How to Reduce Cycle Time Without Sacrificing Quality

Purpose:

Help customers identify and eliminate inefficiencies incycle times so they can produce more parts in less time, without increasingoperator fatigue or compromising quality.

“If you can do the same parts, same quality, at a reduced cycle time… you could be more productive.”
— President, Aluminum Manufacturer

Outcomes:

• Reduction in average cycle time per machine/process
• Elimination of unnecessary variation between shifts or operators
• Clear visibility into where time is lost inside the cycle
• Foundation for automation or process standardization

Tools You’ll Use in Caddis:

• Cycle time history and variance reports
• Shift performance comparisons
• Event markers or tags (for breakouts like tool changes or load/unload time)
• Real-time dashboards for live monitoring during improvement sprints

Timeline:

2–4 weeks for full cycle optimization loop (repeatable quarterly)

Who’s Involved:

Role

• Caddis Champion
  
  • Oversees data review and reporting
• Cell or Area Lead
  
  • Facilitates team discussions and implements changes
• Operator (Engaged)
  
  • Provides real-time feedback on process constraints
• Continuous Improvement Lead
  
  • Helps define metrics and validate gains
• Production Manager
  
  • Ensures follow-through and scale-up

Step-by-Step Execution

Step 1: Identify High-Volume or High-Impact Processes

Start with a part or machine that: 

• Runs frequently
• Has high labor or material cost per part
• Is bottlenecked or often behind schedule

Step 2: Pull Cycle Time Data

From Caddis:

• Download historical cycle time data for the last 7-14 days
• Export to excel to use the dashboard view to analyze
  
  • Average cycle time
  • Standard deviation
  • Maximum and minimum values

Visual tip: Create a histogram to show spread. Identify the “long tail” of cycle time outliers.

Step 3: Compare by Shift and Operator

Segment the data by:

• Operator
• Shift
• Machine (if part runs on more than one)

Ask:

Is one shift consistently slower?

• Are cycle times longer with certain operators?

This can point to training gaps, process differences, or tooling inconsistencies.

Step 4: Conduct a “Gemba Review”

Walk the floor with Caddis data in hand. Observe a few live cycles.

Questions to ask:

• What’s happening during the long cycles?
• Are operators waiting for material?
• Is there extra walking, reaching, or resetting?
• Are tool changes or part handling steps inefficient?

👀 Sometimes it’s as simple as needing a table closer to the press.

Step 5: Host a Cycle Time Huddle

Meeting Length: 30 minutes
Attendees: CI Lead, Operators, Area Lead, Caddis Champion

Agenda:

1. Review current state: avg. time, variance, shift gaps
2. Show top 3 contributors to cycle delays (from Gemba)
3. Brainstorm 1–2 changes to test (new layout, tool rack, digital work aid)
4. Assign a test owner (e.g. “Jake will test new part staging setup for 2nd     shift”)
5. Set date to review impact (usually 3–5 days later)

Step 6: Test and Measure

Use Caddis to monitor impact:

• Look for drop in cycle time average
• Most importantly, reduce cycle time variance (consistency)

Even small drops (e.g., 3 sec/part) add up over thousands of parts.

Step 7: Lock in Gains and Scale

If the test works:

• Update work instructions
• Roll changes out to all shifts
• Recognize team for improvements
• Share “Before/After” data in team meetings

Metrics to Track:

Metric

• Avg. cycle time
  
  • Decreasing trend (by 5–10% typical)
• Standard deviation
  
  • ≤ 10% of average
• Output/hour
  
  • Increasing with same labor force
• Operator feedback
  
  • Easier, more consistent process

Weekly Meeting Cadence:

Monday‍

Review cycle data from previous week, highlight outliers

Wednesday

Gemba walk + team huddle

Friday

Validate improvements and prepare final report

Common Challenges (and Solutions)

• “Operators are defensive about being measured”
  
  • Involve them early. Position this as a way to make their  job easier.
• “We don’t know what’s causing the delay”
  
  • Watch the process live and match timestamps to real motion.
• “Data looks inconsistent”
  
  • Validate machine state tags. Are start/stop points configured correctly in Caddis?

🧩 Bonus Tip:

Use visual tags inside Caddis to mark specific cycle stages — like clamp engagement, mold fill, or load/unload. This gives even deeper insight into what’s consuming time.

✅ What Success Looks Like:

• Cycle times reduced and stabilized
• Less operator variability
• Higher throughput without adding shifts
• Operators engaged in improving their own processes