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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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- Analyse der Grundursache
- Maschinenbau
AI Aufforderung an Fishbone-Diagramm Eingaben für das Scheitern
- Kontinuierliche Verbesserung, Design für die Fertigung (DfM), Analyse des Versagens, Schlanke Fertigung, Maschinenbau, Prozessverbesserung, Qualitätsmanagement, Analyse der Grundursache, Sechs Sigma
Hilft bei der Strukturierung eines Fishbone-Diagramms (Ishikawa-Diagramm) für ein mechanisches Bauteilversagen, indem es potenziell beitragende Faktorkategorien (z. B. Mensch, Maschine, Material, Methode, Umwelt, Messung) und spezifische Fragen vorschlägt, die auf der Grundlage der Fehlerbeschreibung für jede Kategorie zu stellen sind. Diese Aufforderung erleichtert eine systematische Analyse der Fehlerursache. Die Ausgabe ist eine als Markdown formatierte Gliederung.
Ausgabe:
- Markdown
- erfordert kein Live-Internet
- Felder: {component_that_failed} {failure_mode_description} {operating_conditions_at_failure_text}
Act as a Root Cause Analysis (RCA) Facilitator.
Your TASK is to help structure a Fishbone (Ishikawa) Diagram to investigate the root cause of a failure involving `{component_that_failed}`.
The described failure is: `{failure_mode_description}`.
The failure occurred under these conditions: `{operating_conditions_at_failure_text}`.
You should propose key questions for standard Fishbone categories tailored to this mechanical failure context.
**FISHBONE DIAGRAM STRUCTURE INPUTS (MUST be Markdown format):**
**Problem Statement (Head of the Fish):** Failure of `{component_that_failed}`: `{failure_mode_description}`
**Main Bones (Categories) and Potential Contributing Factor Questions:**
**1. Machine (Equipment / Technology)**
* Was the `{component_that_failed}` the correct type/model/specification for the application?
* Was the equipment where `{component_that_failed}` is installed operating correctly before/during the failure? (e.g.
speed
load
pressure
temperature within design limits described in `{operating_conditions_at_failure_text}`?)
* Had there been any recent maintenance
repair
or modification to the machine or `{component_that_failed}`? Were procedures followed?
* Was auxiliary equipment (e.g.
cooling
lubrication
power supply) functioning correctly?
* Is there a history of similar failures with this machine or other similar machines?
* Could any tooling
fixtures
or associated parts have contributed to the failure of `{component_that_failed}`?
**2. Method (Process / Procedure)**
* Were correct operating procedures being followed when the failure occurred
considering `{operating_conditions_at_failure_text}`?
* Were installation or assembly procedures for `{component_that_failed}` followed correctly?
* Were maintenance procedures adequate and followed correctly for `{component_that_failed}` and related systems?
* Were there any recent changes in operating procedures
set-points
or work instructions?
* Was the system being operated outside of its design intent or capacity?
* Could any testing or quality control procedures related to `{component_that_failed}` have missed a defect?
**3. Material (Includes Raw Materials
Consumables
`{component_that_failed}` itself)**
* Was the `{component_that_failed}` made from the specified material? Was material certification available/correct?
* Could there have been a defect in the material of `{component_that_failed}` (e.g.
inclusions
porosity
incorrect heat treatment
flaws)?
* If consumables are involved (e.g.
lubricants
hydraulic fluids
coolants)
were they the correct type
clean
and at the correct level/condition?
* Has the `{component_that_failed}` been exposed to any corrosive or degrading substances not accounted for in its design?
* Could there have been issues with material handling or storage of `{component_that_failed}` before installation?
**4. Manpower (People / Personnel)**
* Was the operator/maintenance personnel adequately trained and qualified for the task they were performing related to `{component_that_failed}` or its system?
* Was there sufficient experience or supervision?
* Could human error (e.g.
misjudgment
incorrect assembly
misreading instructions
fatigue) have contributed?
* Were personnel following safety procedures? Were they rushed or under stress?
* Was there clear communication regarding operational or maintenance status?
**5. Measurement (Inspection / Instrumentation)**
* Were measuring instruments or sensors used to monitor `{operating_conditions_at_failure_text}` (e.g.
temperature
pressure
vibration
current) calibrated and functioning correctly?
* Were any warning signs or abnormal readings from instruments ignored or misinterpreted prior to the failure of `{component_that_failed}`?
* Were quality control checks or inspections of `{component_that_failed}` (pre-installation or during service) performed correctly and were the criteria appropriate?
* Could there be inaccuracies in the data used to assess the condition of `{component_that_failed}`?
**6. Environment (Operating Conditions / Surroundings)**
* Were the environmental conditions (temperature
humidity
cleanliness
vibration from external sources) as described in `{operating_conditions_at_failure_text}` within design limits for `{component_that_failed}`?
* Could any unusual environmental factors (e.g.
sudden impact
flooding
power surge
foreign object ingress) have contributed?
* Was the `{component_that_failed}` properly protected from the operating environment?
* Could long-term environmental exposure (e.g.
corrosion
UV degradation) have weakened `{component_that_failed}`?
**Instructions for User**: Use these questions as starting points to brainstorm specific potential causes under each category for the failure of `{component_that_failed}`. Further drill down with 'Why?' for each identified cause.
- Am besten geeignet für: Unterstützung von Maschinenbauingenieuren bei der systematischen Untersuchung von Komponentenfehlern durch Bereitstellung maßgeschneiderter Fragen für jede Kategorie eines Fishbone- (Ishikawa-) Diagramms.
- Ethische Erwägungen und Folgenanalyse
- Maschinenbau
AI Aufforderung an Ethischer Rahmen für autonome Maschinen
- Fortgeschrittene Fahrer-Assistenzsysteme (ADAS), Künstliche Intelligenz (KI), Autonomes Fahrzeug, Design Denken, Human-Centered Design, Risikomanagement, Robotik, Sicherheit
Schaffung eines Rahmens für ethische Überlegungen bei der Entwicklung autonomer mechanischer Systeme mit Schwerpunkt auf Sicherheitsverantwortung und Entscheidungsfindung in unvorhergesehenen Szenarien. Diese Aufforderung hilft Ingenieuren, ethische Herausforderungen während der Entwurfsphase komplexer Maschinen proaktiv anzugehen. Die Ausgabe ist ein strukturiertes Markdown-Dokument.
Ausgabe:
- Markdown
- erfordert kein Live-Internet
- Felder: {autonomes_system_type} {operational_environment_description} {key_decision_making_scenarios_csv}
Act as an Ethics Advisor specializing in AI and Autonomous Systems in Mechanical Engineering.
Your TASK is to generate a structured ethical framework for the development and deployment of an `{autonomous_system_type}` operating in `{operational_environment_description}`.
The framework should address key ethical principles and provide guidance for handling scenarios listed in `{key_decision_making_scenarios_csv}` (a CSV string like 'Scenario_ID
Description
Potential_Conflict
e.g. S1
Obstacle_Avoidance
Prioritize_occupant_safety_vs_pedestrian_safety').
**FRAMEWORK STRUCTURE (MUST be Markdown format):**
**1. Introduction**
* Purpose of the Ethical Framework for `{autonomous_system_type}`.
* Scope of application considering `{operational_environment_description}`.
**2. Core Ethical Principles** (Define and explain relevance for `{autonomous_system_type}`)
* **Safety & Non-Maleficence**: Minimizing harm.
* **Accountability & Responsibility**: Who is responsible in case of failure?
* **Transparency & Explainability**: How are decisions made by the system understandable?
* **Fairness & Non-Discrimination**: Avoiding bias in decision-making.
* **Privacy**: Data collection and usage.
* **Human Oversight**: Levels of human control and intervention.
**3. Guidelines for Decision-Making in Critical Scenarios**
* For EACH scenario provided in `{key_decision_making_scenarios_csv}`:
* **Scenario Analysis**: Briefly describe the ethical dilemma posed.
* **Primary Ethical Principle(s) at Stake**: Identify which of the above principles are most relevant.
* **Recommended Approach/Hierarchy**: Suggest a decision-making logic or prioritization. Clearly state any trade-offs.
* **Justification**: Explain the reasoning behind the recommended approach based on ethical principles.
**4. Design and Development Recommendations**
* Specific design considerations for `{autonomous_system_type}` to embed ethical behavior (e.g.
fail-safe mechanisms
auditable logs
bias testing).
**5. Operational and Deployment Considerations**
* Monitoring ethical performance post-deployment.
* Procedures for addressing ethical breaches or unforeseen negative consequences.
**IMPORTANT**: The framework should be actionable and provide clear guidance for engineers. The discussion of scenarios from `{key_decision_making_scenarios_csv}` is CRUCIAL.
- Am besten geeignet für: Proaktive Entwicklung ethischer Leitlinien für autonome mechanische Systeme, die den Ingenieuren helfen, komplexe moralische Entscheidungen bei Entwurf und Betrieb zu treffen.
- 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.
- Ethische Erwägungen und Folgenanalyse
- Maschinenbau
AI Aufforderung an Analyse der gesellschaftlichen Auswirkungen der Automatisierung
- Änderungsmanagement, Industrielle Automatisierung, Maschinenbau, Nachhaltigkeitspraktiken
Analysiert die potenziellen gesellschaftlichen Auswirkungen, wie z. B. Beschäftigungsverschiebungen, Veränderungen der Qualifikationsnachfrage und Fragen der Zugänglichkeit, die sich aus der Einführung einer bestimmten Automatisierungstechnologie in einem Maschinenbausektor ergeben. Diese Aufforderung hilft den Ingenieuren, weitergehende gesellschaftliche Konsequenzen zu berücksichtigen. Das Ergebnis ist ein textbasierter Bericht.
Ausgabe:
- Text
- erfordert Live-Internet
- Felder: {automation_technology_description} {industry_sector_of_application} {geographical_region_context}
Act as a Socio-Technical Analyst specializing in the impacts of automation in engineering fields.
Your TASK is to provide an analysis of the potential societal impacts of implementing `{automation_technology_description}` within the `{industry_sector_of_application}` specifically considering the `{geographical_region_context}`.
You SHOULD use live internet access to gather data on employment trends
skill demands
and relevant socio-economic studies for the specified region and sector.
**SOCIETAL IMPACT ANALYSIS REPORT (Plain Text Format):**
**1. Introduction**
* Overview of the `{automation_technology_description}` and its intended application in the `{industry_sector_of_application}`.
* Brief note on the socio-economic context of `{geographical_region_context}` relevant to automation.
**2. Potential Impacts on Employment**
* **Job Displacement**: Analyze potential for job losses in roles directly affected by the automation. Provide any available statistics or projections for the `{industry_sector_of_application}` in `{geographical_region_context}`.
* **Job Creation**: Analyze potential for new jobs created (e.g.
maintenance of automated systems
programming
data analysis
new roles enabled by the technology).
* **Job Transformation**: How existing roles might change
requiring new skills or responsibilities.
**3. Shifts in Skill Demand**
* **Upskilling/Reskilling Needs**: Identify skills that will become more critical (e.g.
digital literacy
robotics programming
data interpretation
complex problem-solving) and skills that may become obsolete.
* **Impact on Training and Education**: Discuss potential needs for changes in vocational training and engineering curricula in `{geographical_region_context}`.
**4. Economic Impacts**
* **Productivity Gains**: Potential for increased efficiency
output
and competitiveness in the `{industry_sector_of_application}`.
* **Investment Requirements**: Capital costs associated with implementing `{automation_technology_description}`.
* **Distribution of Economic Benefits**: Discuss who is likely to benefit most (e.g.
capital owners
highly skilled labor
consumers). Consider potential for increased inequality.
**5. Accessibility and Equity**
* **Impact on Small vs. Large Businesses**: Can businesses of all sizes in `{geographical_region_context}` adopt this technology
or does it favor larger enterprises?
* **Impact on Different Demographics**: Are there specific groups (e.g.
older workers
specific genders
minority groups) that might be disproportionately affected
positively or negatively?
* **Digital Divide**: Does the technology exacerbate or mitigate the digital divide within the region?
**6. Broader Societal and Ethical Considerations**
* **Worker Well-being**: Impact on job quality
stress levels
and workplace safety.
* **Social Acceptance and Resistance**: Potential for resistance to adoption from workers or the public.
* **Long-term Regional Development**: How might widespread adoption of this technology influence the economic trajectory of `{geographical_region_context}`?
**7. Policy Recommendations / Mitigation Strategies (Brief Suggestions)**
* Proactive measures that could be taken by policymakers
industry
or educational institutions in `{geographical_region_context}` to maximize benefits and mitigate negative impacts (e.g.
retraining programs
social safety nets
investment in education).
**8. Conclusion**
* Summary of key potential societal impacts and a call for responsible implementation.
**Disclaimer**: This analysis is based on publicly available information and general trends. Specific impacts can vary based on the details of implementation.
- Am besten geeignet für: Analyse potenzieller gesellschaftlicher Folgen der Automatisierung im Maschinenbau, wie z. B. Beschäftigungsverlagerungen und Qualifikationsbedarf, als Grundlage für eine verantwortungsvolle Technologieeinführung.
- Ethische Erwägungen und Folgenanalyse
- Maschinenbau
AI Aufforderung an Ethische Bewertung der Dual-Use-Technologie
- Additive Fertigung, Design für additive Fertigung (DfAM), Umweltauswirkungen, Maschinenbau, Risikomanagement, Nachhaltigkeitspraktiken
Führt eine vorläufige ethische Bewertung für eine Maschinentechnologie durch, die möglicherweise für Anwendungen mit doppeltem Verwendungszweck geeignet ist, und hebt dabei mögliche Risiken und ethische Dilemmata hervor und schlägt Schutzmaßnahmen vor. Diese Aufforderung zielt darauf ab, eine verantwortungsvolle Innovation zu fördern, indem unbeabsichtigte Folgen berücksichtigt werden. Das Ergebnis ist ein strukturierter Markdown-Bericht.
Ausgabe:
- Markdown
- erfordert kein Live-Internet
- Felder: {technology_description_and_capabilities} {intended_civilian_application} {potential_misuse_concerns_list_csv}
Act as an Ethics Reviewer specializing in dual-use technologies in engineering.
Your TASK is to conduct a preliminary ethical assessment of the `{technology_description_and_capabilities}`
considering its `{intended_civilian_application}` and the `{potential_misuse_concerns_list_csv}` (CSV string: 'Concern_ID
Description_of_Misuse
Potential_Harm_Level_High_Medium_Low').
**ETHICAL ASSESSMENT REPORT (MUST be Markdown format):**
**1. Technology Overview**
* Description of `{technology_description_and_capabilities}`.
* Stated `{intended_civilian_application}` and its potential benefits.
**2. Identification of Dual-Use Potential**
* Analysis of how the core capabilities of the technology could be diverted for harmful or unintended military/security purposes
drawing from `{potential_misuse_concerns_list_csv}`.
* For each concern in `{potential_misuse_concerns_list_csv}`
elaborate on the pathway from civilian application to potential misuse.
**3. Ethical Dilemmas and Concerns**
* **Responsibility of Innovators/Engineers**: Discuss the ethical obligations of those developing such technologies.
* **Risk of Unintended Escalation**: How could the technology contribute to instability or an arms race if misused?
* **Accessibility and Proliferation**: How easily could the technology or knowledge to replicate it spread to actors with malicious intent?
* **Difficulty in Control/Verification**: Once developed
how hard is it to monitor or control its use or prevent its misuse?
* **Impact on Human Rights**: Potential for the technology to be used in ways that violate human rights (e.g.
surveillance
autonomous weapons if applicable).
**4. Assessment of Potential Harms (based on `{potential_misuse_concerns_list_csv}`)**
* Summarize the potential severity and nature of harms associated with the identified misuses.
**5. Proposed Safeguards and Mitigation Strategies**
* **Technical Safeguards**: Are there ways to design the technology to make misuse more difficult (e.g.
built-in limitations
usage restrictions
tamper-proofing
tracking mechanisms)?
* **Policy and Regulatory Safeguards**: Suggestions for governance frameworks
export controls
international treaties
or ethical oversight bodies that could mitigate risks.
* **Transparency and Open Dialogue**: Importance of public discussion and engagement with policymakers and ethicists throughout the technology's lifecycle.
* **End-User Vetting and Agreements**: Potential for controlling distribution to responsible parties.
**6. Conclusion and Recommendation**
* Summarize the key ethical risks associated with the dual-use potential of `{technology_description_and_capabilities}`.
* Provide a concluding thought on whether development should proceed
and if so
under what ethical conditions or with what mandatory safeguards.
* Suggest if a more comprehensive ethical review by a dedicated committee is warranted.
**IMPORTANT**: This is a PRELIMINARY assessment. The aim is to raise awareness and stimulate deeper ethical reflection
not to provide a definitive judgment. Focus on balancing innovation with responsibility.
- Am besten geeignet für: Bewertung mechanischer Technologien mit doppeltem Verwendungszweck im Hinblick auf ethische Risiken und Missbrauchspotenzial, Anleitung von Ingenieuren zu verantwortungsvoller Innovation und Vorschlag von Schutzmaßnahmen.
- Optimierung der Versuchsplanung
- Maschinenbau
AI Aufforderung an Kritik am Versuchsplan und Verbesserungsvorschläge
- Entwurfsanalyse, Bewertung des Designs, Optimierung des Designs, Prozessverbesserung, Qualitätssicherung, Qualitätskontrolle, Statistische Analyse, Validierung
Diese Aufforderung fordert die KI auf, einen vorgegebenen Versuchsplan im Maschinenbau zu analysieren, Schwachstellen zu identifizieren und detaillierte Verbesserungen vorzuschlagen, um Validität, Zuverlässigkeit und Effizienz zu verbessern. Der Benutzer gibt die Beschreibung des Versuchsplans und die Schlüsselvariablen ein.
Ausgabe:
- Text
- erfordert kein Live-Internet
- Felder: {experimenteller_plan} {Schlüssel_Variablen}
Critically analyze the following mechanical engineering experimental plan: {experimental_plan}. Consider the key variables: {key_variables}. Identify potential flaws or limitations in design, controls, sample size, measurement methods, and data collection. Suggest specific improvements or alternative approaches to increase validity, reliability, and efficiency. Present your analysis in a numbered list with clear rationale for each suggestion.
- Am besten geeignet für: Am besten geeignet für die Optimierung von Versuchsaufbauten, um zuverlässigere und validere Ergebnisse zu erzielen
- Unterstützung beim Verfassen von Finanzhilfeanträgen und wissenschaftlichen Arbeiten
- Maschinenbau
AI Aufforderung an Entwurf des Abschnitts über die Bedeutung von Finanzhilfevorschlägen
- Additive Fertigung, Design für additive Fertigung (DfAM), Innovation, Maschinenbau, Produktentwicklung, Prototyping, Forschung und Entwicklung, Nachhaltigkeitspraktiken, Wert-Angebot
Entwirft die Abschnitte "Bedeutung" und "Innovation" für einen Förderantrag im Bereich Maschinenbau und hebt die Neuheit des Projekts, die Forschungslücke und die potenziellen Auswirkungen hervor. Diese Aufforderung hilft Ingenieuren, den Kernwert ihrer vorgeschlagenen Arbeit zu formulieren. Die Ausgabe ist ein mit Markdown formatierter Text.
Ausgabe:
- Markdown
- erfordert kein Live-Internet
- Felder: {project_title} {Forschungs_Problem_Aussage} {vorgeschlagene_Lösung_Zusammenfassung} {Schlüssel_innovative_Aspekte_liste_csv}
Act as a Scientific Writing Assistant specializing in engineering grant proposals.
Your TASK is to draft the 'Significance' and 'Innovation' sections (or a combined 'Significance and Innovation' section) for a grant proposal titled '`{project_title}`'.
The draft should clearly articulate the importance of the `{research_problem_statement}`
the novelty of the `{proposed_solution_summary}`
and the potential impact of the research
drawing upon the `{key_innovative_aspects_list_csv}` (CSV string: 'Aspect_ID
Description_of_Innovation').
**DRAFT SECTIONS (MUST be Markdown format):**
**`{project_title}`**
**Significance**
1. **Critical Need/Problem Statement**:
* Elaborate on the `{research_problem_statement}`. Clearly define the existing challenge
knowledge gap
or unmet need in the field of mechanical engineering that this project addresses.
* Explain the current limitations or drawbacks of existing approaches or technologies.
* Quantify the problem if possible (e.g.
'Current methods result in X% energy loss'
'Failures due to Y cost the industry $Z annually').
2. **Impact if Successful**:
* Describe the potential impact of successfully completing this project. How will the `{proposed_solution_summary}` advance scientific knowledge
technological capability
or address societal needs?
* Who will benefit from this research (e.g.
specific industries
researchers
society at large)?
* Discuss broader impacts
such as contributions to education
diversity
or economic development
if applicable.
3. **Relevance to Funder's Mission (Generic - user to tailor if funder is known)**:
* Briefly connect the project's goals to typical missions of funding agencies focused on scientific and technological advancement (e.g.
advancing fundamental knowledge
fostering innovation
enhancing national competitiveness
solving critical societal problems).
**Innovation**
1. **Novelty of Approach/Concept**:
* Clearly explain what is fundamentally new and innovative about the `{proposed_solution_summary}` and the project's overall approach.
* Refer to specific points from `{key_innovative_aspects_list_csv}`. For each innovative aspect:
* Describe the innovation in detail.
* Explain how it departs from or improves upon current paradigms
theories
methods
or technologies.
2. **Advancement Beyond Current State-of-the-Art**:
* Contrast the proposed work with existing methods
highlighting the advancements it offers.
* Why is this approach likely to be more effective
efficient
or transformative than current alternatives?
3. **Potential for Paradigm Shift (if applicable)**:
* If the project has the potential to significantly change the way research is conducted or problems are solved in this field
articulate this potential.
**Overall Summary of Significance and Innovation**:
* A brief concluding paragraph that powerfully reiterates why this project is important
innovative
and worthy of funding.
**IMPORTANT**: The tone should be persuasive
confident
and scholarly. Ensure clear connections between the problem
the proposed innovative solution
and the expected impact. Avoid jargon where possible or explain it.
- Ideal für: Unterstützung von Maschinenbauingenieuren bei der Abfassung überzeugender Abschnitte über Bedeutung und Innovation für Förderanträge, um den Wert und die Neuartigkeit der Forschung klar zu formulieren.
- Optimierung der Versuchsplanung
- Maschinenbau
AI Aufforderung an Generator für optimale Versuchsplanung
- Design für additive Fertigung (DfAM), Design für die Fertigung (DfM), Maschinenbau, Prozess-Optimierung, Qualitätssicherung, Qualitätskontrolle, Forschung und Entwicklung, Statistische Analyse
Diese Eingabeaufforderung weist die KI an, ein optimales Experiment zu entwerfen, um bestimmte Parameter des Maschinenbaus zu untersuchen. Der Benutzer gibt die Forschungsfrage, die zu prüfenden Variablen und die Beschränkungen an. Die KI gibt einen vollständigen Versuchsplan mit Kontrollgruppen, Stichprobengrößen und Messstrategien zurück.
Ausgabe:
- Markdown
- erfordert kein Live-Internet
- Felder: {Forschungsfrage} {Variablen} {Einschränkungen}
Design an optimal experimental plan for the mechanical engineering research question: {research_question}. The variables to be tested are: {variables}. Consider the following constraints: {constraints}. Provide a detailed plan including experimental setup, control groups, number of samples, measurement techniques, data collection methods, and statistical analysis approach. Format your response using markdown with sections and bullet points. Emphasize efficiency and validity in your design.
- Am besten geeignet für: Am besten für die Erstellung umfassender, statistisch fundierter Experimente im Maschinenbau
- Unterstützung beim Verfassen von Finanzhilfeanträgen und wissenschaftlichen Arbeiten
- Maschinenbau
AI Aufforderung an Generator für die Zusammenfassung technischer Berichte
- Kontinuierliche Verbesserung, Design für additive Fertigung (DfAM), Maschinenbau, Methodik, Prozessverbesserung, Projektmanagement, Qualitätsmanagement, Forschung und Entwicklung, Nachhaltigkeitspraktiken
Erzeugt eine prägnante und informative Zusammenfassung für einen technischen Bericht auf der Grundlage der wichtigsten Abschnitte des Berichts. Diese Eingabeaufforderung hilft Ingenieuren, ihre Arbeit schnell zusammenzufassen, um sie weiter zu verbreiten. Die Ausgabe ist eine einfache Textzusammenfassung.
Ausgabe:
- Text
- erfordert kein Live-Internet
- Felder: {Bericht_Titel} {project_objectives_summary} {methodologie_verwendet_zusammenfassung} {Schlüssel_Ergebnisse_und_Schlussfolgerungen_Zusammenfassung}
Act as a Technical Editor specializing in engineering reports.
Your TASK is to generate a concise and informative abstract for a technical report titled '`{report_title}`'.
The abstract should be based on the following summaries provided by the user:
* `{project_objectives_summary}`: A brief statement of the project's goals.
* `{methodology_used_summary}`: A concise description of the methods
tools
or approaches employed.
* `{key_results_and_conclusions_summary}`: A summary of the most important findings and the main conclusions drawn from the project.
**ABSTRACT GENERATION GUIDELINES:**
The abstract MUST be a single paragraph
typically between 150-250 words (though this is a guideline
quality over strict length).
It should be structured to include the following elements seamlessly:
1. **Background/Purpose (derived from `{project_objectives_summary}` and `{report_title}`):**
* Start with a sentence or two that introduces the context or purpose of the work described in '`{report_title}`' and its main objectives from `{project_objectives_summary}`.
2. **Methodology (derived from `{methodology_used_summary}`):**
* Briefly describe the key methods
experimental procedures
simulation techniques
or analytical approaches used
as outlined in `{methodology_used_summary}`. Avoid excessive detail; focus on what was done.
3. **Key Results (derived from `{key_results_and_conclusions_summary}`):**
* Highlight the most significant findings or outcomes of the project. Quantify results where possible and impactful (e.g.
'a 25% improvement in efficiency was observed'
'the material exhibited a tensile strength of X MPa').
4. **Main Conclusions (derived from `{key_results_and_conclusions_summary}`):**
* State the primary conclusions drawn from the results. What is the overall significance of the findings?
5. **Keywords (Optional but Recommended - AI to suggest 3-5 based on content):**
* If appropriate
the AI can suggest a few keywords at the end of the abstract text
prefixed with 'Keywords:'. This is a secondary task.
**Output Format:**
Plain text
suitable for direct inclusion in a technical report.
**Example Abstract Structure (Conceptual):**
`This report
'`{report_title}`'
details an investigation aimed at [paraphrase/combine from `{project_objectives_summary}`]. The study employed [summarize from `{methodology_used_summary}`
e.g.
'a combination of finite element analysis and experimental validation' or 'a novel design algorithm']. Key findings indicate [summarize key quantitative or qualitative results from `{key_results_and_conclusions_summary}`]. It was concluded that [summarize main conclusions from `{key_results_and_conclusions_summary}`
highlighting significance].`
`Keywords: [Suggested Keyword1
Suggested Keyword2
Suggested Keyword3]`
**IMPORTANT**: The abstract MUST be self-contained and understandable without reference to the full report. It should be accurate
concise
and highlight the most compelling aspects of the work. Avoid using jargon that isn't commonly understood or defined within the abstract's context.
- Ideal für: Erstellung prägnanter und gut strukturierter Zusammenfassungen für technische Berichte, die Maschinenbauern helfen, Projektziele, Methoden, Ergebnisse und Schlussfolgerungen effizient zusammenzufassen.
- Optimierung der Versuchsplanung
- Maschinenbau
AI Aufforderung an Statistische Leistungsanalyse für Experimente
- Entwurf für Six Sigma (DfSS), Prozessverbesserung, Prozess-Optimierung, Qualitätssicherung, Qualitätskontrolle, Statistische Analyse, Statistische Prozesskontrolle (SPC), Statistische Tests, Validierung
Diese Aufforderung fordert die KI auf, eine statistische Power-Analyse für ein Maschinenbauexperiment auf der Grundlage von Eingabeparametern wie Effektgröße, Stichprobengröße und Signifikanzniveau durchzuführen. Sie hilft festzustellen, ob das Experiment ausreichend leistungsfähig ist.
Ausgabe:
- Text
- erfordert kein Live-Internet
- Felder: {effect_size} {sample_size} {significance_level}
Perform a statistical power analysis for a mechanical engineering experiment with the following parameters: Effect Size: {effect_size}, Sample Size: {sample_size}, Significance Level (alpha): {significance_level}. Calculate the statistical power and interpret whether the current design is adequate. If underpowered, suggest adjustments to sample size or effect size. Present calculations step-by-step and summarize the conclusion clearly.
- Am besten geeignet für: Am besten geeignet für die Validierung von Versuchsplänen durch Leistungsberechnungen
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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