SciTransfer
FALCON · Project

Turn Customer Feedback and IoT Sensor Data Into Smarter Product Design

manufacturingTestedTRL 6
falcon-h2020.eu

Imagine every product you sell could tell you exactly how customers use it — what they love, what frustrates them, and when something is about to break. FALCON built a system that collects real-time data from sensors embedded in products and combines it with customer opinions from forums, chats, and reviews. It then feeds all of that back to designers and manufacturers so the next version of the product is genuinely better. Think of it like giving your entire product line the ability to phone home with improvement suggestions.

By the numbers
4
industry demonstrators built and tested
EUR 4,594,973
EU research investment
13
consortium partners across 8 countries
10
industrial partners in the consortium
77%
industry participation ratio
8
SMEs involved in development
The business problem

What needed solving

Most manufacturers lose contact with their products the moment they leave the factory. Customer complaints arrive too late, product usage data stays locked in disconnected silos, and design teams rely on guesswork instead of real-world evidence. This means new product versions repeat old mistakes and service offerings miss what customers actually need.

The solution

What was built

FALCON built 4 industry-specific demonstrators: one for clothing textiles (connecting designers with real customer feedback), one for healthcare products (field-to-maintenance data communication), one for high-tech products (user-product interaction monitoring), and one for white/brown goods (usage behavior observation). Across 11 total deliverables, the project created IoT-based product feedback collection, knowledge representation tools, and lifecycle assessment methods.

Audience

Who needs this

Home appliance manufacturers wanting to reduce warranty claims through usage-informed designFashion and textile companies seeking to shorten new collection time-to-marketHealthcare device companies needing field data to optimize maintenance schedulesConsumer electronics brands wanting to understand real product usage patternsProduct-service companies looking to create data-driven after-sales services
Business applications

Who can put this to work

Consumer Electronics & Home Appliances
enterprise
Target: White goods manufacturers (washing machines, refrigerators, ovens)

If you are a home appliance manufacturer struggling to understand why customers return products or complain after purchase — this project developed a demonstrator for white and brown goods that monitors how users actually interact with your products in real time. It feeds usage patterns and customer experiences back to your design team, so your next product generation addresses real pain points instead of guessed ones.

Textile & Fashion
mid-size
Target: Clothing brands and textile manufacturers

If you are a fashion company facing long time-to-market for new collections and disconnected customer feedback — this project built a clothing textiles demonstrator that connects lifecycle product information with real customer input. It strengthens collaboration between designers and manufacturers, helping you shorten new collection cycles and introduce data-driven services around your garments.

Healthcare Equipment
enterprise
Target: Medical device and healthcare product companies

If you are a healthcare product company dealing with costly field maintenance and limited visibility into how your devices perform after deployment — this project created a healthcare demonstrator with communication and data storage between products in the field and your maintenance organization. It enables predictive service models based on actual product usage data rather than fixed schedules.

Frequently asked

Quick answers

What would it cost to implement this kind of feedback system?

The FALCON project received EUR 4,594,973 in EU funding across 13 partners over 3 years to develop four industry demonstrators. Implementation costs for a single company would depend on product complexity and existing IoT infrastructure. Based on available project data, no per-unit or licensing costs were published.

Can this scale to thousands of products in the field?

The system was designed to handle sensor data from IoT-connected products combined with customer feedback from multiple channels (forums, blogs, chat, idea voting). Four separate demonstrators were built for different industries, suggesting the architecture is adaptable. Based on available project data, exact throughput numbers were not published.

Who owns the intellectual property?

The IP is distributed among the 13-partner consortium led by BIBA in Germany, with technology providers including UBITECH, Holonix, Softeco, and i-Deal. Industrial partners Arcelik and Philips were involved in validation. Licensing terms would need to be negotiated with individual technology owners.

How does this integrate with existing product lifecycle management systems?

FALCON was built around product-service knowledge representation and lifecycle assessment. It uses Product Embedded Information Devices and IoT sensors to collect data, with ontology-based knowledge models. Based on available project data, integration with specific commercial PLM platforms would require discussion with the solution providers in the consortium.

What industries has this been tested in?

Four demonstrators were built and tested: clothing textiles, healthcare products, high-tech products, and white and brown goods. Each demonstrator was tailored to the constraints of its specific industry scenario, covering both consumer and professional product categories.

Is this ready to deploy in my factory today?

The project ended in December 2017 with four working demonstrators validated in specific business scenarios. The technology reached demonstration level but would likely require adaptation and integration work for new deployments. Contact the solution providers (Holonix, Softeco, UBITECH) for current commercial availability.

Does this comply with data privacy regulations for collecting customer data?

The project was designed with principles of sustainability and social responsibility. However, it concluded before GDPR took full effect in May 2018. Any current deployment would need to ensure compliance with GDPR and relevant data protection regulations for IoT sensor data and customer feedback collection.

Consortium

Who built it

This is a strongly industry-driven consortium with 10 out of 13 partners coming from industry (77%), including 8 SMEs — unusual for EU research and a good sign for practical applicability. The consortium spans 8 countries and includes major brands like Arcelik (appliances) and Philips (electronics/healthcare) alongside specialized technology providers (Holonix, Softeco, UBITECH, i-Deal) who built the actual software. Academic backing comes from BIBA (coordinator), EPFL, and TU Delft — all well-known in manufacturing research. The heavy SME presence means the tools were built with smaller companies in mind, not just enterprise budgets.

How to reach the team

BIBA - Bremer Institut fuer Produktion und Logistik GmbH, Bremen, Germany. Technology providers Holonix (IT), Softeco (IT), and UBITECH (EL) may offer commercial solutions.

Order a report on this consortiumSee BIBA - BREMER INSTITUT FUER PRODUKTION UND LOGISTIK GMBH profile →
Next steps

Talk to the team behind this work.

Want to connect with FALCON's IoT feedback technology providers? SciTransfer can arrange an introduction to the right consortium partner for your industry and use case.

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