texfash.com: Mahlo’s legacy spans eight decades of precision engineering in web process control. In an era increasingly driven by AI-enhanced automation, how does the company distinguish between engineering legacy and innovation inertia?
Thomas Höpfl: Mahlo’s legacy is built on pioneering milestones—starting with radio receivers in the 1940s and culminating in the first automatic weft straightener in 1958. This legacy is not a constraint but a launchpad. The company actively avoids innovation inertia by continuously investing in R&D and expanding its product portfolio beyond textiles into nonwovens, film, paper, and battery coatings. Innovation is embedded in Mahlo’s DNA, and the company’s longevity stems from its ability to evolve while maintaining engineering excellence
Your systems are used across textiles, nonwovens, film, paper, and even battery electrode coatings. What are the fundamental principles that allow a technology originally designed for woven fabric distortion to remain relevant across such divergent substrates?
Thomas Höpfl: Mahlo’s systems are grounded in universal physical principles—optical, optoelectrical, near infrared, microwave, laser triangulation, resistance, and radiometric measurement. These principles are not substrate-specific, allowing Mahlo to adapt its technologies across industries. The modularity of its platforms (e.g., Qualiscan QMS, Optipac VMC, Orthopac RVMC) enables customization for different materials, whether it's woven, knitted fabric, nonwoven materials, extruded films and even multi-layer battery films. The company’s success lies in its ability to abstract measurement logic from the material itself, focusing on process behaviour and control dynamics
The concept of “measurability” has evolved—from visible fabric defects to invisible layer deviations in battery films. How is Mahlo adapting its sensor logic and feedback architecture to address this shift from quality control to process governance?
Thomas Höpfl: Historically, Mahlo systems focused on visible defects like fabric distortion. Today, the shift toward invisible deviations—such as thickness variations in battery coatings—requires a new approach. Mahlo is responding by enhancing its sensor logic with real-time analytics, AI-assisted feedback loops, and predictive modelling. The goal is no longer just to detect errors but to govern the process itself, ensuring stability, efficiency, and compliance throughout production.
Digital adoption varies widely among clients. What’s the most persistent implementation hurdle—and has any particular case forced a rethink of your onboarding strategy?
Thomas Höpfl: Digital readiness varies widely among Mahlo’s global clientele. Some operate legacy systems with minimal connectivity, while others demand full integration with Industry 4.0 platforms. The most persistent hurdle is interoperability—especially in retrofitting older lines. Mahlo has adapted by offering hybrid solutions that bridge analogue and digital systems, and by investing in onboarding strategies that include tailored training, remote support, and gradual digital migration.