In-process Measurement Research Articles

Fundamental investigation of process stabilization through combined modification of milling tools with structured functional surfaces and asymmetric dynamic properties

AbstractDisturbance factors, such as self-excited tool vibrations, limit the performance of modern machining processes and thus restrict the quality, productivity, and sustainability of industrially manufactured components. Tools with functional flank-face structures as well as asymmetric dynamic properties represent two approaches that are capable of reducing such dynamic disturbances. Since up to now both approaches have solely been investigated separately, a hybrid concept was developed, applied, and evaluated that combines both techniques and exploits synergistic effects. It was shown that the compliance of milling tools can be specifically adjusted by appropriate dimensioning of laterally inserted grooves on the tool shank. In addition, a preparation of the cutting edges, e.g. applying surface structures, are still feasible. The effect of such a hybrid tool modification was evaluated based on in-process measurements and workpiece analyses. An increase of the process stability and, thus material removal rate of 85% compared to non-modified tools could be achieved, which also exceeded the stabilizing potential of tools that include only one modification approach.

Characterization and Optimization of a Locally Boron-Doped Diamond Tool for Self-sensing of Cutting Temperature

High-sensitivity and rapid-response measurements of micro zone cutting temperature are crucial for characterizing and optimizing machining states in the ultra-precision cutting process. This innovative method uses a locally boron-doped diamond (LBDD) tool itself as the sensor for in-process measurements of cutting temperature. However, the heterogeneity of boron doping and the resulting lattice distortions considerably affect the mechanical properties and temperature-sensing performances of the tool. In this work, optimized synthesis processes and structural designs for LBDD tools that function as self-sensing cutting temperature devices were proposed. Annealing treatments under high-pressure conditions were conducted to promote the diffusion and ionization of boron multimers in the boron-doped diamond zone, thereby enhancing the crystal quality and semiconductor electrical properties of the LBDD. Various LBDDs with thin-layer temperature-sensing structures of different doping concentrations and thicknesses were synthesized. The optimal components and structures were identified as the temperature-sensing cutting tool through comparative analyses of temperature measurement capabilities and semiconductor properties. The selected tool was employed for in-process cutting temperature measurement during single-point diamond turning of copper and carbon fiber. Results indicate that the LBDD tool can accurately monitor cutting temperature during steady cutting processes and identify the micromorphological features of the machined surfaces based on cutting temperature characteristics. These insights are pivotal for controlling cutting temperature and refining the ultra-precision cutting process.

A Case Study on Assessing the Capability and Applicability of an Articulated Arm Coordinate Measuring Machine and a Touch-Trigger Probe for On-Machine Measurement

In modern manufacturing, there is an increasing demand for reliable in-process measurement methods directly on large CNC machine tools, eliminating the need to transport workpieces to metrological laboratories. This study assesses the capability and applicability of an articulated arm coordinate measuring machine and a machine tool touch-trigger probe when measuring to a specified tolerance of 0.05 mm in a production environment. Experiments were conducted using the KOBA calibration standard and included measurements with and without applying the articulated arm coordinate measuring machine leapfrog method. The results were evaluated according to ISO 22514-7:2021 and ISO 14253-1:2017, which establish criteria for measurement system capability. The findings revealed that neither measurement system met the capability requirements of ISO 22514-7:2021, particularly due to unsatisfactory QMS and CMS values. However, under ISO 14253-1:2017, both systems were deemed conditionally suitable for verifying conformity to the specifications, with the articulated arm coordinate measuring machine showing lower applicability when using the leapfrog method. This research supports the idea that unreasonable demands for compliance with current standards may lead to questioning of the systems that previously met older standards. The study contributes to the ongoing discussion on integrating advanced metrological tools into the manufacturing process and underscores the need for careful evaluation to ensure the capability and reliability of measurement systems in industrial practice.

Image processing framework for in-process shaft diameter measurement on legacy manual machines

Image processing framework for in-process shaft diameter measurement on legacy manual machines

AFSD-Physics: Exploring the governing equations of temperature evolution during additive friction stir deposition by a human-AI teaming approach

This paper presents a modeling effort to explore the underlying physics of temperature evolution during additive friction stir deposition (AFSD) by a human-AI teaming approach. AFSD is an emerging solid-state additive manufacturing technology that deposits materials without melting. However, both process modeling and modeling of the AFSD tool are at an early stage. In this paper, a human-AI teaming approach is proposed to combine models based on first principles with AI. The resulting human-informed machine learning method, denoted as AFSD-Physics, can effectively learn the governing equations of temperature evolution at the tool and the build from in-process measurements. Experiments are designed and conducted to collect in-process measurements for the deposition of aluminum 7075 with a total of 30 layers. The acquired governing equations are physically interpretable models with low computational cost and high accuracy. Model predictions show good agreement with the measurements. Experimental validation with new process parameters demonstrates the model’s generalizability and potential for use in tool temperature control and process optimization.

A new negative pressure approach for in-process 2D laser sensor measurement with coolant condition

The in-process optical measurement can provide precise and fast response measurement result to improve machining quality and efficiency. However, the coolant used during machining process would block the optical measurement path and prevent the measurement. Several existing coolant displacing approaches, which utilize air/water/coolant to resist incoming coolant, can help single point laser sensor conduct measurement with coolant condition. Nowadays, the 2D laser sensor is being used more frequently to increase measurement efficiency and to get real-time 3D workpiece profile. To help 2D laser senor to measure workpiece surface with coolant condition, this paper proposed a negative pressure approach. This approach utilizes the negative pressure to suck air/coolant away from measurement window. The experimental results show that the proposed approach can help 2D laser sensor conduct measurement on workpiece surface, even when the workpiece is submerged in coolant with a thickness of Tc = 12 mm. For the measurement on workpiece with PV value of 151.2 μm, the relative uncertainty of 2σ is up to 0.71 %, where the standard deviation is up to 0.536 μm. The experimental results also show that, when compare the new proposed approach with existing coolant displacing approaches, the measurement window size could increase by 7.8 times, and the measurement efficiency could increase by 789 times. This study shows that the new negative pressure approach could help 2D laser sensor successfully conduct measurement with coolant condition, therefore it significantly improves the in-process optical measurement efficiency and makes it possible to get 3D workpiece profile in real-time with coolant condition.

Feature-Model-Based In-Process Measurement of Machining Precision Using Computer Vision

In-process measurement of machining precision is of great importance to advanced manufacturing, which is an essential technology to realize compensation machining. In terms of cost-effectiveness and repeatability of computer vision, it has become a trend to replace traditional manual measurement with computer vision measurement. In this paper, an in-process measurement method is proposed to improve precision and reduce the costs of machining precision. Firstly, a universal features model framework of machining parts is established to analyze the CAD model and give standard information on the machining features. Secondly, a window generator is proposed to adaptively crop the image of the machining part according to the size of features. Then, the automatic detection of the edges of machining features is performed based on regions of interest (ROIs) from the cropped image. Finally, the measurement of machining precision is realized through a Hough transform on the detected edges. To verify the effectiveness of the proposed method, a series of in-process measurement experiments were carried out on machined parts with various features and sheet metal parts, such as dimensional accuracy measurement tests, straightness measurement tests, and roundness measurement tests under the same part conditions. The best measurement accuracy of this method for dimensional accuracy, straightness, and roundness were 99%, 97%, and 96%, respectively. In comparison, precision measurement experiments were conducted under the same conditions using the Canny edge detection algorithm, the sub-pixel edge detection algorithm, and the Otsu–Canny edge detection algorithm. Experimental results show that the feature-model-based in-process measurement of machining precision using computer vision demonstrates superiority and effectiveness among various measurement methods.

Optical tool deflection measurement approach using shadow imaging

In incremental sheet forming, geometrical deviations occur due to deflections of the forming stylus. To compensate the deviations, a non-contact in-process tool deflection measurement is required that is capable of measuring the tool tip position with a measurement uncertainty of 15 μm in a volume of 2.0 m × 1.0 m × 0.2 m. For this purpose, an optical multi-sensor system is designed. Each sensor evaluates lateral shift and magnification of the shadow cast from the LED attached close to the tool tip, to enable measuring the lateral and axial tool tip position component, respectively. The experimental validation shows that the sensing principle is sufficiently robust regarding ambient light. As a result, despite a remaining systematic error after calibration that dominates the uncertainty, the measurement requirements are fulfilled by a single sensor regarding the lateral position component. For the axial position component, a triangulation with two sensors is necessary.

IMPATIENT-qPCR: monitoring SELEX success during in vitro aptamer evolution

SELEX (Systematic Evolution of Ligands by Exponential enrichment) processes aim on the evolution of high-affinity aptamers as binding entities in diagnostics and biosensing. Aptamers can represent game-changers as constituents of diagnostic assays for the management of instantly occurring infectious diseases or other health threats. Without in-process quality control measures SELEX suffers from low overall success rates. We present a quantitative PCR method for fast and easy quantification of aptamers bound to their targets. Simultaneous determination of melting temperatures (Tm) of each SELEX round delivers information on the evolutionary success via the correlation of increasing GC content and Tm alone with a round-wise increase of aptamer affinity to the respective target. Based on nine successful and published previous SELEX processes, in which the evolution/selection of aptamer affinity/specificity was demonstrated, we here show the functionality of the IMPATIENT-qPCR for polyclonal aptamer libraries and resulting individual aptamers. Based on the ease of this new evolution quality control, we hope to introduce it as a valuable tool to accelerate SELEX processes in general.IMPATIENT-qPCR SELEX success monitoring. Selection and evolution of high-affinity aptamers using SELEX technology with direct aptamer evolution monitoring using melting curve shifting analyses to higher Tm by quantitative PCR with fluorescence dye SYBR Green I.Key points• Fast and easy analysis.• Universal applicability shown for a series of real successful projects.Graphical

Design of a multi-modal sensor for the in-process measurement of material properties based on inductive spectroscopy

Ferromagnetic steel magnetic properties undergo isotropic and anisotropic changes during cold forming processes. Although their measurement provides an important basis for material property-controlled process control, it remains particularly challenging, as workpieces are subjected to several influencing effects, such as tilting and distance to the target. In this paper, we propose a robust contactless multi-modal sensor for the in-process measurement of material magnetic properties composed of a central excitation coil surrounded by eight receiving coils. The material magnetic permeability is measured based on a model-based evaluation of the central coil inductance spectrum compensating for the influence of the distance to the target. The sensor realizes a measurement of the magnetic anisotropy independently of the tilting effects based on an FFT-based analysis of the induced voltage in the peripheral coils. The sensor has been validated in a tensile test experiment on standard specimens. The measurement data of the tensile test reveal a systematic relation of permeability and magnetic anisotropy to the mechanical influences of stress and deformation. The measurements remained stable despite strong movements between the sensor and the target. A working distance increase of 80% resulted in variations of the magnetic permeability of only 3%. The observed changes in magnetic anisotropy are uncorrelated to tilting effects. Based on the investigation results a proposal for the design of an in-process measurement system is provided.

Special Issue on On-Machine and In-Process Measurement for Smart and Precision Manufacturing

The Internet of Things is playing an important role, organizing all things that use data and connecting them to the Internet. It has been made possible by the rapid progress in smart and real-time measurement technologies, the miniaturization and speeding up of sensor technologies as well as intelligent data processors, and by the spread of cloud technology, which accumulates huge amounts of data. To establish smart and precision manufacturing, not only the improvement of conventional ultraprecision machining techniques but also the development of the novel, high-performance machining techniques has been made. On-machine and in-process measurement are gaining in importance for emerging machining technologies as well as conventional ones. Advanced techniques of machining and metrology as well as feedback for compensation manufacturing have been required for plasticity to on-machine and in-process conditions. This special issue focuses on metrology and manufacturing measurement and instrumentation for the progress of state-of-the-art on-machine and in-process measurement systems and sensor technologies. It consists of contributions related to, but not limited to, the following topics: - On-machine, in-process measurement and process monitoring - Practical application of on-machine, in-process measurement - Machine tool metrology - Intelligent micro- and nano-metrology - Multi-sensor fusion and multi-sensor cooperation - Form and dimensional measurement and instrumentation - 3D-surface texture and its micro-characteristics - Machine learning, AI aided measurement We would like to sincerely thank all the authors for their contributions, and we sincerely hope that the papers in this special issue further contribute to the development of our future society from a new horizon of metrology.

Phase Retrieval Algorithm for Surface Topography Measurement Using Multi-Wavelength Scattering Spectroscopy

We are currently developing a high-precision and wide-range in-process surface topography measurement system using the laser inverse scattering method. In the laser inverse scattering method, a monochromatic plane wave is illuminated perpendicular to the target surface and the surface topography is measured by retrieving the phase distribution of the reflected light. However, the dynamic range of this method is limited to the sub-micrometer range because of phase wrapping during phase retrieval. In this paper, we propose a laser inverse scattering method using a multi-wavelength light source based on the fact that the phase of light is inversely proportional to the wavelength with the propagation distance as a coefficient. We also constructed a surface profilometer based on the proposed method and measured the profile of a single rectangular groove with a width of 50 µm and a depth of 2 µm. The dimensions of the measured profiles agree well with the nominal dimensions of the rectangular groove.

Shock Wave Detection for In-Process Depth Measurement in Laser Ablation Using a Photonic Nanojet

Three-dimensional micro- and submicrometer-scale structures exhibit unique functions that cannot be obtained with bulk materials. To create such three-dimensional microstructures with high precision and efficiency, we proposed laser ablation using a photonic nanojet. A photonic nanojet is an optical beam with both a small beam diameter and a large depth of focus, which is obtained by irradiating a dielectric microsphere using a laser beam. In this study, we proposed an in-process depth measurement method to improve the machining accuracy of laser ablation using a photonic nanojet. We focused on the propagation characteristics of the shock waves generated during laser ablation. Shock waves were generated at the deepest point of the machining area and reached the microspheres as the pressure decayed, showing that different machining depths exerted different pressures on the microspheres. The microspheres were displaced by the pressure of the shock wave, and the amount of displacement depended on the pressure. Therefore, microspheres can be used as probes for shock wave detection, and the machining depth can be determined by measuring the displacement of microspheres during photonic nanojet machining. In this study, the displacement of a microsphere was measured simultaneously during photonic nanojet machining using a confocal optical system. From the obtained microsphere vibration data, the effect of the shock wave pressure was extracted, and the displacement of the microsphere due to the shock wave was obtained. When the hole depth varied from 155 to 1121 nm, the displacement of the microspheres varied from 0.58 to 0.03 µm. The experimental results show that the displacement of the microspheres vibrated by the shock wave decreased as the machining depth increased. This was due to an increase in the shock wave propagation distance and a decrease in the pressure of the shock wave as the machining depth increased. In conclusion, in-process depth measurements are possible in laser ablation using a photonic nanojet with a microsphere as a probe to detect shock waves.

Sensor-integrated clamping device for machining of AM components

Additive manufacturing processes, such as Laser Powder Bed Fusion (LPBF), provide a high degree of design freedom enabling, for example, the manufacturing of load-optimized lightweight structures. However, this design flexibility is challenging with respect to the required post-processing, e.g., by machining operations. In particular, the selection of a suitable clamping configuration is essential to avoid shape deviations due to too high clamping forces. In this paper, an approach for monitoring the load during milling of an additively manufactured component is presented, in which in-process force measurements with a sensor-integrated clamping device are used.

Structured-light 3D Scanning Performance in Offline and In-process Measurement of 3D Printed Parts

This paper presents a geometric analysis comparison of structured-light 3D scanners against coordinate measuring machines (CMMs) in measuring 3D printed plastic parts. The resulting geometric analysis of a 3D printed part measured with a contact probe on a CMM and measured with a structured light 3D scanner is presented, along with an error analysis that includes a statistical comparison of the measured geometric deviation. This analysis is then used to determine if structured-light 3D scanners are reliable enough to perform a GD&T analysis of specific features. This paper also presents the results of in-process 3D scanning and compares them to offline 3D scanning to determine the suitability of in-process 3D scanning for comprehensive analysis of geometric deviation and GD&T features.

In-situ assessment of laser-chemically machined surfaces by means of an indirect optical measurement approach and scanning confocal fluorescence microscopy

The manufacturing rate of laser-chemical machining (LCM) is limited to avoid disruptive boiling bubbles in the process fluid. Adjustments to e.g. the laser beam or the fluid properties can increase the removal rate. However, the existing understanding of the surface removal mechanisms is insufficient to ensure the removal quality under these conditions. Thus, near-process measurements of the surface geometry and the surface temperature are required for an improved process modeling. Due to the complex process environment, no suitable in-process measurement technique for the geometry or surface temperature exists so far. This contribution presents an indirect geometry measurement approach based on scanning confocal fluorescence microscopy that is integrated into the LCM plant. As a result, it is shown that the approx. 200 μm deep micro-geometry of laser-chemically processed surfaces can be indirectly measured in-situ, i.e. inside the LCM system. The realized setup is designed in such a way that in future it will be additionally possible to measure the temperature by means of the fluorescence life-time.

Real-Time In-Process Measurement and Control of Zinc Coating Weight: Assessing Eddy Current Sensor Proficiency in Industrial Applications

Real-Time In-Process Measurement and Control of Zinc Coating Weight: Assessing Eddy Current Sensor Proficiency in Industrial Applications

A process-reliable tailoring of subsurface properties during cryogenic turning using dynamic process control

Considering the current demands for resource conservation and energy efficiency, innovative machining concepts and increased process reliability have a significant role to play. A combination of martensitic hardening of the subsurface and near-net-shape manufacturing represent a great potential to produce components with wear-resistant subsurfaces in an energy- and time-saving way. Within the scope of the present study, the influence of cryogenic machining of metastable austenitic steel on the martensitic transformation and surface quality was investigated. Different cooling strategies were used. A soft sensor based on eddy current in-process measurements was used to determine and subsequently affect the martensitic transformation of the subsurface. The feed rate and component temperature were identified as significant factors influencing the martensitic transformation. However, a high feed rate leads to an increase in surface roughness, and thus to a reduction in component quality. For this reason, a roughing process for achieving maximum martensitic transformation was carried out first in the present study and then a reduction in the surface roughness by maintaining the martensitic subsurface content was aimed for by a subsequent finishing process. With the knowledge generated, a dynamic process control was finally set up for designing the turning process of a required subsurface condition and surface quality.

Shadow-Imaging-Based Triangulation Approach for Tool Deflection Measurement.

As incrementally formed sheets show large geometric deviations resulting from the deflection of the forming tool, an in-process measurement of the tool tip position is required. In order to cover a measuring volume of 2.0 m × 1.0 m × 0.2 m and to achieve measuring uncertainties of less than 50 µm, a multi-sensor system based on triangulation is realized. Each shadow imaging sensor in the multi-sensor system evaluates the direction vector to an LED attached to the tool, and the three-dimensional position of the LED is then determined from the combination of two sensors. Experimental results show that the angle of view from the sensor to the LED limits both the measurement range and the measurement uncertainty. The measurement uncertainty is dominated by systematic deviations, but these can be compensated, so that the measurement uncertainty required for measuring the tool tip position in the ISF is achieved.

Design and Analysis of Ultra-Precision Smart Cutting Tool for In-Process Force Measurement and Tool Nanopositioning in Ultra-High-Precision Single-Point Diamond Turning.

Ultra-high-precision single-point diamond turning (SPDT) is the state-of-the-art machining technology for the advanced manufacturing of critical components with an optical surface finish and surface roughness down to one nanometer. One of the critical factors that directly affects the quality of the diamond-cutting process is the cutting force. Increasing the cutting force can induce tool wear, increase the cutting temperature, and amplify the positioning errors of the diamond tool caused by the applied cutting force. It is important to measure the cutting force during the SPDT process to monitor the tool wear and surface defects in real time. By measuring the cutting force in different cutting conditions, the optimum cutting parameters can be determined and the best surface accuracies with minimum surface roughness can be achieved. In this study a smart cutting tool for in-process force measurement and nanopositioning of the cutting tool for compensating the displacements of the diamond tool during the cutting process is designed and analyzed. The proposed smart cutting tool can measure applied forces to the diamond tool and correct the nanometric positioning displacements of the diamond tool in three dimensions. The proposed cutting tool is wireless and can be used in hybrid and intelligent SPDT platforms to achieve the best results in terms of optical surface finish. The simulation results are shown to be almost consistent with the results of the derived analytical model. The preliminary results pave the way for promising applications of the proposed smart cutting tool in SPDT applications in the future.