Industrial Talk is talking to Michal Ukropec, CEO at Twinzo about "Operational Digital Twin: Real-Time operational insights from all your connected devices".
Overview
Digital twin and real-time logistics tracking were discussed as ways to improve manufacturing visibility, efficiency, and competitiveness.
Digitalization Gap
Michal said European manufacturers lag behind China and often operate legacy systems without connectivity or a coherent digitalization strategy.
Procurement decisions that remove connectivity features can create long-term data and integration problems.
Twinzo Use Case
Twinzo tracks logistics fleets, materials, and movement from suppliers through production, integrating data from PLCs, MES, and WMS systems.
Real-time location data can reduce forklift fleet requirements, prevent micro-stoppages, and improve material flow without adding equipment or staff.
Adoption Barriers
What leadership commitment and strategy are needed to modernize plants using legacy systems?
How can manufacturers ensure operational data is clean, accurate, and trusted before applying AI or analytics?
The discussion emphasized piloting technologies at limited scale, measuring results, and balancing technology with effective leadership and workforce engagement.
Outline
Manufacturing Competitiveness
Workforce and industrial competitiveness were framed as shared priorities.
Europe’s digitalization gap compared with China and the United States was discussed.
Legacy Infrastructure
Many plants still rely on older PLCs and IBM AS/400-era systems.
Replacing legacy infrastructure can be expensive and disruptive, but inaction limits visibility and efficiency.
Twinzo Platform
Twinzo originated in indoor positioning and evolved toward manufacturing and logistics tracking.
The platform can monitor fleets, materials, workstations, and production movement.
Potential integrations include PLC, MES, and WMS data.
Operational Benefits
Real-time location system data can reveal inefficient routes and unnecessary fleet capacity.
An automated material-ordering workflow was compared to an “Uber for the plant.”
Additional use cases include reducing energy waste and identifying equipment operating without orders.
Technology and Leadership
AI was characterized as a tool requiring appropriate data, evaluation, and measured adoption.
Leadership, culture, workforce capability, and trust remain central to successful transformation.
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MICHAL UKROPEC'S CONTACT INFORMATION:
Personal LinkedIn: https://www.linkedin.com/in/michalukropec/
Company LinkedIn: https://www.linkedin.com/company/twinzo/home/
Company Website: https://www.twinzo.com/
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