How an AI Workshop Helped a Furniture Manufacturer Plan Quality Control Automation for Peak Season
Instead of immediately committing to a high-stakes project, Prohan started with an Industrial AI Workshop, an approach perfect for companies not sure about AI’s ROI and looking for a way to make the potential investment less risky. The goal was to create a blueprint that shows what system design is technically the most feasible and will bring the highest financial impact.
First, let’s understand the production process, so the innovation can make the work easier, not harder
Most of the time the DAC.digital team hosts the workshops online, however, this meeting took place at Prohan’s factory floor to check the exact location’s conditions. One spot was the most critical: right after the gluing machine, before any further value was added to the panel.
Structured error classification and data strategy paved the way for a reliable AI defect detection development
Together with the quality control team, DAC.digital engineers came up with a structured way of classifying errors and agreed on exact criteria to follow. For example, if the gap in glue-line is bigger than 0,5mm, it counts as a defect.This level of precision removed all subjectivity from the quality control process.
A well-planned data strategy was the next step. The team built a balanced dataset with examples of good parts, defective parts, and tricky in-between cases to train the AI model effectively,
Prohan mapped the operators’ workflow to show what happens when a defect is detected, decided how alerts are triggered and agreed on procedures for handling and reworking panels. All that to make sure the technology fits the existing process smoothly.
Seamless integration connected factory machines with business systems
One of the most crucial parts of such projects is making sure the factory machines can communicate with the business systems by setting the right connection points. The team specified control signals from Prohan’s PLCs and identified data integration points with their ERP and quality databases.
The client came up with an operations plan to determine who handles the installation and who takes care of the maintenance so that everything can run smoothly long-term.
ROI-focused business case gave Prohan confidence to invest further
The final stage of the workshop focused on building a business case, giving Prohan the confidence to move forward. It’s extremely important to have skilled facilitators to conduct such exercises. They help build the connection between technical complexity and business value, and translate potential impacts into financial and operational benefits. The customized workshop exercises helped the team see how the solution would deliver measurable ROI so that they can make informed investment decisions.
Clear KPIs aligned technical precision with business goals
After acceptance criteria were set, there was no longer room left for ambiguity. On the technical side, the team defined AI performance metrics, targeting ca. 95% precision for critical defects such as glue-line gaps bigger than 0.5 mm. On the business side, they set clear goals: reduce customer returns for this flaw to zero, as well as cut scrap and rework rates. These KPIs became the north star for the project, impacting every decision and making sure technical and business teams shared the same vision of success.
Prohan saw clear cost savings and brand value before implementation
Next, our teams constructed a detailed ROI model that quantified the true cost of quality for Prohan. We calculated direct savings from fewer rejected panels and reduced material scrap, while also accounting for lower labor costs by minimizing time-consuming manual rework. Beyond cost reductions, we highlighted the value of strengthened customer relationships and enhanced brand reputation through consistently delivering a higher-quality product. By translating these technical improvements into direct financial impact, Prohan gained a clear view of the return on their investment before the project even began.
Proving value through a phased rollout
To demonstrate value quickly and minimize risk, phase one focused on a single, fully functional inspection system at the critical post-gluing station. This system delivered tangible results that both technical and business teams could measure directly against the agreed-upon KPIs, creating a benchmark for future scaling. This pilot-first approach gave Prohan a confident, low-risk path toward full-scale development while proving the solution’s effectiveness before committing to a broader implementation.
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Low-risk pilot delivered measurable results for further investment
Prohan left the workshop with a complete project blueprint, including an annotated process map, optics and lighting specifications, a documented user journey, an OT/IT integration plan, the official defect taxonomy, a data acquisition plan, the KPI and ROI model, and a phased development roadmap.
This planning directly enabled a successful implementation. The system now achieves 90% defect detection accuracy, eliminating customer returns for glue-line gaps and restoring confidence in Prohan’s product quality.
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