Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

A.Levenchuk -- Complexity in Engineering

17,135 views

Published on

Keynote of A.Levenchuk at Open University Skolkovo program "Global Challenges", 12-Nov-2015

Published in: Technology
  • Have you ever used the help of ⇒ www.HelpWriting.net ⇐? They can help you with any type of writing - from personal statement to research paper. Due to this service you'll save your time and get an essay without plagiarism.
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Unlock Her Legs is your passage way to a life full of loving and sex... read more ... ■■■ http://t.cn/AiurDrZp
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • FREE TRAINING: "How to Earn a 6-Figure Side-Income Online" ... ♣♣♣ https://tinyurl.com/y3ylrovq
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Want to earn $4000/m? Of course you do. Learn how when you join today! ♥♥♥ https://tinyurl.com/y4urott2
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • DOWNLOAD FULL BOOKS, INTO AVAILABLE FORMAT ......................................................................................................................... ......................................................................................................................... 1.DOWNLOAD FULL. PDF EBOOK here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. EPUB Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. doc Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. PDF EBOOK here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. EPUB Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. doc Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... ......................................................................................................................... ......................................................................................................................... .............. Browse by Genre Available eBooks ......................................................................................................................... Art, Biography, Business, Chick Lit, Children's, Christian, Classics, Comics, Contemporary, Cookbooks, Crime, Ebooks, Fantasy, Fiction, Graphic Novels, Historical Fiction, History, Horror, Humor And Comedy, Manga, Memoir, Music, Mystery, Non Fiction, Paranormal, Philosophy, Poetry, Psychology, Religion, Romance, Science, Science Fiction, Self Help, Suspense, Spirituality, Sports, Thriller, Travel, Young Adult,
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here

A.Levenchuk -- Complexity in Engineering

  1. 1. Complexity in Engineering Anatoly Levenchuk Open University Skolkovo Global Challenges 12-nov-2015
  2. 2. Measures of Complexity a non--exhaustive list Seth Lloyd http://web.mit.edu/esd.83/www/notebook/Complexity.PDF 1. Difficulty of description. Typically measured in bits. Information; Entropy; Algorithmic Complexity or Algorithmic Information Content; Minimum Description Length; Fisher Information; Renyi Entropy; Code Length (prefix-free, Huffman, Shannon- Fano, error-correcting, Hamming); Chernoff Information; Dimension; Fractal Dimension; Lempel--Ziv Complexity. 2. Difficulty of creation. Typically measured in time, energy, dollars, etc. Computational Complexity; Time Computational Complexity; Space Computational Complexity; Information--Based Complexity; Logical Depth; Thermodynamic Depth; Cost; Crypticity. 3. 3. Degree of organization. This may be divided up into two quantities: a) Difficulty of describing organizational structure, whether corporate, chemical, cellular, etc.; b) Amount of information shared between the parts of a system as the result of this organizational structure. a) Effective Complexity: Metric Entropy; Fractal Dimension; Excess Entropy; Stochastic Complexity; Sophistication; Effective Measure Complexity; True Measure Complexity; Topological epsilon-machine size; Conditional Information; Conditional Algorithmic Information Content; Schema length; Ideal Complexity; Hierarchical Complexity; Tree subgraph diversity; Homogeneous Complexity; Grammatical Complexity. b) Mutual Information: Algorithmic Mutual Information; Channel Capacity; Correlation; Stored Information; Organization. There are a number of related concepts that are not quantitative measures of complexity per se, but that are closely related: Long--Range Order; Self--Organization; Complex Adaptive Systems; Edge of Chaos. 2
  3. 3. Our definition of complexity Complex system – the one that does not fit in the sole engineer’s head, thus collaboration of a team and automation of a knowledge work are mandatory. E.g.: • Aircraft • programming-in-the small vs.programming in the large • VLSI – very large scale integration, more than 1000 transistors on a single chip (now transistor count is more than 20bln. – FPGA Virtex-Ultrascale XCVU440) • Artificial neural network – 16bln. parameters. 3
  4. 4. Sources of ideas for fighting complexity • Software engineering / computer hardware engineering • Banking, insuarance, security market • Retail industry (one of the leaders now!) • Transport engineering (aerospace, railway, automotive) • Other mechanical engineering • Civil engineering 4
  5. 5. 5 Engineering: complexity is about number of independent parts PP&P – process, power & petroleum PLM – product life-cycle management From Dassault Systemes presentation
  6. 6. How to make such people? Hunting and gathering Settled farming
  7. 7. Systems Engineering: dealing with complexity. 7 Systems Engineering (SE) is an interdisciplinary approach and means to enable the realization of successful systems. It focuses on holistically and concurrently understanding stakeholder needs; exploring opportunities; documenting requirements; and synthesizing, verifying, validating, and evolving solutions while considering the complete problem, from system concept exploration through system disposal. http://sebokwiki.org/wiki/Systems_Engineering_%28glossary%29 https://en.wikipedia.org/wiki/Apollo_program Apollo landings (1969-1972) Apollo Program • 24 astronauts orbited Moon • 12 astronauts walked on Moon • 382kg of lunar soil and rocks returned to Earth
  8. 8. System approach in systems engineering standards and public documents • BKCASE, Body of Knowledge and Curriculum to Advance Systems Engineering (2015), http://www.bkcase.org/ • IEC 81346 (2009), Industrial systems, installations and equipment and industrial products -- Structuring principles and reference designations -- Part 1: Basic rules • ISO/IEC/IEEE 15288 (2015) Systems and software engineering - System life cycle processes, • ISO 15926-2 (2003), Industrial automation systems and integration -- Integration of life-cycle data for process plants including oil and gas production facilities -- Part 2: Data model. • ISO/IEC/IEEE 42010 (2011), Systems and software engineering - Architecture description, • OMG Essence (2014) – Kernel and Language for Software Engineering Methods, specification http://www.omg.org/spec/Essence/Current 8
  9. 9. Complexity: divide and conquer • System holonic structure • Separation of concerns • Abstracton (modeling-generation) • Learning (autoencoder-decoder) • Cognitive load management (expression problem) • … 9
  10. 10. System in the eyes of the beholders (stakeholders). Theatre metaphor Stakeholder is role vs. actor/performer, office/position, rank System approach 2.0, based on human action
  11. 11. Holon part-whole relationship 11 System of interest (using system) (system in operation environment) (subsystem) Subsystem (System of interest) (Using system) (system in operation environment) Using system (system-of-interest) (system in operation environment) (subsystem) Enabling system
  12. 12. System of Systems conditional part-whole relationship Enable system
  13. 13. Holarhy zoom – select Leidraadse (2008), Guideline Systems Engineering for Public Works and Water Management, 2nd edition, http://www.leidraadse.nl/
  14. 14. There are 4 systems here: System of interest Requirements System of interest Constraints (Architecture) Using system Stakeholder needs 14 1 2 4 Enabling system System in operation environment 3
  15. 15. Generations of engineering (modeling development for checking, simulation and generation) 15 E f f e c t i v e n e s s Time III generation Model-based engineering: formal languages («executable code») II generation Contemporary («classic») engineering: diagrams and drawings («pseudocode») I generation «Alchemy-like engineering»: informal texts and sketches 199018601400 IV generation Artificial intelligence: formal+informal computations 2020
  16. 16. Interdisciplinary Plurality (on one system level, even without holarchy) On base of Fig.3 ISO 81346-1 -Module =Component +Location All specialties • Mechanics • Cinematics • Electrics • Electronics • Control software • Fluid dynamics • Strength • Temperature • Noise • Vibration • … All life cycle stages • Inception • Design • Construction, manufacturing • Operation • Maintenance • Modernization • Retirement PLM/ALM, ERP, EAM • Product model • Project model 16
  17. 17. System definition and system description ISO 42010 + OMG Essence 17
  18. 18. Basic system structures ISO 81346 • =Components • -Modules • +Locations • Multiple variants of representations of each system aspect. • This is only basic system aspects, there are multiple other system structure types! • Rare completely separated. Usually presented in hybrid form. 18
  19. 19. Hybrid diagrams • There are few ontology engineers, you should not expect too much formalism. • Most of system descriptions are hybrid (with components and modules are mixed). • Terminology can differ (e.g. “component” can be “functional element” and even “module”). 19
  20. 20. Component diagrams (principal schemas) 20
  21. 21. Principal schema complexity • Great metamodels (discipline) • Modelers (collaboration) • Model checking (formalization) • Generate! • Simulation 21
  22. 22. Module diagram examples (1) 22 FR160B PCB 2-Layer USB Portable Power Module -- - Green (3.5 x 2.6 x 1.5cm) Model FR160B Quantity 1 Color Green Material PCB Features Input: 5V/800mA; Output: 5V/1A; LED lightening; With protection board on COB; Output current limited protection Application Great for DIY project Other ON (Press button) / OFF (Automatically) Packing List 1 x Module
  23. 23. Module diagram examples (2) Intellect stack 1. Application 2. Cognitive architecture 3. Learning algorithm 4. Numerical libraries and frameworks 5. Scientific computing programming language 6. Hardware acceleration of computations 23 http://www.slideshare.net/Techtsunami/cn-prt-iot-v1 http://www.w3.org/2001/12/semweb-fin/w3csw http://ailev.livejournal.com/1210678.html Semantic web stack Networking Layer Comparison
  24. 24. Modules: key for complexity • Modularity: links have a price! The more links, the more price! (http://arxiv.org/abs/1207.2743) • Modules: black-boxes with functions, available via interfaces • Interfaces: communications. Conway law, reverse Conway maneuver. • Optimization: DSM 24
  25. 25. Logical and physical architectures matching ISO 81346-1 Figure 7 25 Logical architecture (component structure, functional decomposition) iteratively match with physical architecture (module structure, work product decomposition). Most complex part: modular synthesis
  26. 26. Multiscale * beyond life cycle <<< Inception Architecture Non- architecture part of design Manufacturing Operation>>> Using system IT-1 IT-2 IT-3 IT-4 IT-5 Macro IT1 IT2 IT3 IT4 IT5 Meso IT6 IT7 IT8 IT9 IT10 Micro IT11 IT12 IT13 IT14 IT15 Nano IT16 IT17 IT18 IT19 IT20 Specialization/professionalization in each cell, plus expansion to neighbors Integration at a product level: overall table («enabling eco-system»!) CAD/CAM/codes/PLM/CAE/ERP/EAM/… configuration and change management! Substance (system) levels * realization (life cycle) levels 26
  27. 27. Expression problem • Programming-in-the small vs. programming in the large • Granularity & modularity • Packages (Modula) • Object-oriented approach • Data bases/queries • Julia: multiple dispatch • Functional programming – Johan van Bethem (in https://www.illc.uva.nl/Research/Publications/Reports/PP-2005- 22.text.pdf): «much of logic is about a balance between the expressive power of formal languages and the complexity of performing natural tasks for them, such as model checking for truth, consistency maintenance, or valid inference. This is the thrust of many meta-theorems, including Gödel's and Tarski's celebrated result about the limitations of first-order logic. The 'Golden Rule' of logic says that gains in expressive power are lost in higher complexity». 27
  28. 28. Practice = discipline + technology Disciplined (competent in domain) performers Supported with needed for a discipline tools and work products. 28 Components/alpha – how it is working Modules/work products – how it makeable
  29. 29. Domain and endeavor: KNOWLEDGE is an information that you can use in different projects (economy of thinking!) • Domain/discipline = thinking (operations with abstract typed objects). Changing every 30 years. Studied in schools and universities. • Technologies/way of working = tools and work products (thinking with an exocortex). Changing in every 5 years. Trained in workplace. • Link between discipline and technology, discipline and real life should be trained with a help of a teacher. 29 There is no one word from a textbook in real life There is no one work from real life in a textbook =Components, functional elements, Alphas =Modules, constructive elements, work products
  30. 30. Project Essence Diagram: complexity of organization counts! 30 Engineering management Engineering Technology management Using system Technology management and entrepreneurship System of interest Enabling system
  31. 31. 31 System life cycle practices drive alphas http://arxiv.org/abs/1502.00121 Systems Engineering Essence
  32. 32. System and project life cycle (OMG Essence for systems engineering) 32 satisfied in use represented recognized benefit accrued Solution needed viable identified used for retirement consisted used for operation conceived retired parts demonstrable operational closed prepared under control concluded initiated formed collaborating seeded foundation established in place working well principle established stakeholders opportunity system definition system realization work team way of working inception development deployment испытания manufacturing retiredadjourned ready used for verification involved satisfied for deployment adressed started performingused for production raw materialsIn agreement in usevalue established http://arxiv.org/abs/1502.00121
  33. 33. Case management: issue, ticket, bug 33 issue/request task/order notice
  34. 34. How to fight development flow complexity? Ideas sources: • сomputer operating systems • control engineering • data communications networks • finance and economics • information theory • maneuver warfare • Manufacturing • operations research • probability and statistics • queueing theory According to Donald Reinertsen 34
  35. 35. Connectionism • World is not symbolic! We need means to sense and process raw world complexity! • Non-symbolic models: distributed representations. • Connectionism (e.g. deep learning): deal with informal implicit knowledge processing. • Since 2012 (GPU enabled) 35 NVIDIA® Jetson™ TX1 http://www.nvidia.com/object/embedded-systems.html
  36. 36. Avatarization of engineering software • Learning of CAD and/or programming/configuration • Natural language and/or programming language • Human-computer dialog for justification of intents and constraints • Joint human-computer idea generation and/or editing of ideas by human • Convenient dialog with software: avatar with name and image, emotion recognition and usage Company Virtual intelligent assistant Google Google Apple Siri Microsoft Cortana Facebook M Amazon Alexa Autodesk ??????????? 36
  37. 37. 37 Thank you! Anatoly Levenchuk, TechInvestLab, president INCOSE Russian chapter, research director http://ailev.ru ailev@asmp.msk.su Book «Systems engineering thinking» (in Russian: http://techinvestlab.ru/systems_engineering_thinking)

×