Abstract
The regeneration of complex capital goods is dominated by manual labor and experience-based decisions about machining measures. The functional condition, which describes how well a part performs its task, is unknown before and after regeneration. Instead, the target geometries for the regeneration are based on continuity constraints and subjective assessments. In this study, a new type of process chain for condition- based regeneration is developed that selects the machining measures based on the achievable functional condition, the production effort as well as customer requirements. This allows a targeted and efficient decision on a regeneration process based on the customer requirements for the functional condition. A proof-of-concept process chain was successfully built to demonstrate the feasibility of this novel approach. It was shown that the concept is realizable with currently available technologies and that the functional assessment has minor influence on the regeneration time.
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1 Introduction
Currently, decisions about the repair measures in process chains for the regeneration of complex capital goods are often experience-based or dependent on geometric dimensions. Through manual machining with belt grinders or rotary tools, the skill and experience of the employee affect the result of the regeneration. Furthermore, the decisions are not always understandable, and the same good can be regenerated differently.
This results in different functional conditions and production efforts for each part, dependent on the executing employee (Tsong-Jye Ng et al. 2004).
One example of complex capital goods is aircraft engines. These engines are inspected and disassembled at fixed intervals, and damaged parts are repaired or replaced. Due to the high cost of new parts, regeneration is an economical alternative to replacement (Aschenbruck et al. 2014).
The typical regeneration process of aircraft engines starts with the disassembly, a cleaning process, and an inspection. Besides a visual inspection, computed tomography scans and x-ray inspection are used (Raj et al. 2000). Regulations then specify which damages are repairable. Generally, small dents can be removed by blend repair (N3Engine Overhaul Services 2011). For material deposition, soldering and welding are primarily used. In addition to the complete additive build-up of damaged areas of the blade, additional a patch of the same material can be welded on the blade (Eberlein 2007). Excess material is mostly machined manually either with rotary tools or with a belt grinder (Yilmaz et al. 2005). If the recontouring is automated, industrial robots in combination with a belt grinder or other machine tools are often used (Huang et al. 2002).
The automation of process chains for the regeneration of individual process steps is the focus of different research projects (Denkena et al. 2015; M'Saoubi et al. 2015). Besides an increase in productivity, quality, or repeatability, the emphasis is on substituting human workers with machines. Without automation and machine tools, or the optimization of machining processes themselves, an efficient regeneration process remains unachievable. The reason for this is that customers are primarily interested in the functional condition of the whole engine and not in compliance with geometric tolerances. Since the functional condition of the blade and its influence on the functional condition of the engine is unknown, an efficient and functional condition-oriented regeneration is not possible with the currently available technologies and process chains.
2 Objective
The objective of subproject S: “system demonstrator” of the collaborative research centre (CRC) 871, was to develop a process chain for condition-based regeneration and prove the feasibility using the example of high-pressure turbine blades. To achieve this, research results of nearly all subprojects of the CRC were integrated into something we called “system demonstrator”. Besides the proof-of-concept of condition-based regeneration, the goal was to transfer the research results into the industry and give new impulses for future production systems.
In this new type of process chain, decisions about the machining measures are based on the customer's requirements on the functional condition, considering the production effort. The hypothesis is that through the integration of functional assessment and manufacturing simulations into an automated process chain it is possible to determine the feasible functional condition before the machining is executed. These high-fidelity functional and manufacturing simulations, which are computationally expensive and require extensive manual set-up efforts, are only used in product development.
In chapter “Multiscale Measurement of Blade Geometries with Robot-Supported, Laser-Positioned Multi-Sensor-Techniques”, the structure, all components of the newly developed process chain, and the regeneration procedure are described. In chapter “Exhaust Jet Analysis”, the condition-based approach is exemplified with one regeneration, and a summary of recommendations for industrial applications is provided.
3 Structure of the Condition-Based Process Chain
In the second funding period of CRC 871, a structure for a condition-based regeneration was developed (Fig. 1) (Aschenbruck et al. 2014). It consists of two layers, the real and virtual layers. The real layer includes measuring and inspection cells, as well as machine tools for automated machining. A virtual layer is included in the process chain to calculate the functional condition. Besides the functional assessment, manufacturing simulations and job scheduling are integrated through this layer. To connect both layers, a digital workpiece twin is used as the sole interface for the data.
At the beginning of the process chain, the blade is disassembled and inspected in the real layer. After a preliminary decision in which the repairability of the blade is determined, the functional condition of the operationally stressed blade is assessed.
Machining is divided into different paths. For each path, manufacturing simulations (process simulations) are used to calculate the changes in the geometry, the process times, and the manufacturing costs. In the functional assessment, these changes in the geometry are used to determine the achievable functional condition. In a subsequent evaluation, the achievable functional condition, process times, and process cost for all paths are compared with the customer’s requirements. The path that best fits the customer’s requirements is selected and executed in the real layer. Afterward, the engine is reassembled, and an acceptance test is carried out.
3.1 Flexible Manufacturing System for the Condition-Based Regeneration
For the proof-of-concept of condition-based regeneration, a system that can integrate all of the regeneration necessary process technologies is built. The manufacturing processes are automated to better predict the results. This reduces the variances in machining times. Due to the high individuality of the operationally stressed components and the resulting variances, the machining times and necessary process steps vary for each workpiece. A fixed sequence of cells and machines is, therefore, not recommended. Also, some machines are used more than once in the regeneration process. For example, a milling center is used in preparation for welding and recontouring.
To achieve maximum flexibility in the sequence of processes, a flexible manufacturing system is chosen as a structure of the process chain for condition-based regeneration. For the handling of the workpiece, a combination of zero-point clamping modules in the machines with a workpiece carrier and a mobile handling system (MHS) is selected (Fig. 2). The MHS can transport up to seven workpiece carriers in the mobile storage and load/ unload the machines with a serial robot. It can move freely between the cells and needs no fence or barrier. Each process is executed in an individual cell, allowing the use of standard machines, e.g., milling machines or measuring cells. Expensive specialized machines can thus be avoided.
In the disassembly cell, a piezo stack actuator is used to generate dynamic impacts on the mounted blade. This can reduce the force necessary compared to a static force (Mullo et al. 2019). For measuring the geometry of the blade, a robot-based fringe projection is used. Besides this fringe projection which measures the macroscopic geometry, other measuring methods are also included. For example, a low coherence interferometer (LCI) for surface roughness, or a bidirectional reflectance distribution function (BRDF) sensor to detect burns. The measuring data of all methods can be combined through hand-eye calibration (Betker et al. 2020).
High-frequency induction thermography is used to detect cracks and other defects under the coating. A robot moves an inductor to different positions next to the stationary blade and initiates an eddy current field. Cracks constrict the effective current field, which leads to a local heat-up. A thermography camera that can be moved on 4-axis detects these small heat-ups (Bruchwald et al. 2016). For recoating after the machining, a robot-based thermal spraying process is used. Through the combined application of nickel-based filler metal needed for filling small cracks and dents, and hot gas corrosion protective layer, the coating process chain can be shortened. Because of high logistical constraints, the crack analysis and the repair coating cannot be integrated directly into the system and are replaced with a dummy cell. Through this, the process can be integrated into the process chain without a dedicated cell.
To build up material, a 5-axis laser welding machine is selected because it allows for a targeted and controlled heat input. Additional material is fed into the focus point of the laser in the form of powder through a coaxial nozzle (Kaierle et al. 2017). The machining of the blade is carried out with a 5-axis milling machine. The blade preparation for welding is executed with a flat end mill and a 2.5-axis process. The recontouring process to remove excess material after welding utilizes a ball end mill and a 5-axis process (Denkena et al. 2021a).
3.2 Digital Workpiece Twin—Universal Data Interface
To connect the real and virtual layers, a digital workpiece twin is used to store and transfer all data (Denkena et al. 2019). Although user interfaces in productive environments require individual configuration, for demonstration purposes a case in point was implemented to point out the potential of using a digital workpiece twin (Fig. 3).
The collection of different data is structured and organized through a hierarchic structure—comparable to file systems with folders and files. All elements can be enriched with arbitrary metadata, which in this case is transcribed by a list of pairs of descriptors and values. The grouping nodes can thus define collections and describe their shared attributes, while file nodes store concrete data, such as NC files, point clouds, pictures, or graphs.
3.3 Virtual Layer—Integration of Functional and Process Simulations
Direct integration of high-fidelity simulations into the process chain is not feasible due to the high setup effort, and long calculation times. Instead, the functional simulations are carried out outside the process chain based on a parameter space of a random sample of blades. The results are stored in look-up tables to reduce the calculation times.
In the virtual layer of the process chain, the point cloud of the operationally stressed blade is first read out of the digital workpiece twin and parameterized (Fig. 4). Besides the height of the blade, parameters such as the leading and trailing edge radius, chord length, stagger angle, and others are determined in 20 cutting planes (Stania and Seume 2022).
These parameters are transferred to the ‘lifetime evaluation’ where the look-up tables are used to calculate the remaining lifetime of the blade in flight cycles. The same procedure is carried out in the ‘performance evaluation’. The ‘exhaust gas temperature’ (EGT) is selected to measure the performance. An increase in the EGT corresponds with the deterioration of the performance of the turbine blades.
Besides the evaluation, the parameters are also used in the ‘Forecast’. This module first predicts the changes in the parameters through the machining for each path. Then, the parameters resulting from the machining are used with the performance and life evaluation to determine the achievable functional condition. The ‘Job Scheduling’, based on the achievable functional condition for each path in combination with the ‘Customer Requirement’, selects the path that best fits the customer (Kellenbrink et al. 2022).
3.4 Regeneration Process
The regeneration process is divided into three phases. First is the assessment and evaluation of the operational stressed blade. The second is machining. The third is quality control. In the assessment and evaluation, the first step is to disassemble the blade from the turbine disk and insert it into the workpiece carrier. Measured forces and used frequencies in the piezo stack actor are stored in the digital workpiece twin after the process is finished, as shown in Fig. 5.
If a crack is detected during crack analysis, the position and length are stored in the digital workpiece twin. After this inspection, the geometry measurement scans the blade in 13 different poses and creates a point cloud. Crack information and the point cloud are then used in the functional evaluation to predict the achievable functional condition for each path. Additionally, the process cells and times are also stored. The job scheduling reads this information out of the digital workpiece twin from all blades in the system. It optimizes the process sequence of all blades to minimize waiting times. Also, a path is selected for each blade that finished the functional evaluation. For this, the global profit, which is defined as the sum of the profit of all blades, is used.
To calculate the global profit, a heuristic approach is chosen that iterates through thousands of different work schedules. If no improvement between the iterations is achieved for 10 s time or the time limit of 45 s is expired, the algorithm stops, and the work schedule with the highest global profit is selected (Kellenbrink et al. 2022). For each blade, the selected path and all other information regarding the job schedules are stored in the digital workpiece twin.
The machining can be grouped into paths based on the machining technologies involved. Through a variation in the process parameters, for example the feed rate or the cutting depth, subvariants of a path can be created. Figure 6 shows the different paths available for selection.
If the blade has no critical damage, it can be reinstalled in path 1. If safety-relevant damages occur, this is no longer an option. In path 2, the tip is machined, and the blade is reinstalled afterward. This decreases performance and lifetime, but it is fast and cheap. Path 3 builds up a new tip on the machined surface. Because of the low accuracy of the laser welding process, recontouring is necessary to achieve the desired geometry. Path 4 adds a repair-coating process which can close small cracks or fill in dents. This process is also possible after the removal of the tip (path 5) or without machining (path 6). If the blade has damage that is not technologically or economically repairable, it can be scraped, and a new or refurbished blade will be installed instead in path 7.
After the machining, quality control ensures that only successfully repaired blades exit the process chain. The sequence of processes is shown in Fig. 7. After the blade is inspected for cracks and the regenerated geometry is measured, the functional evaluation calculates the after the machining achieved functional condition and compares this with the forecast. The difference is then used in a quality control loop to improve the forecast.
4 Execution of the Condition-Based Regeneration
Having description of the process chain, the regeneration of a high-pressure turbine blade is used to exemplify the feasibility of the condition-based regeneration approach. For this, a customer with three different quality levels for the functional condition of the blade is modeled (Table 1). It also allows the option to consider individual customer priorities dependent on the business model, e.g., cargo or passenger flights.
The willingness to pay is modeled with a linear interpolation between three support points for each quality level. In addition, the willingness to pay is dependent on the duration of the regeneration. This is the time from the insertion of the blade into the process chain up to the reassembly. Before the first support point, the willingness is static. After the third point, the willingness drops directly to 0 € (Fig. 8). In this proof- of-concept, the performance, lifetime, and regeneration time are only considered for one blade. In an industrial application, these factors should be considered for the whole engine.
4.1 Assessment and Evaluation
After disassembly, a serial robot in the disassembly cell inserts the blade into the workpiece carrier, and the MHS transports it to the crack inspection. The results of the crack inspections are a thermography image of the blade (Fig. 9) and a table with all crack positions and lengths. Both the table and the image are stored in the digital workpiece twin.
After the inspection, the blade is scanned in the geometry measurement and parameterized. Before the parametrization can determine the parameters, the point cloud of the geometry measurement needs to be processed. Because of the assembly tolerances of the workpiece carrier and the low absolute accuracy of the geometry measurement, the position and orientation of the blade vary in this coordinate system. The result is low repeatability of the parametrization. To increase the repeatability, the measured blade is first aligned to a reference blade.
For this alignment, an iterative close point algorithm is used. To increase the speed and the quality of the algorithm, the point cloud of the blade is filtered using a boundary box and downsampled. In Fig. 10, the unfiltered and filtered point clouds are shown. Because of the high wear of the tip, the upper part of the blade is filtered out due to a negative influence on the alignment. Color information of the blade is deleted to reduce the size of the file. For the subsequent parametrization, a 3D-Model with surfaces is necessary instead of a point cloud. Therefore, the initial point cloud is moved using the calculated transformation matrix from the alignment. The moved raw measurement is filtered with a different boundary box to include the tip of the blade and exclude the foundation. This is because the foundation is not considered in the parameterization and leads to errors during the triangulation, which creates the 3D-Model with surfaces.
The height can be determined after the blade is aligned. Therefore, three measuring points are used, as shown in Fig. 11a. From these measuring points, an algorithm finds the closest 12 neighboring points. If the mean distance between the measuring points and the neighboring points is smaller than the illustrated confidence interval (red circle), the median z-height of all neighboring points is used to calculate the height of the measuring point. Then, the mean of all measuring points is used for the blade height. This height is subtracted from the channel height of the engine to get the tip clearance. This is the distance between the blade and the housing, which is an important parameter for functional evaluation.
For other parameters such as the leading and trailing edge radius, the chord length, or other aerodynamic parameters, 20 cutting planes are used. They are evenly distributed on the z-axis, as visualized in Fig. 11b. The repeatability of this parametrization is discussed in Table 2.
To increase the robustness of the system, the aligned point cloud is not directly triangulated for the parametrization, as this often leads to small holes or triangulation errors in the surfaces. Therefore, the aligned point cloud is filtered 600 µm above and below each cutting plane (z-axis). Every emerging point cloud (filtered cut) is triangulated independently using an envelope body. This body guarantees that all holes are closed, or small dents, chipped coating, or rough surfaces are filtered, which increases the robustness of the system. The twenty filtered cuts around the cutting planes and the complete triangulated blade are shown in Fig. 12.
Especially very dark and dirty blades or blades with markings from felt pens would cause problems without this filter step. These surfaces do not reflect enough light, which leads to holes in the point cloud. The complete triangulated blade is saved in the digital workpiece twin, for example, for the control of the measurements by an employee.
The filtered cuts are then used in the parameterization. An algorithm forms the intersection of the filtered cut and a cutting plane to create a blade cut. With different geometric forms, for example, circles, triangles, or ellipses. The aerodynamic parameters are then determined (Fig. 13) (Stania and Seume 2022).
To evaluate the repeatability of the process, a blade is inserted into a workpiece carrier clamped in the zero-point clamping module. After one measurement, the workpiece carrier is lifted out of the clamping module and inserted again. This procedure is repeated five times while the blade remains in the workpiece carrier. The measurements are parameterized, with and without the alignment, and the range of the parameters is determined (RZPC). Additionally, the influence of the workpiece carrier on the parametrization is examined. For this purpose, the same procedure was used, with the exception that between measurements the blade was unclamped from the workpiece carrier and placed in another one (RWC). The results are shown in Table 2.
The alignment reduces the range of the parameters and thus the influence of the unavoidable measurement uncertainties, manufacturing, and assembly tolerances on the functional assessment. The achieved span is acceptable for the used measurement technologies but can be further reduced by using a coordinate measurement machine.
4.2 Functional Evaluation
For the calculation of the functional condition, FEM-simulations and CFD-simulations are used. These are normally only utilized in product development for an ideal geometry, requiring a manual setup and have long calculating times up to numerous weeks. To reduce the calculating and therefore waiting time in the process chain, these simulations are done in advance using a parameter model of the blade. The parameter space for this parametric simulation is derived from a random sample.
In the process chain, the parametrization-determined parameters are used in combination with the lookup table to get a quick assessment of the functional condition. Repeating calculations can also be avoided. If the parameters of a blade exceed the parameter space, it can be expanded outside the process chain.
The number of parameters considered to determine the functional state is arbitrary. The lookup table for the performance, for example, includes the leading-edge radius, tip clearance, and roughness. Between simulated support points, interpolation is performed to decrease the number of necessary simulations.
4.3 Forecast of the Achievable Functional Condition
For the selection of the regeneration measures, the functional condition of the operationally stressed blade is not relevant. Rather, the repair achievable one is. The forecast necessary for this is executed in a separate software module after the evaluation of the operationally stressed blade. First, each path is checked for its technical feasibility (Fig. 14). Afterward, process simulations predict the changes in the parameters for each path and the production effort. This can be divided into process times and cost. For each path with the changed parameters and the functional evaluation, the achievable functional condition is calculated and afterward stored in the digital workpiece twin.
For example, in Table 3 the forecast of a typical blade is shown. Paths 1–3 are not included since they are not able technically to regenerate all the damage. Due to a lack of space, all processes and process times have not been listed.
The job scheduling is executed after the forecast is finished. Because only one blade is in the system, it can directly calculate the duration of the regeneration without waiting times due to the limited capacity of the machines. The customer´s willingness to pay can be determined based on the achieved quality level of the path and the duration of the regeneration. If the costs are deducted from the willingness to pay, this results in a profit, as shown in Table 4. The path with the highest profit is selected, and a work plan is created. If more than one blade is in the system, the job scheduling selects the paths that lead to the maximum global profit. The selected path for each blade must not necessarily be the path with the highest profit due to the capacity limitations of the machines.
4.4 Machining
For the typical blade, the job scheduling selects path 6 based on the possible profit, even if it only achieves quality level B. The machining in this path is carried out by a robot that applies the solder, the hot gas corrosion protective layer, and the thermal barrier coating via thermal spraying. The multilayer system is then processed in a high-vacuum furnace with a defined temperature profile. Due to the near-net-shape coating technology, machining the protruding solder is not necessary. This shortens the processing time significantly. In Fig. 15, the blade is shown before and after the coating process.
4.5 Quality Control
After machining, the blade is inspected for cracks, and the geometry is measured. Afterward, the achieved parameters and functional condition of the machined blade are determined with the functional evaluation. From the digital workpiece twin, the parameters from the forecast are read out, and the deviation between forecasted and the achieved parameters is calculated. This is then stored in a database as the forecast deviation. In the forecast of the next blade, the path-specific forecast errors for each parameter are subtracted from the forecast to improve on it.
In Fig. 16, this quality control loop is demonstrated for path 3. Besides the quality control loop for the forecast, a second quality control loop for the machining will be developed in other subprojects. The regeneration is finished if the blade has no defects and corresponds to the customer’s requirements.
4.6 Analysis of Process Times
In Fig. 17, the movement, handling, and process times of the assessment and evaluation are summarized. Because of the low absolute accuracy of the MHS, a time- intensive reference process is necessary, which increases the handling time. In comparison to the cells in the real layer or the movement and handling times, the functional evaluation and forecast have short process times. In an industrial implementation, the functional evaluation can be executed parallel to the handling, which can reduce the duration of the regeneration.
Figure 18 shows the proportion of the different layers for four different paths, each time with only one blade in the flexible manufacturing system. The new virtual layer, which allows condition-based regeneration, is, in all cases, under 5%. A greater share has the MHS, especially if many cells with short process times <5 min are included in a path. The regeneration time is dominated by the real layer.
It was demonstrated that integration of the virtual layer with the functional evaluation does not significantly increase the regeneration time. Through multiple blades in the system, the functional evaluation can be done parallel to the movement or handling times, which would further decrease the proportion of the regeneration time.
4.7 Lessons Learned from the Proof-Of-Concept
Parametrization of the point cloud in conjunction with lookup tables offers a robust method to quickly calculate the functional condition. Errors in the parametrization or the geometric measurement can be detected through fixed limits or a comparison between different cutting planes of parametrization. This is particularly necessary due to optical measurement technology on the blade’s operational stress surfaces.
For the efficient utilization of the capacity of the cells with multiple blades in the system, the job scheduling needs to consider the movement time and the handling times. These can vary for each combination of start and finish points. In the process chain described, the movement and handling times were so constant that they only had to be measured once.
When using a digital workpiece twin as the sole interface for data, care must be taken to ensure that two programs do not access the twin at the same time. Especially job scheduling, which opens all twins to read out the customer information to create the work plan, triggers these access conflicts.
5 Conclusions
The process chain presented proves the feasibility of condition-based regeneration. By using a fully automated and digitized flexible manufacturing system in combination with the manufacturing and functional simulations, the selection of regeneration measures based on the achievable functional condition becomes possible. It was shown that integrating the simulations has only a minor influence on the regeneration time. Also, it is possible to build up such a process chain with existing technologies.
The flexible manufacturing system developed is scalable and easy to expand due to the mobile handling system (MHS). Since neither rails nor fences or other barriers are needed for the MHS, new technologies can easily be implemented through new process cells. If a machine is a bottleneck, a sister machine can be integrated. Even different workpieces, for example, different blade types, can be processed by the system simultaneously if they do not exceed the weight or size limitation of the MHS.
The regeneration of parts will become more important in the coming years because it requires less energy and materials compared to replacement. With the approach demonstrated, regeneration can be more efficient and economical through automation. Industrial implementation represents the next step for the approach presented.
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Acknowledgements
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) SFB 871/3 119193472. Moreover, the authors would like to thank the other subprojects of CRC 871 for the substantial contribution of cells, software modules, and process knowledge.
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Nuebel, N., Seume, J.R., Denkena, B. (2025). Process Chain for Condition-Based Regeneration. In: Seume, J.R., Denkena, B., Gilge, P. (eds) Regeneration of Complex Capital Goods. Springer, Cham. https://doi.org/10.1007/978-3-031-51395-4_22
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