Knowledge Based Engineering
Knowledge Based Engineering
is contribution to
The Sustainable Development Goals
Goal 4: Quality Education:
Discover how Knowledge Based Engineering promotes equal education by optimising and ensuring access for all, including vulnerable populations.
Investigate how Industry Knowledge Management and Agile Knowledge Management contribute to equal education by facilitating efficient knowledge systems, enabling informed decision-making and eco-conscious practices accessible to all, including vulnerable populations.
Goal 8 : Decent Work and Economic Growth:
Analyse how Knowledge Based Engineering creates fair job opportunities by optimizing manufacturing for sustainable production, supporting economic growth and job creation for all
Investigate how Industry Knowledge Management and Agile Knowledge Management contribute to fair job opportunities by enhancing sustainability efforts, facilitating efficient knowledge systems and informed decision-making, thereby supporting economic growth and job creation.
Goal 9: Industry, Innovation, and Infrastructure:
Discover how Knowledge Based Engineering drives Sustainable Industrialisation by optimising manufacturing for eco-friendly production through design automation and informed decision-making.
Investigate how Industry Knowledge Management and Agile Knowledge Management promote Sustainable Industrialisation by facilitating efficient data systems and informed decision-making, supporting eco-conscious design practices within industrial operations.
Goal 12 : Responsible Consumption and Production:
Delve into how Knowledge Based Engineering aligns with global collaborations for sustainable development by optimising manufacturing processes for eco-friendly production through design automation and informed decision-making.
Explore how Industry Knowledge Management and Agile Knowledge Management contribute to international efforts for sustainable development by facilitating efficient data systems and promoting informed decision-making, thereby enhancing eco-conscious design practices in industries worldwide.
Goal 16 : Peace, Justice and Strong Institutions:
Learn how Knowledge Based Engineering optimises manufacturing for eco-friendly production, enhancing social welfare and justice access, and fostering global sustainable development goals
See how Industry Knowledge Management and Agile Knowledge Management advance sustainability through efficient data systems and informed decision-making, promoting social welfare and accountable governance.
Goal 17: Partnerships for the Goals:
Discover how Knowledge Based Engineering drives sustainability by integrating design automation and knowledge-based decision-making, optimising manufacturing for eco-friendly production.
Investigate how Industry Knowledge Management and Agile Knowledge Management enhance sustainability by facilitating efficient data systems, promoting informed decision-making and eco-conscious design practices.
Who Can Join
Research Scholars
Technology Experts
Students & Alumini’s
Editorial Board Members of Journals
Government Officials
Industry Professionals
Knowledge Based Engineering
Tracks:
1 Data, Information and Knowledge Systems
2 Design Automation
3 Design for Manufacturing
4 Industry Knowledge Management
5 Knowledge Based Decision Making
6 Agile Knowledge Management
Author Guidelines
Guidelines for Abstract Submission:
- Language: Abstracts must be written in English.
- Length: Limited to one paragraph with 200-250 words.
- Format: Submit in MS Word (.doc or .docx) document format.
- Content: Abstracts should provide an informative summary of the original work. Include a brief biography with your abstract, following the example provided in the template.
- Formatting: Center-align the Title, Author's Names, and Affiliations. Underline the presenting author's name.
- Submission: Please submit your abstract through the designated submission portal.
- Acknowledgment: Upon abstract submission, you will receive an acknowledgment email within three working days.
Evaluation Process
Guidelines for Full Paper Submission
If your abstract has been accepted and the registration fee for LASMCER-2024 has been paid, you are invited to submit the full paper. Please adhere to the following guidelines for the submission:
- Total number of pages: 6-8 in double-column format
- Language: English (checked for grammar and language errors)
- Tables, figures, and images should be properly named and of high quality.
- Keywords should be written in lowercase letters (except for names/scientific names) and separated by commas.
- Affiliation names, including the country, must be provided.
- Each paper should be structured into the following sections:
- Background, Motivation, and Objective
- Statement of Contribution/Methods
- Results, Discussions, and Conclusions
Once your full paper is prepared according to the above instructions, please proceed to submit it through the provided link. Submit your Full paper Here.
Session Lists
PEER-REVIEWED GOOGLE SCHOLAR INDEXED JOURNAL
Computational Intelligence And Machine Learning
ISSN: 2582-7464
TechnoareteTransactions on Intelligent Data Mining and Knowledge Discovery
ISSN: 2583-195X