Capabilities in Systems Engineering: an Overview
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Need Means Analysis
The Systems Engineering Tool Box Dr Stuart Burge “Give us the tools and we will finish the job” Winston Churchill Needs Means Analysis (NMA) What is it and what does it do? Needs Means Analysis (NMA) is a systems thinking tool aimed at exploring alternative system solutions at different levels in order to help define the boundary of the system of interest. It is based around identifying the “need” that a system satisfies and using this to investigate alternative solutions at levels higher, the same and lower than the system of interest. Why do it? At any point in time there is usually a “current” or “preferred” solution to a particular problem. In consequence organizations will develop their operations and infrastructure to support and optimise that solution. This preferred solution is known as the Meta-Solution. For example Toyota, Ford, General Motors, Volkswagen et al all have the same meta-solution when it comes to automobile – in simple terms two-boxes with wheel at each corner. All of the automotive companies have slowly evolved in to an industry aimed at optimising this meta-solution. Systems Thinking encourages us to “step back” from the solution to consider the underlying problem or purpose. In the case of an automobile, the purpose is to “transport passengers and their baggage from one point to another” This is also the purpose of a civil aircraft, passenger train and bicycle! In other words for a given purpose there are alternative meta-solutions. The idea of a pre-eminent meta-solution has also been discussed by Pugh (1991) who introduced the idea of dynamic and static design concepts. -
Putting Systems to Work
i PUTTING SYSTEMS TO WORK Derek K. Hitchins Professor ii iii To my beloved wife, without whom ... very little. iv v Contents About the Book ........................................................................xi Part A—Foundation and Theory Chapter 1—Understanding Systems.......................................... 3 An Introduction to Systems.................................................... 3 Gestalt and Gestalten............................................................. 6 Hard and Soft, Open and Closed ............................................. 6 Emergence and Hierarchy ..................................................... 10 Cybernetics ........................................................................... 11 Machine Age versus Systems Age .......................................... 13 Present Limitations in Systems Engineering Methods............ 14 Enquiring Systems................................................................ 18 Chaos.................................................................................... 23 Chaos and Self-organized Criticality...................................... 24 Conclusion............................................................................ 26 Chapter 2—The Human Element in Systems ......................... 27 Human ‘Design’..................................................................... 27 Human Predictability ........................................................... 29 Personality ............................................................................ 31 Social -
Fundamentals of Systems Engineering
Fundamentals of Systems Engineering Prof. Olivier L. de Weck Session 12 Future of Systems Engineering 1 2 Status quo approach for managing complexity in SE MIL-STD-499A (1969) systems engineering SWaP used as a proxy metric for cost, and dis- System decomposed process: as employed today Conventional V&V techniques incentivizes abstraction based on arbitrary do not scale to highly complex in design cleavage lines . or adaptable systems–with large or infinite numbers of possible states/configurations Re-Design Cost System Functional System Verification Optimization Specification Layout & Validation SWaP Subsystem Subsystem . Resulting Optimization Design Testing architectures are fragile point designs SWaP Component Component Optimization Power Data & Control Thermal Mgmt . Design Testing . and detailed design Unmodeled and undesired occurs within these interactions lead to emergent functional stovepipes behaviors during integration SWaP = Size, Weight, and Power Desirable interactions (data, power, forces & torques) V&V = Verification & Validation Undesirable interactions (thermal, vibrations, EMI) 3 Change Request Generation Patterns Change Requests Written per Month Discovered new change “ ” 1500 pattern: late ripple system integration and test 1200 bug [Eckert, Clarkson 2004] fixes 900 subsystem Number Written Number Written design 600 major milestones or management changes component design 300 0 1 5 9 77 81 85 89 93 73 17 21 25 29 33 37 41 45 49 53 57 61 65 69 13 Month © Olivier de Weck, December 2015, 4 Historical schedule trends -
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. -
Lecture 9 – Modeling, Simulation, and Systems Engineering
Lecture 9 – Modeling, Simulation, and Systems Engineering • Development steps • Model-based control engineering • Modeling and simulation • Systems platform: hardware, systems software. EE392m - Spring 2005 Control Engineering 9-1 Gorinevsky Control Engineering Technology • Science – abstraction – concepts – simplified models • Engineering – building new things – constrained resources: time, money, • Technology – repeatable processes • Control platform technology • Control engineering technology EE392m - Spring 2005 Control Engineering 9-2 Gorinevsky Controls development cycle • Analysis and modeling – Control algorithm design using a simplified model – System trade study - defines overall system design • Simulation – Detailed model: physics, or empirical, or data driven – Design validation using detailed performance model • System development – Control application software – Real-time software platform – Hardware platform • Validation and verification – Performance against initial specs – Software verification – Certification/commissioning EE392m - Spring 2005 Control Engineering 9-3 Gorinevsky Algorithms/Analysis Much more than real-time control feedback computations • modeling • identification • tuning • optimization • feedforward • feedback • estimation and navigation • user interface • diagnostics and system self-test • system level logic, mode change EE392m - Spring 2005 Control Engineering 9-4 Gorinevsky Model-based Control Development Conceptual Control design model: Conceptual control sis algorithm: y Analysis x(t+1) = x(t) + -
Capability Management Policy NHS West Essex Clinical Commissioning Group Policy Reference Number: WECCG43
Capability Management Policy NHS West Essex Clinical Commissioning Group Policy Reference Number: WECCG43 Policy Title Capability Management Policy V1.0 Hertfordshire, Bedfordshire, West Essex and Luton Clinical Commissioning Page 1 of 42 Groups DOCUMENT CONTROL SHEET Document Owner: Director of Workforce Document Author(s): Tina Ryan Version: V1.0 Directorate: HR and ODL Approved By: Policy Forum Date of Approval: 23 May 2017 Date of Review: 1 June 2019 Effective Date: 1 June 2017 1.1 Change History: Version Date Reviewer(s) Revision Description V1.0 April 2017 Human Resources Adapted for use as the Shared Business Partner Service Policy. Team 1.2 1.3 Implementation Plan: Development and Developed in conjunction with the joint forum, and ratified by, Consultation the relevant committees of the Hertfordshire, Bedfordshire, West Essex and Luton CCGs. Dissemination This policy will communicate to staff representatives. It will be communicated electronically to all staff and managers and will be published on the CCG’s intranet. Training HR Masterclasses will be made available to all managers on Performance Management Managers will also be able to access advice from the HR and ODL Shared Service on the implementation and interpretation of this policy. Monitoring and All complaints of performance management are recorded by the Review HR and ODL Shared Service and activity is reported on at least annually, together with a breakdown of policy application across the protected characteristics under the Equality Act. Policy Title Capability Management Policy V1.0 Hertfordshire, Bedfordshire, West Essex and Luton Clinical Commissioning Page 2 of 42 Groups The data identified from monitoring will be used to update the policy and ensure best practice as necessary. -
Theoretical Approach to the Interaction Between the Meta-System Schemas of the Artificial (Built) Environment and Nature
Theoretical Approach to the Interaction Between the Meta-system Schemas of the Artificial (Built) Environment and Nature José L. Fernández-Solís, Ph. D. Kent D. Palmer, Ph. D. Timothy Ferris, Ph. D. Texas A&M University, 3137 TAMU, College Station, TX 77843-3137 USA P.O. Box 1632, CA 92867 USA University of South Australia, Mawson Lakes Blvd., Mawson Lakes, 5095 AU Emails: [email protected] ; [email protected] ; [email protected] Abstract: This is an exploration of how the artificial environment links with the natural environment and requires a conceptual construct that bridges these two environments. Palmer’s General Schema Theory, a highly theoretical work, elaborated on in a dissertation by Fernández-Solís (2006), provides a theory of schemas and a theory of the schema of meta-systems which will be useful for interpreting the relationship between the artificial and natural environment. The concept of meta-system is used first to generate and then to validate the concept of meta-industry. This paper argues that the building construction industry (which produces the built or artificial environment) that is categorized as an ‘industry’ by academia, actually acts as a meta-industry. Meta-industry is a concept that encapsulates an ‘industry of industries,’ which implies that the artificial and the natural environment interact at the meta-level. Climate change is construed as the reaction of the natural to the artificial environment at the meta- level. The approach to this pre-paradigmatic work uses the tools of philosophical and critical thinking, rationality and logic. General Schemas thinking at the meta- systemic level is presented as a new approach towards the formation of a novel paradigm of the artificial environment. -
And Deployment in the New Zealand State Service
Michael J. Pratt and Murray Horn Leadership and Capability Development and Deployment in the New Zealand State Service companies, such as Procter & Gamble, for leadership This article describes the design during 2013 of a model and development (Filipkowski implementation principles of a leadership and capability and Donlon, 2013). The development and deployment (LCDD) model for the state model was then enhanced services system. In this process, an initial prototype model based on our research in was developed to describe a desired future state. It was other jurisdictions, including informed by the best traditions of state services leadership Australia, Singapore and the development, together with models used by the world’s best United Kingdom, and co- creation with stakeholders. Dr Mike Pratt is Professor of Leadership and Sustainability at the University of Waikato, and a This is further discussed in professional director and business adviser. Dr Murray Horn is a former Secretary to the Treasury of New Zealand and bank chief executive, and a professional director and business adviser. the article. Policy Quarterly – Volume 10, Issue 1 – February 2014 – Page 45 Leadership and Capability Development and Deployment in the New Zealand State Service The Better Public Services review Services Commission and implementation delivering on the sorts of social outcomes conducted in 2011 found that improved began in September 2013. described by the ten Better Public Services and more collaborative leadership is One unique feature of the framework goals is changing. The big policy settings a necessary precondition for high- is the deliberate integration from an are now broadly aligned with OECD performing public services (Better early stage in the project of leadership norms, so far more hangs on the public Public Services Advisory Group, 2011). -
People Capability Maturity Model® (P–CMM®) Version 2.0 CMU/SEI-2001-MM-01
Pittsburgh, PA 15213-3890 People Capability Maturity Model® (P–CMM®) Version 2.0 CMU/SEI-2001-MM-01 Bill Curtis TeraQuest Metrics, Inc. William E. Hefley Q-Labs Sally A. Miller Software Engineering Institute July 2001 Unlimited distribution subject to the copyright. This report was prepared for the SEI Joint Program Office HQ ESC/DIB 5 Eglin Street Hanscom AFB, MA 01731-2116 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. FOR THE COMMANDER Norton L. Compton, Lt Col., USAF SEI Joint Program Office 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 2001 by 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 internal use is granted, provided the copyright and “No Warranty” statements are included with all reproductions and derivative works. -
Perspectives on the Capabilities for the Selection of Strategic Projects
sustainability Review Perspectives on the Capabilities for the Selection of Strategic Projects Khalifa Mohammed Al-Sobai, Shaligram Pokharel * and Galal M. Abdella Department of Mechanical and Industrial Engineering, Qatar University, P.O. Box 2713 Doha, Qatar; [email protected] (K.M.A.-S.); [email protected] (G.M.A.) * Correspondence: [email protected] Received: 6 August 2020; Accepted: 25 September 2020; Published: 4 October 2020 Abstract: Strategic projects are large scale, complex, and require significant investments and resources. These projects aim at gaining long-term social and economic benefits. Therefore, organizations focusing on strategic projects should use a consistent approach that suits their strategy, capability, and long-term expectations. Based on the four research questions and content analysis of the literature, generic processes used for the strategic project selection in tandem with the managerial capabilities are identified in this paper. The generic processes and managerial capabilities are used to develop a generic framework for strategic project selection. The framework is used for literature analysis in the paper. The review shows that both qualitative and quantitative methods are used for strategic project selection. Some possible research directions have also been proposed at the end of the review. The paper provides value to both researchers and practitioners in terms of tools available and a guidance on project selection through a structured process framework. Keywords: strategic projects; process framework; decision making; project selection 1. Introduction Strategic projects can be categorized based on time, investments, sustainability, or long-term business or social values. These projects require significant investments and resources; therefore, their alignment with the long-term organizational capability [1] and sustainability becomes very important. -
Meta-Systems Engineering -- Kent Palmer
Meta-Systems Engineering -- Kent Palmer world schema, etc. that help us elucidate META-SYSTEMS phenomena2. Each of these various schema calls for a different response from ENGINEERING engineering, and thus engenders new engineering disciplines, or at least new approaches to the engineering of large scale A NEW APPROACH TO SYSTEMS systems. Among them are Meta-systems ENGINEERING BASED ON Engineering3, Special Systems based Holonic EMERGENT META-SYSTEMS AND Engineering4 and Domain Engineering5, HOLONOMIC SPECIAL SYSTEMS World Engineering6 and Whole Systems THEORY Design7. What is needed is a way to understand how these various kinds of Kent D. Palmer, Ph.D. schema and their associated engineering disciplines fit together into a coherent set of P.O. Box 1632 approaches. In this paper we will develop a Orange CA 92856 USA theory of how this coherence of different 714-633-9508 [email protected] 2 The approach taken in this work is further Copyright 2000 K.D. Palmer. elucidated by several papers by the author written for All Rights Reserved. International Society for the Systems Sciences (ISSS; Draft Version 1.0; 04/23/2000 http://isss.org) 2000 conference in Toronto. These papers may be seen at Paper for http://dialog.net:85/homepage/autopoiesis.html International Council on Systems Engineering including the following titles “Defining Life And The 10th Annual Symposium Living Ontologically And Holonomically;” “New General Schemas Theory: Systems, Holons, Meta- Keywords: Holonomics, Meta-systems, Systems & Worlds;” “Intertwining Of Duality And Systems Theory, Systems Engineering, Non-Duality;” “Holonomic Human Processes;” and “Genuine Spirtuality And Special Systems Theory” Meta-systems engineering, Special 3 Systems, Emergent Meta-systems, Whole Van Gigch, John P. -
Formal System Concepts
Paper #106 Formal Systems Concepts Joseph J. Simpson Mary J. Simpson System Concepts System Concepts 6400 32nd Avenue N.W., #9 6400 32nd Avenue N.W., #9 Seattle, WA 98107 Seattle, WA 98107 [email protected] [email protected] Abstract A common conceptual thread that runs through a large portion of systems, systems engineering, and software engineering literature is explored by this paper. This conceptual thread is based on the formal concept of a Moore type of sequential machine (Moore 1956) as well as the definition of a system and a meta-system. Practical approaches and applications generated by this common thread are outlined and discussed in terms of complexity reduction, design efficiency and communication enhancement. Hartmanis and Stearns utilized the abstract definition of a sequential state machine as a mathematical model of discrete, deterministic computing devices with finite memory. These machines have a finite set of inputs, outputs and internal configurations. Wymore expanded on this work while developing his model-based systems engineering approach. In each case, Moore and Wymore, the system concept has the same form. The system content; specific inputs, outputs types and transition functions, are different. In the software engineering arena, “abstract state machines” and “requirements state machines” have been developed as formal approaches closely related to Moore state machines. This paper presents an expanded systems and meta-systems framework that extends the formal system concepts. System abstraction stacks are introduced in this paper. Introduction Similar to formal logic, formal system concepts are concerned with the form of the system and not the system content.