{"closest_prior_art":[{"name":"Siemens model-based quality, Variation Analysis, and dimensional planning/validation","overlap":"A first-party deployed toolchain performs Monte Carlo manufacturing and assembly variation simulation, models assembly operations and component flexibility, validates GD&T before production, captures dimensional measurements, and supports an as-built/as-designed quality loop.","remaining_difference":"The retained Siemens materials do not establish a mandatory controlled-drawing release interlock requiring disposition of every predicted envelope violation, nor prospective scoring of frozen, version-linked pre-release distributions against held-out assemblies.","source_ids":["SRC2"]},{"name":"NIST closed-loop tolerance engineering and QIF digital-thread framework","overlap":"The framework connects functional requirements, tolerancing, process capability, product performance, statistical tolerance optimization during design, quality feedback, metrology data, and engineering-change requests.","remaining_difference":"It describes a lifecycle framework and feedback infrastructure rather than an implemented probabilistic drawing-release gate with preregistered forecasts, uncertainty-based abstention rules, and calibration scoring for each released assembly.","source_ids":["SRC1"]},{"name":"Design-stage probability and process-capability-based tolerance allocation","overlap":"Prior research predicts assembly nonconformance from statistical process characteristics and optimizes component tolerance allocations during design, including nonlinear industrial assemblies, materials, geometry, capability targets, and failure severity.","remaining_difference":"These sources do not add the proposal's controlled-release interlock and post-build comparison of frozen predictive distributions with as-built measurements.","source_ids":["SRC3","SRC4"]}],"contrastive_claim_falsifier":"The remaining contrast would be falsified by evidence that an existing workflow already blocks controlled drawing release until probabilistic assembly-envelope crossings are dispositioned by the responsible signatories and then routinely scores the frozen, version-linked pre-release distributions against held-out as-built measurements to recalibrate or restrict the model.","contrastive_claim_remaining":"Relative to existing statistical tolerance analysis and closed-loop quality toolchains, the testable increment is a configuration-controlled release interlock that requires accountable disposition of probabilistic functional-envelope violations and prospectively evaluates the frozen prediction against later builds. The bounded claim is that this increment improves correct pre-release interface classification without excessive false blocks or unauthorized relaxation of requirements.","experiment_id":"eoa_inverse_innovation_exp13_second_slot_policy60_20260806","gates":{"adequate_source_search":{"rationale":"Four lanes covered direct probabilistic tolerance analysis, historical statistical-tolerancing and closed-loop terminology, first-party products and quality standards infrastructure, and combinations of process capability, assembly simulation, tolerance allocation, and measurement feedback. Four opened sources span NIST, Siemens, SAE International, and Mechanics & Industry/Cambridge Core.","source_ids":["SRC1","SRC2","SRC3","SRC4"],"status":"PASS"},"bounded_next_test":{"rationale":"The proposed archived-design shadow replay is bounded, reversible, and measurable. Freezing inputs and thresholds before examining held-out outcomes permits comparison of missed violations, false blocks, calibration error, unsupported assumptions, and validity-boundary failures without changing drawings or production.","source_ids":["SRC1","SRC2","SRC3","SRC4"],"status":"PASS"},"distinct_testable_claim":{"rationale":"Although most technical components substantially collide with prior art, the combination of a mandatory configuration-controlled release disposition and prospective calibration of frozen predictions remains separable and falsifiable against baseline review.","source_ids":["SRC1","SRC2"],"status":"PASS"},"no_obvious_safety_or_authority_stop":{"rationale":"The first test is limited to an archived shadow analysis, preserves existing configuration, manufacturing, quality, and safety authority, and explicitly forbids drawing changes, production authorization, inspection substitution, and unjustified capability inputs. Safety-critical worst-case and physical-qualification requirements remain intact.","source_ids":[],"status":"PASS"},"supported_problem":{"rationale":"NIST identifies manufacturing variability, costly tolerance failures, incomplete or non-prevalent digital feedback, and largely manual remediation; Siemens markets pre-production variation simulation and closed-loop dimensional quality to reduce risk. This makes the problem visible, though the retained evidence does not quantify how often assemblies are released with incomplete integrated analysis.","source_ids":["SRC1","SRC2"],"status":"PASS"}},"prior_art_disposition":"SUBSTANTIAL_COLLISION","problem_evidence":{"finding":"The problem is partly supported: manufacturing variability can produce clearance, interference, quality, cost, and yield problems; statistical tolerance analysis and quality feedback are recognized responses, while integrated feedback and remediation remain incompletely standardized or prevalent. The sources do not establish incidence or magnitude for the exact release-stage failure described.","source_ids":["SRC1","SRC2","SRC3","SRC4"],"status":"PARTLY_SUPPORTED"},"research_id":"eoa_inverse_innovation_exp13_light_screen_20260806","schema_version":1,"screen_id":"E13P108","screen_survival":false,"search_lanes":{"component_combination":{"no_result_note":null,"queries":["software tolerance analysis process capability assembly sequence release gate drawings","closed loop tolerance engineering production measurements feedback design tolerance allocation"],"source_ids":["SRC1","SRC2","SRC3"]},"direct_problem_and_intervention":{"no_result_note":null,"queries":["probabilistic tolerance analysis before design release manufacturing variation assembly Monte Carlo","closed loop tolerance engineering as-built measurement feedback tolerance analysis"],"source_ids":["SRC1","SRC2","SRC4"]},"products_practices_and_standards":{"no_result_note":null,"queries":["site:siemens.com tolerance analysis statistical variation analysis Teamcenter quality measurement feedback","ASME probabilistic tolerance analysis standard statistical tolerancing assembly"],"source_ids":["SRC1","SRC2"]},"synonyms_and_historical_terms":{"no_result_note":null,"queries":["CETOL 6 sigma tolerance analysis statistical product design process capability official","closed loop tolerance engineering production measurements feedback design tolerance allocation"],"source_ids":["SRC1","SRC3","SRC4"]}},"sources":[{"claims_supported":["Computer-aided and statistical tolerance analysis model clearance or interference and assembly likelihood during design.","Tolerance optimization can use statistical analysis to improve yield, cost, and quality.","Closed-loop tolerance engineering connects functional requirements, tolerancing, process capabilities, product performance, and feedback.","Quality feedback, measurement uncertainty, metrology data, and engineering-change requests can participate in a bidirectional manufacturing digital thread.","Integrated feedback was described as not yet prevalent, with much remediation remaining manual or incompletely standardized."],"publisher":"National Institute of Standards and Technology / U.S. Government Publishing Office","source_id":"SRC1","source_type":"PRIMARY_RESEARCH","title":"End-to-End Quality Information Framework (QIF) Technology Survey (NISTIR 8127)","url":"https://www.govinfo.gov/content/pkg/GOVPUB-C13-da4e037714b436909a8a0b3effc25a9c/pdf/GOVPUB-C13-da4e037714b436909a8a0b3effc25a9c.pdf"},{"claims_supported":["Variation Analysis uses Monte Carlo simulation to predict and quantify manufacturing and assembly variation.","The product models assembly operations and can incorporate component flexibility from clamping, welding, and springback.","Siemens model-based quality joins variation analysis, inspection, measurement collection, analytics, and reporting before production.","Siemens describes an as-built/as-designed closed quality loop and measurement-informed design and manufacturing decisions."],"publisher":"Siemens Digital Industries Software","source_id":"SRC2","source_type":"FIRST_PARTY_PRODUCT","title":"Discover what's new in model-based quality (August 2023)","url":"https://blogs.sw.siemens.com/tecnomatix/discover-whats-new-in-model-based-quality-august-2023/"},{"claims_supported":["A design-stage statistical method combines process-capability estimates with assembly-stack tolerance allocation.","The method models realistic distributions using manufacturing-process, material, and geometry knowledge.","Tolerance optimization and capability targets can incorporate failure severity and were illustrated with an automotive case study."],"publisher":"SAE International","source_id":"SRC3","source_type":"PRIMARY_RESEARCH","title":"Allocating Capable Tolerances in Assembly Stack Design","url":"https://saemobilus.sae.org/papers/allocating-capable-tolerances-assembly-stack-design-1999-01-0053"},{"claims_supported":["Advanced Probability-Based Tolerance Analysis predicts assembly defect probability during design.","The prediction uses nominal dimensions, tolerances, capability levels, and variable process means and standard deviations.","The method covers linear and nonlinear assembly relations and was demonstrated on industrial products."],"publisher":"Mechanics & Industry / Cambridge University Press","source_id":"SRC4","source_type":"PRIMARY_RESEARCH","title":"APTA: Advanced Probability-Based Tolerance Analysis of Products","url":"https://www.cambridge.org/core/journals/mechanics-and-industry/article/apta-advanced-probabilitybased-tolerance-analysis-of-products/3179F5E0F62CBE50428CDCB2A7D4E6B4"}],"world_novelty_boundary":"This bounded public-web screen found substantial collision across design-stage probabilistic tolerance analysis, process-capability-based allocation, assembly simulation, dimensional metrology, and closed-loop quality feedback. It did not establish a single source implementing every governance and calibration detail. The result cannot establish world novelty, patentability, freedom to operate, market size, expert acceptance, implementation prevalence, or realized value."}