Improve performance by introducing controlled oscillation, iteration, or repetition instead of static operation.
Attribution
Creator: Dzmitryi Kharlanau (SAP Lead).
Canonical: https://dkharlanau.github.io/datasets/TRIZ-bytes/TRIZ-18.json
JSON (copy / reuse)
{
"id": "TRIZ-18",
"title": "Mechanical Vibration",
"intent": "Improve performance by introducing controlled oscillation, iteration, or repetition instead of static operation.",
"triz_principle": {
"number": 18,
"name": "Mechanical Vibration",
"definition": "Cause an object or system to oscillate or repeatedly change state to improve its effectiveness."
},
"problem_understanding": {
"core_contradiction": "We want stability, but static operation prevents learning, optimization, and responsiveness.",
"why_this_hurts": "Without cycles and feedback, systems drift away from reality and degrade silently.",
"typical_signals": [
"rare feedback loops",
"long periods between reviews or releases",
"decisions made once and never revisited",
"optimization based on outdated assumptions"
]
},
"solution_logic": {
"core_idea": "Introduce frequent, controlled cycles that allow adjustment and learning.",
"key_rule": "Oscillate deliberately instead of drifting unconsciously.",
"how_it_resolves_the_contradiction": "The system stays aligned with reality through constant small corrections instead of rare big ones."
},
"application_patterns": {
"consulting": [
"regular review and calibration cycles",
"short feedback workshops instead of annual reviews",
"iterative recommendations with checkpoints"
],
"software_engineering": [
"short release cycles",
"continuous integration and testing",
"periodic refactoring sprints"
],
"architecture": [
"health checks and periodic self-tests",
"adaptive tuning based on metrics",
"rolling upgrades instead of big-bang releases"
],
"enterprise_sap": [
"regular data quality monitoring runs",
"periodic MDG rule tuning based on rejection patterns",
"scheduled reconciliation cycles"
]
},
"anti_patterns": [
"oscillation without learning or metrics",
"too frequent cycles causing instability",
"rituals that exist without impact"
],
"usage_guidance": {
"use_when": [
"feedback arrives too late",
"system behavior drifts over time",
"learning is slow or reactive"
],
"do_not_use_when": [
"changes are costly or disruptive",
"system requires long stable periods"
]
},
"diagnostic_questions": [
"Where do we get feedback too late?",
"Which assumptions should be tested repeatedly?",
"What cycle frequency would balance learning and stability?"
],
"example": {
"before": "Data quality rules are defined once and rarely revisited.",
"after": "Rules are reviewed and adjusted regularly based on actual rejection and error patterns."
},
"meta": {
"schema": "dkharlanau.dataset.byte",
"schema_version": "1.1",
"dataset": "TRIZ-bytes",
"source_project": "cv-ai",
"source_path": "TRIZ-bytes/TRIZ-18.json",
"generated_at_utc": "2026-02-03T14:33:32+00:00",
"creator": {
"name": "Dzmitryi Kharlanau",
"role": "SAP Lead",
"website": "https://dkharlanau.github.io",
"linkedin": "https://www.linkedin.com/in/dkharlanau"
},
"attribution": {
"attribution_required": true,
"preferred_citation": "Dzmitryi Kharlanau (SAP Lead). Dataset bytes: https://dkharlanau.github.io"
},
"license": {
"name": "",
"spdx": "",
"url": ""
},
"links": {
"website": "https://dkharlanau.github.io",
"linkedin": "https://www.linkedin.com/in/dkharlanau"
},
"contact": {
"preferred": "linkedin",
"linkedin": "https://www.linkedin.com/in/dkharlanau"
},
"canonical_url": "https://dkharlanau.github.io/datasets/TRIZ-bytes/TRIZ-18.json",
"created_at_utc": "2026-02-03T14:33:32+00:00",
"updated_at_utc": "2026-02-03T15:29:02+00:00",
"provenance": {
"source_type": "chat_export_extraction",
"note": "Extracted and curated by Dzmitryi Kharlanau; enriched for attribution and crawler indexing."
},
"entity_type": "triz_byte",
"entity_subtype": "",
"summary": "Improve performance by introducing controlled oscillation, iteration, or repetition instead of static operation."
}
}