Automotive:

Published: Dec 9, 2024

Reading time: 4 min

Introduction

PACCAR faced significant challenges with inefficient tooling management, which was marked by fragmented data collection and poor tool performance tracking. This led to heightened operational costs and downtime. In response, PACCAR partnered with eMoldino and implemented a data-driven, IoT-enabled tooling management system to boost operational efficiency.

Business Challenge

PACCAR’s initial tooling management practices revealed significant systemic inefficiencies:

 

  1. Tooling Movement: PACCAR needed a robust system to track tooling in real-time across multiple manufacturing facilities, ensuring enterprise-wide visibility and the ability to quickly locate any piece of tooling.
  2. Maintenance Scheduling: The company sought to digitalize and standardize maintenance records, enabling more informed scheduling and extending tooling lifespan. By streamlining maintenance activities, PACCAR aimed to reduce downtime and improve overall operational efficiency.
  3. Asset Management: PACCAR aimed to gain clear visibility into its entire asset base with fully digitized tooling records. This would enable informed decisions about when to deploy, refurbish, or retire specific tools, ultimately improving resource utilization and asset lifecycle management.
  4. CapEx Budget Forecasting: Accurate, data-driven forecasting was needed to better anticipate annual tooling expenditures. By leveraging insights from asset condition and maintenance history, PACCAR aimed to confidently predict costs for repairs, refurbishments, and replacements, ensuring more effective budgeting and strategic planning.

These shortcomings translate into tangible financial losses. Without a holistic view of tooling performance, PACCAR struggled to align tooling lifecycle management with production demands, driving up costs and hampering operational reliability.

Implementation Roadmap & Stakeholder Alignment

The deployment followed a structured timeline to ensure systematic adoption:

  • June-July 2024: Initial setup with bi-weekly training and pilot trials on two presses.
  • August-September 2024: Expansion to additional presses.
  • October-November 2024: Optimization phase with monthly reviews and advanced training.
  • December 2024: large-scale deployment, including scrap reporting integration and broader press expansions.

By the end of the initial rollout, PACCAR had deployed 274 IoT sensors, 22 terminals, and 20 mounting brackets. Robust stakeholder engagement—weekly tooling head meetings, monthly management sessions, and bi-weekly training—ensured that technical teams, supervisors, and leadership were aligned with the new processes and technologies. 

Technical Integration & Data Architecture

PACCAR leveraged eMoldino’s IoT-enabled tooling management solution to transform operational visibility and enhance decision-making. The system integrated several critical data streams to support improved operational efficiency:

  • Production Metrics: Real-time press operation data.
  • Tool Condition Insights: Continuous monitoring of tooling health and performance.

Automated Analytics: Immediate performance analysis for proactive decision-making.

Operational Impact and Improvements

Within a month, PACCAR’s tooling operations exhibited transformative change:

Systematic tracking of digitized tooling operations revealed substantial performance improvements. Overall Equipment Effectiveness (OEE) increased from 56.8% to 71.3% (+25.5%), while Equipment Availability rose from 58.5% to 76.5% (+30.8%). Beyond these gains, average cycle times remain 20-60% faster than Actual cycle time.

Overall Equipment Effectiveness (OEE) Improvement by Period

OEE rose significantly between weeks 33 and 44—from 55.6% to 69.6%. This improvement was closely tied to a 29.8% boost in equipment availability, indicating that efforts in reliability enhancement, scheduling optimization, and proactive maintenance substantially reduced downtime and improved overall operational performance.

Machine Availability Improvement by Period

Machine availability increased notably between weeks 33 and 44—from 57.8% to 75.0%. This 29.8% improvement indicates that enhanced maintenance strategies, more effective scheduling, and better tooling reliability contributed to a more stable and consistently productive operating environment.

Financial Outcomes

The data-driven transformation yielded significant cost savings:

In total, PACCAR realized approximately $89.35 million in annual cost optimization. Refurbishment decisions are now data-backed, enabling $100,000 investments for extended tool life to be validated with precise ROI metrics.

Conclusion

The implementation began with significant inefficiencies and delivered measurable results through a systematic approach and strong stakeholder alignment:

  • Overall Equipment Effectiveness (OEE) increased from 56.8% to 71.3%.
  • Equipment availability improved by 29.8%, rising from 57.8% to 75.0%.
  • Annual cost savings reached approximately $89.35 million, validated by data-backed refurbishment and investment strategies.

These achievements underscore the impact of IoT technology and data-driven strategies.

About the author

eMoldino

eMoldino aims to digitalize, streamline, and transform your manufacturing and supply chain operations. We help global manufacturers who want to drive corporate innovation while maintaining the core values of collaboration and sustainability. Talk with us to learn more 

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