The machining workflow was designed to isolate the effect of tool shape and motion control on dimensional variation. Each variable was assigned a fixed range, and sample processing followed an identical sequence to ensure reproducibility. All cutting tools were inspected before and after each batch to eliminate edge-wear interference.

Raw datasets were produced through controlled machining trials. Measurement readings were obtained using a calibrated coordinate measuring machine (CMM), a surface profilometer, and high-speed accelerometers placed near the tool post. Previously published tolerance datasets were used as comparative references to benchmark performance.

• Machining Equipment: 5-axis CNC turning center with motorized spindle

• Cutting Tools: Carbide inserts (0.4 / 0.8 mm nose radius)

• Measurement Instruments: CMM (±1 μm), profilometer (Resolution 0.01 μm), dual-axis vibration sensors

• Statistical Models: Multivariate regression for tolerance deviation; spectral analysis for vibration patterns
  All parameters, formulas, and sequences were documented to allow full procedural replication.

Measured dimensional deviations decreased when insert radius increased from 0.4 mm to 0.8 mm. The improved radius reduced tool deflection, leading to a mean deviation reduction from 12 μm to 7 μm. This agrees with reference data showing similar reductions in mid-strength alloys.

Table 1 summarizes average deviation across materials.

Surface roughness Ra improved consistently when spindle speed was stabilized within ±15 rpm. The profilometer recorded a 27% improvement in aluminum samples and an 18% improvement in mild steel. This pattern aligns with spectral vibration peaks that shifted downward as tool-workpiece resonance decreased.

Compared with existing studies, the test results show a narrower distribution of tolerance errors when thermal drift was compensated every 20 minutes. Published work typically reports wider variance for un-compensated machining cycles, highlighting the significance of temperature control in small-batch turning.

The reduction in dimensional deviation is primarily linked to lower lateral tool vibration. The increased insert radius generated a more stable contact path, resulting in smoother chip flow and reduced thermal stress. Consistent spindle speed further minimized dynamic changes in cutting force, supporting stable roughness levels.

The study focused on two materials and a single class of carbide inserts. Cutting fluids, machine rigidity levels, and hybrid tooling strategies were not evaluated. These factors could influence results under different industrial setups.

The reproducible process demonstrates a practical path for factories aiming to improve turning accuracy, particularly in mixed-material orders or high-precision prototype work. Factories can integrate vibration monitoring and thermal calibration into existing workflows with moderate cost.

The machining tests show that balancing insert geometry with controlled spindle speed provides measurable gains in dimensional stability and surface quality. Consistent thermal compensation strengthens tolerance repeatability in aluminum and mild steel turning. The validated workflow offers a scalable technical reference for precision manufacturers and suggests further examination of tool coatings, coolant strategies, and multi-material optimization.