Evaluate whether a productivity improvement is truly beneficial when equipment wear, maintenance, downtime, throughput, revenue, and reliability are considered together.
Work toward the lesson goal: Optimization Impact Study. Use the directions and success criteria in the activity below.
Materials
For the online work: a browser and your engineering notebook. Follow the activity’s materials list for any physical build, and get teacher approval before using equipment.
Plan your time
Suggested work block: 45–60 minutes. Physical builds and projects may span several classes; follow your teacher’s schedule.
Learning Targets
By the end of this lesson
Evaluate a preventive-maintenance schedule using operational data.
Compare system behavior before and after a productivity optimization.
Calculate maintenance cost, downtime cost, and production value.
Create data visualizations and defend an engineering recommendation.
Equipment & Systems
What you will use
Optimization Impact Study data set
Spreadsheet software
Data-visualization tools
Maintenance schedule and cost information
Student Workflow
What You Will Do
Analyze the baseline crystal-puller data and identify normal ranges, maintenance events, and warning patterns.
Evaluate whether the preventive-maintenance schedule is appropriate.
Analyze the post-optimization data and compare wear, yield, throughput, and failure indicators.
Calculate relevant maintenance, downtime, and production values.
Create at least one useful visualization and develop a predictive-maintenance recommendation.
Decide whether the optimization should be adopted and defend the decision with evidence.
Programming Focus
How coding supports the lesson
This project is primarily a spreadsheet and data-analysis task. Use AI tools only as directed by your instructor; calculations, visualizations, and recommendations must be supported by the data.
What You Will Submit
What You Submit
Completed before / after data analysis
Cost, downtime, throughput, and yield calculations
At least one decision-support visualization
Predictive-maintenance recommendation
Final adopt / do-not-adopt engineering recommendation
