Assessment of LP Theoretical background of using AI in process preparation and evaluation

Learning outcomes

1. The learner compares and contrasts different AI approaches and selects the most suitable approach for machining process planning and evaluation. They justify their selection based on the specific requirements and characteristics of the machining domain. In addition, they provide a comprehensive explanation of the chosen approach, considering its benefits and limitations after completing this lesson.
2. The learner demonstrates proficiency in each stage of the creation of AI models for machining. They accurately describe and apply the step-by-step procedure, including data acquisition, signal processing, feature extraction and selection, and data structure design. They select and utilize appropriate methods and techniques at each stage to create an effective AI model for the planning and evaluation of the machining process after completing this lesson.
3. The learner explains the fundamental functionality of the AI model used in the planning and evaluation of the machining process. They interpret the results generated by the AI model considering its limitations and potential biases. They articulate the implications and practical significance of the AI model's outputs and provide insights into its usage in the machining domain after completing this lesson.