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Object-Context-Goal analysis

Object-Context-Goal analysis. Prof . Dr. Christos Spitas. Recall: Challenges. Product Engineering is a subset of product development. Challenges, as explored previously, give rise to the need for systematic product engineering

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Object-Context-Goal analysis

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  1. Object-Context-Goal analysis Prof. Dr. Christos Spitas

  2. Recall: Challenges • Product Engineering is a subset of product development. • Challenges, as explored previously, give rise to the need for systematicproduct engineering • Advanced Embodiment Design systematises product engineering, aiming to increase its success rate by maximising impact of prior knowledge, time, human and other resources (i.e. computing/ product validation possibilities)

  3. Recall: Importance Q: What is the rate that new products fail? For every seven new product ideas, about four enter development, 1.5 are launched, and only one succeeds (Cooper, 2011).

  4. context relevance Product Engineering The rest of the context/ world robustness quality of ideas The product cost-price The business market relevance Safety usability, ergonomy qualified process ownership brand identity consistency The human

  5. A systematic model for the design process: Ontology IDEAS And Synapses

  6. Defining ideas • Anything currently/ potentially present to consciousness • ‘Currency’ for cognition • Idea comprises of • Name • Attribute(s) (ideas) • Value (idea) • Null idea • No genetic inheritance: emergence • Different levels of abstraction

  7. Classifying ideas: Ontology vs. Activity • Ontology • Topology • Structure • Shape • Colour • Exists • True/ False • Activity • Event • Function • Happens • True/ False • It is what it does/ does what it is • Clear design intent in final product • Simplicity, elegance Conceptual Unification

  8. Visualising ideas

  9. Mathematically representing ideas • Idea comprises of • Name • Attribute(s) (ideas) • Value (idea) • Design can be fully recorded, reported and understood • i.e. SHAFT • (list (solid) (cylinder)) • (list (solid) (cylinder (list (diameter 3.20mm) (length 8mm) ))) • ‘Value’ visited in next lecture

  10. Organisation of ideas: Synaptic Networks • Ideas ‘connect’ to each other through common attributes • Forming larger networks • i.e. abstract knowledge/ general laws connect to our product, producing more knowledge, which is product-specific

  11. Building an idea network

  12. Design in terms of the creation of ideas and synaptic networks • Analyse wheelbarrow • Adapt to snow • Analysesnowboard • Adapt to heavy weights • Analysecart • Adapt to high speeds • Analysebicycle • Adapt to... • AnalyseSegway hard ground link ground soft snow

  13. A systematic model for the design process: Activity Analysis, Heuresis, Evaluation, Choice

  14. Operations and manipulations of ideas • Analysis • ανάλυσις (to take apart) • substitution, mapping • same or higher abstraction • Heuresis • εύρεσις (to find) • discovery, mapping, (analogy, synthesis)... • any level of abstraction • Evaluation • establishing the (unknown) value of ideas • Choice • fundamentally from affective domain!

  15. Experimental findings

  16. Experimental findings: Heuresis

  17. Method OBJECT-CONTEXT-GOAL (OCG) Analysis

  18. Object-Context-Goal classification • goal-related ideas (i.e. our wishes, requirements) • object-related ideas: all those (possibly) subject to our intervention and/ or choice (i.e. the product description) • context-related ideas: all not subject to intervention (i.e. the laws of physics, materials availability, market culture)

  19. Identify ideas goal context other interim ideas (i.e. ‘criteria’, ‘insights’ etc case-specific/ volatile ideas) ‘things’, systems, components state of the art given idea at any level of specification

  20. Identify and evaluateOCG networks goal context other interim ideas (i.e. ‘criteria’, ‘insights’ etc case-specific/ volatile ideas) ‘things’, systems, components state of the art given idea at any level of specification

  21. Case Studies OCG Analysis in Action

  22. Challenges in Product Development • 1/9: Burger King Pokemon container • Massive original success • Turned out that hemispherical halves posed suffocation risk • Product recall • Challenge: Safety!

  23. Challenges in Product Development • 2/9: Breakfast mates • Did not deliver ‘on-the-go’ promise (cold milk?) • Poor packaging ergonomics • Challenge: Usability! • Challenge: Ergonomy!

  24. Challenges in Product Development • 5/9: Space shuttle • Risks addressed through inspections & rules • Gasket failure at low temperature during lift-off • Catastrophic failure • 32-month stop • Challenge: Robustness!

  25. Challenges in Product Development • 6/9: Apple Lisa • Pioneering GUI • High-quality • Cost 50M$ in hardware and 100M$ in development • Sold only 10,000 items, brought 100M$ • Challenge: Cost-price!

  26. Challenges in Product Development • 7/9: Apple III • Misplaced involvement by marketing department in product engineering • Unusable upon release • Pulled and rereleased 1 year later • Challenge: Qualified process ownership!

  27. Challenges in Product Development • 8/9: BiC safety lighter • Forcing functions impair usability • Child safety bypass gets the most Google hits! • Challenge: Quality of ideas! • Moderation in the use of design means!

  28. Challenges in Product Development • 9/9: Itera all-composite bicycle • Volvo, tech-push • Failures non-serviceable • Incompatible to other bicycles • Production ended after 30,000 items, stock sold to Caribbean • Challenge: Context-relevance!

  29. A systematic model for the design process Process Analysis

  30. Process convergence: what, when and why? t waste of resources? make learn rushed development? challenge: graduate the abstraction scale

  31. Process stage-gating, control of decision making prior knowledge starting wish coarse-grained decision: no/ vague models rough predictions make stage-gates turn object into context ... (everything in-between) learn fine-grained decision: precise models exact predictions

  32. Explicit Object-Context-Goal assisted decision-making goal goal

  33. Process = sequence of Activities • Analysis • identify first-level attributes • assign as attributes • Heuresis • ‘Idea watching’ (let emerge) • mapping/ transformation (analogy/ interpolation/ extrapolation, synthesis) • Evaluation • identify/ calculate values • Choice • ‘listen’ to internal process

  34. Points of attention Methods

  35. What to do with methods taught in areas of expertise? • Use at appropriate time, in clear and focused way. • Methods are taught irrespective of when/ if needed: No spoon-feeding or pushing. • Methods are integrated into the analysis, heuresis, evaluation, choice pattern. Show them as such. • Question everything! Review yourselves! Synaptic networks help.

  36. Points of attention Product-Process integration

  37. Vital aspects of product-process integration Situational awareness Persistent knowledge Values are needed to qualify knowledge for re-use Knowledge (values) only valid when associations to the synaptic network are maintained Keep explicit: graphical representations and data sheets help (wiki/ linked notes) • Let your situational awareness co-evolve with the data (ideas and values) • Use OCG representations (incl. synaptic networks) to communicate intuitively; instead, ‘Making it simple’ often leads to OCG disconnect: Use less rigorous representations carefully

  38. Object-Context-Goal (OCG) tips • By advancing through stage gates, parts of the object become context, mark them! • Keep sight of the goals at all times, evaluate in terms of OCG clusters • Persistently identify needs (for ideas): needs drive the process • Build stage-gates into your project: reporton which objects become context & how goals translate • Keep goals clear and at appropriate granularity/ abstraction • Design = managing OCG clusters, make them explicit

  39. Measuring your process

  40. Measuring your process: detail

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