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Course Description

Prompt

Analyze the course description at 01-course-description.md and rewrite it using the 2001 Bloom’s Taxonomy.

The six levels are:

  1. remember
  2. understand
  3. apply
  4. analyze
  5. evaluate
  6. create

Response

I'll rewrite the course description using Bloom's Taxonomy to structure the learning objectives and course content. This will help align the curriculum with recognized educational standards for cognitive development.

Advanced Fluid Power Systems: AI, Controls, and Sustainable Design

Course Description

This course equips technicians with skills to install, maintain, and optimize fluid power systems (HVAC, vacuum, compressed air, cooling water, dust collection, hydraulics, pumping, and fans) while leveraging artificial intelligence (AI), advanced controls, data collection, and software tools. Students will progress through all six levels of Bloom's Taxonomy, developing cognitive skills from basic recall to complex creation of optimized systems. Through hands-on labs, software simulations, and real-world scenarios, students will prepare for roles in smart, eco-conscious industries.

Learning Objectives

By the end of the course, students will be able to:

Remember - Identify the major components of fluid power systems - Recall safety protocols for working with high-pressure systems - List industry standards relevant to fluid power systems - Identify basic AI and control system components

Understand - Explain the principles of operation for various fluid power systems - Describe how AI uses historical data to predict system issues - Interpret data from sensors and monitoring systems - Explain the relationship between system adjustments and energy efficiency

Apply - Install and connect system components according to specifications - Deploy software tools for system monitoring and maintenance - Implement AI-driven controls to optimize system performance - Apply troubleshooting procedures to identify system issues

Analyze - Diagnose complex system problems using data-driven approaches - Differentiate between mechanical, electrical, and control-related issues - Examine sensor data to determine system efficiency and health - Compare traditional and AI-enhanced maintenance approaches

Evaluate - Assess system performance against industry benchmarks - Justify maintenance decisions based on data analysis - Critique system designs for labor efficiency and sustainability - Determine optimal settings for energy conservation

Create - Design integrated fluid power systems with AI and control elements - Develop custom monitoring solutions for specific applications - Construct sustainable system upgrades that reduce resource consumption - Formulate predictive maintenance schedules based on AI analysis

Prerequisites

  • Basic mechanical aptitude (familiarity with tools and equipment)
  • High school-level math (algebra and measurements)
  • Basic computer skills (e.g., using apps or spreadsheets)
  • No prior engineering or AI knowledge required

Course Outline

Week 1: Introduction to Fluid Power Systems and AI

Remember - Identify core fluid power system types and components - Recognize the role of AI in modern industrial systems

Understand - Describe the basic principles of fluids (water, oil, air) - Explain how AI uses historical data for prediction

Apply - Use basic monitoring tools to observe system behavior

Lab: Explore a fluid power system and a demo AI dashboard

Week 2: System Components and Smart Controls

Remember - Identify pumps, fans, compressors, valves, and filters - Recall sensor types and their functions

Understand - Explain component relationships within systems - Describe how sensors collect real-time performance data

Apply - Connect sensors to system components - Interpret basic sensor readings

Lab: Disassemble a pump, connect a sensor, and view data on a tablet/app

Week 3: HVAC Systems with AI Optimization

Remember - Identify HVAC system components - List common HVAC maintenance tasks

Understand - Explain airflow, cooling, and heating principles - Describe how AI optimizes HVAC operations

Apply - Perform basic HVAC maintenance procedures - Use AI tools to adjust system settings

Analyze - Examine energy consumption patterns

Lab: Service an HVAC unit and use an AI tool to adjust settings

Week 4: Vacuum Systems and Data-Driven Maintenance

Remember - Identify vacuum system components - Recall common vacuum system issues

Understand - Explain vacuum principles and industrial applications - Describe how AI analyzes pressure data

Apply - Test seals and detect leaks - Implement maintenance based on AI recommendations

Analyze - Diagnose vacuum system inefficiencies using data

Lab: Test a vacuum system and interpret AI-generated maintenance alerts

Week 5: Compressed Air Systems and Efficiency

Remember - Identify compressor types and components - List common air leak sources

Understand - Explain pressure regulation principles - Describe how sensors detect compressed air leaks

Apply - Set up compressors and maintain air lines - Use AI tools to locate system leaks

Analyze - Analyze pressure data to identify system inefficiencies

Evaluate - Justify repair priorities based on data analysis

Lab: Troubleshoot an air system with an AI diagnostic tool

Week 6: Cooling Water Systems and Smart Monitoring

Remember - Identify cooling system components - Recognize signs of corrosion and scaling

Understand - Explain heat transfer principles in cooling systems - Describe how IoT sensors track water quality

Apply - Perform cooling tower inspection and cleaning - Deploy water quality monitoring systems

Analyze - Interpret water quality data to predict system issues

Evaluate - Assess system efficiency against benchmarks

Lab: Inspect a cooling system and use software to analyze water data

Week 7: Dust Collection Systems and Automation

Remember - Identify dust collection system components - Recall safety protocols for combustible dust

Understand - Explain airflow principles in dust collection - Describe automated filter cleaning processes

Apply - Maintain fans, filters, and ductwork - Implement AI controls for system operation

Analyze - Analyze airflow data to optimize system performance

Evaluate - Assess safety compliance of system operations

Lab: Service a dust collector and adjust settings via a control panel

Week 8: Hydraulic Systems and Predictive Maintenance

Remember - Identify hydraulic system components - Recall fluid types and specifications

Understand - Explain hydraulic pressure principles - Describe how AI predicts component wear

Apply - Perform fluid checks and seal replacements - Implement predictive maintenance schedules

Analyze - Diagnose hydraulic system issues using data patterns

Evaluate - Justify fluid selection based on environmental impact

Lab: Service a hydraulic cylinder and review AI maintenance logs

Week 9: Pumping Systems and Real-Time Controls

Remember - Identify pump types and components - Recognize signs of cavitation

Understand - Explain flow and pressure relationships - Describe how AI optimizes pump speed

Apply - Install and align pumps properly - Implement real-time monitoring solutions

Analyze - Analyze flow data to identify inefficiencies

Evaluate - Assess pump performance against specifications

Create - Develop custom pump control parameters

Lab: Install a pump and use a control app to adjust flow

Week 10: Fan Systems and Smart Integration

Remember - Identify fan types and components - Recall noise reduction techniques

Understand - Explain fan laws and vibration principles - Describe how AI analyzes vibration data

Apply - Perform belt replacement and blade inspection - Deploy vibration monitoring systems

Analyze - Diagnose balance issues through data analysis

Evaluate - Assess energy efficiency of fan operations

Create - Design noise reduction solutions

Lab: Balance a fan and use software to monitor performance

Week 11: System Optimization and Software Deployment

Remember - Recall system integration principles - Identify software tools for system monitoring

Understand - Explain how AI combines historical and live data - Describe lifecycle analysis concepts

Apply - Deploy SCADA and CMMS software - Implement optimization techniques

Analyze - Examine system interactions to identify inefficiencies

Evaluate - Assess labor utilization and energy consumption

Create - Develop integrated monitoring dashboards

Lab: Optimize a mixed system using AI software and controls

Week 12: Safety, Standards, Sustainability, and Final Project

Remember - Recall industry standards and regulations - Identify green certification requirements

Understand - Explain compliance monitoring principles - Describe sustainability metrics

Apply - Implement safety protocols in system operations - Deploy compliance tracking tools

Analyze - Examine systems for compliance gaps

Evaluate - Assess overall system sustainability

Create - Design and optimize a complete fluid power system using AI tools - Create a comprehensive maintenance plan integrating all course concepts

Final Project: Design and optimize a fluid power system using AI tools, controls, and data collection; present labor and sustainability benefits

Assessment and Grading

  • Class Participation and Labs: 25%
  • Weekly Hands-On and Software Assignments: 25%
  • AI and Controls Exercises: 20% (e.g., using monitoring apps or dashboards)
  • Final Project: 20% (system design with AI/controls integration)
  • Final Skills Test: 10% (troubleshoot with AI and control tools)

Required Materials

  • Textbook: Fluid Power Basics by Jay F. Hooper (or similar technician guide)
  • PPE: safety glasses, gloves, ear protection
  • Basic toolkit: wrenches, screwdrivers, multimeter
  • Access to AI-enabled software (e.g., free CMMS apps, IoT demo tools, or instructor-provided platforms)
  • Tablet or laptop for accessing control dashboards (optional, provided by program if needed)

Bloom's Taxonomy Integration Benefits

This revised course structure explicitly integrates all levels of Bloom's Taxonomy:

  • Remember and Understand: Foundation phases build knowledge of components, principles, and terminology
  • Apply: Hands-on labs and software deployment develop practical skills
  • Analyze: Data interpretation activities build diagnostic abilities
  • Evaluate: Performance assessment exercises develop critical thinking about system efficiency
  • Create: The final project and optimization exercises cultivate design thinking and innovation

By progressing through these cognitive levels, students develop both technical competence and higher-order thinking skills essential for adapting to evolving technologies in the fluid power industry.