Optimizing Quality and Measurement Systems for a Precision Machined Assembly

Automobility Enterprises (AE) was engaged by a Tier 1 automotive customer struggling with high reject rates on a critical, precision-machined assembly. This complex product required stringent quality validation through intricate measurement processes, which were failing to reliably identify and prevent defects. The core request was to validate the supplier’s production process and optimize the overall quality output.

The Challenge: Unstable Quality and Unreliable Data

The supplier was experiencing a frustrating and costly high reject rate, but their internal quality control systems were failing to pinpoint the true source of the dimensional variation. Initial analyses suggested a specific operation was the primary culprit, but the fundamental issue lay deeper in the data itself.

AE's Intervention: Root Cause and Measurement System Analysis (MSA)

AE executed a thorough root cause analysis, extending beyond the process floor and into the quality lab.

  1. Deep Root Cause Analysis (RCA): Initial process review confirmed that the majority of rejects appeared to stem from a single, critical process point.
  2. Measurement System Analysis (MSA): However, upon further evaluation, AE conducted an in-depth Measurement System Analysis (MSA). This critical review revealed the true systemic problem: the existing measurement system was fundamentally flawed and not correctly designed or validated to meet the extremely tight tolerances of the product design. The system’s inherent variation (gage error) was consuming a significant portion of the allowable product tolerance, making it impossible to confidently separate product variation from measurement error.

The Solution: SPC and High-Fidelity Measurement Strategy

AE moved swiftly to establish a robust and reliable quality validation system:

  • Developed a New Measurement Strategy: AE designed a brand-new measurement system strategy tailored specifically to the tight tolerances of the precision assembly.
  • Gauge R&R Validation: The new system was rigorously validated using a Gauge Repeatability and Reproducibility (Gauge R&R) study. This confirmed the system’s variation was now appropriately minimized, making the data trustworthy and ensuring the system was capable of accurately assessing product quality.

Incorporated Statistical Process Control (SPC): The validated measurement system was integrated with Statistical Process Control (SPC) tracking. This step was crucial, as it established a dynamic monitoring system that provided adequate warning by detecting process shifts before they resulted in out-of-specification defects.

The Outcome: Reduced Variation and Enhanced Safety Margins

The implementation of the new, reliable measurement and control system yielded immediate and lasting benefits:

  • True Process Understanding: The accurate data provided by the new system revealed that the variation coming from previous upstream operations could also be significantly reduced.
  • Increased Safety Margin: By controlling upstream variation and employing a validated, high-fidelity measurement system, the overall process capability improved, creating an even higher safety margin against the specified design tolerances.
  • Sustainable Quality: AE successfully transitioned the client from a reactive inspection state (detecting defects) to a proactive control state (preventing defects), resulting in a sustained reduction in the high reject rate and significant cost savings for the customer.

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Validating and Optimizing a Greenfield Autonomous Vehicle Manufacturing Plant

Automobility Enterprises (AE) partnered with an innovative developing startup to validate the production readiness of their new autonomous vehicle manufacturing facility. The core objective was to move beyond theoretical planning and confirm that the proposed manufacturing system could efficiently and effectively build the autonomous vehicle from the ground up.

The Challenge

The startup had made significant initial investments in plant design and process planning based on standard industry assumptions. However, they needed an experienced partner to validate these assumptions in a real-world scenario before full-scale production launch.

AE was engaged to rigorously test and confirm all critical elements, including:

  • Process Layout and flow efficiency.
  • Number of Stations and cycle time capability.
  • Manpower Requirements and ergonomic feasibility.
  • Part Presentation and Accessibility at the point of use.
  • Planning for System Testing and Validation integrated throughout the assembly process.

AE's Solution: The Pilot Build and Validation

AE’s team worked on-site with the startup, executing a hands-on, end-to-end evaluation. The project’s centerpiece was the construction of a single vehicle from the ground up, strictly following the initially proposed assembly sequence and process assumptions.

This “pilot build” served as a live, high-fidelity stress test for the entire manufacturing system. By meticulously executing each step, AE was able to capture real-time data on process cycle times, identify bottlenecks, and assess the true physical constraints of the design, supply chain, and logistics setup.

The Results and Key Improvements

The pilot build successfully validated that the core process assumptions would work, confirming the fundamental feasibility of the production plan.

However, the build also generated an extensive and critical list of targeted improvements necessary to ensure the target takt time and overall process requirements could be reliably met in mass production.

Key areas of improvement developed by AE included:

  • Design-for-Assembly (DFA) Enhancements:
    • Improvements to fasteners, fit, and component interconnectivity to reduce assembly time and effort.
  • Supply Chain and Logistics Optimization:
    • Optimization of parts kitting to streamline station delivery.
    • Improvements in dunnage (packaging) size, orientation, and presentation for better ergonomics and component protection.
    • Adjustments to ensure sufficient space for feasible part delivery to the line.
  • Process and Equipment Improvements:
    • Adjusting equipment layout for optimized flow and safety.
    • Integrating additional lift assists and adjusting platform heights to improve worker access to/from the vehicle.
    • Implementing jigs and fixtures to allow for faster installation (e.g., wire harnesses).

Designing protective covers to safeguard sensitive components during subsequent installation steps.

Conclusion

Automobility Enterprises delivered a comprehensive validation that de-risked the client’s manufacturing launch. By transitioning from theoretical plans to a hands-on pilot build, AE provided the startup with the confidence that their process was sound, while also delivering a detailed, actionable roadmap for optimization. This work ensured the startup could move toward full-scale production with a refined, efficient, and ergonomically superior assembly process ready to meet aggressive production targets.

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