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Procedia CIRP 21 ( 2014 ) 189 194 Available online at 2212-8271 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:/creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the International Scientific Committee of “24th CIRP Design Conference” in the person of the Conference Chairs Giovanni Moroni and Tullio Tolio doi: 10.1016/j.procir.2014.03.120 ScienceDirect 24th CIRP Design Conference Robust design of fixture configuration Giovanni Moroni a , Stefano Petro a,* , Wilma Polini b a Mechanical Engineering Department, Politecnico di Milano, Via La Masa 1, 20156, Milano, Italy b Civil and Mechanical Engineering Department, Cassino University, Via di Biasio 43, 03043, Cassino, Italy Corresponding author. Tel.:+39-02-2399-8530; fax:+39-02-2399-8585. E-mail address: stefano.petropolimi.it Abstract The paper deals with robust design of fixture configuration. It aims to investigate how fixture element deviations and machine tool volumetric errors aect machining operations quality. The locator position configuration is then designed to minimize the deviation of machined features with respect to the applied geometric tolerances. The proposed approach represents a design step that goes further the deterministic positioning of the part based on the screw theory, and may be used to look for simple and general rules easily applicable in an industrial context. The methodology is illustrated and validated using simulation and simple industrial case studies. c2014 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of the International Scientific Committee of “24th CIRP Design Conference” in the person of the Conference Chairs Giovanni Moroni and Tullio Tolio. Keywords: Tolerancing; Error; Modular Fixture. 1. Introduction When a workpiece is fixtured for a machining or inspection operation, the accuracy of an operation is mainly determined by the eciency of the fixturing method. In general, the machined feature may have geometric errors in terms of its form and posi- tion in relation to the workpiece datum reference frame. If there exists a misalignment error between the workpiece datum ref- erence frame and machine tool reference frame, this is known as localization error 1 or datum establishment error 2. A localization error is essentially caused by a deviation in the po- sition of the contact point between a locator and the workpiece surface from its nominal specification. In this paper, such a the- oretical point of contact is referred to as a fixel point or fixel, and its positioning deviation from its nominal position is called fixel error. Within the framework of rigid body analysis, fixel errors have a direct eect on the localization error as defined by the kinematics between the workpiece feature surfaces and the fixels through their contact constraint relationships 3. The localization error is highly dependent on the configu- ration of the locators in terms of their positions relative to the workpiece. A proper design of the locator configuration (or locator layout) may have a significant impact on reducing the localization error. This is often referred to as fixture layout op- timization 4. A main purpose of this work is to investigate how geomet- ric errors of a machined surface (or manufacturing errors) are related to main sources of fixel errors. A mathematic frame- work is presented for an analysis of the relationships among the manufacturing errors, the machine tool volumetric error, and the fixel errors. Further, optimal fixture layout design is speci- fied as a process of minimizing the manufacturing errors. This paper goes beyond the state of the art, because it considers the volumetric error in tolerancing. Although the literature demon- strates that the simple static volumetric error considered here is only a small portion of the total volumetric error, a general framework for the inclusion of volumetric error in tolerancing is established. There are several formal methods for fixture analysis based on classical screw theory 5,6 or geometric perturbation tech- niques 3. In nineties many studies have been devoted to model the part deviation due to fixture 7. Sodenberg calculated a sta- bility index to evaluate the goodness of the locating scheme 8. The small displacement torsor concept is used to model the part deviation due to geometric variation of the part-holder 9. Con- ventional and computer-aided fixture design procedures have been described in traditional design manuals 10 and recent lit- erature 11,12, especially for designing modular fixtures 13. A number of methods for localization error analysis and reduc- tion have been reported. A mathematical representation of the localization error was given in 14 using the concept of a dis- placements screw vector. Optimization techniques were sug- 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:/creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the International Scientifi c Committee of “24th CIRP Design Conference” in the person of the Conference Chairs Giovanni Moroni and Tullio Tolio 190 Giovanni Moroni et al. / Procedia CIRP 21 ( 2014 ) 189 194 gested to minimize the magnitude of the localization error vec- tor or the geometric variation of a critical feature 14,15. An analysis is described by Chouduri and De Meter 2 to relate the locator shape errors to the worst case geometric errors in machined features. Geometric deviations of the workpiece da- tum surfaces were also analyzed by Chouduri and De Meter 2 for positional, profile, and angular manufacturing tolerance cases. Their eects on machined features, such as by drilling and milling, were illustrated. A second order analysis of the localization error is presented by Carlson 16. The computa- tional diculties of fixture layout design have been studied with an objective to reduce an overall measure of the localization er- ror for general three dimensional (3D) workpieces such as tur- bine air foils 1,4. A more recent paper shows a robust fixture layout approach as a multi-objective problem that is solved by means of Genetic Algorithms 17. It considers a prismatic and rigid workpiece, the contact between fixture and workpiece is without friction, and the machine tool volumetric error is not considered. About the modeling of the volumetric error, several models have been proposed in literature. Ferreira et al. 18,19 have proposed quadratic model to model the volumetric error of ma- chines, in which each axis is considered separately, thoghether with a methodology for the evaluation of the model parame- ters. Kiridena and Ferreira in a series of three papers 2022 discuss how to compensate the volumetric error can be mod- eled, the parameters of the model evaluated, and then the er- ror compensated based on the model and its parameters, for a three-axis machine. Dorndorf et al. 23 describe how volu- metric error models can help in the error budgeting of machine tools. Finally, Smith et al. 24 describe the application of vol- umetric error compensation in the case of large monolithic part manufacture, which poses serious diculties to traditional vol- umetric error compensation. Anyway, it is worth noting that all these approaches are aimed at volumetric error compensation: generally volumetric error is not considered for simulation in tolerancing. In previous papers a statistical method to estimate the po- sition deviation of a hole due to the inaccuracy of all the six locators of the 3-2-1 locating scheme was developed for 2D plates and 3D parts 25,26. In the following, a methodology for robust design of fixture configuration is presented. It aims to investigate how fixel errors and machine tool volumetric er- ror aect machining operations quality.In2 the theoretical approach is introduced, in3 a simple industrial case study is presented, and in4 some simple and general rules easily ap- plicable in an industrial contest are discussed. 2. Methodology for the simulation of the drilling accuracy To illustrate the proposed methodology, the case study of a drilled hole will be considered. The case study is shown in Fig. 1. A location tolerance specifies the hole position. Three locators on the primary datum, two on the secondary datum, and one on the tertiary determine the position of the workpiece. Each locator has coordinates related to the machine tool refer- ence frame, represented by the following six terns of values: p 1 (x 1 ,y 1 ,z 1 ) p 2 (x 2 ,y 2 ,z 2 ) p 3 (x 3 ,y 3 ,z 3 ) p 4 (x 4 ,y 4 ,z 4 ) p 5 (x 5 ,y 5 ,z 5 ) p 6 (x 6 ,y 6 ,z 6 ) (1) Fig. 1. Locator configuration schema. The proposed approach considers the uncertainty source in the positioning error of the machined hole due to the error in the positioning of the locators, and the volumetric error of the machine tool. The final aim of the model is to define the ac- tual coordinates of the hole in the workpiece reference system. The model input includes the nominal locator configuration, the nominal hole location (supposed coincident with the drill tip) and direction (supposed coincident with the drill direction), and the characteristics of typical errors which can aect this nomi- nal parameters. 2.1. Eect of locator errors The positions of the six locators are completely defined by their eighteen coordinates. It is assumed that each of these coor- dinates is aected by an error behaving independently, accord- ing to a Gaussian N parenleftBig 0, 2 parenrightBig distribution. The actual locator coordinates will then identify the work- piece reference frame. In particular, the z prime axis is constituted by the straight line perpendicular to the plane passing through the actual positions of locators p 1 , p 2 and p 2 , the x prime axis is the straight line perpendicular to the z prime axis and to the straight line passing through the actual position of locators p 4 and p 5 , and finally the y prime axis is straightforward computed as perpendicular to both z prime and x prime axes. The origin of the reference frame can be obtained as intersection of the three planes having as normals the x prime , y prime , and z prime axes and passing through locators p 4 , p 6 and p 1 respectively. The formulas for computing the axis-direction vectors and origin coordinates from the actual locators coordi- nates are omitted here, for reference see the work by Armillotta et al. 26. The axis-direction vectors and origin coordinates define an homogeneous transformation matrix 0 R p 27, which allows to convert the drill tip coordinate expressed in the machine tool reference frame P 0 to the same coordinates expressed in the workpiece reference frame P prime 0 , through the formula: P prime 0 = 0 R 1 p P 0 (2) 191 Giovanni Moroni et al. / Procedia CIRP 21 ( 2014 ) 189 194 2.2. Eect of machine tool volumetric error To simulate the hole location deviation due to the drilling operation, i.e. to the volumetric error of the machine tool, the classical model of three-axis machine tool has been considered 27. It will be assumed the drilling tool axis is coincident with the machine tool z axis, so that, in nominal conditions and at the beginning of the drilling operation, its tip position can be de- fined by the nominal hole location and the homogeneous vector k = 0010 T . The aim is to identify the position error p of the drill tip in the machine tool reference system, and the direction error d of the tool axis. According to the three-axis machine tool model it is possible to state that: p = 0 R 1 1 R 2 2 R 3 P 3 P 0 (3) where P 0 = bracketleftbig xyzl 1 bracketrightbig T is the nominal drill tip location in the machine tool reference system (x, y, and z being the trans- lations along the machine tool axes, and l being the drill length), P 3 = 00l 1 T is the drill tip position in the third (z axis) reference system, and 0 R 1 , 1 R 2 , 2 R 3 are respectively the perturbed transformation matrices due to the perturbed transla- tion along the x, y, and z axes. These matrices share a similar form, for example: 0 R 1 = 1 z (x) y (x) x+ x (x) z (x) 1 x (x) y (x) y (x) x (x) 1 z (x) 000 1 (4) where theandterms are the translation and rotation errors along and around the x, y, and z axes (e.g. z (x) is the rotation error around the z axis due to a translation along the x axis). Considering three transformation matrices, there are eighteen error terms. These errors are usually a function of the volu- metric position (i.e. the translations along the three axes), but if the volumetric error is compensated, their systematic com- ponent can be neglected and they can be assumed to be purely random with mean equal to zero. Developing Eq. (3) leads to very complex equations; for example, dx = x (x)+ x (y) z (x)( y (y)+y) y (z) ( z (x)+ z (y) x (y) y (x)+ z (y) y (x) x (z)( y (x) y (y)+ z (x) z (y)1) l( y (x)+ y (y)+ x (z)( z (x)+ z (y) x (y) y (x)+ x (y) z (x) y (z)( y (x) y (y)+ + z (x) z (y)1)+( z (z)+z)( y (x)+ y (y)+ + x (y) z (x) (5) However, volumetric errors in general should be far smaller than translations along the axes, so only the first order com- ponents of Eq. (3) are usually significant. Finally, Assuming the drilling tool axis coincide with the z axis, Eq. (3) can also calculate the direction error d by substituting P 0 =P 3 =k. If only the first order components are considered, it is possi- ble to demonstrate that p and d are linear combination of the andterms. In particular, lets define as = bracketleftBigg p d bracketrightBigg (6) the six-elements vector containing p and d staked. Applying Eq. (3), neglecting terms above the second order, it is possible to demonstrate that (please note that, due format constraints, in Eq. (7) the dots . indicate that a row of the matrix is bro- ken over more lines, so the overall linear combination matrix appearing here isa6X18matrix) = 111000. 000000. zlzl l y 00 000111. 000lzlzl. 000000 000000. 111000. 000000 000000. 000100. 1 1 1000 000000. 000111. 010000 000000. 000000. 000001 x (x) x (y) x (z) y (x) y (y) y (z) z (x) z (y) z (z) x (x) x (y) x (z) y (x) y (y) y (z) z (x) z (y) z (z) =Cd (7) Now, lets assume that each term is independently dis- tributed according to a Gaussian N parenleftBig 0, 2 p parenrightBig distribution, and that each term is independently distributed according to a N parenleftBig 0, 2 d parenrightBig distribution. It is then possible to demonstrate 28 that follows a multivariate Gaussian distribution, with null expected value and covariance matrix which can be calculated by the formula CC T , where is the covariance matrix of d, which happens to be a diagonal 18 X 18 matrix with the first nine diagonal elements equal to 2 p , an the remaining diagonal 192 Giovanni Moroni et al. / Procedia CIRP 21 ( 2014 ) 189 194 elements equal to 2 d . The final covariance matrix of is: 2 d y 2 + +2 2 d (lz) 2 + +3 2 p + +l 2 2 d 00 2 d (3l 2z) 2 d (lz) 0 0 2 2 d (lz) 2 + +3 2 p + +l 2 2 d 0 2 d (lz) 2 d (3l 2z) 0 003 2 p 000 2 d (3l 2z) 2 d (lz) 04 2 d 00 2 d (lz) 2 d (3l 2z) 004 2 d 0 00000 2 d (8) This model can be adopted to simulate the error in the loca- tion and direction of the hole due to the machine tool volumetric error. 2.3. Actual location of the manufactured hole Now, it is possible to simulate the tip location and direction according to the model described in 2.2, and to transform it into the workpiece reference frame as described in2.1: P 0 prime = 0 R 1 p parenleftBig P 0 + p parenrightBig k prime = 0 R 1 p (k+ d ) (9) With this information it is possible to determine the entrance and exit location of the hole in the workpiece reference system. Point P prime 0 and vector k prime define a straight line, which is nothing else than the hole axis, as: p prime =P 0 prime +sk prime p x prime p y prime p z prime = P 0 x prime P 0y prime P 0z prime +s k x prime k y prime k z prime (10) where p is a generic point belonging to the line and s R is a parameter. Defining T as the plate thickness, it is possible to calculate the values of s for which p prime z is equal respectively to 0 and T: s exit =P 0z prime /k z prime s entrance =(P 0z prime T)/k z prime (11) These values of s substituted in Eq. (10) yield respectively the coordinates of the exit and entrance point of the hole. Finally, it is possible to calculate the distances between the two exit and entrance points of the drilled and nominal holes: d 1 = vextendsingle vextendsingle vextendsingleP 0 prime +s entrance k prime P 0 vextendsingle vextendsingle vextendsingle d 2 = vextendsingle vextendsingle vextendsingleP 0 prime +s exit k prime P 0,exit vextendsingle vextendsingle vextendsingle (12) where P 0,exit is the nominal location of the hole exit point. The axis of the drilled hole will be inside location tolerance zone of the hole if both the distances calculated by Eq. (12) will be lower than the half of the location tolerance value t: d 1 t/2 d 2 t/2 (13) 3. Case study results The model proposed so far has been considered to identify the expected quality due to locator configuration, given a ma- chine tool volumetric error. To identify which is the optimal one an experiment has been designed and results have been an- alyzed by means of analysis of variance (ANOVA) 29. Because the aim of the research regards only the choice of locators positions, most of the model parameters can be kept constant. The constant parameters include: the nominal size of the plate (100 x 120 x 60 mm); the standard deviation of the random errors in locator positioning (= 0.01 mm); the nominal location of the entrance (P 0 = 40 70 60 T ) and exit (P 0 = 40 70 0 T ) points of the hole; the length of the drill (l = 60 mm); the standard deviation of the machine tool axes positioning errors ( p =0.01 mm) and of their rotational errors ( d = 0.01); the location tolerance value (t = 0.1 mm); the plate thickness (T = 60 mm). Each locator has instead been left free to change in order to evaluate its influence on the drilling accuracy; candidate configurations will be introduced in the next paragraphs, together with their impact discussion. By substituting the simulation parameters indicated so far in Eq. (8) the following covariance matrix is yielded (all values are in mm 2 ): 68 0 0 0.18 0.18 0 06300.18 0.18 0 0030000 0.18 0.18 0 0.01 0 0 0.18 0.18 0 0 0.01 0 0 000 00.003 10 5 (14) The considered performance indicator is the fraction of con- forming parts generated by a specific locator configuration, i.e. the fraction of parts for which both of the inequalities in Eq. (13) hold. The conforming fraction has been evaluated ten times for each experimental condition, for each evaluation ten thousand workpieces have been simulated. Of course, higher values of this performance indicator are preferable. The ANOVA analysis has worked eciently, with its hy- potheses correctly verified. The main eect plot in Fig. 2 sum- 193 Giovanni Moroni et al. / Procedia CIRP 21 ( 2014 ) 189 194 Fig. 2. Main eect plot for the fraction of conforming workpieces. marizes the results, which are described in depth in the follow- ing paragraphs. 3.1. Impact of p 1 , p 2 and p 3 locator configuration The p 1 , p 2 and p 3 locators define the part z prime axis, so they have been indicated in Fig. 2 as “z locator configuration”. To evaluate their impact on the hole accuracy three candidate con- figurations have been considered. The first one (“max area”) tries to cover as much as possible the surface of the workpiece touched by the locators themselves. The second one (“barycen- tric”) has the barycenter of the locators coincident with the hole position, but with an area coverage smaller than the max area configuration. The last one (“non barycentric”) has the same area coverage of the barycentric one, but is far from the hole. Please note that the plate equilibrium has been neglected in this first analysis. The ANOVA suggests that the bes