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Define the term 'prognosis' in the context of Industry 4.0.
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Prognosis in Industry 4.0 refers to using data science to predict future events and trends within industrial processes.
Why is an understanding of Python essential for this course?
Python is essential for coding, data set analysis, and completing assignments related to Industry 4.0 applications.
What is the role of 5G in Industry 4.0?
5G provides high-speed, low-latency communication essential for real-time data transfer and autonomous operations in industrial settings.
What future advancements are expected in the manufacturing business due to Industry 4.0?
Future advancements like 3D printing are expected to revolutionize business models and manufacturing processes.
What are the key elements covered in the lectures of this course?
Lectures cover theoretical aspects, business applications, and data science topics related to Industry 4.0.
What is 'Quality 4.0' and how is it utilized in Industry 4.0?
Quality 4.0 refers to real-time quality control using sensor data to ensure consistent product quality and efficiency.
What challenges might India face in adopting Industry 4.0 technologies?
Challenges could include infrastructure limitations, lack of skilled workforce, and economic constraints.
List the key pillars of Industry 4.0.
Digital transformation, 5G, and IIOT (Industrial Internet of Things).
Describe the difference between dynamic and static decision-making in the context of Industry 4.0.
Dynamic decisions are moment-specific, such as supply chain disruptions, while static decisions are long-term strategic choices like factory layout and facility location.
What are the prerequisites for enrolling in the Industry 4.0 elective course?
Basic understanding of AI, ML, statistics, and Python.
How does process control differ from machine control in Industry 4.0?
Process control involves managing industrial operations, while machine control focuses on the operation and coordination of machinery.
Explain the concept of inventory optimization in the context of Industry 4.0.
Inventory optimization involves using data-driven approaches to manage inventory efficiently, such as in retail or spare parts management.
What type of hands-on experience can be expected from the tutorials in this course?
Tutorials will include Python coding, data set analysis, and assignments focusing on Industry 4.0 applications.
What is the significance of data-driven decisions in Industry 4.0?
Data-driven decisions enable autonomous decision-making and enhance the efficiency and accuracy of industrial processes.
What is Logistics 4.0 and its significance in Industry 4.0?
Logistics 4.0 involves setting up optimal transportation networks and solving routing problems to improve logistics efficiency.
What role does machine learning play in dynamic pricing strategies in Industry 4.0?
Machine learning helps determine optimal pricing strategies by analyzing market data, demand trends, and competitor prices.
What is the main textbook for this course and who is the author?
The main textbook is 'Industry 4.0' by Bill Chris, published in 2016.
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