Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Manufacturing • 22 CNC Machines

Case Study 48: Machine Shop

Marketing-optimized case study for Canadian SMBs.

$164,000
Annual Savings
380%
ROI
3.8 months
Payback
Manufacturing • 22 CNC Machines
Industry Focus

Executive Summary

Quote Automation: AI analyzes CAD files (STEP, IGES) to extract features, calculate material needs, estimate machining time, and generate quotes. 93% accuracy.

Challenge

Solution

  • Quote Automation: AI analyzes CAD files (STEP, IGES) to extract features, calculate material needs, estimate machining time, and generate quotes. 93% accuracy.
  • Job Scheduling: Optimization algorithm schedules jobs across machines considering setup time, material availability, due dates, and machine capabilities.
  • Quality Prediction: ML analyzes machine data (feed rate, vibration, tool wear) to predict when parts may fall out of tolerance. Prevents scrap.

Technical Stack

Key Metrics

2.5
Quote turnaround reduced from 2.5 days to 2 hours
64%
Machine utilization increased from 64% to 81%
2.4%
Scrap rate reduced from 2.4% to 0.7%
84%
On-time delivery improved from 84% to 96%
3
Eliminated 3 FTE (2 estimators, 1 scheduler) - $89k savings

Implementation Timeline

12 weeks including machine connectivity setup

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