2016/07/28 10:35 Bill Schindel, “The S* minimal general systems meta-model, and its prospects as a general modelling foundation for Systems Engineering”, ISSS 2016 Boulder

Plenary @ISSSMeeting Bill Schindel, Keynote #isss2016USA, 60th Annual Meeting of the International Society for the Systems Sciences and 1st Policy Congress of ISSS, Boulder, Colorado, USA

Day 4 theme:  Systems Theory, Management, and Practice

Plenary VIII: Prospects for Scientific Systemic Synthesis

  • Description: Recent times have seen the emergence of new theoretical insights that may help to establish the frameworks, theories and methodologies we need to understand, design, build, explain, communicate about, utilize or operate, maintain, and evolve resilient and sustainable socio-ecological systems. In this panel we bring together experts to present on such emerging developments in the areas of engineering, science, research, practice and philosophy, and to reflect on how these different stands can contribute to the formation of a new systemic synthesis that will make the ‘whole systems perspective’ scientific and practical. The panel presentations will be delivered in the last plenary before lunch, and be followed by an open discussion between the panellists and audience in a break-out session immediately after lunch.

Chair: David Rousseau, Centre for Systems Philosophy

This digest was created in real-time during the meeting, based on the speaker’s presentation(s) and comments from the audience. The content should not be viewed as an official transcript of the meeting, but only as an interpretation by a single individual. Lapses, grammatical errors, and typing mistakes may not have been corrected. Questions about content should be directed to the originator. The digest has been made available for purposes of scholarship, posted by David Ing.

Bill Schindel, INCOSE Pattern-Based System Challenge Team, and Agile Systems Engineering Life Cycle Model Project


[Bill Schindel]

Bill Schindel, Thursday plenary

A framework to represent large complex systems

Perspective:

  • 40 years in engineered system
  • Pattern-Based Systems Engineering spun off from university into INCOSE Systems Sciences Working Group

Systems engineering is 50 to 60 years old, not old compared to other disciplines

  • Civil engineering, chemical engineering, where tied to other systems disciplines
  • Systems engineering was started when complexity of systems got to be overwhelming in mid-20th century

Systems engineering (traditional, 50 years)

  • Model based systems engineering (small, fastest growing, 10 years)
  • One way of MBSE is S* Metamodel (20 years)
  • Within S* Metamodel is Pattern-Based SE (20 years)

Many think of metamodels that came out of the software movement

  • Don’t necessary represent the natural world
  • Making a transition, why metamodel discussions are important
  • Turning roots back to science

Bill Schindel, S-asterisk

Metamodel is minimum underlying model

  • Metamodel about nature
  • Interested in construction of patterns, e.g. agile, farms
  • Many patterns we call dark patterns, e.g. know about cars, however a new person would take years to learn
  • Patterns as explicit models

Bill Schindel, Terrestrial Vehicle S Pattern

Extracts from Terrestrial Vehicle S* Pattern

  • Visual or tabular, rather than prose (the old way)

S* Patterns in space tourism, education, agile systems, etc.

INCOSE Patterns Working Group is primary, work with other working groups

Multiple hierarchies involved

  • Most are containment hierarchies, inside bigger

Features:

  • Stakeholder
  • Interactions, about business, what really happens

Interactions and systems phenomenon

  • Traditional mechanics, hard science for underlying phenomena
  • Argument (usually in bar):  specialists argue their fields are based on real physical laws
  • Where’s your phenomena?
  • Process, organizing, critical thinking

The system phenomenon:

  • What’s your definition of a system?
  • Interacting components
  • Exchange of energy, mass or information … which impacts state of components …
  • Then all other phenomena are a special case of the system phenomenon
  • Hamilton:  systems evolve in time, according to principle of stationary action, calculus of variation
  • Equations that can’t be solve anyways, scientific verification
  • Instead of lacking theoretical foundations, all of the hard sciences are borrowing from systems sciences
  • e.g. chemistry arising out of electron and other interactions
  • Thus, systems engineering provides foundations for other disciplines

Emergence of purpose, value, fitness in an ecology of interactions

  • S* Patterns emphasize complete stakeholder feature models
  • Becomes the ultimate scoreboard for measuring
  • A trace base
  • Basis of systems selection
  • Express all risks

The System of Innovation Pattern (socio-technical)

  • Emerge
  • Purpose-discovery loop, which is “pivoting” on a minimum viable product

Bill Schindel, System Of Innovation Pattern

Different ideas at different levels

Bill Schindel, Emergence Of Patterns From Patterns

Patterns used in Agile System Life Cycle

Where do systems come from and go?  System life cycle trajectories in S* space