January 2026
The system launched in January 2026 placed quality processes at the center of the system, going beyond classic stock and accounting tracking. The goal was to keep the data generated from the moment a production order is opened through to the shipment or rework decision for the product linked together. This made it possible to see, retrospectively, not just what was produced, but by which method and under which process conditions.
On the quality side of the program, topics such as control plans, nonconformity records, corrective actions, measurement results, equipment and calibration tracking, raw material acceptance, in-process control points and final product approval were addressed within a shared workflow. The aim was for a nonconformity not to be recorded merely as a note, but to be linked to the relevant work order, material batch, process step and product family.
This approach made it easier to see whether the same type of problem was recurring across different projects and to measure the results of process changes. Revisions to production recipes, approved technical documents and control criteria were managed through the same system, aiming to reduce the gap between practices in the field and up-to-date engineering data.
A company's digital twin is not just a 3D facility model or a visual management dashboard. It requires representing the actual production flow, capacity utilization, quality trends, material movements and decision points with current data. For this, the data must first be standardized, relatable and comparable over time.
For this reason, the ERP program Tulkas developed was designed as the data backbone of the AI-based digital twin. The historical data collected from the system is intended to be usable in later stages for areas such as lead-time estimation, capacity planning, nonconformity trend analysis, maintenance needs, process deviation and cost analysis. The initial rollout in January 2026 was the step of building the necessary institutional memory and data discipline before the AI model.
Tulkas treats digital transformation not as a one-time software installation, but as a phased engineering program that evolves together with production and quality processes. In the first phase, focus was placed on core data models, work-order flows, product and material traceability, and standardization of quality records.
In later phases, the goals are to bring machine data into the system, automatically capture data from measurement devices, compare actual production against plans, and develop decision-support algorithms. In this way, Tulkas is building a digital operating infrastructure capable of managing its growing process and product variety without relying solely on human memory.
Tulkas continues to develop its digital quality and production management infrastructure not only for internal operational efficiency, but also to offer customers higher traceability and repeatable quality.
Tulkas Develops a Four-Axis Cutting Machine for Precision Fiber Cutting in Prepreg Production
Tulkas Mühendislik developed a four-axis fiber cutting machine in 2019 to prepare ply geometries for prepreg composite production with precision and repeatability.
