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CIRP Journal of Manufacturing Science and Technology
journal homepage: www.elsevier.com/locate/c irpj
CIRP Journal of Manufacturing Science and Technology 6 (2013) 181–186
An integrated approach to support the joint design of machine tools and process planning
M. Leonesio, L. Molinari Tosatti, S. Pellegrinelli, A. Valente *
Institute of Industrial Technologies and Automation (ITIA), National Research Council of Italy (CNR), Via Bassini 15, 20133 Milano, Italy
A R T I C L E I N F O
Article history:
Available online 9 April 2013
Keywords:
Process planning
Machine tool kinematics and dynamics Machine design
STEP-NC
A B S T R A C T
The con?guration of machine tools and process planning problem are traditionally managed as independent stages, where the process plan is designed by considering a number of machine tool solutions available from catalogue. This strategy presents a number of disadvantages in terms of process results and machine capabilities fully exploitation. The current paper proposes an integrated approach for jointly con?guring machine tools and process planning. The approach is structured in 4 major recursive steps that eventually ensure the accomplishment of the best trade-off between the machine tool static and dynamic behaviour, the process quality and the resulting economic ef?ciency. The bene?ts of the approach have been evaluated for a test case application in the railway and automotive sectors.
。 2013 CIRP.
1. Introduction
The design and con?guration of machine tools is instrumental for European manufacturing competitiveness [1]. Coherently with the mass customization principles and the traditional European know how in the ?eld of instrumental goods production, machine tools should result from a con?guration process tightly related to the analysis of the families of products and process quality requirements rather than being a standard and rigid catalogue equipment. This makes the machine con?guration and the process planning as two steps of the same problem where the machine tool geometric and kinematics features in?uence the accessibility to the workpiece operations along with the ?xturing system con?guration and the machine dynamic impacts on the ?nal quality and costs of the workpiece.
The relationships between machine tool con?guration and process planning have been widely investigated by the scienti?c literature with reference to the following topics: the evaluation of machine capabilities to statically realize a process plan [2], the execution of a process plan across several resources [3], the energy ef?cient process planning [4–7] and, ?nally, evaluation of the impact of machine tool dynamic behaviour on the process planning de?nition [8]. However, the interest of these works is mostly focused on the impact of a speci?c machine tool architecture and performance on the process planning problem.
* Corresponding author. Tel.: +39 0223699917; fax: +39 0223699941.
E-mail address: anna.valente@itia.cnr.it (A. Valente).
The current paper presents an integrated approach to support the joint design of machine tools and process planning. The proposed approach is structured in four major steps as illustrated in Fig. 1.
The ?rst step consists in the analysis of the workpiece CAD model. The workpiece is analysed according to the STEP standard [9] through the identi?cation of machining feature (geometrical description of the region of the workpiece to be machined), machining operations (selection of cutting tools, machining parameters and strategies) and machining workingsteps (MWS
– association between a machining feature and a machining operation). On the basis of a number of alternative MWSs, Step 1 identi?es the MWSs that globally better match the production requirements and machine behaviour.
The geometric and technological information related to the family of products together with the data about the production demand and the forecasts about possible product evolutions are utilized in Step 2 related to the machine tool design. The outcome of this step is a domain of general-purpose machine tools that ?t the production requirements from both the dynamic and static point of view Steps 1 and 2 are traditionally handled as independent phases as general-purpose machine tools are normally con?gured with no knowledge of the actual products to machine and the process planning is usually developed starting from an existing machine catalogue.
Step 3 regards the dynamic simulation of the machine tool solutions resulting from Step 2 while executing the MWSs identi?ed in Step 1. The dynamic behaviour of machine tools is evaluated against a number of Key Performance Indicators (KPIs) dealing with the energy consumption, tool wear, surface
1755-5817/$ – see front matter 。 2013 CIRP. http://dx.doi.org/10.1016/j.cirpj.2013.03.002
M. Leonesio et al. / CIRP Journal of Manufacturing Science and Technology 6 (2013) 181–186
185
MWS
assessment
Workpiece CAD Model
Long-term production requirements
1. WORKPIECE
ANALYSIS
MWSs
2. MACHINE TOOL
DESIGN
Machine Tool
3. DYNAMIC CUTTING SIMULATION
KPIs
Dynamic and
Kinematic
4. FIXTURE SELECTION AND SETUP PLANNING
Alternative Process Plans
Machine tool design assessment
starts from the collection of data about the family of products to be processed. These data include the geometrical and technological characteristics of products synthesized in the workpiece analysis step along with the production volumes.
The con?guration process involves the identi?cation of the minimum set of machine tool requirements that accomplish the process constraints (such as the minimum working cube, the number of axes, the spindle orientation and power). On the basis of this minimum set, other types of constraints can be taken into account such as the productivity, the reliability, the available budget, the energy ef?ciency as well as the machine global size (in the case it should be integrated in a prede?ned shop-?oor). In the case the demand is expected to be variable over time, additional evaluations can be done with regard to the customization of the
machine ?exibility degree to match the forecasted changes.
Fig. 1. The integrated approach.
roughness, maximal required spindle power and torque. The KPIs are concurrently relevant to the MWS assessment as they could drive the adjustment of process parameters and to the machine tool design by leading to the tuning of the kinematic and dynamic characteristics.
The last step of the approach concerns the selection of one or more ?xtures and the de?nition of workpiece orientations as well as the association of the operations to a given orientation (workpiece setup) [10,11]. The outcome of this phase is the generation of alternative process plans feasible from the workpiece quality requirements [12]. Production time and costs are investigated and optimized on the basis of the MWS KPIs.
The following section of this work will provide the reader with a more comprehensive description of each step of the proposed approach (from Sections 2 to 6). Section 7 will present an industrial test case considered to evaluate the approach bene?ts. Section 8 will outline the conclusions and future work.
2. Workpiece analysis
The workpiece analysis is the ?rst activity in feature-based process planning [13] and aims at de?ning the operations that are necessary for the complete machining of the workpiece. As stated in Section 1, the workpiece analysis is based on the STEP-NC standard, leading to the de?nition of the machining feature (geometric description of the region to be machined), machining operations (strategy of machining) and machining workingstep (association between a feature and an operation). As a region can be machined on the basis of alternative strategies in terms of cutting tools, machining parameters or tool path, the same feature can be realized by alternative operations and, consequently, alternative MWSs. The complete realization of a workpiece implies the identi?cation of the technological constraints among the MWSs to be executed. The proposed approach considers two different kinds of technological constraints: precedence and tolerance constraints [14]. Precedence constraints impose an order of execution between two MWSs whereas tolerance constraints require the execution of two MWSs in the same setup to ensure the accomplishment of quality requirements. On the basis of these technological constraints, a network of operations can be built by taking into account the precedence constraints and the alternative strategies to process a speci?c feature. This network will be employed during the last step of the approach dealing with the ?xture selection and setup planning.
3. Machine tool design
The con?guration of the machine tool is an extremely articulated process that, coherently with the proposed approach,
All this information leads to the identi?cation of a domain of alternative machine solutions characterized by different archi- tectures, performance and costs. At this stage, the machine design process requires the evaluation of machine performance while executing the process. The analysis of machine–process dynamic interactions enables the evaluation of the machine criticalities and possible improvements.
The next section outlines the dynamic cutting simulation as a means to assess the machine tool design and the workpiece analysis as part of the process plan.
4. Dynamic cutting simulation
In the metal cutting strategy, the objective of decreasing manufacturing time and costs is strictly connected to the need for ensuring the requested level of quality. The quality can concern directly the workpiece geometrical properties, or it may refer to the process, for instance, its ef?ciency in terms of energy consumption.
The workpiece quality is affected by all the phenomena that determine an undesired displacement of the tool with respect to the nominal path. A comprehensive assessment of workpiece quality entails an analysis of four major categories of phenomena: thermal deformations of machines and parts; volumetric position- ing errors of the tool tip; dynamic interaction among machine, process and workpiece; trajectories errors due to CNC and/or feed drives performance. Due to the high demanding performance in terms of material removal rate (MRR), the modelling and minimization of vibrations, either forced or caused by chatter instability, represents a major limitation for improving productiv- ity and part quality in metal removal processes. Vibrations occurrence has several negative effects: poor surface quality, out of tolerances, excessive noise, disproportionate tool wear, spindle damage, reduced MRR to preserve surface quality, waste of materials, waste of energy and, consequently, environmental impact in terms of materials and energy [15]. Besides the surface quality and the violation of tolerances, the other effects deal with process quality and have a direct impact of the overall production ef?ciency. The key for evaluating the level and the effects of vibrations onset is the so-called dynamic cutting process simula- tion, able to couple the forces originating from the material removal with the relative dynamic and static response between tool tip and workpiece [16]. While the simulation of single processes or machine characteristics is state of the art, the integration of process and the machine tool modelling in the simulations is particularly innovative. The interactions between machine tool, the workpiece and the process surely represent a great challenge as their modelling must be evaluated to address the forced vibrations onset and regenerative chatter instability. The discontinuous cutting forces produced by the machining process excite the tool tip causing a chip section modulation
in?uencing the cutting force itself. In order to incorporate the described effects, the architecture of the dynamic cutting simulation approach should integrate the following functional modules:
? A part program interpreter able to provide the tool path with the related velocity law, together with the cutting parameters de?ning the operation (for instance, spindle speed and feed rate);
? A ‘‘geometric engine’’ for computing the workpiece-tool engage- ment and the chip geometry computation;
? A force model relating the chip geometry with the cutting forces expressed by each engaged cutter and their summation;
? A representation of the tool tip and workpiece relative dynamics;
? A time-domain integrator for the overall dynamic simulation.
In most of existing commercial applications, the dynamic loop
All the above-mentioned considerations are automatically taken into account by the developed SW module.
4.1.2. Spindle bearings load
Spindle bearings usually face a progressive wear during machining and most of the spindle maintenance time is devoted to bearings substitution. The bearing catalogues report a stan- dardized formula to compute bearing life by referring to the ‘‘dynamic equivalent load’’, able to synthesize in a single number the effort requested to a bearing during a complex load history. Assuming that spindle bearings load is proportional to the spindle shaft bending moment, the ‘‘dynamic equivalent load’’ can be computed for each MWS, and used to compare the induced bearing stress. In formula:
xy
3 F3 etT
Z TMWS s?????????????????
between machine and process is not closed, as cutting forces disturbances are supposed to not affect tool position and
BL ? Ltool ·
0
dt
TMWS
(2)
consequently chip section. Actually, the complexity of the model severely reduces the existing commercial applications: the unique commercial application realizing a proper ‘‘Virtual Machining’’ taking into account dynamic cutting is MachProTM by MALINC.
The dynamic simulation results contribute in evaluating the quality of the machining process. This means to identify a number of KPIs to be measured and tracked over time.
4.1. Key Performance Indicators (KPI)
The KPIs considered in the proposed approach are interpreted as a measure of the machine tool dynamics with respect to the required machining operations. On the basis of the value of these indicators some instrumental choices can be realized with reference to the machine structure and control system. In the following part of the current section, the most important considered KPIs are brie?y introduced.
4.1.1. Energy consumption
The mechanical energy necessary to perform the machining operation can be obtained by computing the integral of the mechanical power over machining time, namely:
Etot ? Es pindle t Eaxes
where Ltool is the tool length and Fxy is the cutting force resultant in
the milling plane (xy).
4.1.3. Roughness
Surface roughness depends on several factors related to cutting kinematic and vibration onset. In the proposed approach, the tool vibrations and de?ection are directly addressed as a surface roughness indicator. They are crucial in determining an acceptable level of surface roughness and comparing the in?uence of different dynamic responses on this parameter. Thus, the indicator becomes:
T
R ? maxek~xtooletTkT (3)
MWS
where ~xtooletT is the tool tip displacement over time.
4.1.4. Tool cutter load
Tool chipping occurs when the shear pressure on the cutting edge overcomes the mechanical resistance of the material. The shear stress is proportional to the cutting force expressed by the
single cutter Fcutter normalized with respect to the cutting edge engagement (b). Therefore, the corresponding indicator is:
1
TMWS
Cl ? b maxeFcutter etTT (4)
Z TMWS
?
Vs pindleTs pindleetTdt t
Z TMWS *
v feedetT × ~Fc etTdt (1)
The other KPIs consist in an estimation of the tool wear exploiting
0 0
by Taylor formula, the maximum spindle power and maximum
where Vspindle is the spindle velocity, Tspindle is the spindle torque,
spindle torque requested to cut the material, as well as the
~v feed is the instantaneous feed velocity, ~Fc
TMWS is the MWS duration.
is the cutting force and
maximum load requested by machine tool axes to provide feed movement. They are directly available from simulation and
The computation of electrical energy consumption can be more precisely computed by keeping separated axes and spindle mechanical power since the ef?ciency of the corresponding drives (whose estimation is out of scope) is usually different. Moreover, in order to compare the copper losses in spindle winding for different MWSs, the Root Mean Squared value (RMS) of spindle torque can be computed as well, starting from torque time history.
In literature, cutting energy consumption is commonly estimated by a constant volumetric speci?c energy associated to the material type: this approximated approach con?icts with the experimental data, whereas the speci?c energy changes with tool, process parameters and machines [17]. The speci?c spindle power consumption (SSPC) is inversely related to cutting speed, feed per tooth, depth of cut and width of cut. The situation can be different if the process becomes unstable (chatter occurrence): as the spindle copper losses are proportional to the RMS of the torque, the presence of a dynamic component in cutting force may cause an increase of SSPC.
represent constraints that the machine tool must respect to be able to perform a given operation.
5. Machine tool design and MWS assessment
Coherently with the proposed approach, the interpretation of KPIs can drive the improvement choices both for the process planning and the machine tools.
Based upon the KPIs values, a number of MWSs can be updated to obtain a more performing and feasible process. For example, in case the KPI expressing the surface roughness indicates that the process is not compliant to the workpiece quality constraints, some MWS such as feed rate or spindle speed can be adjusted; similarly, according to maximum spindle power, feed rate, spindle speed or cut of depth can be modi?ed in order to reduce the cost associated to the manufacturing process.
The impact of KPIs on the machine tool choices is more complex to be addressed. The KPIs expressing the required
Fig. 2. Machine tool dynamic compliance and boundaries. (For interpretation of the references to colour in this ?gure legend, the reader is referred to the web version of this article.)
maximum spindle power and maximum spindle torque can be directly exploited to size the proper motor, while the spindle bearings load can be used to choose the proper bearings guaranteeing the desired component life. On the other hand, the KPIs associated to energy consumption, tool life, tool cutter load, may be wrongly related to the sole process parameters, whereas, together with surface roughness indicator,
they strictly depend on machine tool dynamic performance, being severely degraded by vibration onset. Therefore, the enhancement of these latter KPIs can be traced back to the assessment of the best MT dynamic performance able to prevent chatter occurrence. A method to carry out this task is outlined in the following.
The relationship between chatter occurrence and the KPIs can be analysed by exploiting a reduced set of variables; for example, adopting the 0th-order approach described in [16]. Under the following hypothesis:
? Milling operation in X and Y plane, characterized by a straight line trajectory,
? No regeneration in Z direction,
? No low immersion angles,
the relationship between chatter instability occurrence and machine tool is ana
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