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| 1 | +--- |
| 2 | +description: 'Deep expertise for Method 7: High-Fidelity Prototypes; fidelity translation, architecture, and specification writing' |
| 3 | +applyTo: '' |
| 4 | +--- |
| 5 | + |
| 6 | +# Method 7: Deep Expertise |
| 7 | + |
| 8 | +Advanced reference material for the DT coach when facing complex hi-fi prototyping questions. Load this file via `read_file` during Method 7 work requiring depth beyond the method-tier instruction file. Content is organized by hat affinity for fast lookup. |
| 9 | + |
| 10 | +## Fidelity Translation |
| 11 | + |
| 12 | +### Fidelity Mapping Matrix |
| 13 | + |
| 14 | +For each lo-fi prototype element, assign a treatment category before beginning hi-fi work: |
| 15 | + |
| 16 | +| Category | Treatment | Selection Criteria | |
| 17 | +|-----------------------|---------------------------------------------------|-----------------------------------------------------------------------------------------| |
| 18 | +| Elevate to functional | Build working implementation with real data | Element tests the core hypothesis; user feedback depends on authentic behavior | |
| 19 | +| Keep rough | Preserve lo-fi representation with minimal polish | Element supports context but is not under test; roughness does not distort results | |
| 20 | +| Defer | Exclude from hi-fi prototype entirely | Element is out of scope for the current hypothesis or introduces unnecessary complexity | |
| 21 | + |
| 22 | +Tie each assignment to specific Method 6 constraint discoveries. Elements without a traceable constraint warrant re-evaluation. |
| 23 | + |
| 24 | +### Fidelity Gradient |
| 25 | + |
| 26 | +Five stages from roughest to most functional. Each stage has an advancement criterion and an over-engineering signal: |
| 27 | + |
| 28 | +1. Paper or cardboard serves as the Method 6 output. Advance when the hypothesis requires interactive behavior paper cannot provide. |
| 29 | +2. A static digital mockup provides visual layout without logic. Advance when users need to interact with the system to provide meaningful feedback. |
| 30 | +3. An interactive simulation introduces logic with simulated data. Advance when simulated data masks behaviors the hypothesis depends on. |
| 31 | +4. A functional prototype uses real data within constrained scope and represents the target state for Method 7. Advance to production only in Method 9. |
| 32 | +5. Reaching production-ready during Method 7 is an anti-pattern; redirect effort to testing preparation. |
| 33 | + |
| 34 | +### Learning Preservation |
| 35 | + |
| 36 | +Patterns for carrying lo-fi insights forward without losing context during technical translation: |
| 37 | + |
| 38 | +* Constraint inventory: catalog all Method 6 environmental findings (noise levels, lighting, physical dimensions, workflow sequences) as testable technical requirements. |
| 39 | +* Assumption traceability: link each hi-fi design decision to the lo-fi assumption it validates or invalidates. |
| 40 | +* User-quote anchoring: attach direct user observations from Method 6 testing to the technical requirements they generated, preserving the human reasoning behind specifications. |
| 41 | + |
| 42 | +### Translation Anti-Patterns |
| 43 | + |
| 44 | +| Anti-Pattern | Signal | Remediation | |
| 45 | +|-----------------------|----------------------------------------------------------------------------|-------------------------------------------------------------------------------------------| |
| 46 | +| Gold plating | Non-critical elements receive full fidelity treatment | Return to fidelity map; re-evaluate each element against the core hypothesis | |
| 47 | +| Constraint amnesia | Technical decisions ignore Method 6 environmental findings | Cross-reference the constraint inventory before each design decision | |
| 48 | +| Fidelity leapfrogging | Jump from paper prototype to near-production implementation | Enforce intermediate validation stages in the fidelity gradient | |
| 49 | +| Audience confusion | Prototype built for stakeholder presentation instead of hypothesis testing | Clarify prototype purpose: functional proof, not demo | |
| 50 | +| Feature creep | Scope expands beyond the original constraint-validated concept | Lock the element list from the fidelity map; new items require explicit re-prioritization | |
| 51 | + |
| 52 | +## Technical Architecture |
| 53 | + |
| 54 | +### Build-vs-Simulate Decision Tree |
| 55 | + |
| 56 | +Select build or simulate based on the primary question the prototype must answer: |
| 57 | + |
| 58 | +* Does the hypothesis require real system behavior? Build the component. |
| 59 | +* Is the integration point the core question? Build the interface; simulate the backend. |
| 60 | +* Is the constraint environmental (noise, vibration, lighting)? Build and test in-situ. |
| 61 | +* Is timeline the primary risk? Simulate with documented assumptions; build only validated paths. |
| 62 | +* Is cost the primary risk? Simulate first; build only after simulation confirms viability. |
| 63 | + |
| 64 | +When multiple factors conflict, prioritize the factor that most directly tests the hypothesis. |
| 65 | + |
| 66 | +### Architecture Trade-Off Analysis |
| 67 | + |
| 68 | +Evaluate implementation approaches across these dimensions: |
| 69 | + |
| 70 | +* Assess implementation complexity by evaluating effort, skills required, and tooling dependencies. |
| 71 | +* Evaluate constraint compliance through alignment with noise, safety, environmental, and workflow constraints from Method 6. |
| 72 | +* Gauge integration risk by examining compatibility with existing systems, data format requirements, and protocol support. |
| 73 | +* Measure iteration speed as the time to modify and retest after Method 8 user feedback. |
| 74 | +* Characterize the technical debt profile by identifying the nature and volume of shortcuts and whether debt blocks user testing. |
| 75 | + |
| 76 | +Each approach receives a comparative rating per dimension. The optimal choice minimizes integration risk and maximizes iteration speed, accepting complexity trade-offs that do not block testing. |
| 77 | + |
| 78 | +### Technical Debt Budget |
| 79 | + |
| 80 | +Acceptable debt in prototypes: |
| 81 | + |
| 82 | +* Hardcoded configurations, manual deployment steps, limited error handling, single-user assumptions, simplified authentication. |
| 83 | + |
| 84 | +Unacceptable debt: |
| 85 | + |
| 86 | +* Security bypasses exposing real data, data corruption risks, silent failures masking test results, untested integration points the hypothesis depends on. |
| 87 | + |
| 88 | +Review trigger: reassess the debt budget when accumulated debt would prevent Method 8 user testing from producing reliable results. |
| 89 | + |
| 90 | +## Specification Writing |
| 91 | + |
| 92 | +### Specification Audience Mapping |
| 93 | + |
| 94 | +Different stakeholders need different views of the prototype documentation: |
| 95 | + |
| 96 | +| Audience | Documentation Needs | |
| 97 | +|--------------------------------|---------------------------------------------------------------------------------------------------------| |
| 98 | +| Developers | Architecture decisions, API contracts, data flows, known limitations, build and deployment instructions | |
| 99 | +| Product managers | Feature scope boundaries, trade-off rationale, user impact summary, deferred decisions | |
| 100 | +| Testers (Method 8) | Test boundaries, known failure modes, environment setup requirements, expected vs unexpected behaviors | |
| 101 | +| Future implementors (Method 9) | Scalability assumptions, production gaps, deployment constraints, rebuild-vs-extend guidance | |
| 102 | + |
| 103 | +### Decision Rationale Capture |
| 104 | + |
| 105 | +For each significant technical decision, document five fields: |
| 106 | + |
| 107 | +* What was decided. |
| 108 | +* What alternatives were considered and why they were rejected. |
| 109 | +* What constraints drove the decision. |
| 110 | +* What assumptions the decision depends on. |
| 111 | +* What conditions would invalidate the decision. |
| 112 | + |
| 113 | +Capture rationale during implementation, not after. Post-hoc reconstruction omits rejected alternatives and distorts constraint reasoning. |
| 114 | + |
| 115 | +### Assumption and Gap Documentation |
| 116 | + |
| 117 | +Track four categories: |
| 118 | + |
| 119 | +* Tested assumptions are beliefs validated through Method 6 or 7 testing, with evidence references. |
| 120 | +* Untested assumptions have been identified but deferred; document why deferral is acceptable for the current prototype. |
| 121 | +* Known unknowns are gaps identified during prototyping that require future investigation. |
| 122 | +* External dependencies are decisions or resources controlled by other teams, systems, or timelines not yet confirmed. |
| 123 | + |
| 124 | +## Manufacturing-Specific Patterns |
| 125 | + |
| 126 | +### PLC/SCADA Prototyping |
| 127 | + |
| 128 | +Prototypes interact with industrial control systems through read-only data taps or simulation layers. Direct write operations to production PLCs are out of scope. |
| 129 | + |
| 130 | +* Simulation approaches include OPC-UA test servers, PLC simulators (Siemens PLCSIM, Allen-Bradley emulators), and recorded sensor data playback. |
| 131 | +* Test integration fidelity with actual communication protocols (Modbus, OPC-UA, EtherNet/IP) against simulated endpoints. Protocol timing and error handling must be realistic even when endpoints are simulated. |
| 132 | +* Constraint categories to evaluate include scan cycle timing, network latency tolerance, data format compatibility, and historian integration requirements. |
| 133 | + |
| 134 | +### Digital Twin Prototyping |
| 135 | + |
| 136 | +Four fidelity levels for digital twin prototypes: |
| 137 | + |
| 138 | +1. A static model provides historical data visualization with no live connection. |
| 139 | +2. A dynamic model integrates live data streams with real-time updates. |
| 140 | +3. A predictive model runs scenario simulations using current data to forecast outcomes. |
| 141 | +4. A prescriptive model generates automated response recommendations. This level exceeds Method 7 scope; treat as a Method 9 target. |
| 142 | + |
| 143 | +Identify the minimum sensor coverage for meaningful twin behavior. Document data quality assumptions and compare twin predictions against actual system behavior to calibrate divergence tolerance. |
| 144 | + |
| 145 | +### Safety-Critical Boundaries |
| 146 | + |
| 147 | +* Prototypes do not issue commands to safety-critical systems, including emergency stops, safety interlocks, pressure relief, and fire suppression. |
| 148 | +* Prototypes may read safety system status in safety zones but must not interfere with safety PLC logic or certified safety functions. |
| 149 | +* In regulated industries (pharmaceuticals, food, energy), prototype testing requires documented risk assessment even for observation-only deployments. |
| 150 | +* Prototype hardware placed in safety zones must meet the same ingress protection and electrical safety standards as production equipment. |
| 151 | + |
| 152 | +### Operator Interface Fidelity |
| 153 | + |
| 154 | +* Touch targets require a minimum of 15 mm for bare hands and 20 mm for gloved operation, with no fine-motor gestures. |
| 155 | +* Screens must be readable at arm's length under industrial lighting, with high-contrast displays and no glossy screens. |
| 156 | +* Interface state must be comprehensible to an incoming operator during shift handoff without training on prototype specifics. |
| 157 | +* Audio feedback is unreliable above 80 dB; use visual and haptic feedback patterns instead. |
| 158 | +* Interfaces exposed to oil, dust, or moisture need appropriate enclosures. Prototype enclosures can be improvised (sealed bags, ruggedized tablets) but must be tested under actual conditions. |
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