinking and Modeling for a complex world, McGraw Hill, 2000 consideration of our actions Dynamic Complexity • Dynamic (changing over time) • Governed by feedback (actions feedback on themselves) • Nonlinear (effect is rarely proportional to cause, and what happens locally often doesn’t apply in distant regions) • History‐dependent (taking one road often precludes taking others and determines your destination, you can’t unscramble an egg) • Adaptive (the capabilities and decision rules of agents in complex systems change over time) • Counterintuitive (cause and effect are distant in time and space) • Policy resistant (many seemingly obvious solutions to problems fail or actually worsen the situation) • Char acterized by trade‐offs (h(the l ong run is often differ ent f rom the short‐run response, due to time delays. High leverage policies often cause worse‐before‐better behavior while low leverage policies often generate transitory improvement before the problem grows worse. Modes of Behavior Exponential Growth Goal Seeking S-shaped Growth Time Time Time Oscillation Growth with Overshoot Overshoot and Collapse Time Time Time Image by MIT OpenCourseWare. Ref: Figure 4-1, J. -
A Systems Engineering Framework for Bioeconomic Transitions in a Sustainable Development Goal Context
sustainability Article A Systems Engineering Framework for Bioeconomic Transitions in a Sustainable Development Goal Context Erika Palmer 1,* , Robert Burton 1 and Cecilia Haskins 2 1 Ruralis—Institute for Rural and Regional Research, N-7049 Trondheim, Norway; [email protected] 2 Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway; [email protected] * Correspondence: [email protected] Received: 3 July 2020; Accepted: 13 August 2020; Published: 17 August 2020 Abstract: To address sustainable development goals (SDGs), national and international strategies have been increasingly interested in the bioeconomy. SDGs have been criticized for lacking stakeholder perspectives and agency, and for requiring too little of business. There is also a lack of both systematic and systemic frameworks for the strategic planning of bioeconomy transitions. Using a systems engineering approach, we seek to address this with a process framework to bridge bioeconomy transitions by addressing SDGs. In this methodology paper, we develop a systems archetype mapping framework for sustainable bioeconomy transitions, called MPAST: Mapping Problem Archetypes to Solutions for Transitions. Using this framework with sector-specific stakeholder data facilitates the establishment of the start (problem state) and end (solution state) to understand and analyze sectorial transitions to the bioeconomy. We apply the MPAST framework to the case of a Norwegian agricultural bioeconomy transition, using data from a survey of the Norwegian agricultural sector on transitioning to a bioeconomy. The results of using this framework illustrate how visual mapping methods can be combined as a process, which we then discuss in the context of SDG implementation.