FUNDAMENTALS OF SYSTEMS THINKING: ----- WHO, WHAT, … · • Provides a common modeling and simulation environment • Requirements, functional, logical, and physical inter -relationships

FUNDAMENTALS OF SYSTEMS THINKING:----- WHO, WHAT, WHEN, WHERE, WHY & HOW?

Rod Dreisbach, PhD - Independent Engineering Simulation ConsultantNAFEMS Technical Fellow; Chair of NAFEMS Americas Region; Member of NAFEMS Council, Multiple Working Groups; Boeing Retired Senior Technical Fellow

Across the entire product lifecycle for the design, manufacture and maintenance of tomorrow’s interconnected multidisciplinary systems

NAFEMS.org/SystemsThinking Pervasive Systems Thinking and Simulation RevolutionInSimulation.org/SystemsThinking

Pervasive Systems Thinking: Who and What? the basic elements of an engineering organization

Technology• Math & Physics• Engineering• Computing hardware & software• Data management• etc.

Processes• Sharing knowledge• Reusing knowledge• Best practices• etc.

People• Tacit knowledge• Collaboration• Cultures• Global• etc.

Business• Customer knowledge• Market intelligence• Strategic goals• etc.


Competitive Advantage

Innovation

Critical Thinking--- Knowledge and Wisdom ---

Model Based Enterprise --- Integrated MBx ---

Governance--- Design, Build & Operate ---

Systems Thinking

Pervasive Systems Thinking: Why and How?

Through People,

Processes and

Technology


Characteristics of Innovation--- the Interaction of the Four Groups

• Innovation– Feeds off of the knowledge of a company– Is based on sharing knowledge across different domain groups and

organizational boundaries– Is generally associated with the development of new products and services– Is generally the result of a series of incremental improvements– Results from well-managed, disciplined business processes---it is not

accidental!

“Invention is 1% inspiration versus 99% perspiration” --- Thomas Edison


• Provides a common modeling and simulation environment • Requirements, functional, logical, and physical inter-relationships• 3D CAx parametric, cross-discipline functions• Virtual design, build, test, and certify• Multi-physics modeling & simulation• Common meta-model• Knowledge capture

What ?

Model-Based Engineering: What and Why?

Why? • Allows for rapid prototyping and architecture optimization• Leads to early integration and requirements validation• Creates a truly representative simulation of the product• Supports model-based requirements to suppliers• Increased overall fidelity of the simulations• Reduced development time and cost


Model-based integration across multiple technical disciplines (Extract from NAFEMS “What is SMS” Flyer)


Integrated Systems Engineering and Engineering Simulation (Extract from NAFEMS “What is SMS” Flyer)


Engineering Simulation Governance and Management(Extract from NAFEMS “What is Simulation Governance and Management” Flyer) The “Who and What”


• Curiosita: An insatiably curious approach to life and an unrelenting quest for continuous learning

• Dimonstrazione: Tests knowledge through experience, persistence, and willing to learn from mistakes

• Sensazione: Continually refines the senses, especially sight, as a means to enliven experience

• Sfumato: (literally "Going up in smoke") Willing to embrace ambiguity, paradox, and uncertainty

• Arte/Scienza: Develops a balance between art and science, imagination and logic. "Whole-Brain" thinking

• Corporalita: Cultivates grace, ambidexterity, fitness, and poise

• Connessione: Recognizes and appreciates the interconnectedness of all things and phenomena - systems thinking

* Book by Michael J. Gelb

Critical Thinking like Leonardo da Vinci* --- Seven da Vincian Principles

Not Bad For A Man Who Was Born In 1452!


The Internet of Things-----Physical and Digital!




An Autonomous Car???

A Hyperloop Tube???LA to San Francisco in 35 minutes!



An Autonomous Car???

A Hyperloop Tube???LA to San Francisco in 35 minutes!

What Advanced Technologies can now be Applied to Engineering Simulation???



Systems Engineering

Engineering Governance

Systems Thinking---An Essential Skill---

Pervasive Systems Thinking: What and Where?


A Glossary of Some Fundamental Terms• Critical Thinking: the objective analysis and evaluation of facts associated with an issue to form a judgment.• Cybernetics (Cyber-Physical): the study of how humans and machines control and communicate with each other.• Digital Thread: An analytical framework that seamlessly expedites the controlled interplay of technical data and information

in an enterprise data-information-knowledge system.• Digital Twin: a dynamic (real-time) digital surrogate (model) of a physical asset (physical twin), such as a system, device,

process, person or place for use in the operation, monitoring, control, and upgrade of the asset in a cyber-physical mode. • Governance: policies and procedures describing how the rules, norms and actions are structured, sustained, regulated and

held accountable.• Model-Based Engineering: an approach that uses models as an integral part of the engineering processes that includes

the requirements, analysis, design, implementation, verification and validation of a system throughout its lifecycle.• Model-Based Enterprise: an organization where models serve as the authoritative information source for processes

beyond engineering. • Model-Based Systems Engineering: a subset of Model-Based Engineering based on the formalized application of

integrated models of a system.• Reductionist (Traditional) Thinking: an approach that focuses on analysis of the constituent parts of a complex system

by breaking it down into its separate elements by sub-components or by technical disciplines.• System (Product, Process): a group of interacting or interrelated entities with spatial and temporal boundaries that form a

unified whole.• System Lifecycle Management (SysLM): Spans the six phases of a system’s lifecycle; Pre-Definition, Definition,

Acquisition/Development, Implementation, Operations and Maintenance, and Termination.• Systems Thinking: a holistic approach that focuses on synthesis of how a complex system's constituent parts interrelate

and how systems work over time and within the context of the larger systems.

PERVASIVE SYSTEMS THINKING & SIMULATIONWHO, WHAT, WHEN, WHERE, WHY & HOW…

Malcolm PanthakiCo-Founder, RevolutionInSimulation.orgVP of Analysis Solutions, Aras


It‘s been all about Product Development...

Product

Product Lifecycle Management (PLM)


Copyright AUDI AG

Electronics

Physical Interaction Simulation

Control Flow

Simulation

MechanicalCAD

Software

Product

Products & Markets are more complicated…

3-D Simulation


Materials Advancements & Additive

Verification & Validation

Need for

Simulation

Increasing

Rapidly

Design Space Explorationsource: wirth research

source:yourcar


Connected & Autonomous

Digital Twin

MBSE / System Models

Future:More & More

Simulations

across the

Lifecyclesource: autoevolution

source: squir

source: bmw

System Simulation


Silos:Unable to

Achieve

Business of

Engineering

Strategies

Disconnected from Processes

FEA

CFD

Highly Diverse & Increasing

Thermal

EMI

0D / 1D

Composites

EmbeddedSoftware / Firmware

wiring & bonding

Optics

nonlinear analysis

vibro-acoustics

Co-simulation

materialscharacterization plastic

flow metal forming casting

ESD

chips & circuits

Separate & Complicated to Manage

source: centers of grain excellence


Simulation Management: Challenges

• Statistical correlation withTest results

• Notified about design / model changes

• Aware of Variants / Options

• Mapped to Requirements

• Traceable for Liability issues / Digital Thread

Reduce Physical Test


Simulation Management: Challenges

• Statistical correlation withTest results

• Notified about design / model changes

• Aware of Variants / Options

• Mapped to Requirements

• Traceable for Liability issues / Digital Thread

Reduce Physical Test

• System architecture representation of product

• Simulation available on-demand

• Co-simulations / trade studies / cross-discipline

• Mixed fidelity models, Different data types

• Tool agnostic

MBSE / Systems

• Repeatable / reuse

• Proceduralized forops environment

• Access to Digital Twin config & performance data

• Simulation data forMachine Learning / AI

Predictive Maintenance


Future Risks: Without

New Approach

to

System

Management

Risks

Design Quality Problems

Delays / Missed Deadlines

Cost Overruns

Operational Shutdowns

Regulatory Actions

Liability

Safety Issues

Loss of Life

Catastrophic Failures

Ramifications

Misdirected Actions

Wrong Design Simulated

Inaccurate Conclusions

source: ansys

Risks compounded by Multidisciplinary Systems & Use of Machine Learning and AI


OBSTACLES

1. Small pool ofSystems Thinkers

2. Ingrained practices (Reductionism: divide-and-conquer)

3. SilosExperts, tools, data

4. Simulation limitedOnly to the experts

5. Multiple/Incompatible digital languages

6. Manual, error-pronedisconnected processes

7. Fragmented, inflexibledata platforms


1. Product or System?

QUESTIONS

2. Reductionism or Systems Thinking?

3. Simulation ROI?4. PDM/PLM or

System Lifecycle Mgmt?

5. Advanced technologies,standards?


It should be about System Management

The Productis a

System

The Productis a

System

Performance Optimization

Hardware

Software

Electronics



The Productis a

System

System of SystemsExpand BeyondProduct-Centric

Approach

The Productis a

System


Cost Optimization

Sustainability

Manufacturability (global supply chain)

Operating EnvironmentSystem of Systems Connected Systems

Hardware

Software

Electronics

Maintainability / Upgradeability



The Productis a

System

System Lifecycle Management (SysLM)*

* Martin Eigner, Thomas Dickopf, Hristo Apostolov. System Lifecycle Management: An Approach for Developing Cybertronic Systems in Consideration of Sustainability Aspects, 24th CIRP Conference on Life Cycle Engineering, Procedia CIRP 61 (2017) 128-133.

System of SystemsExpand BeyondProduct-Centric

Approach

The Productis a

System


Cost Optimization

Sustainability

Manufacturability (global supply chain)

Operating EnvironmentSystem of Systems Connected Systems

Hardware

Software

Electronics

Maintainability / Upgradeability


source: tesla

System Sub-Systems PartsSub-Systems

Systems Thinking VS Reductionism?


source: tesla

System Parts

Requirements? Responsibilities, Tasks System Behavior? System comprehension? System tradeoffs?Holistic/emergent system behavior? System optimization?Blinders!

Systems Thinking VS Reductionism?Sub-Systems Sub-Systems


source: tesla

System Parts

Systems Thinking AND ReductionismAchieving balance between holism and divide-and-conquer

Systems Thinking VS Reductionism?

Systems: Interactions Patterns Complexity & Uncertainty

Requirements? Responsibilities, Tasks System Behavior? System comprehension? System tradeoffs?Holistic/emergent system behavior? System optimization?Blinders!

Sub-Systems Sub-Systems


source: tesla

Pervasive Systems Thinking, Requirements & Simulation:Connected by a Customizable Digital Thread


Systems Thinkingunderstand

System Requirementsgoals/purpose

source: tesla

MBSErepresent

System Architectureorganize

Systems Engineeringintervene/design

Simulation (and Test)explore/validate




System Requirementsgoals/purpose

source: tesla

MBSErepresent


Systems Engineeringintervene/design

Simulation (and Test)explore/validate

Open, Customizable, Upgradeable SysLM Platformcaptures/supports your lifecycle Digital Thread – content & intent



Product Development Process:The System V is Not Reality…


An agile, iterative, spiral design processthat starts at any level of completeness

of the design

Spiral Design Process: Continuous Exploration & Validation


ContinuousDesign Evolution

Continuous Exploration & Validation

An agile, iterative, spiral design processthat starts at any level of completeness

of the design

Spiral Design Process: Continuous Exploration & Validation


Multidisciplinary Silos: Reductionism at work


Seamless IntegrationSystems Modeling to 3-D SimulationMultidisciplinary Systems Modelling

Systems

When systems models sit at the center of all product data,

they become the connective tissue.

The Digital Thread runs through them.

MBSE

Systems Models at the Core: Connecting silos


Open Digital Thread PlatformTraceabilityAgile DevelopmentConfiguration Mgmt, Variant MgmtCollaborative, Continuous Engineering

Design Evolution

Exploration & Validation

Spiral, Agile, CollaborativeProcess

Pervasive Requirements-Aware Digital Thread

Enterprise Digital Thread: For Content & Intent

Systems


Open Digital Thread PlatformTraceabilityAgile DevelopmentConfiguration Mgmt, Variant MgmtCollaborative, Continuous Engineering

Open, Extensible, Upgradeable SysLM Platformcaptures/supports full lifecycle Digital Thread – content & intent

Design Evolution


Spiral, Agile, CollaborativeProcess

Pervasive Requirements-Aware Digital Thread

PDM/PLM SysLM

Enterprise Digital Thread: For Content & Intent

Systems


Open Digital Thread PlatformRequirements & System Architectureat the core of all data including simulation data

Design Evolution


Right-Fidelity Simulation on-demand across the lifecycle Effective Enterprise SPDMSystem ExplorationSystem OptimizationSystem ValidationEmergent Behavior

Mixed-Fidelity simulationSystems3D

Multidisciplinary simulationSoftware, controls

Intelligent simulation automation

Pervasive Requirements-Driven Digital Thread

Spiral, Agile, Collaborative Process

Pervasive Simulation: Provides Systems Thinking Context

Systems


Open Digital Thread PlatformRequirements & System Architectureat the core of all data including simulation data

Design Evolution


Right-Fidelity Simulation on-demand across the lifecycle Effective Enterprise SPDMSystem ExplorationSystem OptimizationSystem ValidationEmergent Behavior

Pervasive Simulation for continuous System Exploration & Validationprovides necessary context for Systems Thinking

Mixed-Fidelity simulationSystems3D

Multidisciplinary simulationSoftware, controls

Intelligent simulation automation

Pervasive Requirements-Driven Digital Thread

Spiral, Agile, Collaborative Process

Pervasive Simulation: Provides Systems Thinking Context

Systems


• Systems Thinking and Reductionism: complementary, pervasive

• Requirements-Driven Systems Models: connective tissue of the Digital Thread

• Simulation connected to the Digital Thread: need growing exponentially‾ Current silo’ed & manual simulation is not adequate

• Effective enterprise SPDM: provides the Systems Thinking context

• System Lifecycle Management (SysLM) Platform: enhance your product-centric PDM/PLM platforms

Here are the Key Takeaways…


• Better understanding of product behavior, resulting in optimized products (engineering and manufacturing costs, brand retention, warranty costs…)

• Capture and reuse a growing pool of corporate knowledge

• Better management of complexity growth – current and future

• Better management of risk – current and future

• Better management of unanticipated market drivers – current and future

With Pervasive Systems Thinking and Simulation, supported by an enterprise Digital Thread, comes collaborative and continuous engineering, resulting in

designs that better meet requirements and a reduction of physical tests

…and the Benefits

SPACE- & GROUND-BASED OPTICAL SYSTEMSCASE STUDIES IN SYSTEM COMPLEXITY

David Thomas, PhD, Sr. Optical Engineer, Giant Magellan Telescope Organization


Large Telescopes

Hubble Space TelescopeGiant Magellan Telescope

• Highly complex, one-of-a-kind products• Multiple Engineering Disciplines involved

• Optics, Mechanical, Structures, Thermal, Electronics, Software and Controls• Large, expensive high-quality optics and tight alignment tolerances• Harsh operational environments• Must be highly reliable - no to limited opportunity for repair


Reductionist System EngineeringMission

Observatory

Instruments

Subsystems

Engineering Disciplines

• Single string flow down of Requirements from top to bottom• Document centered process – 100’s to 1000’s in databases

(DOORS, Docushare) to link them together.• Low-fidelity statistical error budget views of system performance

used to allocate requirements to the pieces.• Interface Control Documents (ICD’s) to specify interfaces

between related subsystems.• Work performed to and evaluated against local flowed down

requirements only – assumes the product will work if you meet your error budget allocations.

• No System Thinking or Ownership for Product Success.• A tedious, overhead focused process that is slow and difficult to

adjust to emerging product realities (Change Control Boards).


A “Humpty Dumpty” Approach“If I break my whole product down into 100’s of pieces according to a set of rules, I can get it back by gluing the pieces back together according to those rules.”

An approach born of Adam Smith at the start of the Industrial Revolution – High volume manufacture of high quality, affordable products by breaking complex product manufacture into a series of specialized steps.


Why Reductionism Doesn’t Really Work

• Lack of Systems Thinking – focus on the trees, but not the forest.• Interactive complexity is not accounted for

• Changes in any of the physics affect all the others in ways that are nontrivial to evaluate.• Coordinating effort across organizational and technical boundaries is complex and fluid in

complex endeavors.• Whole products have emergent properties that are greater than the sum of the properties

of its parts in ways that can be hard to predict.• Important failure modes can be hard to anticipate in complex systems (Ref. 3)

• Practical drift always happens• Design and hardware reality diverge from documented baselines over time, sometimes

with catastrophic results (Ref. 3)• Limited access to data in making design decisions

• The technical data needed by team members to understand salient features of the product outside of their own area of expertise to make informed decisions is generally not available to them.


What do we Need vs. What do we Have?Characteristic Properties What we have todaySystem Thinking Work organized around whole products,

attention to component parts and their harmonious integration into a whole at all stages of design and fabrication, ownership for product success by every team member

Reductionism - making sure each part meets its flowed down requirement allocations.

Pervasive Simulation Simulation at the appropriate level of fidelity at every program stage from start to finish as it is needed.

High fidelity only for each technical discipline. System performance predicts are low fidelity (error budgets)

Assured data consistency

Project design file structure ensures version control and model consistency as design evolves, and all discipline models stem from a common CAD design.

Relies on conformance to documents and drawings archived in large databases


What do we Need vs. What do we Have?Characteristic Properties What we have todayRobust access to relevant design data

Full access to all CAD/CAE data relevant to product design and problem resolution by all team members across discipline boundaries. Data display permits spatial comparisons across discipline boundaries during design reviews and problem diagnoses.

High fidelity data accessible only to discipline specialists. System level performance is low fidelity - block diagrams and error budgets. PowerPoint culture – information presented in fragments over many charts.

Capture and reuse of multidisciplinary analyses

Multidisciplinary engineering knowledge captured for reuse in Simulation Processes that can be run by all team members.

Serial manual handoffs between technical disciplines, with delays and errors at each handoff point.

Highly collaborative work style, agile response to change

Regular concurrent design sessions alternate with off-line detailed work to a common data model.

Stove piped approach from beginning to end with limited product level focus.


A Different Organizational Model is Needed

• A “Knights of the Round Table” product organization.• A Team Lead (Arthur) and a small team of equals

(Knights) – one for each technical discipline area.• Work is organized around a whole product having

simple interfaces to other system components.• Individuals are responsible for delivering their

specialty as usual.• The team is collectively responsible for the delivery

and success of the whole product.• System Engineering that is focused always on the

hardware, not on overhead documentation.


A Concurrent Engineering Environment

An example of this new paradigm developed for Electro-Optical Systems design at JPL and The Aerospace Corp.

• CAD/CAE shared across discipline boundaries with Model Based System Engineering (MBSE) software tools

• Engineers use the CAD/CAE tools they prefer.

• Project Tree file structure for version control and model consistency.

• Discipline models derive from a common CAD model at each product design iteration.

• All models project to a common screen.

• Design Reviews held directly from the design – no PowerPoint charts.


Motivations for these new design environments• Development of proposals for new work

• Proposals for new optical instrument funding at NASA and in the National Security Space communities must now be done at an advanced preliminary design level to a short schedule for limited B&P funding.

• Enabled by a Concurrent Engineering Environment.

• Diagnosis of unexplained hardware test anomalies• The environment was initially developed and applied successfully to the diagnosis of

a thermal focus anomaly with a critical camera system during thermal vacuum testing of the hardware.

• Problem was not explained by contractor’s own analysis.• Needed an analysis tool that would permit the requisite Structural/Thermal/Optical

analysis of system performance to be executed on the same time scale as hardware testing while providing physical insight into the root causes of underlying problems.


STOP Analyses of Optical System PerformanceCAD and Structures

Thermal

Optics

• STOP analysis computes changes in telescope image quality due to thermally induced changes in telescope optical components and metering structure

• Requires expertise in thermal control, mechanical CAD and structural analysis, and optical design.

• Normally done with manual handoffs between discipline experts.


Re-usable STOP Simulation Process• Our Concurrent

Engineering Environment integrated the sequence of engineering analysis steps needed for STOP into a re-usable Simulation Process in the MBSE software that reduced STOP analysis cycle times from days to hours.

• Allowed data analysis to be done in parallel with hardware testing for a mission-critical space flight hardware lens assembly.


Concurrent Engineering Diagnosis of Design IssuesTelescope WFE is very large – about 200 waves of spherical aberration

Almost all of the WFE is coming from the primary mirror

Structures model shows WFE to be due to bending of the mirror due to excess clamping force at cold temperatures. Remedy = thermal design change and/or more

compliant primary mirror mount.

• Multidisciplinary engineering teams can view all the relevant engineering data in a single eye span to discover and diagnose design performance issues in a more robust and effective way.


Features of Model Based System Engineering

• Logistical complexity and software costs are higher• Higher fidelity designs earlier in the acquisition cycle saves program cost and schedule• Design problems and conflicts are caught early and often• Reduces errors and delays at handoffs between disciplines• Enables and promotes System Thinking among product team• Enables capture and re-use of multidisciplinary engineering knowledge• Reduces design cycle time by 2x to 3x• Allows models at different levels of fidelity to be integrated• Ensures design consistency and captures design history through an integrated Project Tree File

Structure• Prevents over-design through high fidelity view of integrated product performance• Improves decision making by enabling spatial comparisons between all relevant engineering data• Creates ownership for overall product success among team members• Trains young engineers to become more senior, product-focused engineers more quickly• It’s just fun to work this way


References


Thank You!Thank you!


Q&A


Thank you!


Next Webinar TitleDate/Time


EXTRA SLIDES


80

Systems Thinking and Simulation are Pervasive…Technology Areas Involving Simulation

Systems Thinking

MBSE (Requirements

& Systems Modeling)

Automated Design Space

Exploration (Generative

Design)

New Manufacturing

Techniques (Additive

Manufacturing)

Predictive Maintenance &

Improved Product Design (Digital Twins)

SPDM (Digital Thread)

AI/ML


81

1. Systems Thinking Applied to Product Lifecyle Simulation 2. Bringing MBSE (Requirements Engineering & System

Modeling)& Simulation Together3. SPDM & the Digital Thread4. Automated Design Space Exploration (Generative Design &

Additive Manufacturing)5. Digital Twins and Predictive Maintenance

Important: Each presentation must tie back to the main theme of “Systems Thinking Applied to Simulation.”

Systems Thinking Webinar Series – NAFEMS & Rev-Sim


Democratization Simulation Governance Business Challenges

Expert Knowledge Capture & Reuse

Usability Accessibility Next-Generation Computing

Architectures

Simulation Governance and Model Management

Risk Mitigation Managing Simulation Verification, Validation &

Uncertainty Quantification

ROI Licensing Models Communication Influence of SMEs Vendor & End-User

Collaboration

Started: August 2015Ended: November 2015

Started: December 2015Ended: June 2016

Anticipated Start Date: July 2016Anticipated End Date: November 2016


83

Previous NAFEMS Democratization Webinar Series• In 2015/16:

– Simulation 20/20 series, which addressed Democratization, Simulation Governance, and Business Challenges.

– 15 webinars

– 2,231 attendees


source: tesla


MBSErepresent


Systems Engineeringintervene/designCredits

Dave Long, VitechPawel Chadzynski, Aras

Systems Analysisexplore/validate

System Requirementsgoals

Systems Terms – in a word or two…

AIRCRAFT here?


85

INCOSE

• The idea of a system as 'a set of parts which, when combined, have qualities that are not present in any of the parts themselves' is a very productive way of looking at the world – which turns out to be full of systems. Many engineered systems are much broader than the association with 'engineering' might imply: the 'elements' or 'parts' of a system may include, for example, people, processes, information, organizations and services, as well as software, hardware and complex products.

• The qualities that 'emerge' at the level of the whole also deserve a special mention. They arise when system elements interact with each other and their environment, and indeed only exist when the components of a system are able to interact. A system may be buffeted, constricted, triggered or driven by outside forces. But the system’s response to these forces is characteristic of itself, and that response is seldom simple in the real world, giving the impression of emergent behavior.

• Although 'emergence' brings the risk of unintended consequences, a major cause of embarrassing system failures, skilled systems engineers can create higher value for less cost by using emergence to deliver desired system qualities.

What Are Systems? Why are they important?

https://incoseonline.org.uk/Normal_Files/WhatIs/Systems_Thinking.aspx?CatID=What_Is_SE


86

INCOSE

• "Systems Thinking enables you to grasp and manage situations of complexity and uncertainty in which there are no simple answers. It’s a way of learning your way to effective action by looking at connected wholes rather than separate parts. It is sometimes called practical holism." [Open University definition]

• "Systems thinking is a framework for seeing interrelationships rather than things, for seeing patterns rather then static snapshots. It is a set of general principles spanning fields as diverse as physical and social sciences, engineering and management." [Peter Senge , The Fifth Discipline]

• Systems Thinking is a way of thinking used to address complex and uncertain real world problems. It recognizes that the world is a set of highly interconnected technical and social entities which are hierarchically organized producing emergent behavior.

NOTE:Systems Thinking is not a better way of seeing systems than the reductionist way – these are complementary approaches that should be applied simultaneously when designing or analyzing a complex system. These approaches can be used at any level of the system, in any domain.

Systems Thinking: What is it?



87

INCOSE

• Systems thinking provides a rigorous way of seeing (understanding) and integrating people, purpose, process and performance holistically, and also:

– relating systems to their environment;

• understanding the behavior of complex systems in complex situations;

• avoiding or minimising the impact of unintended consequences (understanding inherent system behavior);

– maximising the outcomes that can be achieved by a system;

– aligning teams, disciplines, specialties and interest groups;

– managing uncertainty and risk;

– identifying root causes of problems and seeing new opportunities.

Benefits of Systems Thinking



• Their engineering is complex– Even when the product is not– Often need sophisticated CAE tools– Need good engineers and tool experts

• They are multidisciplinary– In their performance attributes– In their Interaction with the environment

• They require teams – To design, validate manufacture,

maintain & upgrade

Is It Quiet Enough?

Is It Strong Enough?

Which Is Better?

Will It Last?

Does It Work?

Is It Safe?

The vast majority of manufacturing companiesdesign, manufacture and sell families of products

All Products are Systems…


Gearbox Consumer Products

Heat Exchangers

Control Arms

PneumaticComponents

Hitch Products

Beverage Containers

Faucets

Most Companies Develop Families of ProductsCommon Architecture - Different Geometry/Topology


Unified Data Model: Open & extensible Across all physics, levels of model fidelity and disciplines Simulation data captured mostly independent of the underlying tools

Vendor- & tool-agnostic

Support for any required standards through input/output Connectors

Connector Architecture: Open & extensible Cover in-house tools & data Enable commercial tools covering all required physics and levels of fidelity

Tight integration between parametric CAD & parametric mixed-fidelity CAE models

Robust Automation: Across design changes & configuration variants Simulation rules not based on CAD, instead product engineering / system architecture

Digital Thread: Integral to mainstream processes across the lifecycle Connected to Requirements, System Architecture, Product Engineering (BOMs), ALM, Test Data Mgmt

Foundations of Effective Simulation Management