Case Study: TechAssembly Solutions — Collaborative Robot Assembly Line Automation

How an electronics manufacturer scaled production with collaborative robots, achieving 45% throughput increase and 52% labor cost reduction with zero safety incidents.

Industry
Manufacturing & Assembly
Services
Collaborative Robots · Assembly Automation · Quality Control
Timeline
9 Months
Collaborative Robot Assembly

Project Overview

TechAssembly Solutions manufactures electronic control modules for industrial equipment. The company operated 6 manual assembly lines with 120+ workers performing repetitive, high-precision tasks — resulting in high turnover (35% annually), quality inconsistencies (2.4% defect rate), and difficulty scaling to meet growing demand.

GridMatrix designed and deployed a hybrid human-robot collaborative assembly system with 12 UR+ collaborative arms, vision-based quality control, and intelligent task allocation — enabling 45% production increase with near-zero defects and improved worker safety.

Challenges
  • High worker turnover due to repetitive manual assembly tasks
  • Quality inconsistencies causing 2.4% defect rate and customer complaints
  • Difficult to scale production without hiring more workers
  • Repetitive strain injuries (RSI) among assembly workers
  • Long cycle times limiting throughput (180 units/day per line)
  • Manual inspection processes missing defects
Strategy
  • Deploy 12 collaborative robots for repetitive assembly tasks
  • Implement vision-based defect detection at checkpoints
  • Design safe human-robot collaboration workflows
  • Create intuitive programming interface for task adaptation
  • Train workforce to work alongside robots (not replace)
  • Achieve continuous improvement through data analytics

Actions Taken

Collaborative Robot Deployment
  • Installed 12 UR10e collaborative arms across 6 assembly lines
  • Equipped robots with gripper tooling for component handling and fastening
  • Designed ergonomic workstations with robot-human task separation
  • Implemented force-limited safety protocols allowing safe human-robot proximity
Vision-Based Quality Control
  • Deployed 18 machine vision cameras for 100% automated inspection
  • Trained deep learning models on 100,000+ images for defect detection
  • Achieved 99.6% defect detection accuracy with <50ms per-unit inspection
  • Integrated automated rejection system removing defective units
Task Planning & Worker Collaboration
  • Redesigned assembly workflows optimizing human and robot strengths
  • Robots handle precision fastening; humans handle complex manual assembly
  • Built intuitive teach pendant interface for rapid task reprogramming
  • Implemented skill-based training to upskill workers for robot supervision

Results (9 Months)

+45%
Production Throughput Increase
-52%
Labor Cost Per Unit
-81%
Defect Rate Reduction
Zero
Safety Incidents in Year 1

Technical Implementation

The system integrates 12 UR10e collaborative arms programmed via graphical task builder — no specialized robotics knowledge required. Each robot is equipped with a Schunk intelligent gripper for part handling and adaptive force control. Vision-based quality control uses industrial cameras with Basler APIs and deep learning inference running on edge GPUs. The control system connects all robots via industrial Ethernet to a central orchestration engine built on ROS (Robot Operating System). Data from all robots and vision systems is collected in real-time for KPI tracking (cycle time, defects, OEE). Safety systems include force-torque sensors, emergency stop protocols, and collaborative force limitations per ISO/TS 15066 standards.

Final Outcome

TechAssembly Solutions successfully transformed its assembly operations from manual to collaborative robotic production. With 45% throughput increase and 52% labor cost reduction per unit, the company increased profitability while reducing worker injury rates. Defect detection improved from 2.4% to 0.45%, enhancing customer satisfaction and reducing warranty costs. Workforce turnover decreased to 8% (from 35%) as workers transitioned to higher-skill robot supervision roles. The company has now doubled production capacity with the same factory footprint, positioning it to capture new enterprise contracts and expand into adjacent markets.