INS3705
Assignment 2 Semester 2 2024
Detailed Solutions, References & Explanations
Unique number:
Due Date: 2024
QUESTION 1 (2 ANSWERS PROVIDED)
Knowledge Management Processes at Eskom
1. Knowledge Creation Purpose: The purpose of knowledge creation at Eskom, South Africa's
primary electricity supplier, is to generate new insights, innovative solutions, and advancements
in power generation, distribution, and management. This process involves transforming tacit
knowledge, such as the expertise of engineers and technicians, into explicit knowledge that can
be documented and shared across the organization. This is crucial for improving operational
efficiency, ensuring safety, and developing sustainable energy solutions.
Examples of AI Technologies:
• Machine Learning Algorithms: These can analyze vast amounts of operational data
from power plants to identify patterns and predict equipment failures, thereby facilitating
the creation of new knowledge on maintenance and operational efficiency.
Terms of use
By making use of this document you agree to:
• Use this document as a guide for learning, comparison and reference purpose,
• Not to duplicate, reproduce and/or misrepresent the contents of this document as your own work,
• Fully accept the consequences should you plagiarise or misuse this document.
Disclaimer
Extreme care has been used to create this document, however the contents are provided “as is” without
any representations or warranties, express or implied. The author assumes no liability as a result of
reliance and use of the contents of this document. This document is to be used for comparison, research
and reference purposes ONLY. No part of this document may be reproduced, resold or transmitted in any
form or by any means.
Assignment 2 Semester 2 2024
Detailed Solutions, References & Explanations
Unique number:
Due Date: 2024
QUESTION 1 (2 ANSWERS PROVIDED)
Knowledge Management Processes at Eskom
1. Knowledge Creation Purpose: The purpose of knowledge creation at Eskom, South Africa's
primary electricity supplier, is to generate new insights, innovative solutions, and advancements
in power generation, distribution, and management. This process involves transforming tacit
knowledge, such as the expertise of engineers and technicians, into explicit knowledge that can
be documented and shared across the organization. This is crucial for improving operational
efficiency, ensuring safety, and developing sustainable energy solutions.
Examples of AI Technologies:
• Machine Learning Algorithms: These can analyze vast amounts of operational data
from power plants to identify patterns and predict equipment failures, thereby facilitating
the creation of new knowledge on maintenance and operational efficiency.
Terms of use
By making use of this document you agree to:
• Use this document as a guide for learning, comparison and reference purpose,
• Not to duplicate, reproduce and/or misrepresent the contents of this document as your own work,
• Fully accept the consequences should you plagiarise or misuse this document.
Disclaimer
Extreme care has been used to create this document, however the contents are provided “as is” without
any representations or warranties, express or implied. The author assumes no liability as a result of
reliance and use of the contents of this document. This document is to be used for comparison, research
and reference purposes ONLY. No part of this document may be reproduced, resold or transmitted in any
form or by any means.
