
Online-KI-Tools verändern den Maschinenbau rapide, indem sie die menschlichen Fähigkeiten in den Bereichen Konstruktion und Analyse ergänzen, Herstellungund Wartung. Diese KI-Systeme können riesige Datenmengen verarbeiten, komplexe Muster erkennen und neue Lösungen viel schneller als herkömmliche Methoden entwickeln. So kann KI Sie beispielsweise bei der Optimierung von Konstruktionen im Hinblick auf Leistung und Herstellbarkeit unterstützen, komplexe Simulationen beschleunigen, Materialeigenschaften vorhersagen und eine Vielzahl von Analyseaufgaben automatisieren.
Die nachstehenden Hinweise helfen beispielsweise bei der generativen Konstruktion, beschleunigen Simulationen (FEA/CFD), helfen bei der vorausschauenden Wartung, bei der KI Sensordaten von Maschinen analysiert, um potenzielle Ausfälle zu prognostizieren, ermöglichen eine proaktive Wartung und minimieren Ausfallzeiten, helfen bei der Materialauswahl und vieles mehr.
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- Ethische Erwägungen und Folgenanalyse
- Maschinenbau
AI Aufforderung an Überblick über die Umweltverträglichkeitsprüfung während des gesamten Lebenszyklus
- Kreislaufwirtschaft, Umweltverträgliche Herstellung, Umweltauswirkungen, Umweltverträglichkeitsprüfung, Lebenszyklus, Lebenszyklusbewertung (LCA), Nachhaltigkeitspraktiken, Nachhaltige Entwicklung, Nachhaltiges Produktdesign
Umreißt die wichtigsten Phasen und Überlegungen für die Durchführung einer Ökobilanz für ein neues mechanisches Produkt. Diese Aufforderung hilft Ingenieuren bei der Strukturierung ihrer LCA-Anstrengungen, indem sie die benötigten Daten, die Wirkungskategorien und die Möglichkeiten zur Schadensbegrenzung ermittelt. Das Ergebnis ist ein Markdown-Dokument, das den LCA-Plan detailliert beschreibt.
Ausgabe:
- Markdown
- erfordert Live-Internet
- Felder: {product_name_and_function} {bill_of_materials_csv} {manufacturing_processes_overview_text} {expected_use_phase_and_disposal_text}
Act as an Environmental Engineering Consultant specializing in Lifecycle Assessments (LCA) for mechanical products.
Your TASK is to generate a structured OUTLINE for conducting a Lifecycle Environmental Impact Assessment for `{product_name_and_function}`.
Consider the product's composition from `{bill_of_materials_csv}` (CSV string: 'Material
Quantity
Source_Region_if_known')
its `{manufacturing_processes_overview_text}`
and its `{expected_use_phase_and_disposal_text}`.
You MAY use live internet to identify common impact assessment tools
databases (e.g.
Ecoinvent
GaBi)
and relevant ISO standards (e.g.
ISO 14040/14044).
**LCA OUTLINE STRUCTURE (MUST be Markdown format):**
**1. Goal and Scope Definition**
* **1.1. Purpose of the LCA**: (e.g.
Identify environmental hotspots
Compare with alternative designs
Eco-labeling).
* **1.2. Product System Description**: Define `{product_name_and_function}`.
* **1.3. Functional Unit**: Quantified performance of the product system (e.g.
'Provide X amount of torque for Y hours'
'Manufacture Z parts').
* **1.4. System Boundaries**: Detail what stages are INCLUDED and EXCLUDED (Cradle-to-Grave
Cradle-to-Gate
Gate-to-Gate). Justify exclusions.
* Raw Material Acquisition (based on `{bill_of_materials_csv}`).
* Manufacturing & Assembly (based on `{manufacturing_processes_overview_text}`).
* Distribution/Transportation.
* Use Phase (based on `{expected_use_phase_and_disposal_text}`).
* End-of-Life (Disposal/Recycling
based on `{expected_use_phase_and_disposal_text}`).
* **1.5. Allocation Procedures** (if dealing with multi-output processes or recycled content).
* **1.6. Impact Categories Selection**: (e.g.
Global Warming Potential (GWP
kg CO2 eq)
Acidification Potential
Eutrophication Potential
Ozone Depletion Potential
Smog Formation
Resource Depletion
Water Footprint). Select relevant categories for this product type.
* **1.7. LCA Methodology & Software/Databases**: (e.g.
CML
ReCiPe
TRACI. Mention common software like SimaPro
GaBi
openLCA
and databases like Ecoinvent).
**2. Life Cycle Inventory Analysis (LCI)**
* **2.1. Data Collection Plan**: For each life cycle stage:
* Identify required input data (energy
materials
water
transport) and output data (emissions
waste).
* Data sources (primary vs. secondary
from `{bill_of_materials_csv}`
literature
databases).
* **2.2. Data Quality Requirements** (e.g.
precision
completeness
representativeness).
**3. Life Cycle Impact Assessment (LCIA)**
* **3.1. Classification**: Assigning LCI results to selected impact categories.
* **3.2. Characterization**: Calculating category indicator results (e.g.
converting greenhouse gas emissions into CO2 equivalents).
* **3.3. Normalization (Optional)**: Expressing impact indicator results relative to a reference value.
* **3.4. Weighting (Optional
and to be used with caution)**: Assigning weights to different impact categories.
**4. Life Cycle Interpretation**
* **4.1. Identification of Significant Issues**: Hotspot analysis.
* **4.2. Evaluation**: Completeness
sensitivity
and consistency checks.
* **4.3. Conclusions
Limitations
and Recommendations for Mitigation** (e.g.
material substitution
process optimization
design for disassembly).
**IMPORTANT**: This outline should guide an engineer in planning a comprehensive LCA. Emphasize the iterative nature of LCA and the importance of data quality.
- Am besten geeignet für: Strukturierung der Umweltverträglichkeitsprüfung mechanischer Produkte über den gesamten Lebenszyklus, damit Ingenieure die Umweltauswirkungen systematisch bewerten und verringern können.
- Übersetzung und Sprachadaption
- Maschinenbau
AI Aufforderung an Mehrsprachiger Glossar-Generator
- Design für die Fertigung (DfM), Design Denken, Maschinenbau, Prozessverbesserung, Produktentwicklung, Projektmanagement, Qualitätsmanagement, Nachhaltigkeitspraktiken
Generiert ein Glossar mit vom Benutzer bereitgestellten Begriffen aus dem Maschinenbau in mehreren Zielsprachen. Dies hilft bei der Erstellung konsistenter mehrsprachiger Dokumentation und Kommunikation. Die Ausgabe erfolgt in Form eines CSV-formatierten Glossars.
Ausgabe:
- CSV
- erfordert kein Live-Internet
- Felder: {technical_terms_list_english_csv} {target_languages_iso_codes_csv}
Act as an Engineering Lexicographer and Terminology Specialist.
Your TASK is to create a multilingual glossary for a list of English mechanical engineering terms provided in `{technical_terms_list_english_csv}`
translating them into the languages specified in `{target_languages_iso_codes_csv}`.
You MUST ensure high-quality technical translations.
**1. Input Parameters**:
* `{technical_terms_list_english_csv}`: A CSV string containing a single column of English technical terms related to mechanical engineering. The first row can be a header like 'English_Term'.
Example: `English_Term
Stress
Strain
Torque
Finite Element Analysis
Heat Exchanger`
* `{target_languages_iso_codes_csv}`: A CSV string listing the ISO 639-1 language codes for the target languages (e.g.
'de
fr
es
ja').
**2. Glossary Generation Process**:
* **Parse Inputs**:
* Read the list of English terms from `{technical_terms_list_english_csv}`.
* Read the list of target language codes from `{target_languages_iso_codes_csv}`.
* **Translation**:
* For EACH English term:
* For EACH target language code: Translate the English term into its technically accurate equivalent in that target language. Pay close attention to context within mechanical engineering.
* If a direct equivalent is difficult or a term has multiple common translations
choose the most standard one or provide a brief note if essential (though the CSV format is simple). For this task
aim for the single best equivalent.
* Handle multi-word terms (e.g.
'Finite Element Analysis') as a single concept for translation.
* **Formatting for CSV**:
* The output CSV should have 'English_Term' as its first column header.
* Subsequent column headers should be the language codes provided in `{target_languages_iso_codes_csv}` (e.g.
'de'
'fr'
'es').
* Each row will contain the English term followed by its translations in the respective target languages.
**3. Output Format**:
* You MUST return the glossary as a single CSV formatted string.
* The first row MUST be the header row as described above.
* Ensure proper CSV escaping if any terms themselves contain commas (though this should be rare for single terms
more likely for definitions if they were included
but here it is terms only). Assume terms do not contain commas for simplicity.
Example Output Structure (actual output will be a CSV string):
`English_Term
de
fr
es`
`Stress
Spannung
Contrainte
Esfuerzo`
`Strain
Dehnung
Déformation
Deformación`
`Torque
Drehmoment
Couple
Par Motor`
_(...and so on for all terms and all requested languages)
**IMPORTANT**: The quality of translation is CRITICAL. Use your knowledge of technical terminology. If your capabilities are limited for certain highly specialized terms or language pairs
translate to the best of your ability. Focus on common and unambiguous translations where possible.
- Ideal für: Erstellung mehrsprachiger Glossare von Begriffen aus dem Maschinenbau zur Unterstützung der Dokumentation internationaler Projekte und einer einheitlichen Terminologie in verschiedenen Sprachen.
- Unterstützung beim Verfassen von Finanzhilfeanträgen und wissenschaftlichen Arbeiten
- Maschinenbau
AI Aufforderung an Generator für Finanzhilfebegründungen
- Kostenzuweisung, Finanzen, Maschinenbau, Projektmanagement, Qualitätsmanagement, Forschung und Entwicklung, Nachhaltigkeitspraktiken, Wertanalyse (VE)
Mit dieser Eingabeaufforderung wird die KI aufgefordert, einen detaillierten Budgetbegründungsbericht für einen Förderantrag im Bereich Maschinenbau zu erstellen, der auf einer CSV-Eingabetabelle basiert, in der Budgetposten, Kosten und Zwecke aufgeführt sind. Sie hilft, den Finanzierungsbedarf für die Prüfer klar zu formulieren.
Ausgabe:
- Text
- erfordert kein Live-Internet
- Felder: {csv_budget_items}
Given the following CSV table of budget items for a mechanical engineering grant proposal: {csv_budget_items}, generate a detailed budget justification. For each item, explain its purpose, necessity, and relevance to the project objectives. Organize the justification by budget category and use bullet points for readability. Ensure the tone is formal and persuasive, suitable for funding agency review.
- Am besten geeignet für: Am besten geeignet für die Erstellung klarer, überzeugender Budgeterklärungen zur Unterstützung von Finanzierungsanträgen
- Übersetzung und Sprachadaption
- Maschinenbau
AI Aufforderung an Anpassung von Patentansprüchen in einfacher Sprache
- Design für additive Fertigung (DfAM), Innovation, Geistiges Eigentum, Maschinenbau, Patent, Produktentwicklung, Qualitätsmanagement, Forschung und Entwicklung, Benutzerzentriertes Design
Schreibt einen formalen Patentanspruch in eine einfache Erklärung um, die für ein Publikum ohne juristisches oder tiefes technisches Fachwissen auf dem patentierten Gebiet verständlich ist. Dies hilft dabei, das Wesentliche einer Erfindung zu vermitteln. Die Ausgabe ist Text.
Ausgabe:
- Text
- erfordert kein Live-Internet
- Felder: {patent_claim_text} {Erfindung_Allgemeine_Beschreibung}
Act as a Patent Analyst with skills in technical communication.
Your TASK is to adapt the provided `{patent_claim_text}` into a plain language explanation. The explanation should be understandable to an audience described by `{invention_general_description}` which also provides context about the invention's field.
The goal is to convey the SCOPE and ESSENCE of what the claim protects
without using legal jargon or overly technical details from the claim itself unless explained.
**1. Input Details**:
* `{patent_claim_text}`: The full text of a single patent claim (typically Claim 1
or another independent claim). Patent claims have a very specific structure
preamble
transitional phrase like 'comprising'
and then a series of elements or limitations.
* `{invention_general_description}`: A brief description of what the invention is generally about and its intended audience for this explanation (e.g.
'This invention is a new type of bicycle braking system
explain for a product development team including marketing staff.' OR 'This is a software algorithm for optimizing CNC machining paths
explain for mechanical engineers not specialized in software patents.').
**2. Adaptation Process**:
* **Deconstruct the Claim**:
* Identify the PREAMBLE (what the invention IS
e.g.
'A system for...'
'A method of...').
* Identify the KEY ELEMENTS or steps listed after the transitional phrase (e.g.
'comprising:'
'consisting of:'). Each element defines a necessary part of the invention to be covered by the claim.
* Understand the RELATIONSHIPS between these elements.
* **Simplify Terminology**:
* Replace patent-specific legal jargon (e.g.
'wherein'
'said'
'means for') with plain language.
* Simplify overly technical terms if possible
using the `{invention_general_description}` to gauge appropriate vocabulary
or briefly explain them.
* **Explain the Scope**:
* Clearly articulate what combination of features or steps defines the invention according to that claim. Emphasize that ALL listed key elements must typically be present for something to fall under the claim.
* Use analogies or simple examples if they help clarify the inventive concept
drawing from the `{invention_general_description}`.
* **Focus on 'What it Does' and 'Key Unique Parts'**:
* Instead of just listing parts
explain their function or purpose within the invention
if clear from the claim.
* Highlight what seems to be the core inventive aspect or the main differentiators suggested by the claim's structure.
* **Structure for Clarity**:
* Use short sentences and paragraphs.
* Bullet points can be effective for listing the key components or features in plain language.
**3. Output Format**:
* The output MUST be a plain text explanation.
* It should start by stating what the invention generally is (drawing from the preamble and `{invention_general_description}`).
* Then
it should break down what the specific claim covers.
* It should NOT be a legal opinion
but an educational simplification.
Example (Conceptual Flow):
`This invention is about [general description from input].
Specifically
this patent claim describes a [preamble in simple terms] that includes several key parts working together:
* First
it has a [simplified element A] that does [function of A].
* Second
there's a [simplified element B]
which is connected to [element A or other part] and is responsible for [function of B].
* Finally
[simplified element C] ensures that [outcome or function of C].
To be covered by this particular claim
a system would need to have all these described features and connections.`
**IMPORTANT**: Maintain the technical and conceptual accuracy of the claim's scope. The simplification should not broaden or narrow the claim improperly
but make its existing scope understandable. Avoid offering any legal advice or infringement opinions.
- Am besten geeignet für: Erläuterung des Umfangs und des Wesens formaler Patentansprüche in einfacher Sprache für Maschinenbauingenieure oder Wirtschaftsbeteiligte, die sich nicht mit Patentrecht auskennen.
- Unterstützung beim Verfassen von Finanzhilfeanträgen und wissenschaftlichen Arbeiten
- Maschinenbau
AI Aufforderung an Generator für die Zusammenfassung der Literaturübersicht
- Design für additive Fertigung (DfAM), Optimierung des Designs, Maschinenbau, Prozessverbesserung, Qualitätsmanagement, Forschung und Entwicklung, Statistische Analyse, Nachhaltigkeitspraktiken
Mit dieser Aufforderung wird die KI angewiesen, eine Liste akademischer Arbeiten oder Artikel zu einem Thema des Maschinenbaus zusammenzufassen und zu synthetisieren, die als Liste von Titeln und Zusammenfassungen bereitgestellt wird. Es wird ein strukturierter Überblick über die Literatur erstellt.
Ausgabe:
- Markdown
- erfordert Live-Internet
- Felder: {list_of_papers}
You are given a list of academic papers related to the mechanical engineering topic: {list_of_papers}. For each paper, summarize the key findings, methodologies, and relevance. Then synthesize the information into a coherent literature review section highlighting gaps, trends, and consensus. Use markdown formatting with headings, bullet points, and italicized paper titles. Provide citations in a consistent style.
- Am besten geeignet für: Am besten geeignet für die schnelle Erstellung umfassender Literaturübersichten für Forschungsanträge
- Literaturübersicht und Trendanalyse
- Maschinenbau
AI Aufforderung an Literaturüberblick zu materiellen Fortschritten
- Additive Fertigung, Verbundwerkstoffe, Herstellung, Materialien, Maschinenbau, Mechanische Eigenschaften, Produktentwicklung, Forschung und Entwicklung, Nachhaltigkeitspraktiken
Fasst die jüngsten Fortschritte (in den letzten N Jahren) in einer bestimmten Werkstoffklasse zusammen und konzentriert sich auf deren Anwendung in einem bestimmten Bereich des Maschinenbaus. Es werden wichtige Forschungstrends und bahnbrechende Veröffentlichungen identifiziert. Die Ausgabe ist eine Zusammenfassung in Markdown-Form.
Ausgabe:
- Markdown
- erfordert Live-Internet
- Felder: {material_class_name} {application_area_focus} {Zeit_Zeitraum_Jahre}
Act as a Materials Science Research Analyst specializing in Mechanical Engineering applications.
Your TASK is to conduct a concise literature review summarizing recent advancements in `{material_class_name}` with a focus on their application in `{application_area_focus}` over the past `{time_period_years}` years.
You MUST use live internet access to gather information from scholarly articles
conference proceedings
and reputable technical sources.
**1. Search Strategy and Information Gathering**:
* Define search keywords based on `{material_class_name}` (e.g.
'High Entropy Alloys'
'Self-healing Polymers'
'Metal Matrix Composites'
'Biodegradable Magnesium Alloys')
`{application_area_focus}` (e.g.
'aerospace structural components'
'biomedical implants'
'automotive lightweighting'
'tribological coatings')
and terms like 'advancements'
'recent research'
'trends'
'review'.
* Query academic databases (like Google Scholar
Scopus
Web of Science if accessible through your tools) and leading publisher sites (e.g.
Elsevier
Springer
Wiley
Nature
Science).
* Filter results to the last `{time_period_years}` years.
* Prioritize review articles
highly cited research papers
and significant breakthrough reports.
**2. Analysis and Synthesis**:
* **Identify Key Advancements**: What are the most significant improvements or new discoveries related to `{material_class_name}` in the context of `{application_area_focus}`? This could include:
* New processing or manufacturing techniques.
* Improved mechanical properties (strength
toughness
fatigue resistance
wear resistance
etc.).
* Enhanced functional properties (e.g.
corrosion resistance
thermal stability
biocompatibility
self-healing capabilities).
* Novel compositions or microstructures.
* Successful application examples or case studies.
* **Identify Research Trends**: What are the current hot topics or directions in research for this material-application combination?
* **Key Researchers/Institutions (Optional
if prominent)**: Briefly mention any leading research groups if they consistently appear.
* **Seminal Publications (2-3 examples)**: Cite (author
year
title
journal if possible
or just a descriptive reference) a few highly impactful papers from the review period that exemplify these advancements.
**3. Output Format (Markdown)**:
* **Title**: Literature Review: Recent Advancements in `{material_class_name}` for `{application_area_focus}` (Last `{time_period_years}` Years).
* **1. Introduction**: Briefly introduce `{material_class_name}` and its importance in `{application_area_focus}`.
* **2. Key Advancements**: Use subheadings for different categories of advancements if logical
or a narrative style. Be specific and provide examples.
* **3. Current Research Trends**: Summarize the dominant research directions.
* **4. Notable Publications**: List 2-3 key papers as described above.
* **5. Challenges and Future Outlook**: Briefly discuss any remaining challenges or potential future developments.
* **6. Sources Consulted (General Statement)**: Indicate that the review is based on publicly available scholarly literature and state if specific databases were primarily used if known by your tools.
**IMPORTANT**: The summary should be concise yet informative
targeted at a mechanical engineer looking for an update on the topic. Ensure information is up-to-date by leveraging live internet search. Properly attribute information conceptually if not citing formally (e.g.
'Research indicates...'
'Studies have shown...').
- Am besten geeignet für: Maschinenbauingenieure erhalten einen zusammenfassenden Überblick über die jüngsten Fortschritte, Forschungstrends und Schlüsselpublikationen in einer bestimmten Werkstoffklasse, die für ihren Anwendungsbereich relevant ist.
- Literaturübersicht und Trendanalyse
- Maschinenbau
AI Aufforderung an Tool zur Identifizierung von Schlüsselpersonen in der Forschung
- Additive Fertigung, Design für additive Fertigung (DfAM), Technische Grundlagen, Maschinenbau, Produktentwicklung, Forschung und Entwicklung, Robotik, Nachhaltigkeitspraktiken
Identifiziert und listet wichtige Forscher oder Forschungsgruppen und die ihnen angeschlossenen Institutionen auf, die in einem Nischenthema des Maschinenbaus sehr aktiv sind. Dies hilft bei der Suche nach Experten für die Zusammenarbeit oder relevanter Literatur. Die Ausgabe ist eine CSV-Liste.
Ausgabe:
- CSV
- erfordert Live-Internet
- Felder: {niche_mechanical_engineering_topic} {number_of_results_desired}
Act as a Research Intelligence Analyst specializing in mapping expertise in engineering fields.
Your TASK is to identify key researchers (or research groups) and their institutions who are highly active and influential in the `{niche_mechanical_engineering_topic}`. You should aim to provide `{number_of_results_desired}` distinct entries.
You MUST use live internet access to query academic search engines
university research portals
and publication databases.
**1. Search and Identification Strategy**:
* Formulate targeted search queries using keywords derived from `{niche_mechanical_engineering_topic}` (e.g.
if topic is 'triboelectric nanogenerators for vibration energy harvesting'
use these terms plus 'researcher'
'professor'
'publications'
'lab').
* Utilize academic search engines (Google Scholar
Semantic Scholar
etc.) and potentially specific university/research institution websites.
* Look for indicators of significant contribution and activity:
* High number of relevant publications in reputable journals/conferences.
* High citation counts for relevant work.
* Principal Investigator (PI) status on relevant grants or projects.
* Keynote speaker invitations or leadership roles in relevant conferences/societies.
* Patents filed in the area.
* Prioritize individuals who have published consistently or significantly on the topic in recent years (e.g.
last 5-10 years).
**2. Data Extraction and Formatting**:
* For each identified key researcher/group
try to find:
* Full Name of the lead researcher (if an individual) or Research Group Name.
* Primary Affiliated Institution (University
Research Institute).
* Department or Lab (if readily available).
* A key publication or a very brief summary of their focus within the `{niche_mechanical_engineering_topic}` (e.g.
'Focus on material development for TENGs' or a specific highly cited paper title).
* (Optional but helpful) A URL to their official profile or lab page if easily found.
**3. Output Format (CSV)**:
* You MUST return the results as a single CSV string.
* The CSV header row MUST be: `Rank
Researcher_Or_Group_Name
Affiliated_Institution
Department_Or_Lab
Focus_Or_Key_Publication
Profile_URL`
* Populate the table with up to `{number_of_results_desired}` entries
ranked roughly by perceived influence or activity if possible (this is subjective
so best effort is fine
or simply list them). If ranking is hard
'Rank' can be a simple serial number.
* If some information (e.g.
Department
Profile_URL) is not easily found
leave that cell blank in the CSV row but maintain comma separators.
Example of a CSV row:
`1
Prof. John Doe
Massachusetts Institute of Technology
Dept. of Mechanical Engineering
Pioneering work on XYZ sensors
http://mit.edu/johndoe`
**IMPORTANT**: The quality of results depends on effective searching and interpretation of academic output. Prioritize relevance to the `{niche_mechanical_engineering_topic}`. State that the list is based on publicly available information accessed at the time of the query.
- Am besten geeignet für: Unterstützung von Maschinenbauingenieuren bei der Suche nach führenden Forschern und Institutionen in Nischenthemen für die Zusammenarbeit mit Experten oder die Suche nach Literatur.
- Literaturübersicht und Trendanalyse
- Maschinenbau
AI Aufforderung an Entwurfsmethodik Entwicklungsanalyse
- Agile Methodik, Kontinuierliche Verbesserung, Design für additive Fertigung (DfAM), Entwurf für Six Sigma (DfSS), Design Denken, Schlanke Fertigung, Produktentwicklung, Qualitätsmanagement
Analysiert und skizziert die historische Entwicklung, die wichtigsten Meilensteine und die aktuellen Trends einer bestimmten mechanischen Konstruktionsmethodik oder -philosophie. Dies hilft den Ingenieuren, den Kontext und die Fortschritte bei den Konstruktionsansätzen zu verstehen. Das Ergebnis ist ein Bericht oder eine Zeitleiste in Stichpunkten.
Ausgabe:
- Markdown
- erfordert Live-Internet
- Felder: {design_methodology_name} {approximate_start_year_or_era}
Act as an Engineering Design Historian and Theorist.
Your TASK is to analyze and outline the evolution of the mechanical design methodology known as `{design_methodology_name}`
starting from approximately `{approximate_start_year_or_era}` to the present day.
You should use live internet access to research its history
key proponents
seminal publications/tools
and current trends.
**1. Research and Information Gathering**:
* Use `{design_methodology_name}` (e.g.
'Design for Six Sigma (DFSS)'
'Axiomatic Design'
'TRIZ (Theory of Inventive Problem Solving)'
'Robust Design (Taguchi Methods)'
'Topology Optimization') and terms like 'history'
'evolution'
'key developments'
'timeline'
'impact' in your searches.
* Consult scholarly articles
books
historical accounts
and reputable engineering resources.
* Identify:
* Origins and foundational concepts/principles.
* Key individuals or organizations that developed or promoted the methodology.
* Significant milestones
publications
or software tools that marked turning points.
* How the methodology has been adapted or integrated with other approaches over time.
* Its impact on mechanical engineering practice.
* Current trends
criticisms
or areas of ongoing development related to it.
**2. Structuring the Analysis (Output as Markdown)**:
You can choose a chronological narrative or a timeline-based structure. Ensure the following aspects are covered:
* **Title**: The Evolution of `{design_methodology_name}` in Mechanical Engineering.
* **1. Introduction**: Briefly define `{design_methodology_name}` and state its core objectives.
* **2. Origins and Early Development (around `{approximate_start_year_or_era}` and following period)**:
* Describe the context or problems that led to its development.
* Mention key founders/pioneers and their initial contributions.
* **3. Key Milestones and Expansion**:
* Detail significant developments
theoretical refinements
or practical breakthroughs in chronological order or by thematic progression.
* Mention any influential books
papers
or case studies that popularized or validated the methodology.
* Discuss the development of associated tools or software
if applicable.
* **4. Mainstream Adoption and Impact**:
* When and how did it gain wider acceptance in industry and academia?
* What has been its primary impact on how mechanical design is approached or taught?
* **5. Current Status
Trends
and Criticisms**:
* How is `{design_methodology_name}` viewed or used today?
* Are there new interpretations
integrations with digital tools (e.g.
AI
MBSE)
or extensions of the methodology?
* Are there any common criticisms or limitations discussed in the literature?
* **6. Future Outlook**:
* Brief speculation on its future trajectory or relevance.
**IMPORTANT**: The analysis should be insightful and provide a good historical overview for a mechanical engineer. Focus on conceptual evolution and practical impact. Ensure information is corroborated from reliable sources accessed via the internet.
- Am besten geeignet für: Maschinenbauingenieure erhalten einen historischen Überblick und ein aktuelles Verständnis dafür, wie sich bestimmte Konstruktionsmethoden entwickelt und auf das Fachgebiet ausgewirkt haben.
- Literaturübersicht und Trendanalyse
- Maschinenbau
AI Aufforderung an Identifizierung von Wissenslücken anhand von Abstracts
- Additive Fertigung, Design für additive Fertigung (DfAM), Innovation, Maschinenbau, Prozessverbesserung, Qualitätsmanagement, Forschung und Entwicklung, Nachhaltigkeitspraktiken
Identifiziert potenzielle Wissenslücken oder Bereiche für künftige Forschung in einem bestimmten Bereich des Maschinenbaus durch die Analyse einer Sammlung aktueller Forschungszusammenfassungen. Dies hilft den Forschern, neue Forschungsfragen zu identifizieren. Die Ausgabe ist eine Markdown-Liste.
Ausgabe:
- Markdown
- erfordert kein Live-Internet
- Felder: {research_area_description_text} {Sammlung_von_Abstracts_text}
Act as a Research Strategist with expertise in identifying emerging research fronts in Mechanical Engineering.
Your TASK is to analyze a `{collection_of_abstracts_text}` from recent research within the `{research_area_description_text}` and identify potential knowledge gaps
unanswered questions
or underexplored aspects that could suggest avenues for future research.
**1. Input Processing**:
* `{research_area_description_text}`: A clear description of the specific field or sub-field of mechanical engineering (e.g.
'Additive Manufacturing of Nickel Superalloys for High-Temperature Applications'
'Vibration Damping using Metamaterials in Rotating Machinery'
'Machine Learning for Predictive Maintenance of Hydraulic Systems').
* `{collection_of_abstracts_text}`: A single block of text containing multiple research paper abstracts (e.g.
5-10 abstracts). Each abstract should be clearly demarcated if possible
or just concatenated.
**2. Analysis Methodology**:
* **Thematic Analysis**: Read through all abstracts to understand the main themes
methodologies
and findings being reported in the `{research_area_description_text}`.
* **Identify Common Focus Areas**: What specific problems
materials
techniques
or applications are frequently addressed?
* **Look for Limitations Stated**: Do any abstracts explicitly mention limitations of their own work
or suggest future work? These are direct pointers to gaps.
* **Note Unaddressed Intersections**: Are there logical connections between sub-topics that don't seem to be explored? (e.g.
if one abstract discusses material A for application X
and another discusses material B for application X
is the comparison between A and B for X a gap?).
* **Consider Unexplored Parameters or Conditions**: Are studies typically focused on a narrow range of conditions
materials
or scales? What happens outside these ranges?
* **Methodological Gaps**: Are certain advanced methodologies (e.g.
novel simulation techniques
AI/ML approaches
new experimental methods) not yet widely applied in this area despite potential benefits?
* **Contradictory or Inconclusive Findings**: Do any abstracts present conflicting results or highlight areas where findings are still inconclusive?
* **Assumptions and Simplifications**: What common assumptions are made that might not hold true in all scenarios
suggesting a need for more complex models or experiments?
**3. Output Format (Markdown)**:
* **Title**: Potential Knowledge Gaps and Future Research Directions in `{research_area_description_text}` (Based on Provided Abstracts).
* **1. Overview of Current Research Focus**: Briefly summarize the dominant themes identified in the provided abstracts.
* **2. Identified Potential Knowledge Gaps / Research Questions**: This is the main section. List each potential gap or research question as a clear
concise bullet point. For each point
briefly explain the reasoning based on your analysis of the abstracts. Examples:
* `* **The long-term performance of [Material X] under cyclic thermal loading combined with [Environmental Factor Y] appears underexplored.** While abstracts A and B discuss thermal performance
and abstract C mentions Factor Y independently
their combined effect is not addressed.`
* `* **Comparative analysis of [Technique 1] vs. [Technique 2] for achieving [Specific Outcome Z] is lacking.** Abstracts D and E advocate for different techniques but no direct comparison of efficacy or cost-effectiveness was found.`
* `* **Most studies focus on [Specific Scale/Condition A]
leaving a gap in understanding behavior at [Different Scale/Condition B].** This is evident as abstracts F
G
H all operate within Condition A.`
* **3. Concluding Remarks**: Briefly reiterate the value of exploring these gaps.
**IMPORTANT**: The identified gaps MUST be logically derived from the content of the `{collection_of_abstracts_text}` and the context of `{research_area_description_text}`. Avoid speculating wildly beyond the provided information. The output should stimulate critical thinking for new research.
- Am besten geeignet für: Unterstützung von Forschern bei der Identifizierung neuer Forschungsfragen und Wissenslücken in einem Teilbereich des Maschinenbaus durch Analyse von Trends und Einschränkungen in einer Sammlung aktueller Abstracts.
- Risikobewertung und Sicherheitsanalyse
- Maschinenbau
AI Aufforderung an FMEA-Tabellenerstellung für Teilsystem
- Design für die Fertigung (DfM), Design-Validierung, Fehlermöglichkeits- und Einflussanalyse (FMEA), Maschinenbau, Prozessverbesserung, Qualitätskontrolle, Qualitätsmanagement, Risikoanalyse, Risikomanagement
Erzeugt eine Vorlage für eine Fehlermöglichkeits- und Einflussanalyse (FMEA) für ein bestimmtes mechanisches Teilsystem, in der potenzielle Fehlermöglichkeiten und -effekte aufgelistet und erste Schweregrade für das Auftreten und die Erkennung empfohlen werden. Damit wird der Prozess der Risikobewertung in Gang gesetzt. Die Ausgabe ist eine CSV-Tabellenstruktur.
Ausgabe:
- CSV
- erfordert kein Live-Internet
- Felder: {subsystem_name_und_funktion} {key_components_list_csv} {operating_environment_description}
Act as a Reliability Engineer specializing in FMEA for Mechanical Systems.
Your TASK is to generate a structured FMEA table (as a CSV string) for the `{subsystem_name_and_function}`
considering its `{key_components_list_csv}` and `{operating_environment_description}`. You should populate the table with common
plausible failure modes
causes
and effects
and suggest initial placeholder RPN ratings or qualitative assessments.
**1. Input Analysis**:
* `{subsystem_name_and_function}`: Clear description (e.g.
'Fuel Pumping Unit for Diesel Engine - delivers pressurized fuel to injectors'
'Landing Gear Retraction Actuator - hydraulic cylinder that retracts/deploys landing gear').
* `{key_components_list_csv}`: CSV string listing major components within the subsystem (e.g.
'Pump_Housing
Electric_Motor
Impeller
Pressure_Regulator
Seals
Bearings').
* `{operating_environment_description}`: Details of operational context (e.g.
'Automotive under-hood
-40C to 120C
high vibration
exposure to fuel/oil'; 'Aerospace
high cycle fatigue
wide temperature range
safety-critical').
**2. FMEA Table Generation Logic**: For each key component in `{key_components_list_csv}` (or for the subsystem as a whole
focusing on its functions):
* **Identify Potential Failure Modes**: What are common ways this component or function can fail? (e.g.
For a pump: 'Fails to deliver pressure'
'Leaks'
'Noisy operation'
'Seizure'. For a motor: 'Fails to start'
'Overheats'
'Excessive vibration').
* **Identify Potential Causes**: For each failure mode
list plausible causes (e.g.
For pump 'Fails to deliver pressure': 'Impeller wear'
'Motor failure'
'Blocked inlet'
'Internal leakage'). Consider material degradation
wear and tear
manufacturing defects
operational errors
environmental factors from `{operating_environment_description}`.
* **Identify Potential Effects**: For each failure mode
what are the consequences on the subsystem
the larger system
and the end-user/environment? (e.g.
For pump 'Fails to deliver pressure': 'Engine stalls (system effect)'
'Vehicle stranded (end-user effect)'
'Loss of mission (aerospace context)').
* **Current Controls (Prevention/Detection)**: Suggest typical preventative controls (design features
manufacturing tests) or detection controls (sensors
inspection methods) that might be in place. If none obvious
state 'None Assumed' or 'To be determined'.
* **Assign Initial S-O-D Ratings (Severity
Occurrence
Detection)**: Use a 1-10 scale (10 being worst for S/O
10 being worst/hardest for D). These are INITIAL ESTIMATES to be reviewed by the engineering team.
* Severity (S): Based on the worst potential effect.
* Occurrence (O): Likelihood of the cause occurring. Consider `{operating_environment_description}`.
* Detection (D): Likelihood of detecting the cause or failure mode before it has a major effect
based on current controls.
* **Calculate RPN (Risk Priority Number)**: S x O x D.
* **Recommended Actions (Placeholder)**: Initially can be 'Investigate further'
'Consider design change'
'Improve detection method' or leave blank for team input.
**3. Output Format (CSV String)**:
* The CSV header MUST be: `Item_Or_Function
Potential_Failure_Mode
Potential_Effect_of_Failure
Severity_S
Potential_Cause_of_Failure
Occurrence_O
Current_Design_Controls_Prevention
Current_Design_Controls_Detection
Detection_D
RPN
Recommended_Actions`
* Each row will represent one failure mode.
* Example row snippet (conceptual):
`Electric_Motor
Fails_to_start
Subsystem_inoperable
Engine_does_not_start
Vehicle_stranded
8
Open_circuit_in_winding
Corrosion_due_to_environment
4
Visual_inspection_at_assembly
None_during_operation
7
224
Review_winding_protection
Consider_sealed_unit`
**IMPORTANT**: This FMEA is a STARTER TEMPLATE. The AI should populate it with plausible
common mechanical failure scenarios. The ratings are subjective and for initial discussion by the engineering team. Emphasize that this output needs thorough review and validation by experts familiar with the specific design.
- Am besten geeignet für: Rationalisierung des FMEA-Prozesses durch Generierung einer vorausgefüllten Tabelle mit potenziellen Fehlerarten, Ursachen, Auswirkungen und anfänglichen RPZ-Bewertungen für mechanische Teilsysteme.
Gehen wir davon aus, dass KI im Maschinenbau immer die besten Prompts generieren kann? Wie werden diese im Übrigen generiert?
Wird die KI menschliche Ingenieure überflüssig machen?
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