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Approach for the observation of surface conditions in-process by soft sensors during cryogenic hard turning
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52nd CIRP Conference on Manufacturing Systems 52nd CIRP Conference on Manufacturing Systems
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Approach for the observation of surface conditions in-process by soft 28th CIRP Design Conference, May 2018, France Approach for the observation ofcryogenic surface conditions in-process by soft sensors during hardNantes, turning sensors during cryogenic hardc turning a*, Felix Ströerato b, Lukas Heberger A new methodology analyze theb, Werner functional and, Hendrik physical ofb, Julian Uebel , Stephan Basten Ankener Hotzarchitecture a, Benjamina Kirschb, Marek Smaga c, Jörg Seewig a*, Felix c, aHendrik b, bLukas , Jan C. Aurich , Tilmann Beckbc, Gerhard Stelzer Julian Uebel Ströer , Stephan Bastenb, oriented Werner Ankener Hotzidentification Heberger existing products for an assembly product family a b c a b c , Benjamin Kirsch , Marek Smaga , Jörg Seewig , Jan C. Aurich , Tilmann Beck Gerhard StelzerInstitute for Measurement and Sensor-Technology, Gottlieb-Daimler-Str. 44, 67663 Kaiserslautern, Germany Institute for Manufacturing Technology and Production Systems, Gottlieb-Daimler-Str. 44, Ali 67663Siadat Kaiserslautern, Germany Paul Stief *, Jean-Yves Dantan, Alain Etienne, Institute forofMeasurement and Sensor-Technology, Gottlieb-Daimler-Str.44, 44,67663 67663Kaiserslautern, Kaiserslautern,Germany Germany Institute Materials Science and Engineering, Gottlieb-Daimler-Str. a
b
a
bInstitute
c
for Manufacturing Technology and Production Systems, Gottlieb-Daimler-Str. 44, 67663 Kaiserslautern, Germany École Nationalec Supérieure d’Arts et Métiers, Arts et Métiers ParisTech, LCFC EA 4495, 4 Rue Augustin Fresnel, Metz 57078, France Institute of Materials Science and Engineering, Gottlieb-Daimler-Str. 44, 67663 Kaiserslautern, Germany * Corresponding author. Tel.: +49-631-205-4120; fax: +49-631-205-3963. E-mail address: [email protected]
**Corresponding 3 87 37 54 30; E-mail address: [email protected] Correspondingauthor. author.Tel.: Tel.:+33 +49-631-205-4120; fax: +49-631-205-3963. E-mail address: [email protected]
Abstract Abstract Abstract
Even though required for a robust production, direct measurement of the surface condition in-process is a challenge due to limitations. A concept for towards in-process monitoring of and surface conditions like hardness using Intechnical today’s business environment, the trend more product variety customization to or thismicrotopography development, the need Even though required for a robust production, direct measurement of the surfaceis unbroken. condition Due in-process is a challenge due of to observer-like structures will be systems discussed in thistopaper fromvarious a metrological point of view. Initially, the and background regarding agile and reconfigurable production emerged cope with products and product families. To design optimize production technical limitations. A concept for in-process monitoring of surface conditions like hardness or microtopography using manufacturing material is summarized. Afterwards, themethods problem isneeded. analysed frommost a control engineering point systems as well structures asand to choose thesciences optimal product product are Indeed, thebackground known methods aim of to observer-like will be discussed in matches, this paper fromanalysis a metrological point of view. Initially,ofthe regarding view and challenges and solutions are discussed. Finally, a concept for families, a new sensor, themay opto-pneumatic scattered light sensor,and is analyze a product or one product family on the physical level. Different product however, differ largely in terms of the number manufacturing and material sciences is summarized. Afterwards, the problem is analysed from a control engineering point of presented, which contributes to the indirect measurement of the microtophography in-process. nature of components. fact impedes efficient comparison and choice appropriate family combinations forlight the production view and challenges This and solutions are an discussed. Finally, a concept for aofnew sensor, product the opto-pneumatic scattered sensor, is system. A new methodology is proposed to analyze existing products view of their functional and physical architecture. The aim is to cluster presented, which contributes to the indirect measurement of theinmicrotophography in-process. © 2019 The Authors. Publishedoriented by Elsevier Ltd.families This is an access articleofunder the assembly CC BY-NC-ND license these products in new assembly product foropen the optimization existing lines and the creation of future reconfigurable © 2019 The Authors. Published by Elsevier Ltd. the physical structure of the products is analyzed. Functional subassemblies are identified, and (http://creativecommons.org/licenses/by-nc-nd/3.0/) assembly systems. Based on Datum Flow Chain, © 2019 The Authors. Published by Elsevier Ltd. This is license an open(http://creativecommons.org/licenses/by-nc-nd/3.0/) access article under the CC BY-NC-ND license This is an open access article under the scientific CC BY-NC-ND under responsibility of Moreover, the committee of the 52nd CIRP Conference on graph Manufacturing Systems. aPeer-review functional analysis is performed. a hybrid functional and physical architecture (HyFPAG) is the output which depicts the (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on Manufacturing Systems. similarity between product families by scientific providingcommittee design support to both, production system planners and Systems. product designers. An illustrative Peer-review under responsibility of the of the 52nd CIRP Conference on Manufacturing Keywords: surface condition; in-process, indirect measurement; opto-pneumatic scattered light sensor example of soft-sensor; a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach. Keywords: soft-sensor; surface condition; in-process, indirect measurement; opto-pneumatic scattered light sensor © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018.
1. Introduction
The surface layer is defined as the volume fraction of a component, which is bounded by thefraction surface of anda Keywords: Assembly; Design method; Family identification The surface layer is definedonasone theside volume 1. Introduction on the other side by an assumed boundary extending within Future high-tech components must be produced resourcecomponent, which is bounded on one side by the surface and the material of the surface layer depends within on the efficiently and without rejects, while at be theproduced same timeresourcemeeting on the other[2]. sideThe by depth an assumed boundary extending Future high-tech components must depth to which the conditions of the surface layer are the highest demands in terms of service life and wear the material [2]. The depth of the surface layer depends on the efficiently and without rejects, while at the same time meeting 1.resistance. Introduction of the product range and characteristics manufactured and/or important for the function of the component. The surface For such products, the surface of the part has a depth to which the conditions of the surface layer are the highest demands in terms of service life and wear assembled in this system. In thisthat context, the challenge in layer conditions all states an main influence on the particular importance, since thethe functionality important for thearefunction of the have component. The surface resistance. For such products, surface ofand the service part haslifea Due to the under fast mechanical developmentandin thermal the domain of modelling and analysis is now not only to cope with single component functions during operation [3]. of components stress are layer conditions are all states that have an influence on the particular importance, since the functionality and service life communication and byantheongoing of digitization products, a limited product range or existing product families, mainly determined surface trend condition and thus on and the component functions during operation [3]. of components under mechanical and thermal stress are digitalization, manufacturing enterprises are facing important but also to be able to analyze and to compare products to define surface of a component [1]. condition mainly layer determined by the surface and thus on the challenges in today’s market environments: a continuing new product families. It can be observed that classical existing surface layer of a component [1]. tendency towards reduction of product development times and product families are regrouped in function of clients or features. shortened product lifecycles. In addition, there is an increasing However, assembly oriented product families are hardly to find. demand of customization, being at the same time in a global On the product family level, products differ mainly in two competition with competitors all over the world. This trend, main characteristics: (i) the number of components and (ii) the which is inducing the development from macro to micro type of components (e.g. mechanical, electrical, electronical). markets, results in diminished lot sizes due to augmenting Classical methodologies considering mainly single products product varieties (high-volume to low-volume production) [1]. or solitary, already existing product families analyze the 2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license To cope with this augmenting variety as well as to be able to product structure on a physical level (components level) which (http://creativecommons.org/licenses/by-nc-nd/3.0/) 2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license an efficient definition and identify possible optimization potentials in the existing causes regarding Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on difficulties Manufacturing Systems. (http://creativecommons.org/licenses/by-nc-nd/3.0/) production system, it is important to have a precise knowledge comparison of different product families. Addressing this Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on Manufacturing Systems. 2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an©open article Published under theby CC BY-NC-ND 2212-8271 2017access The Authors. Elsevier B.V. license (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of scientific the scientific committee theCIRP 52ndDesign CIRPConference Conference2018. on Manufacturing Systems. Peer-review under responsibility of the committee of the of 28th 10.1016/j.procir.2019.03.304
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Fig. 1. schematic overview of the structure of the surface layer, the bulk material and the surface layer condition through the example of AISI 347 [8].
The depth of the surface layer for cryogenic hard turning can be up to several µm [4]. Quantifiable conditions of the surface layer include the (local) hardness (hardness as a function on the surface of the manufactured part), (local) microtopography and (local) structure distribution and residual stresses. A schematic overview of the structure of the surface layer and his states through the example of AISI 347 is given in Fig. 1. Manufacturing processes, such as cryogenic hard turning, acting forces and temperatures on the component surface layer and can thus have a negative (e.g. in the form of so-called brittle and hard “white layers” [5]), as well as a positive (e.g. increased hardness and improved wear resistance on the functional surface [6, 7]) influence on it. Correlations between process variables such as cutting forces and the resulting surface layer [9, 10], as well as between surface layer condition and resulting component properties [11] are known and have been qualitatively and quantitatively investigated in literature. However, the influence of disturbance variables on the process is not sufficiently investigated. In a first step, these influences have to be examined. With this a-priori knowledge, a non-linear feedforward control for the process can be reached. In a second step, in order to produce a surface layer with defined characteristics reliably (robustly) and to be able to control on disturbances, it is necessary to measure the quantifiable surface layer characteristics in-process during the production process, to carry out a target/actual comparison and to adopt the process parameters accordingly using a feedback loop. It is currently state of the art to quantitatively measure the surface layer conditions under laboratory conditions, i.e. exsitu. Here, there is a multitude of measuring techniques available like the tactile roughness measurement or confocal microscopy for surface microtopography quantification as well as x-ray diffraction measurement for detection of the residual stresses [12, 13]. However the direct transfer of these measurement techniques into the manufacturing process is difficult or impossible in many cases, and thus not applicable for the industrial production. Therefore a different approach is needed which is not based on the direct transfer of existing measuring instruments. An indirect approach to measurement of surface conditions (such as hardness or microstructure) in-process is to use process variables, which in some cases are already recorded (such as the process forces), in combination with additional sensors which operate close to the surface layer (like 3MA sensors [14] or scattered light measurement technology [15])
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and process knowledge in the form of models (like finite element models [16]). On the basis of these combined information, it should be possible to deduce not directly measurable surface layer conditions, by using observer-like structures from control theory. Goal of the research project presented is therefore to examine the possibilities for the observation of surface conditions during cryogenic hard turning of 100Cr6. Cryogenic hard turning is particularly relevant as a process for this research question, as the CO2 mass flow increases the tool life compared to conventional cooling strategies and improves the surface layer condition and topography [17]. In this paper, the possibility of indirect measurement of surface conditions such as hardness and roughness by observer structures will be discussed in more detail from a measurement technology point of view. First, the requirements of the materials and manufacturing will be presented and then the measurement technology will be discussed. 2. Overview of the material 100Cr6 and manufacturing technology The cryogenic hard turning of 100Cr6 was chosen as the manufacturing process to investigate the observability of the surface layer condition. The workpiece material (100Cr6) is chosen because it is a well-understood material for highly stressed, rotationally symmetrical machine parts, and well described in literature [11, 18, 19, 20, 21]. A lot of fundamental interrelations have already been qualitatively investigated and described. For example, thin austeniticmartensitic layers (so-called “white layers”) can form on the surface of the workpiece during hard turning of 100Cr6. One explanation for the formation of “white layers” is local heating and subsequent cooling. The exact origin, however, is still being investigated in other researches. The properties of these layers differ significantly from those of the bulk material, e.g. with regard to the hardness [22]. The resulting state of the surface layer after machining of 100Cr6 is thus significantly dependent on chosen machining parameters. In general, the surface layer condition of machined workpieces can be positively influenced by the use of cryogenic cooling media, which made it an alternative to conventional cooling strategies [17]. Among other positive effects, the layer thickness of the white layer can be noticeably reduced when using cryogenic cooling [23]. The fundamental qualitative relationships between cryogenic hard turning as a process, the effect of the process control variables and the surface layer of the material 100Cr6 as a process result (surface layer condition as a function of location) have already been investigated in literature [24, 25]. However, the correlations between in-process measured variables and the surface layer conditions as a function of place and time have yet to be examined. Due to the knowledge of the material 100Cr6 and the process of cryogenic hard turning, static models can already be set. However, these models mostly lack fine resolution and don’t consider dynamics and disturbances, such as tool wear or vibrations in the system. In order to evolve these static
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models into dynamic models, further experiments are required. For the samples (workpieces), consistency is important to exclude unknown factors as additional disturbances, such as deviations of the initial geometry of the sample or heat treatment variations, in order to be able to determine only wear effects and disturbance variables of the machine. It must therefore be ensured that the same heat treatment condition is set for all samples before processing. To investigate the effect, three quenching and tempering stages were selected which, depending on the tempering time, produce a different residual austenite content and thus different hardness. An overview of the chosen heat treatment time by 180°C and the expected residual austenite and hardness is given in Table 1. Table 1. tempering time and the expected residual austenite / hardness by a tempering temperature of 180°C [26]
Number 1 2 3
Time 102 min 103 min 104 min
Residual austenite < 15% < 10% < 1%
Hardness > 62 HRC 58 - 62 HRC < 58 HRC
After this overview of the material and the production process, the in-process surface layer observation will be discussed from a control theory point of view. 3. Cryogenic hard turning as a system: Challenges and solutions from the point of view of measurement technology From a control theory point of view, the process “cryogenic hard turning of 100Cr6” can be understood as a dynamic system with inputs u (t ) , state variables x (t ) , outputs (measurement) y (t ) and disturbance variables d (t ). But the correlation between this variables is non-linear, so neither is the system. Project goal is to estimate elements of the inprocess not measureable state vector x (t ) , like the hardness HV (t ) , by breaking down the entire system into a non-linear feedforward control and a linear control loop. It can be assumed that there is a (in general unknown) functional relationship between an applied force F (t ) and temperature J (t ) on a workpiece, and the resulting hardness HV (t ) : (1) HV (t ) = f ( F (t ),J (t ),...) An overview of the process is given in Fig. 2. Especially knowledge of the force and temperature is important since the evolution of the surface layer is mainly being influenced by the force and temperature (gradient) applied. Input variables for the process “cryogenic turning” can be combined in a vector u (t ) . These are: • • • •
Feed f (t ) Cutting Speed v (t ) Depth of cutting a (t ) CO2 Mass Flow m! CO 2 (t )
• • •
Aq values Aq( x, y ) Temperature J ( x, y, z ) and
C
p
In-process measurable quantities are bundled in the vector of the in-process measure y (t ) :
Jz ,i (t ), i = 1...3
Process Forces F ( x, y, z ) The actual surface layer condition is represented in the vector x (t ) and includes among others:
3
Fig. 2. process of cryogenic hard turning of 100Cr6 from a control engineering point of view.
Distribution of hardness of the workpiece surface layer HV ( x, y, z, t ) and • Microtopography Rk ( x, y, t ) . From the infinite-dimensional vector of the surface layer conditions, these two are primarily examined for the project. Therefore, in-process measurements must be taken that correlate as directly as possible with the previous mentioned surface zone conditions. The hardness of workpiece material is related to the temperature profile, the cooling rate and the forces applied to it [3]. To determine the process forces in x-, y- and zdirection, there will be integrated a force measuring platform in the turning machine. The temperature will be detected in three ways: with a pyrometer, the local temperature on the surface Jx , y (t ) at one fixed position of the workpiece can be measured. This measure value can be used to calibrate the thermographic camera. With the camera a planar temperature profile J ( x, y, t ) of the workpiece can be determined. Thermography cameras, however, have the same disadvantages in-process as other imaging techniques, especially, when cooling lubricants are used in the process. To complete the temperature measurement the internal local temperatures Jz ,i (t ), i = 1...3 of the workpiece will be detected with three integrated thermocouples. The use of thermocouples in the workpiece is also not suitable for later use in an industrial process. However, on the basis of the results of the research, it is possible to select from the three principles the one, that has the most expressive power with regard to the surface layer and to reconstruct the temperature profile via model. Together with a yet to be formulated model it should be possible to first reconstruct the whole temperature profile J ( x, y, z , t ) and afterwards drawing a conclusion from the temperature and the cutting forces to the hardness. In order to characterize the surface condition, not only hardness but also microtopography is considered a target quantity. For this purpose, the surface is measured after machining using the profile method. From the measured surface profile, roughness parameters such as Ra or Rz can then be determined. However, these do not contain any information about the shape of the surface profile. This information is contained in the Rk-parameters, which can also be determined from the surface profile using the Abbott curve. Based on this additional information, the group of Rkparameters was selected as target values. In-process, however, the tactile profile method can’t be used. However, an angle •
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resolving scattered light (ARS) sensor can also be used to record Aq-values in-process. The Aq-value is calculated as the variance from the scattered light distribution. If it is now assumed that surface structures are similar, i.e. have a similar surface profile, the Aq-value changes proportionally to the Rk parameters [27]. Disturbances are summarized in the disturbance vector d (t ) . This will be: • Wear of the tool • Workpiece initial state or • Vibrations • Disturbances, which will be detected during the research From a control theory point of view, there is a functional relationship f Sys between input variables u (t ), (known and unknown) disturbances d (t ) and hidden states x (t ) : (2) x! (t ) = f Sys ( x (t ), u (t ), d (t ))
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measuring principles, most optical measuring methods are sensitive to vibrations and therefore not applicable in-process, e.g. white-light interferometry [28], focus variation or confocal microscopy. In order to measure the microtopography and form, a combination of an angle resolved scattered light (ARS) sensor and a pneumatic distance sensor will be developed. Both sensors themselves are state of the art for in-process measurement. The insensitivity of the ARS sensor to vibrations is based on the measuring principle, since it detects surface angles and these are not influenced by vibrations. The measurement principle and evaluation algorithms for the ARS are described in detail in literature [15, 29, 30]. The in-process capability of the ARS sensor has
As mentioned before, the surface conditions like
HV ( x, y, z, t ) are included in the vector x (t ) and for example the tool wear in the disturbance vector d (t ) , but aren’t direct
measurable in-process. It can also be assumed for the inprocess measured variables y (t ) that these depend on the workpiece condition itself, on input and disturbance variables: (3) y (t ) = f Meas ( x (t ), u (t ), d (t ))
Surface layer conditions that can be measured in the laboratory, e.g. the resulting hardness, can be understood as elements of the state vector at the end time of machining: ì HV ( x, y, z , te ) ï (4) x (t e ) = í ! ï ! î If a reasonably accurate correlation between input variables u(t), measured variables y (t ) and state variables x (t ) can be described mathematically, in form of a set of nonlinear functions f ( x (t ), u (t ),...) , implemented in the form of a feedforward control, and a linear system, implemented in the form of a control loop, then - assuming that the system is observable - the state x (t ) can be calculated from the measured variables y (t ) with an observer. With the surface layer condition observed, the difference between nominal and actual can be compensated using the controller. This goal from a control theory point of view is visualized in a block diagram in Fig. 3. To observe the surface layer, the measured variables must be connected to the state variables over modellike correlations. 4. Opto-pneumatic scattered light sensor In order to be able to observe and indirectly measure the surface layer condition, apart from the knowledge of the input variables of the system, special measurement variables are relevant which correlate directly with the surface zone condition. Because of the rough environmental conditions during the process of turning, like vibrations, chips and lubrication, the in-process measurement of the microtopography can only be implemented contactless. Optical topography measurement technology is widespread in the industry. Due to the physical
Fig. 3. Goal of the research from a control theory point of view.
also already been demonstrated in several investigations [31]. The measurement result of the ARS sensor gives information about the surface roughness as the extent of roughness directly correlates with the light scattering [27, 32]. Pneumatic measurement technology is widely spread in the industry for in-process and in-line measurement of shape and distance. There are different measuring principles for pneumatic measuring, e.g. pressure measurement or the flow measurement method. The pressure measurement method is the mostly used method and also used in this research. The function principle and influence factors on the measurement, e.g. the tilt of the sensor, are also described in publications before [33]. For the in-process usage of the ARS sensor during cryogenic turning, the measuring point has to be cleaned from CO2 snow. Therefore a pneumatic cleaning nozzle would have to be installed. To dispense with this additional component and safe space in the measurement setup, the measuring spot of the ARS sensor can be blown freely directly with the pneumatic sensor. To achieve this object, the light of the ARS sensor has to be lead through the measuring nozzle of the pneumatic sensor. This layout brings a lot of positive synergies: • The measuring spot for the ARS sensor is freed from the CO2 snow or other cooling lubricant by the pneumatic sensor • The overpressure in the ARS sensor prevents contamination of the lenses • The measuring values can be assigned to each other, if they get the same trigger signal
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5
The sampling frequency of the integrated pneumatic sensor depends on the used transducer and the response time of the sensor by itself. The response time of the pneumatic sensor depends on several factors, e.g. diameter of pre- and measuring nozzle and their ratio, the volume of the measuring chamber. Further researches will show how a variation of these parameters reduces the response time of the pneumatic sensor. Commercial, pneumo-electronic transducers have a response time of 15ms and therefore a sampling frequency of 66 Hz. This frequency isn’t high enough for in-process measuring. So the pneumatic sensor can be used for positioning of the sensor during the setting up of the machine, the cleaning of the measuring spot of the ARS sensor and for in-line measurement of the shape. 5. Conclusion and outlook
Fig. 4. schematic layout of the opto-pneumatic ARS sensor: a) linear PDA – b) LED – c) collimated beam – d) scattering light – e) lens – f) window – g) measuring chamber – h) measuring nozzle – i) workpiece - j) pre-nozzle – k) pre-chamber – l) air supply
By measuring the distance of the pneumatic sensor, the ARS sensor can be set up in the ideal focal plane affected by the construction A schematic layout of the combination from the ARS sensor and the pneumatic distance sensor is given in Fig. 4. The volume of the measuring chamber of the pneumatic sensor should be chosen as small as possible to achieve a short response time of the sensor, because the response behavior correlates with the volume of the measuring chamber [33]. Therefore, the entire area in front of the lenses cannot be used to form the measuring chamber. To reduce the volume, the measuring chamber is constructed near the measuring nozzle. A window must therefore be inserted on the opposite site of the measuring chamber, seen from the measuring nozzle. For this the normal linear design of the pneumatic components (air supply, pre-chamber, pre-nozzle, measuring chamber and measuring nozzle) within the sensor has to be changed: the pre-nozzle is now sideways from the measuring chamber. That has the consequence: the fluid must stream around the corner from the pre- to the measuring nozzle. To investigate the effect of this new layout, the flow analysis must be done with a CFD simulation. The measuring result of an ARS sensor, like the Aq-value, contains the information of predominant surface angles of the illuminated area. This is a round area with a diameter of 0,9 mm. With a sampling frequency of 2 kHz, the in-process measuring is possible with 50% overlap along the circumference within the defined process parameters. Caused by the feed, every point along the workpiece axis is measured 6 times, so the overlap in this direction is nearly 80%. •
The goal of the research discussed in this paper is the observation of the surface conditions, explicitly hardness and microtopography, in-process. Hardness HV and the microtopography, in the form of Rk parameters, cannot be measured directly during machining. Therefore, in following investigations, the measurement variables are recorded, which are linked to these states. Subsequently, the surface layer condition to be observed is deduced by means of deposited models, which have to be developed. To be able to deduce the hardness, the temperature and the process forces are recorded in-process. In order to draw conclusions about the microtopography, the surface angles are to be measured by means of an ARS sensor, because the Aqvalues obtained here correlate with the Rk-parameters. Therefore the surface has to be cleaned from the CO2 snow. To achieve this, a pneumatic distance sensor is integrated in an existing ARS sensor. This combination brings a lot of positive synergies, e.g. the overpressure in the ARS sensor prevents contamination of the lenses. In the further course of the project, the samples are first prepared in such a way, that all samples achieve one of the three defined initial states. These are then processed. The surface layer condition is then measured ex situ and compared with the surface layer condition calculated in models. If the surface layer condition can be sufficiently well represented by the models, a process control can then be set up, whereby in the future a targeted surface layer condition can be set independently of disturbance variables in the process. 6. Acknowledgements The scientific work has been supported by the DFG within the research priority program SPP 2086. The authors thank the DFG for this funding and intensive technical support. References [1] Aurich, C., Schneider, F., Mayer, P., Kirsch, B., Hasse, H., 2016, Oberflächenerzeugungs-Morphologie-Eigenschafts-Beziehungen: Vom Fertigungsverfahren direkt zu den Bauteileigenschaften, ZWF 04/2016, p. 213-216 [2] The International Academy for Production, 2014, Encyclopedia of Production Engineering, Lapperrière, L., Reinhard, G.. Editors. Springer
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[3] Brinksmeier, E., 1991. Prozeß-und Werkstückqualität in der Feinbearbeitung, Habitilation, Düsseldorf, VDI-Verlag [4] Umbrello, D., Micari, F., Jawahir, I.S., 2012. The effects of cryogenic cooling on surface integrity in hard machining: A comparison with dry machining, CIRP Annals – Manufacturing Technology 61, p. 103-106 [5] Müller, C., 2008. Prozessgrößen und Randzoneneigenschaften beim Drehen gehärteter Stähle, Dissertation, Universiät Hannover [6] Yildiz, Y., Nalbant, M., 2008, A review of cryogenic cooling in machining processes, International Journal of Machine Tools & Manufacture 48, p. 947-964 [7] Bicek, M., Dumont, F., Courbon, C., Pusavec, F., Rech, J., Kopac, J., 2012, Cryogenic machining as an alternative turning process of normalized and hardened AISI 52100 bearing steel, Journal of Materials Processing Technology 212, p. 2609-2618 [8] Smaga, M., Skorupski, R., Eifler, D., Beck, T., 2017, Microstructural characterization of cyclic deformation behavior of metastable austenitic stainless steel AISI 347 with different surface morphology, in “Journal of Materials Research 32 / 23”, Cambridge University Press, p. 4452-4460 [9] Denkena, B., Grove, T., Maiss, O., 2015, Influence of the cutting edge radius on surface integrity in hard turn-ing of roller bearing inner rings, Production Engineering – Research and Development 9, p. 299-305 [10] Jawahir, I.S., Brinksmeier, E., M’Saoubi, R., 2011, Surface integrity in material removal processes: Recent advances, CIRP Annals – Manufacturing Technology 60/2, p. 603-626 [11] Kerscher, E., 2005, Steigerung der Schwingfestigkeit von 100Cr6 durch thermomechanische Behandlungen, Dissertation, Universität Karlsruhe (TH), Nr. 024 [12] Rahlves, M., Seewig, J., 2009, Optisches Messen technischer Oberflächen. Messprinzipien und Begriffe, Berlin, Wien, Zürich, Beuth [13] Balle, F., Huxhold, S., Emrich, S., Wagner, G., Kopnarski, M.,Eifler, D., 2013, Influence of Heat Treatments on the Mechanical Properties of Ultrasonic Welded AA 2024/CF-PA66-Joints, in “Advanced Engineering Materials”, p. 837-845 [14] Szielasko, K., Youssef, S., Wolter, B., Schuppmann, M., Weingard, C., Rodner, C., Kopp, H., Elzatma, M., Mironenko, I., Kiselmann, I., 2014, High-Speed-3MA zur mikromagnetischen Werkstoffcharakterisierung in schnellen Produktionsprozessen, DGZfP-Jahrestagung 2014, Mo.3.A.4 [15] Seewig, J., Beichert, G., Brodmann, R., Bodschwinna, H., Wendel, M., 2009, Extraction of shape and roughness using scattering light, Proc.SPIE 7389 73890N-1 [16] Umbrello, D., Bordin, A., Imbrogno, S., Bruschi, S., 2017. 3D finite element modelling of surface modification in dry and cryogenic machining of EBM Ti6AL4V alloy, CIRP Journal of Manufacturing Science and Technology, Volume 18, p. 92-100 [17] Jawahir, I.S., Attia, H., Biermann, D., Duflou, J., Klocke, F., Meyer, D., Newman, S.T., Pusavec, F., Putz, M., Rech, J., Schulze, V., Umbrello, D., 2016, Cryogenic manufacturing processes, CIRP Annals - Manufacturing Technology 65, p. 713-736 [18] Ellermann, A., Scholtes, B., 2015, The strength differential effect in different hear treatment conditions of steels 42CrMoS4 and 100Cr6, Materials Science & Engineering A620, p. 262-272 [19] Gabelli, A., Lai, J., Lund, T., et al., 2012, The fatigue limit of bearing steels – Part II: Characterization of life rating standards, International journal of fatigue 38, p. 169-180 [20] Grad, P., Reuscher, A.B., Brodyanski, A., Kopnarski, M., Kerscher, E., 2012, Mechanism of fatigue crack initiation and propagation in the very high cycle fatigue regime of high-strength steels, Scripta Materialia 67, p. 838-841 [21] Kang, J.-H., Vegter, R.H., Rivera-Díaz-del-Castillo, P. E.J., 2014, Rolling contact fatigue in martensitic 100Cr6: Subsurface hardening and crack formation, Materials Science & Engineering A 607, p. 328–333 [22] Barry, J., Byrne, G., 2002, TEM study on the surface white layer in two turned hardenet steels, Materials Science and Engineering 325, p. 356-364 [23] Rotella, G., Umbrello, D., Dillon Jr., O.W., Jawahir, I.S., 2012, Evaluation of Process Performance for Sustainable Hard Machining, Journal of Advanced Mechanical Design, Systems and Manufacturing 6/6, p. 989-998 [24] Umbrello, D., 2012, Analysis of the white layers formed during machining of hardened ALSI 52100 steel under dry and cryogenic cooling conditions, International Journal of Advanced Manufacturing Technology, Springer, Berlin
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[25] Ramesh, A., Melkote, S.N., Allard, L.F., Riester, L., Watkins, T.R., 2005, Analysis of white layers formed in hard turning of AISI 52100 steel. Materials Science and Engineering: A, Volume 390, Issues 1–2, p. 88-97 [26] Leimbach, H.-J., 1969, Anlaßuntersuchungen am gehärteten Stahl 100Cr6 unter Berücksichtigung einer Tiefkühlbehandlung, PhD Dissertation, University of Karslruhe [27] VDA Verband der Automobilindustrie e.V., 2009, Geometrische Produktspezifikation (GPS); Oberflächenbeschaffenheit; Winkelaufgelöste Streulichtmesstechnik, DKF, Bietigheim-Bissingen [28] Schäfer, P., Broschart, D., Seewig, J., 2013, Aktive Schwingungsdämpfung eines Weißlichtinterferometers. tm - Technisches Messen 80 1, p. 16–20 [29] Wendel, M., Stelzer, G., Karatas, A., Seewig, J., 2013, Qualification of a new scattering light sensor for simultaneos areal form and roughness measurement, The 11th Int. Symp. of Measurement Technology and Intelligent Instruments, Aachen [30] Wendel, M., 2015, Qualifizierung eines Streulichtsensors und Untersuchung erste Ansätze zur dreidimensionalen Streulichterfassung, PhD Dissertation, Institute for Measurement and Sensor Technology, University of Kaiserslautern [31] Seewig, J., Wendel, M., 2011, An approach to extract the depth information of surface topography using an angle resolved non coherent light scatter sensor, 13th International Converence on Metrology and Properties of Engineering Surfaces, p. 363 - 368 [32] Vorburger, T., Silver, R., Brodmann, R., Brodmann, B., Seewig, J., 2011, 12 Light Scattering Methods, in “Optical Measurement of Surface Topography” R. Leach, Editor. Springer, Berlin [33] Schäfer, P., 2015, Modellbasierte Entwicklung pneumatischer Abstandssensoren für prozessintegrierte Messungen, PhD Dissertation, Institute for Measurement and Sensor Technology, University of Kaiserslautern
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Approach for the observation of surface conditions in-process by soft 28th CIRP Design Conference, May 2018, France Approach for the observation ofcryogenic surface conditions in-process by soft sensors during hardNantes, turning sensors during cryogenic hardc turning a*, Felix Ströerato b, Lukas Heberger A new methodology analyze theb, Werner functional and, Hendrik physical ofb, Julian Uebel , Stephan Basten Ankener Hotzarchitecture a, Benjamina Kirschb, Marek Smaga c, Jörg Seewig a*, Felix c, aHendrik b, bLukas , Jan C. Aurich , Tilmann Beckbc, Gerhard Stelzer Julian Uebel Ströer , Stephan Bastenb, oriented Werner Ankener Hotzidentification Heberger existing products for an assembly product family a b c a b c , Benjamin Kirsch , Marek Smaga , Jörg Seewig , Jan C. Aurich , Tilmann Beck Gerhard StelzerInstitute for Measurement and Sensor-Technology, Gottlieb-Daimler-Str. 44, 67663 Kaiserslautern, Germany Institute for Manufacturing Technology and Production Systems, Gottlieb-Daimler-Str. 44, Ali 67663Siadat Kaiserslautern, Germany Paul Stief *, Jean-Yves Dantan, Alain Etienne, Institute forofMeasurement and Sensor-Technology, Gottlieb-Daimler-Str.44, 44,67663 67663Kaiserslautern, Kaiserslautern,Germany Germany Institute Materials Science and Engineering, Gottlieb-Daimler-Str. a
b
a
bInstitute
c
for Manufacturing Technology and Production Systems, Gottlieb-Daimler-Str. 44, 67663 Kaiserslautern, Germany École Nationalec Supérieure d’Arts et Métiers, Arts et Métiers ParisTech, LCFC EA 4495, 4 Rue Augustin Fresnel, Metz 57078, France Institute of Materials Science and Engineering, Gottlieb-Daimler-Str. 44, 67663 Kaiserslautern, Germany * Corresponding author. Tel.: +49-631-205-4120; fax: +49-631-205-3963. E-mail address: [email protected]
**Corresponding 3 87 37 54 30; E-mail address: [email protected] Correspondingauthor. author.Tel.: Tel.:+33 +49-631-205-4120; fax: +49-631-205-3963. E-mail address: [email protected]
Abstract Abstract Abstract
Even though required for a robust production, direct measurement of the surface condition in-process is a challenge due to limitations. A concept for towards in-process monitoring of and surface conditions like hardness using Intechnical today’s business environment, the trend more product variety customization to or thismicrotopography development, the need Even though required for a robust production, direct measurement of the surfaceis unbroken. condition Due in-process is a challenge due of to observer-like structures will be systems discussed in thistopaper fromvarious a metrological point of view. Initially, the and background regarding agile and reconfigurable production emerged cope with products and product families. To design optimize production technical limitations. A concept for in-process monitoring of surface conditions like hardness or microtopography using manufacturing material is summarized. Afterwards, themethods problem isneeded. analysed frommost a control engineering point systems as well structures asand to choose thesciences optimal product product are Indeed, thebackground known methods aim of to observer-like will be discussed in matches, this paper fromanalysis a metrological point of view. Initially,ofthe regarding view and challenges and solutions are discussed. Finally, a concept for families, a new sensor, themay opto-pneumatic scattered light sensor,and is analyze a product or one product family on the physical level. Different product however, differ largely in terms of the number manufacturing and material sciences is summarized. Afterwards, the problem is analysed from a control engineering point of presented, which contributes to the indirect measurement of the microtophography in-process. nature of components. fact impedes efficient comparison and choice appropriate family combinations forlight the production view and challenges This and solutions are an discussed. Finally, a concept for aofnew sensor, product the opto-pneumatic scattered sensor, is system. A new methodology is proposed to analyze existing products view of their functional and physical architecture. The aim is to cluster presented, which contributes to the indirect measurement of theinmicrotophography in-process. © 2019 The Authors. Publishedoriented by Elsevier Ltd.families This is an access articleofunder the assembly CC BY-NC-ND license these products in new assembly product foropen the optimization existing lines and the creation of future reconfigurable © 2019 The Authors. Published by Elsevier Ltd. the physical structure of the products is analyzed. Functional subassemblies are identified, and (http://creativecommons.org/licenses/by-nc-nd/3.0/) assembly systems. Based on Datum Flow Chain, © 2019 The Authors. Published by Elsevier Ltd. This is license an open(http://creativecommons.org/licenses/by-nc-nd/3.0/) access article under the CC BY-NC-ND license This is an open access article under the scientific CC BY-NC-ND under responsibility of Moreover, the committee of the 52nd CIRP Conference on graph Manufacturing Systems. aPeer-review functional analysis is performed. a hybrid functional and physical architecture (HyFPAG) is the output which depicts the (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on Manufacturing Systems. similarity between product families by scientific providingcommittee design support to both, production system planners and Systems. product designers. An illustrative Peer-review under responsibility of the of the 52nd CIRP Conference on Manufacturing Keywords: surface condition; in-process, indirect measurement; opto-pneumatic scattered light sensor example of soft-sensor; a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach. Keywords: soft-sensor; surface condition; in-process, indirect measurement; opto-pneumatic scattered light sensor © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018.
1. Introduction
The surface layer is defined as the volume fraction of a component, which is bounded by thefraction surface of anda Keywords: Assembly; Design method; Family identification The surface layer is definedonasone theside volume 1. Introduction on the other side by an assumed boundary extending within Future high-tech components must be produced resourcecomponent, which is bounded on one side by the surface and the material of the surface layer depends within on the efficiently and without rejects, while at be theproduced same timeresourcemeeting on the other[2]. sideThe by depth an assumed boundary extending Future high-tech components must depth to which the conditions of the surface layer are the highest demands in terms of service life and wear the material [2]. The depth of the surface layer depends on the efficiently and without rejects, while at the same time meeting 1.resistance. Introduction of the product range and characteristics manufactured and/or important for the function of the component. The surface For such products, the surface of the part has a depth to which the conditions of the surface layer are the highest demands in terms of service life and wear assembled in this system. In thisthat context, the challenge in layer conditions all states an main influence on the particular importance, since thethe functionality important for thearefunction of the have component. The surface resistance. For such products, surface ofand the service part haslifea Due to the under fast mechanical developmentandin thermal the domain of modelling and analysis is now not only to cope with single component functions during operation [3]. of components stress are layer conditions are all states that have an influence on the particular importance, since the functionality and service life communication and byantheongoing of digitization products, a limited product range or existing product families, mainly determined surface trend condition and thus on and the component functions during operation [3]. of components under mechanical and thermal stress are digitalization, manufacturing enterprises are facing important but also to be able to analyze and to compare products to define surface of a component [1]. condition mainly layer determined by the surface and thus on the challenges in today’s market environments: a continuing new product families. It can be observed that classical existing surface layer of a component [1]. tendency towards reduction of product development times and product families are regrouped in function of clients or features. shortened product lifecycles. In addition, there is an increasing However, assembly oriented product families are hardly to find. demand of customization, being at the same time in a global On the product family level, products differ mainly in two competition with competitors all over the world. This trend, main characteristics: (i) the number of components and (ii) the which is inducing the development from macro to micro type of components (e.g. mechanical, electrical, electronical). markets, results in diminished lot sizes due to augmenting Classical methodologies considering mainly single products product varieties (high-volume to low-volume production) [1]. or solitary, already existing product families analyze the 2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license To cope with this augmenting variety as well as to be able to product structure on a physical level (components level) which (http://creativecommons.org/licenses/by-nc-nd/3.0/) 2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license an efficient definition and identify possible optimization potentials in the existing causes regarding Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on difficulties Manufacturing Systems. (http://creativecommons.org/licenses/by-nc-nd/3.0/) production system, it is important to have a precise knowledge comparison of different product families. Addressing this Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on Manufacturing Systems. 2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an©open article Published under theby CC BY-NC-ND 2212-8271 2017access The Authors. Elsevier B.V. license (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of scientific the scientific committee theCIRP 52ndDesign CIRPConference Conference2018. on Manufacturing Systems. Peer-review under responsibility of the committee of the of 28th 10.1016/j.procir.2019.03.304
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Fig. 1. schematic overview of the structure of the surface layer, the bulk material and the surface layer condition through the example of AISI 347 [8].
The depth of the surface layer for cryogenic hard turning can be up to several µm [4]. Quantifiable conditions of the surface layer include the (local) hardness (hardness as a function on the surface of the manufactured part), (local) microtopography and (local) structure distribution and residual stresses. A schematic overview of the structure of the surface layer and his states through the example of AISI 347 is given in Fig. 1. Manufacturing processes, such as cryogenic hard turning, acting forces and temperatures on the component surface layer and can thus have a negative (e.g. in the form of so-called brittle and hard “white layers” [5]), as well as a positive (e.g. increased hardness and improved wear resistance on the functional surface [6, 7]) influence on it. Correlations between process variables such as cutting forces and the resulting surface layer [9, 10], as well as between surface layer condition and resulting component properties [11] are known and have been qualitatively and quantitatively investigated in literature. However, the influence of disturbance variables on the process is not sufficiently investigated. In a first step, these influences have to be examined. With this a-priori knowledge, a non-linear feedforward control for the process can be reached. In a second step, in order to produce a surface layer with defined characteristics reliably (robustly) and to be able to control on disturbances, it is necessary to measure the quantifiable surface layer characteristics in-process during the production process, to carry out a target/actual comparison and to adopt the process parameters accordingly using a feedback loop. It is currently state of the art to quantitatively measure the surface layer conditions under laboratory conditions, i.e. exsitu. Here, there is a multitude of measuring techniques available like the tactile roughness measurement or confocal microscopy for surface microtopography quantification as well as x-ray diffraction measurement for detection of the residual stresses [12, 13]. However the direct transfer of these measurement techniques into the manufacturing process is difficult or impossible in many cases, and thus not applicable for the industrial production. Therefore a different approach is needed which is not based on the direct transfer of existing measuring instruments. An indirect approach to measurement of surface conditions (such as hardness or microstructure) in-process is to use process variables, which in some cases are already recorded (such as the process forces), in combination with additional sensors which operate close to the surface layer (like 3MA sensors [14] or scattered light measurement technology [15])
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and process knowledge in the form of models (like finite element models [16]). On the basis of these combined information, it should be possible to deduce not directly measurable surface layer conditions, by using observer-like structures from control theory. Goal of the research project presented is therefore to examine the possibilities for the observation of surface conditions during cryogenic hard turning of 100Cr6. Cryogenic hard turning is particularly relevant as a process for this research question, as the CO2 mass flow increases the tool life compared to conventional cooling strategies and improves the surface layer condition and topography [17]. In this paper, the possibility of indirect measurement of surface conditions such as hardness and roughness by observer structures will be discussed in more detail from a measurement technology point of view. First, the requirements of the materials and manufacturing will be presented and then the measurement technology will be discussed. 2. Overview of the material 100Cr6 and manufacturing technology The cryogenic hard turning of 100Cr6 was chosen as the manufacturing process to investigate the observability of the surface layer condition. The workpiece material (100Cr6) is chosen because it is a well-understood material for highly stressed, rotationally symmetrical machine parts, and well described in literature [11, 18, 19, 20, 21]. A lot of fundamental interrelations have already been qualitatively investigated and described. For example, thin austeniticmartensitic layers (so-called “white layers”) can form on the surface of the workpiece during hard turning of 100Cr6. One explanation for the formation of “white layers” is local heating and subsequent cooling. The exact origin, however, is still being investigated in other researches. The properties of these layers differ significantly from those of the bulk material, e.g. with regard to the hardness [22]. The resulting state of the surface layer after machining of 100Cr6 is thus significantly dependent on chosen machining parameters. In general, the surface layer condition of machined workpieces can be positively influenced by the use of cryogenic cooling media, which made it an alternative to conventional cooling strategies [17]. Among other positive effects, the layer thickness of the white layer can be noticeably reduced when using cryogenic cooling [23]. The fundamental qualitative relationships between cryogenic hard turning as a process, the effect of the process control variables and the surface layer of the material 100Cr6 as a process result (surface layer condition as a function of location) have already been investigated in literature [24, 25]. However, the correlations between in-process measured variables and the surface layer conditions as a function of place and time have yet to be examined. Due to the knowledge of the material 100Cr6 and the process of cryogenic hard turning, static models can already be set. However, these models mostly lack fine resolution and don’t consider dynamics and disturbances, such as tool wear or vibrations in the system. In order to evolve these static
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models into dynamic models, further experiments are required. For the samples (workpieces), consistency is important to exclude unknown factors as additional disturbances, such as deviations of the initial geometry of the sample or heat treatment variations, in order to be able to determine only wear effects and disturbance variables of the machine. It must therefore be ensured that the same heat treatment condition is set for all samples before processing. To investigate the effect, three quenching and tempering stages were selected which, depending on the tempering time, produce a different residual austenite content and thus different hardness. An overview of the chosen heat treatment time by 180°C and the expected residual austenite and hardness is given in Table 1. Table 1. tempering time and the expected residual austenite / hardness by a tempering temperature of 180°C [26]
Number 1 2 3
Time 102 min 103 min 104 min
Residual austenite < 15% < 10% < 1%
Hardness > 62 HRC 58 - 62 HRC < 58 HRC
After this overview of the material and the production process, the in-process surface layer observation will be discussed from a control theory point of view. 3. Cryogenic hard turning as a system: Challenges and solutions from the point of view of measurement technology From a control theory point of view, the process “cryogenic hard turning of 100Cr6” can be understood as a dynamic system with inputs u (t ) , state variables x (t ) , outputs (measurement) y (t ) and disturbance variables d (t ). But the correlation between this variables is non-linear, so neither is the system. Project goal is to estimate elements of the inprocess not measureable state vector x (t ) , like the hardness HV (t ) , by breaking down the entire system into a non-linear feedforward control and a linear control loop. It can be assumed that there is a (in general unknown) functional relationship between an applied force F (t ) and temperature J (t ) on a workpiece, and the resulting hardness HV (t ) : (1) HV (t ) = f ( F (t ),J (t ),...) An overview of the process is given in Fig. 2. Especially knowledge of the force and temperature is important since the evolution of the surface layer is mainly being influenced by the force and temperature (gradient) applied. Input variables for the process “cryogenic turning” can be combined in a vector u (t ) . These are: • • • •
Feed f (t ) Cutting Speed v (t ) Depth of cutting a (t ) CO2 Mass Flow m! CO 2 (t )
• • •
Aq values Aq( x, y ) Temperature J ( x, y, z ) and
C
p
In-process measurable quantities are bundled in the vector of the in-process measure y (t ) :
Jz ,i (t ), i = 1...3
Process Forces F ( x, y, z ) The actual surface layer condition is represented in the vector x (t ) and includes among others:
3
Fig. 2. process of cryogenic hard turning of 100Cr6 from a control engineering point of view.
Distribution of hardness of the workpiece surface layer HV ( x, y, z, t ) and • Microtopography Rk ( x, y, t ) . From the infinite-dimensional vector of the surface layer conditions, these two are primarily examined for the project. Therefore, in-process measurements must be taken that correlate as directly as possible with the previous mentioned surface zone conditions. The hardness of workpiece material is related to the temperature profile, the cooling rate and the forces applied to it [3]. To determine the process forces in x-, y- and zdirection, there will be integrated a force measuring platform in the turning machine. The temperature will be detected in three ways: with a pyrometer, the local temperature on the surface Jx , y (t ) at one fixed position of the workpiece can be measured. This measure value can be used to calibrate the thermographic camera. With the camera a planar temperature profile J ( x, y, t ) of the workpiece can be determined. Thermography cameras, however, have the same disadvantages in-process as other imaging techniques, especially, when cooling lubricants are used in the process. To complete the temperature measurement the internal local temperatures Jz ,i (t ), i = 1...3 of the workpiece will be detected with three integrated thermocouples. The use of thermocouples in the workpiece is also not suitable for later use in an industrial process. However, on the basis of the results of the research, it is possible to select from the three principles the one, that has the most expressive power with regard to the surface layer and to reconstruct the temperature profile via model. Together with a yet to be formulated model it should be possible to first reconstruct the whole temperature profile J ( x, y, z , t ) and afterwards drawing a conclusion from the temperature and the cutting forces to the hardness. In order to characterize the surface condition, not only hardness but also microtopography is considered a target quantity. For this purpose, the surface is measured after machining using the profile method. From the measured surface profile, roughness parameters such as Ra or Rz can then be determined. However, these do not contain any information about the shape of the surface profile. This information is contained in the Rk-parameters, which can also be determined from the surface profile using the Abbott curve. Based on this additional information, the group of Rkparameters was selected as target values. In-process, however, the tactile profile method can’t be used. However, an angle •
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resolving scattered light (ARS) sensor can also be used to record Aq-values in-process. The Aq-value is calculated as the variance from the scattered light distribution. If it is now assumed that surface structures are similar, i.e. have a similar surface profile, the Aq-value changes proportionally to the Rk parameters [27]. Disturbances are summarized in the disturbance vector d (t ) . This will be: • Wear of the tool • Workpiece initial state or • Vibrations • Disturbances, which will be detected during the research From a control theory point of view, there is a functional relationship f Sys between input variables u (t ), (known and unknown) disturbances d (t ) and hidden states x (t ) : (2) x! (t ) = f Sys ( x (t ), u (t ), d (t ))
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measuring principles, most optical measuring methods are sensitive to vibrations and therefore not applicable in-process, e.g. white-light interferometry [28], focus variation or confocal microscopy. In order to measure the microtopography and form, a combination of an angle resolved scattered light (ARS) sensor and a pneumatic distance sensor will be developed. Both sensors themselves are state of the art for in-process measurement. The insensitivity of the ARS sensor to vibrations is based on the measuring principle, since it detects surface angles and these are not influenced by vibrations. The measurement principle and evaluation algorithms for the ARS are described in detail in literature [15, 29, 30]. The in-process capability of the ARS sensor has
As mentioned before, the surface conditions like
HV ( x, y, z, t ) are included in the vector x (t ) and for example the tool wear in the disturbance vector d (t ) , but aren’t direct
measurable in-process. It can also be assumed for the inprocess measured variables y (t ) that these depend on the workpiece condition itself, on input and disturbance variables: (3) y (t ) = f Meas ( x (t ), u (t ), d (t ))
Surface layer conditions that can be measured in the laboratory, e.g. the resulting hardness, can be understood as elements of the state vector at the end time of machining: ì HV ( x, y, z , te ) ï (4) x (t e ) = í ! ï ! î If a reasonably accurate correlation between input variables u(t), measured variables y (t ) and state variables x (t ) can be described mathematically, in form of a set of nonlinear functions f ( x (t ), u (t ),...) , implemented in the form of a feedforward control, and a linear system, implemented in the form of a control loop, then - assuming that the system is observable - the state x (t ) can be calculated from the measured variables y (t ) with an observer. With the surface layer condition observed, the difference between nominal and actual can be compensated using the controller. This goal from a control theory point of view is visualized in a block diagram in Fig. 3. To observe the surface layer, the measured variables must be connected to the state variables over modellike correlations. 4. Opto-pneumatic scattered light sensor In order to be able to observe and indirectly measure the surface layer condition, apart from the knowledge of the input variables of the system, special measurement variables are relevant which correlate directly with the surface zone condition. Because of the rough environmental conditions during the process of turning, like vibrations, chips and lubrication, the in-process measurement of the microtopography can only be implemented contactless. Optical topography measurement technology is widespread in the industry. Due to the physical
Fig. 3. Goal of the research from a control theory point of view.
also already been demonstrated in several investigations [31]. The measurement result of the ARS sensor gives information about the surface roughness as the extent of roughness directly correlates with the light scattering [27, 32]. Pneumatic measurement technology is widely spread in the industry for in-process and in-line measurement of shape and distance. There are different measuring principles for pneumatic measuring, e.g. pressure measurement or the flow measurement method. The pressure measurement method is the mostly used method and also used in this research. The function principle and influence factors on the measurement, e.g. the tilt of the sensor, are also described in publications before [33]. For the in-process usage of the ARS sensor during cryogenic turning, the measuring point has to be cleaned from CO2 snow. Therefore a pneumatic cleaning nozzle would have to be installed. To dispense with this additional component and safe space in the measurement setup, the measuring spot of the ARS sensor can be blown freely directly with the pneumatic sensor. To achieve this object, the light of the ARS sensor has to be lead through the measuring nozzle of the pneumatic sensor. This layout brings a lot of positive synergies: • The measuring spot for the ARS sensor is freed from the CO2 snow or other cooling lubricant by the pneumatic sensor • The overpressure in the ARS sensor prevents contamination of the lenses • The measuring values can be assigned to each other, if they get the same trigger signal
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The sampling frequency of the integrated pneumatic sensor depends on the used transducer and the response time of the sensor by itself. The response time of the pneumatic sensor depends on several factors, e.g. diameter of pre- and measuring nozzle and their ratio, the volume of the measuring chamber. Further researches will show how a variation of these parameters reduces the response time of the pneumatic sensor. Commercial, pneumo-electronic transducers have a response time of 15ms and therefore a sampling frequency of 66 Hz. This frequency isn’t high enough for in-process measuring. So the pneumatic sensor can be used for positioning of the sensor during the setting up of the machine, the cleaning of the measuring spot of the ARS sensor and for in-line measurement of the shape. 5. Conclusion and outlook
Fig. 4. schematic layout of the opto-pneumatic ARS sensor: a) linear PDA – b) LED – c) collimated beam – d) scattering light – e) lens – f) window – g) measuring chamber – h) measuring nozzle – i) workpiece - j) pre-nozzle – k) pre-chamber – l) air supply
By measuring the distance of the pneumatic sensor, the ARS sensor can be set up in the ideal focal plane affected by the construction A schematic layout of the combination from the ARS sensor and the pneumatic distance sensor is given in Fig. 4. The volume of the measuring chamber of the pneumatic sensor should be chosen as small as possible to achieve a short response time of the sensor, because the response behavior correlates with the volume of the measuring chamber [33]. Therefore, the entire area in front of the lenses cannot be used to form the measuring chamber. To reduce the volume, the measuring chamber is constructed near the measuring nozzle. A window must therefore be inserted on the opposite site of the measuring chamber, seen from the measuring nozzle. For this the normal linear design of the pneumatic components (air supply, pre-chamber, pre-nozzle, measuring chamber and measuring nozzle) within the sensor has to be changed: the pre-nozzle is now sideways from the measuring chamber. That has the consequence: the fluid must stream around the corner from the pre- to the measuring nozzle. To investigate the effect of this new layout, the flow analysis must be done with a CFD simulation. The measuring result of an ARS sensor, like the Aq-value, contains the information of predominant surface angles of the illuminated area. This is a round area with a diameter of 0,9 mm. With a sampling frequency of 2 kHz, the in-process measuring is possible with 50% overlap along the circumference within the defined process parameters. Caused by the feed, every point along the workpiece axis is measured 6 times, so the overlap in this direction is nearly 80%. •
The goal of the research discussed in this paper is the observation of the surface conditions, explicitly hardness and microtopography, in-process. Hardness HV and the microtopography, in the form of Rk parameters, cannot be measured directly during machining. Therefore, in following investigations, the measurement variables are recorded, which are linked to these states. Subsequently, the surface layer condition to be observed is deduced by means of deposited models, which have to be developed. To be able to deduce the hardness, the temperature and the process forces are recorded in-process. In order to draw conclusions about the microtopography, the surface angles are to be measured by means of an ARS sensor, because the Aqvalues obtained here correlate with the Rk-parameters. Therefore the surface has to be cleaned from the CO2 snow. To achieve this, a pneumatic distance sensor is integrated in an existing ARS sensor. This combination brings a lot of positive synergies, e.g. the overpressure in the ARS sensor prevents contamination of the lenses. In the further course of the project, the samples are first prepared in such a way, that all samples achieve one of the three defined initial states. These are then processed. The surface layer condition is then measured ex situ and compared with the surface layer condition calculated in models. If the surface layer condition can be sufficiently well represented by the models, a process control can then be set up, whereby in the future a targeted surface layer condition can be set independently of disturbance variables in the process. 6. Acknowledgements The scientific work has been supported by the DFG within the research priority program SPP 2086. The authors thank the DFG for this funding and intensive technical support. References [1] Aurich, C., Schneider, F., Mayer, P., Kirsch, B., Hasse, H., 2016, Oberflächenerzeugungs-Morphologie-Eigenschafts-Beziehungen: Vom Fertigungsverfahren direkt zu den Bauteileigenschaften, ZWF 04/2016, p. 213-216 [2] The International Academy for Production, 2014, Encyclopedia of Production Engineering, Lapperrière, L., Reinhard, G.. Editors. Springer
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