Projects / BAM

BAM: data and control for a 3D concrete printing rig

Five years as the only software and data engineer on a research rig: real-time OPC UA ingestion across the PLC network, an in-house control stack, closed-loop bead-width control, statistical process control, and 5+ publications (2 as first author). Since May 2026, as a guest researcher, I rebuilt its acquisition and storage layer: sensor ingestion up 5×, lossless Parquet storage, and a private API serving layer.

Data

• Lossless storage for high-frequency machine data: raw logs into Parquet with session manifests and schema-drift capture, up to 6.4× smaller, queried with DuckDB.

Process engineering

• Parameter sweeps that defined a stable printing window and cut failed prints, where one failed print cost a day of material and rig time.
• A mass balance for a continuous mixer with no solids measurement, from timed nozzle weighings and a stirred-tank model, giving an online water-to-solids ratio.
• Water-valve-to-torque dynamics identified from routine production data, and PI versus model-predictive water control compared in a simulator that replays real prints (simulation).

Mechanical engineering and instrumentation

• A pumping line instrumented with pressure and temperature transmitters, a vortex flow meter and a proportional water valve, with 4 to 20 mA loop fault detection.
• The rig's support grillage designed in Siemens Solid Edge and machined.

Projects and operations

• A research rig taken from concept and component specification through build, commissioning and handover; supplier offers compared and deliveries accepted.
• About EUR 30,000 saved by replacing a quoted commercial control package with an in-house Python, OPC UA and Node-RED stack.
• Operators trained, runbooks and checklists written, statistical process control with material QC tests.