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i4Q · Project

Smart Data Tools That Cut Factory Defects and Boost Product Quality

manufacturingPilotedTRL 7
i4q-project.eu

Imagine every machine on a factory floor constantly whispering what it sees, feels, and measures — temperature, vibration, pressure, shape. Now imagine a smart system that listens to all those whispers at once and spots the moment something starts going wrong, before a single defective product rolls off the line. That is what i4Q built: a suite of 22 connected tools that collect data from cheap factory sensors, check that the data is trustworthy, then use digital twins and simulations to keep quality perfect in real time. It was tested with real manufacturers making everything from washing machines to ceramic tiles.

By the numbers
22
Connected quality control solutions in the i4Q suite
6
Industrial use cases demonstrated at real factories
26
Consortium partners across Europe and Israel
11
Countries represented in the consortium
74
Total project deliverables produced
5
Core data capabilities: sensing, communication, computing, storage, analysis
10
SMEs participating in the consortium
The business problem

What needed solving

Manufacturers lose significant revenue to defective products, scrap, rework, and warranty claims — but traditional quality control catches problems too late, after bad parts are already made. Factory data from sensors and machines is often unreliable, fragmented across systems, or simply too massive to process in real time. Companies need a way to trust their production data and use it to prevent defects before they happen, not just detect them afterward.

The solution

What was built

A complete suite of 22 interconnected industrial data tools — from cheap smart sensors to digital twins and process simulators — that monitor manufacturing quality in real time and automatically optimize production to prevent defects. The final demonstrator (v3) was validated across 6 real factory environments covering white goods, wood, metal, ceramics, and plastics manufacturing.

Audience

Who needs this

Appliance and consumer goods manufacturers with high-volume assembly linesPlastic injection molding companies supplying automotive or electronics sectorsCeramic and building materials producers with pressing or forming processesMachine tool builders looking to add smart quality features to their equipmentMetal machining and precision parts manufacturers targeting zero-defect production
Business applications

Who can put this to work

Home Appliances & White Goods
enterprise
Target: Large appliance manufacturers with high-volume production lines

If you are an appliance manufacturer dealing with defect rates that drive up warranty costs and returns — this project developed a suite of 22 data-driven quality tools tested at Whirlpool's production lines. The system uses cheap interconnected sensors and digital twins to catch quality issues in real time, before defective units reach customers. It was validated across 6 industrial use cases with final demonstrators delivered.

Plastics & Injection Molding
mid-size
Target: Mid-size plastic component manufacturers supplying automotive or consumer goods

If you are a plastics manufacturer struggling with inconsistent part quality from injection molding — this project built virtual sensors and process simulation tools specifically tested at Farplas, a plastic injection company. The system monitors your production data in real time and optimizes process parameters to push toward zero-defect output without expensive hardware upgrades.

Ceramics & Building Materials
mid-size
Target: Ceramic tile or pressed product manufacturers looking to reduce scrap

If you are a ceramics manufacturer losing margin to scrap and rework from pressing defects — this project delivered smart monitoring and optimization tools demonstrated at Riastone's ceramic pressing facility. The 22-tool suite handles everything from sensor data collection to quality diagnosis and automatic process reconfiguration, using cost-effective small sensors rather than expensive inspection systems.

Frequently asked

Quick answers

What would it cost to implement these quality control tools in my factory?

The project specifically designed its solutions around cheap, cost-effective, smart, and small size interconnected factory devices. While exact licensing costs are not published, the emphasis on affordable sensors and open industrial standards (with DIN as a standardisation partner) suggests the system was built to be accessible to mid-size manufacturers, not just large enterprises.

Can this scale to a full production line, not just a lab demo?

Yes. The i4Q tools were demonstrated in 6 industrial use cases at real production companies including Whirlpool (white goods), Biesse (wood equipment), Riastone (ceramics), Farplas (plastics), Factor (metal machining), and Fidia (metal equipment). The final demonstrator (v3) confirms full-scale industrial validation.

Who owns the IP and can I license these tools?

The consortium of 26 partners across 11 countries jointly developed the 22 solutions. FundingBox was specifically included as an exploitation partner to handle commercialization. Contact the coordinator or individual technology providers like IBM, Engineering, or ITI for licensing discussions.

Does this work with my existing factory equipment and systems?

The system was designed for integration with existing manufacturing lines. TIAG contributed industrial communication protocols and standards expertise, and DIN (the German standardisation body) was a consortium partner. The 6 use cases covered diverse manufacturing processes — pressing, injection, machining, and assembly — confirming broad equipment compatibility.

How long would it take to deploy this in my facility?

The project ran from January 2021 to May 2024, delivering 74 total deliverables including a final solutions demonstrator. Based on the 6 industrial pilot deployments, a factory implementation would likely require an initial assessment phase followed by sensor installation and system integration. The use of existing cheap sensors speeds up deployment compared to custom inspection systems.

Is there regulatory or standards backing for this approach?

DIN, the German Institute for Standardization, was a dedicated consortium partner working on standardisation. The system addresses manufacturing quality certification and continuous process qualification, which aligns with ISO quality management requirements. The blockchain component also provides auditable data trails for compliance purposes.

Consortium

Who built it

The i4Q consortium is exceptionally strong for commercialization. With 26 partners across 11 countries, 54% are industry players — well above typical EU project ratios. The lineup reads like a manufacturing who's who: Whirlpool and Biesse bring end-user production scale, IBM and Engineering bring enterprise IT muscle, while 10 SMEs ensure the solutions work for smaller companies too. The deliberate inclusion of FundingBox for exploitation, DIN for standardisation, and INTEROP-VLAB for dissemination shows this project was built with market uptake in mind from day one. The 6 diverse industrial pilots — spanning plastics, ceramics, metals, and wood — prove the tools are not locked to one manufacturing niche.

How to reach the team

Coordinator is ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS (CERTH), a major Greek research centre. SciTransfer can facilitate a warm introduction to the right team.

Order a report on this consortiumSee ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS profile →
Next steps

Talk to the team behind this work.

Want to explore how i4Q's zero-defect manufacturing tools could work in your production line? SciTransfer can connect you directly with the technology providers and arrange a tailored demo. Contact us for a one-page brief.

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