Doosan Bobcat

Doosan Bobcat's Dobris facility in the Czech Republic — one of its primary European manufacturing plants producing over 12,000 machines annually — faced persistent OEE challenges in its fabrication area. The root causes were structural: equipment data lived in disconnected silos, shop floor reporting relied on paper-based collection, and there were no real-time dashboards to surface operational trends. Across a workforce of 600+ employees, this meant decisions were made on instinct rather than data, and a significant portion of operator time was consumed by manual data gathering rather than value-added work. For a high-volume industrial machinery manufacturer, these inefficiencies compounded directly into constrained throughput and inconsistent quality outcomes.

Bobcat partnered with Rockwell Automation to deploy an Industrial IoT platform that connected plant equipment, sensors, and devices into a unified data layer — replacing fragmented, paper-based processes with live operational visibility. The platform aggregated machine and process data into role-appropriate dashboards, giving operators, supervisors, and plant managers a shared view of fabrication performance for the first time. Integration with existing plant equipment was prioritized to avoid rip-and-replace disruption. Critically, the deployment strategy treated people as central to the transformation: employees were engaged early in the design process, ensuring the dashboards and workflows reflected how the floor actually operated. This change management approach ran in parallel with the technical rollout, building adoption before go-live rather than after.

The IIoT deployment delivered measurable improvements across both production output and operational discipline at the Dobris facility:

• Production capacity increased in the fabrication area, contributing to the plant's ability to sustain 12,000+ units of annual output with greater consistency
• Quality assurance improved through real-time data visibility, reducing reliance on after-the-fact inspection
• Non-value-added tasks eliminated — operators no longer spent shift time on manual data collection, redirecting that effort toward production activities
• Data-driven decision-making became standard practice across the 600+ person workforce

The transformation validated that IIoT adoption at scale is achievable in high-mix discrete manufacturing environments when change management is treated as equal in importance to technology deployment.

• Engage employees before deployment, not after — at Dobris, early workforce involvement was the primary driver of adoption and a key reason the platform delivered results at scale.
• Data silos are an OEE problem — before investing in automation or capacity, audit whether fabrication decisions are being made on real-time data or manual approximations.
• Connecting existing equipment matters more than replacing it — integrating legacy machines into a unified IIoT layer typically delivers faster ROI than greenfield capital expenditure.
• OEE gains in fabrication have downstream multiplier effects — improvements at the constraint propagate through final assembly and quality gates, amplifying overall plant output.