Make every tightening operation
traceable.
Tightening process control and assembly quality analysis
Plan tightening, carry out assembly, diagnose deviations and improve the next batch.
Trace work from an individual bolt to the joint group and field assembly.
After seating, apply load through rotation while tracking torque and bolt force.
- torque N·m
- 38.5
- rotation angle °
- 62.5
- axial force kN
- 15.1
Compare the process trajectory with the target.
Planning demonstration. Change the target, lubrication and stiffness to see how the strategy and process variables respond. The teaching model and values are for illustration.
Look at how you reached
the final value.
View process stages, envelopes and evidence of deviations together.
Go beyond pass or fail to identify where a deviation occurred and why it warrants review.
Check whether the target was reached and how it was reached.
Continue viewing the establishment of preloadThe same torque can
produce different preload.
Review torque, angle and axial force over the same tightening process.
Use direct measurements when a sensor is available. Otherwise,
show the model estimate and its uncertainty range.
Planning function demonstration · Curves and intervals are synthetic examples. Virtual preload requires real sample training and independent verification. Estimated intervals do not represent verified prediction accuracy.
Meet each bolt target
and check uniformity across the group.
The previous load may change when the next bolt is tightened.
Comparison sequence, stepwise loading, and target compensation
See how a single operation affects the entire group of joints.
Select a bolt to see its target load and the current demo load.
Bolt tightening sequence and compensation jointly affect the final distribution.
Planning function demonstration · 12 bolts, 32 kN as an example. Use a simplified coupled model to explain load redistribution; actual sequence, coupling coefficient, and compensation amount need to be determined based on structure and test.
Use one batch of data
to improve the next tightening process.
Compare suppliers, surface treatments, and lubrication conditions.
Identify offset and discrete points, then convert existing samples into process recommendations.
retain basis before and after adjustment.
Each point represents a synthetic assembly sample; the shaded area is an example window of 28–36 kN.
Planning function demonstration · It is recommended to calculate based on the median friction of the current synthetic sample. Corrected mean will not automatically eliminate batch dispersion; real process optimization still requires new samples for retesting.
Fit the samples
and validate against independent measurements.
From synchronized sampling, model correction to independent re-verification.
Using the same non-linear teaching data set
Understand the difference between underfitting, proper fitting, and overfitting.
Data points used for fitting
Synthetic Inputs and Reference Values Paired, Sampling Concentrated in the Middle
| participation | Voltage / µV | Standard / N·m |
|---|---|---|
| is | 50.0 | 0.0 |
| is | 905.0 | 50.0 |
| is | 1800.0 | 100.0 |
Fitting residuals cannot replace the accuracy verification of physical measurements.
The center model converts voltage to engineering quantities on the computer; activation requires matching sensors and effective range.
Fit → retain version → read parameters → reload verification. Each step should have independent evidence.
The 8 fitting points and 4 independent test points are synthetic. This example shows how noise and sparse sampling can lead to overfitting with higher-order models.
Trace an anomaly
back through the evidence.
Associate bolt numbering, work process, tool calibration, and reinspection.
AI-assisted positioning based on evidence, engineers complete the review;
The Same Record Continues into Quality Report and Field System
Final tightening torque enters the window, load deviation from the reference envelope is in the middle.
- Process / version
- Torque-angle method P-03
- Final torque / axial force
- 80.0 N·m28.6 kN
- Tool / Calibration version
- T-01 CAL-007
- Batch / operator
- B-DEMO example operator
Follow the evidence through the analysis.
Starting from the record, associate the abnormal interval, reference process, and calibration version to form a verifiable explanation.
AI workflow illustration · This uses a preset explanation corresponding to the recorded data, without calling an online model.
History, personnel, equipment number, and date are all demonstration data. Actual applications are composed of original records, rule versions, and audit results as a complete evidence chain; the web page does not write data to MES.
A workbench for
measurement and calibration.
The current development version supports torque and force measurement, record playback, center and wrench calibration, as well as AI-assisted operations. The following shows the actual working area.
Desktop software actual interface · test data
Implemented functions include torque and force measurement, center and wrench calibration, record review, and AI-assisted operation. Angle acquisition, assembly strategies, process quality decisions, joint grouping, and batch traceability are future directions. Hardware measurement accuracy, physical recalibration, and parameter retention after power loss still require validation.
Joint design, field assembly and service.
TD Atlas Provide knowledge, standards, and engineering data support. For complex connection groups,TD Nexus The overall analysis can be used to study preload distribution and assembly conditions. When involving thread profile and engagement area details, further reference can be made. TD Forge research method
Cross-product data collaboration belongs to the kit planning direction, specific integration is subject to official release notes.
Keep a more complete record
of your next tightening operation.
Communication assembly and measurement requirementsTD Cadence · Intelligent control and quality analysis of the intelligent fastening assembly process