Systems and methods for predictive assembly

Abstract

To provide a system and method for predictive assembly based on a predicted gap between mating surfaces.SOLUTION: The system 100 for predictive assembly includes a model generator, a model analyzer, and an assembly planner. The model generator generates a first model of the first part and a second model of the second part before the first part and the second part are coupled together, and analyzes the first model and the second model to identify a dimension of a gap between a first mating surface of the first part and a second mating surface of the second part after the first part and the second part are coupled together. The assembly planner recommends a task based on the comparison of the clearance to the clearance threshold.SELECTED DRAWING: Figure 2A

Description

[Technical Field]

[0001] Priority

[0001] This application claims priority from U.S. Application No. 63 / 664,340, filed June 26, 2024, the entire contents of which are incorporated herein by reference.

[0002]

[0002] The present disclosure relates generally to predictive assembly, and more particularly to systems and methods for predictive assembly based on predicted gaps between mating surfaces. [Background technology]

[0003] When parts are joined together during the manufacture of an object, various surfaces come together. In some cases, one or more gaps exist between the mating surfaces after they are joined together. However, depending on the specific manufacturing requirements, gaps larger than a certain threshold may not be tolerated or may not be able to be filled. Thus, gaps exceeding the threshold may require disassembly and remanufacturing of one or both of the parts. While techniques exist for predicting gaps between mating surfaces, traditional predictive assembly methods fail to adequately predict dimensions when one or more of the parts has a shape, at the time of measurement, that is different from the shape it will have after being joined with its counterpart. Therefore, those skilled in the art continue to conduct research and development efforts in the field of predictive assembly. Summary of the Invention

[0004]

[0004] Disclosed are embodiments of a system for predictive assembly, a method for predictive assembly, and a computer program product for predictive assembly. The following is a non-exhaustive list of embodiments of the subject matter according to the present disclosure, which may or may not be claimed.

[0005] In one embodiment, the disclosed system includes a model generator, a model analyzer, and an assembly planner. The model generator generates a first model of a first part and a second model of a second part before the first part and the second part are bonded together. The model analyzer analyzes the first model and the second model to identify a gap dimension between a first mating surface of the first part and a second mating surface of the second part after the first part and the second part are bonded together. The assembly planner recommends an operation based on a comparison of the gap to a gap threshold.

[0006]

[0006] In one embodiment, the disclosed method includes the steps of: (1) generating a first model of a first part and a second model of a second part before the first part and the second part are bonded together; (2) filtering out deformations of at least one of the first part and the second part before the first part and the second part are bonded together; (3) determining a dimension between a first mating surface of the first part and a second mating surface of the second part after the first part and the second part are bonded together; and (4) recommending work based on the gap dimension.

[0007]

[0007] In another embodiment, the disclosed method includes the steps of: (1) generating a first model of a first part and a second model of a second part before the first part and the second part are bonded together; (2) analyzing the first model and the second model to identify a gap dimension between a first mating surface of the first part and a second mating surface of the second part after the first part and the second part are bonded together; and (3) recommending an action based on a comparison of the gap to a gap threshold.

[0008] In one embodiment, a computer program product is disclosed that includes a non-transitory computer-readable medium containing program code that, when executed by one or more processors, causes the one or more processors to perform a plurality of steps, including (1) generating a first model of a first part from first data before the first part is coupled to a second part, (2) generating a second model of a second part from second data before the second part is coupled to the first part, (3) determining a first overall deviation in a normal direction between the first model and the first nominal model of the first part, (4) determining a second overall deviation in a normal direction between the second model of the second part and the second nominal model, and (5) determining a first overall deviation in a normal direction between the first model and the first nominal model of the second part. (6) performing a best fit alignment between a first model of the first part and a first nominal model to identify a deviation; (7) performing a best fit alignment between a second model of the second part and a second nominal model to identify a second overall deviation; (8) identifying a first overall dimension of the first overall deviation in the normal direction; (9) identifying a first overall dimension of the second overall deviation in the normal direction; (10) determining a first value of the first overall dimension of the first overall deviation along the W axis; (10) mapping the second total deviation from the XYZ coordinate system to the UVW coordinate system so that a second value of a second total dimension of the second total deviation is represented along the W axis; (11) filtering the first value of the first total dimension of the first total deviation into a first form deviation and a first waviness deviation; (12) filtering the second value of the second total dimension of the second total deviation into a second form deviation and a second waviness deviation; (13) ) mapping the first waviness deviation from the UVW coordinate system to the XYZ coordinate system such that a first value of a first waviness dimension of the first waviness deviation is represented as a first distance to the first nominal model; (14) mapping the second waviness deviation from the UVW coordinate system to the XYZ coordinate system 126 such that a second value of a second waviness dimension of the second waviness deviation is represented as a second distance to the second nominal model; (15) after the first part and the second part are bonded together, the first modified nominal model is(16) modifying a first nominal model of the first part by the first waviness deviation so that the first nominal model represents a first mating surface of the first part; (17) analyzing the first modified nominal model and the second modified nominal model to identify a gap dimension between the first mating surface of the first part and the second mating surface of the second part after the first part and the second part are bonded together; and recommending an action based on a comparison of the gap to a gap threshold. In that case, the operation includes at least one of joining the first part and the second part together when the gap size is less than or equal to the gap threshold, reworking at least one of the first part and the second part when the gap size is greater than the gap threshold, redesigning at least one of the first part and the second part when the gap size is greater than the gap threshold, and repairing at least one of the first part and the second part when the gap size is greater than the gap threshold.

[0009] In one embodiment, the disclosed system implements the disclosed method.

[0010] In one embodiment, the disclosed computer program product implements the disclosed method.

[0011]

[0011] In one embodiment, the disclosed method can be performed using an embodiment of the disclosed system or the disclosed computer program product.

[0012] In one embodiment, a portion of an aircraft is manufactured and assembled using the disclosed system or the disclosed computer program product, or according to the disclosed method.

[0013]

[0013] Other embodiments of fittings, connection assemblies, and methods will become apparent from the following detailed description, the accompanying drawings, and the appended claims. [Brief explanation of the drawings]

[0014] [Figure 1] FIG. 1 is a schematic block diagram of an embodiment of a manufacturing environment. [Figure 2A]

[0015] FIG. 1 is a schematic block diagram of an example analytical environment. [Figure 2B] FIG. 1 is a schematic block diagram of an example analytical environment. [Figure 3]

[0016] 1 is a schematic diagram of an embodiment of an aircraft; [Figure 4]

[0017] 1 is a schematic diagram of an example of a portion of an object produced by joining components; [Figure 5]

[0018] FIG. 2 is a graphical representation of one embodiment of a portion of a first nominal model representing a first part and a second nominal model representing a second part. [Figure 6]

[0019] FIG. 2 is a graphical representation of an example of a portion of a first model representing a first part and a second model representing a second part. [Figure 7]

[0020] FIG. 2 is a graphical representation of an example of a portion of a first model representing a first part and a second model representing a second part. [Figure 8]

[0021] FIG. 2 is a graphical representation of one embodiment of a portion of a first modified nominal model representing a first part and a second modified nominal model representing a second part. [Figure 9]

[0022] FIG. 10 is a graph of one example of the total deviation between the first model and the nominal model in the XYZ coordinate system. [Figure 10]

[0023] FIG. 10 is a graph of one example of the total deviation between a first model and a nominal model in a UVW coordinate system. [Figure 11]

[0024] FIG. 10 is a graph of an example of shape deviation between a first model and a nominal model in a UVW coordinate system. [Figure 12]

[0025] FIG. 10 is a graph of an example of waviness deviation between a first model and a nominal model in a UVW coordinate system. [Figure 13]

[0026] FIG. 10 is a graph of an example of waviness deviation between a first model and a nominal model in an XYZ coordinate system. [Figure 14]

[0027] FIG. 1 is a flow diagram of one embodiment of a method for predictive assembly. [Figure 15]

[0028] FIG. 1 is a flow diagram of one embodiment of a method for predictive assembly. [Figure 16]

[0029] FIG. 1 is a block diagram of an embodiment of a data processing system. [Figure 17]

[0030] FIG. 1 is a flow diagram of an embodiment of an aircraft manufacturing and service method. [Figure 18]

[0031] FIG. 1 is a schematic block diagram of an embodiment of an aircraft. DETAILED DESCRIPTION OF THE INVENTION

[0015]

[0032] 1-15 , by way of example, the present disclosure is directed to a system 100 and method 1000, 2000 for predictive assembly. In particular, the system and method are directed to proactive predictive assembly, which for purposes of this disclosure refers to improved predictive assembly methodologies, whereby pre-assembly deformations of parts are removed, gap geometries (e.g., dimensions, shape, size, etc.) between mating surfaces after assembly can be predicted, and pre-emptive action can be taken. By way of example, pre-assembly deformations of parts can be “filtered out” from three-dimensional (3D) measurement data of the parts, thereby enabling the 3D measurement data used to proactively predict gap dimensions between mating surfaces of joined parts.

[0016]

[0033] The present disclosure recognizes that traditional assembly methods may not accurately capture variations in the surfaces of the parts being joined. The present disclosure also recognizes that traditional predictive assembly may not fully account for deformations of the parts during measurement, thereby resulting in excessively large gaps after assembly. Therefore, a determination of whether manufacturing tolerances have been met can only be made after assembly and measurement of the gap. Therefore, it is desirable to have a system and method for predicting gaps between surfaces that account for deformations and recommending operations based on the predicted gaps.

[0017]

[0034] The disclosed systems and methods use data filtering, such as a robust Gaussian surface regression filter, on 3D measurement data representing parts to robustly filter out part deformations while preserving mating surface waviness (e.g., peaks and valleys) associated with gaps between surfaces. Geometry representing the waviness (e.g., dimensional orientation and magnitude) is offset to accurately predict any gaps prior to part assembly.

[0018]

[0035] 1 illustrates an example of a manufacturing environment 172. Manufacturing environment 172 is an example of a manufacturing environment in which an object 180 is manufactured.

[0019]

[0036] In one or more embodiments, object 180 includes or is manufactured using multiple parts, such as at least first part 106 and second part 110. In various other embodiments, any number of other parts may also be used to form or manufacture object 180. First part 106 includes first mating surface 118, and second part 110 includes second mating surface 120. As used herein, "surface" refers to a continuous surface or a discontinuous surface formed from multiple surfaces.

[0020]

[0037] In one or more embodiments, the first part 106 and the second part 110 are joined, attached, or otherwise coupled together such that the first mating surface 118 and the second mating surface 120 are mated together. For example, the first part 106 and the second part 110 are joined such that the first mating surface 118 and the second mating surface 120 are mated together using any suitable joining process 194.

[0021]

[0038] In one or more embodiments, the joining process 194 includes any number of steps configured to physically attach the first part 106 and the second part 110 such that the first mating surface 118 and the second mating surface 120 are mated together. For example, without limitation, the joining process 194 may include at least one of clamping, adhering, attaching, welding, fastening, pinning, sewing, stapling, knotting, gluing, or otherwise joining the first part 106 and the second part 110 together.

[0022]

[0039] In one or more embodiments, the first part 106 and the second part 110 are made from any suitable material or combination of materials. In one or more embodiments, the first part 106 and the second part 110 are made from the same material. In one or more embodiments, the first part 106 and the second part 110 are made from different materials. For example, without limitation, the first part 106 and the second part 110 can be made from a metallic material, a composite material, a polymeric material, combinations thereof, etc.

[0023]

[0040] In one or more embodiments, the first component 106, and thus each one of the first mating surfaces 118, has a first shape 146. In one or more embodiments, the second component 110, and thus the second mating surface 120, has a second shape 246.

[0024]

[0041] For purposes of this disclosure, the "geometry" of a part or surface, as used herein, refers to the shape of the part or surface, the dimensions of the part or surface, and the form of the part or surface. As one example, the geometry of a part or surface is the three-dimensional shape of the part or surface.

[0025]

[0042] In one or more embodiments, the first shape 146 includes the first feature 198 and the first undulation 184. In one or more embodiments, the second shape 246 includes the second feature 298 and the second undulation 284.

[0026]

[0043] For purposes of this disclosure, as used herein, "morphology" refers to the gross or global shape of a part or surface. For purposes of this disclosure, as used herein, "waviness" refers to local variations or undulations in the shape of a part or surface.

[0027]

[0044] In one or more embodiments, first shape 146 of first part 106, and therefore first mating surface 118, may change throughout the assembly process of object 180, e.g., from manufacturing to assembly. In one or more embodiments, second part 110, and therefore second mating surface 120, may change throughout the assembly process of object 180, e.g., from manufacturing to assembly.

[0028]

[0045] In one or more embodiments, the first component 106, and thus the first mating surface 118, has a first initial shape 174 (e.g., the first shape 146 before the joining process 194) and a first assembled shape 176 (e.g., the first shape 146 after the joining process 194). In one or more embodiments, the second component 110, and thus the second mating surface 120, can have a second initial shape 274 (e.g., the second shape 246 before the joining process 194) and a second assembled shape 276 (e.g., the second shape 246 after the joining process 194).

[0029]

[0046] In one or more embodiments, at least one of first part 106 and second part 110, and therefore at least one of first mating surface 118 and second mating surface 120, may experience or exhibit some degree of deformation in shape at some points during manufacturing and assembly (e.g., joining) of object 180. As one example, first part 106 and therefore first mating surface 118 may experience or exhibit some degree of first deformation 162 of first shape 146. As one example, second part 110 and therefore second mating surface 120 may experience or exhibit some degree of second deformation 262 of second shape 246.

[0030]

[0047] For purposes of this disclosure, as used herein, "deformation" refers to a temporary variation in the form of a shape. In several embodiments disclosed herein, the deformation is substantially removed from the shape of the part after or as a result of assembly of object 180 (e.g., after bonding process 194). As an example, first deformation 162 is represented in first initial shape 174 and is not represented in first assembled shape 176. As an example, second deformation 262 is represented in second initial shape 274 and is not represented in second assembled shape 276.

[0031]

[0048] In one or more embodiments, the first component 106 experiences or tends to exhibit some degree of first deformation 162 (e.g., global deformation) after fabrication, such that the first mating surface 118 also exhibits some degree of first deformation 162. As one example, the first component 106 can be flexible, such that the first mating surface 118 is also flexible. As one example, the first component 106 can temporarily bend, deform, flex, sag, or otherwise change shape without causing any undesirable permanent effects to the first component 106 or the first mating surface 118.

[0032]

[0049] In one or more embodiments, second component 110 experiences or tends to exhibit some degree of second deformation 262 (e.g., global deformation) after fabrication, such that second mating surface 120 also exhibits some degree of second deformation 262. As one example, second component 110 can be flexible, such that second mating surface 120 is also flexible. As one example, second component 110 can be temporarily bent, deformed, flexed, sagged, or otherwise changed shape without causing any undesirable permanent effects to second component 110 or second mating surface 120.

[0033]

[0050] This non-permanent change in shape (e.g., deformation) may be due to several factors, such as the size, shape, weight, etc. of the part after fabrication, boundary conditions, gravity, etc. Ultimately, in these embodiments, the shape of the part and therefore the mating surfaces may change throughout the manufacturing process of object 180.

[0034]

[0051] As an example, first component 106, and therefore first mating surface 118, may have first initial shape 174 prior to assembly of object 180 and may have first assembled shape 176 after assembly of object 180. In these examples, first initial shape 174 and first assembled shape 176 are different and are the result of first deformation 162.

[0035]

[0052] As an example, second part 110, and therefore second mating surface 120, may have second initial shape 274 before assembly of object 180 and may have second assembled shape 276 after assembly of object 180. In these examples, second initial shape 274 and second assembled shape 276 are different and are the result of second deformation 262.

[0036]

[0053] In other embodiments, second part 110 does not experience or tends not to exhibit a degree of second deformation 262 after manufacturing, such that second mating surface 120 also does not exhibit a degree of second deformation 262. As one example, second part 110 can be rigid, such that second mating surface 120 is also rigid. As one example, second part 110 cannot be temporarily bent, deformed, flexed, sagged, or otherwise changed in shape without causing any undesirable permanent effects to second part 110 or second mating surface 120. Consequently, in these embodiments, second shape 246 of second part 110, and therefore second mating surface 120, cannot change throughout the manufacturing process of object 180. As an example, second component 110, and therefore second mating surface 120, may have second initial shape 274 prior to assembly of object 180 and may have second assembled shape 276 after assembly of object 180. In these examples, second initial shape 274 and second assembled shape 276 are substantially the same.

[0037]

[0054] In one or more embodiments, second part 110 provides or acts as a support structure for object 180 to which first part 106 is coupled. Thus, first part 106, and thus first mating surface 118, has first assembled shape 176 after first part 106 and second part 110 are coupled together. As one example, mating forces may pull out first deformation 162 from first part 106 during assembly of object 180. In these embodiments, the magnitude of the difference between first initial shape 174 and first assembled shape 176 may be due to several factors. For example, the load and / or force applied to the first part 106 during the joining process 194, the number of attachment points between the first part 106 and the second part 110, the orientation of the first part 106 and / or the second part 110, and several other factors that may affect the first shape 146 of the first part 106 before, during, and / or after the joining process 194.

[0038]

[0055] In one or more embodiments, several gaps 116 may exist between first mating surface 118 and second mating surface 120. As used herein, "several" refers to one or more. In this manner, several gaps 116 includes one gap 116 or multiple gaps 116. For purposes of this disclosure, "gap" refers to the open space between the mating surfaces of the parts that form object 180. Thus, gap 116 may also be referred to as space.

[0039]

[0056] In one or more embodiments, the gap 116 (e.g., each one of the gaps 116) has a dimension 114. Generally, the dimension 114 of the gap 116 refers to a measurable parameter or shape of the gap 116, such as its thickness, length, width, etc. More specifically, the dimension 114 of the gap 116 refers to the thickness of the gap 116 or the linear distance between the first mating surface 118 and the second mating surface 120.

[0040]

[0057] In some cases, it may be desirable to predict the dimensions 114 of the gap 116, as needed, before manufacturing and / or shipping the parts, before the joining process 194, and / or before assembling the object 180, and to proactively modify the assembly process, the joining process, the part design, etc. Therefore, it may be desirable to predict the dimensions 114 (e.g., 3D shape information) of the gap 116 that may form between the first mating surface 118 and the second mating surface 120. In other words, the gap 116 may form after the first part 106 and the second part 110 are bonded together. The gap 116 is predicted before the first part 106 and the second part 110 are bonded together.

[0041]

[0058] Thus, as disclosed herein, a system 100 for predictive assembly (FIG. 2) is used to predict the size 114 of the gaps 116, the number of gaps 116, and other information related to the gaps 116, and to determine recommended (e.g., preemptive or corrective) manufacturing actions based on the gap prediction before parts are manufactured and / or before parts are assembled to form an object.

[0042]

[0059] 2A and 2B, collectively referred to herein as FIG. 2, illustrate one example of an analysis environment 182. Analysis environment 182 is an example of an analysis environment in which system 100 is implemented to proactively predict dimensions 114 (e.g., 3D shape information) of gaps 116 ( FIG. 1 ). In one or more embodiments, analysis environment 182 is remote from or in a separate location relative to manufacturing environment 172. However, in other embodiments, at least a portion of system 100 is located or implemented within manufacturing environment 172. In that case, at least another portion of system 100 is located or implemented within analysis environment 182. In still other embodiments, system 100 may be implemented entirely within manufacturing environment 172.

[0043]

[0060] In one or more embodiments, system 100 includes or is implemented using computer 148. For example, system 100 is a computer-implemented system. In one or more embodiments, computer 148 executes instructions 170 to perform the operations performed by system 100. In these embodiments, computer 148 may include one or more computers, computing devices, or computing systems. When computer 148 includes two or more computers, the computers may communicate with each other using any number of wired, wireless, optical, or other types of communication links.

[0044]

[0061] In one or more embodiments, the system 100 includes a model generator 102. The model generator 102 generates (e.g., is configured or adapted to generate) a first model 104 of a first part 106 (FIG. 1). The model generator 102 also generates (e.g., is configured or adapted to generate) a second model 108 of a second part 110 (FIG. 1).

[0045]

[0062] In one or more embodiments, the first model 104 is generated before the first part 106 and the second part 110 are bonded together. In one or more embodiments, the first model 104 represents the first part 106 having a first initial shape 174 and therefore the first mating surface 118.

[0046]

[0063] In one or more embodiments, the first initial shape 174 of the first part 106 differs from the first assembled shape 176 (e.g., the final shape after the joining process 194). In one or more embodiments, the first initial shape 174 includes a first deformation 162 of the first shape 146 of the first part 106 (e.g., the first part 106 is flexible).

[0047]

[0064] In one or more embodiments, the second model 108 is generated before the first part 106 and the second part 110 are bonded together. In one or more embodiments, the second model 108 represents the second part 110 having a second initial shape 274 and therefore the second mating surface 120.

[0048]

[0065] In one or more embodiments, the second initial shape 274 of the second part 110 is different from the second assembled shape 276 (e.g., the final shape after the bonding process 194). In one or more embodiments, the second initial shape 274 includes a second variation 262 of the second shape 246 of the second part 110 (e.g., the second part 110 is flexible).

[0049]

[0066] In one or more embodiments, the second initial shape 274 of the second part 110 is the same as the second assembled shape 276 (e.g., the final shape after the joining process 194). In one or more embodiments, the second initial shape 274 does not include the second deformation 262 of the second shape 246 of the second part 110 (e.g., the second part 110 is rigid).

[0050]

[0067] In one or more embodiments, the system 100 includes a model analyzer 112. The model analyzer 112 analyzes (e.g., is configured or adapted to analyze) the first model 104 and the second model 108 to identify (e.g., predict) a dimension 114 of the gap 116. The gap 116 is formed between a first mating surface 118 of the first part 106 and a second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together (e.g., after a joining process 194).

[0051]

[0068] As used herein, the singular use of the term "dimension" can refer to a single dimension (e.g., dimension 114) or one or more of the dimensions (e.g., dimension 114) of one or more gaps 116. Also, as used herein, the singular use of the term "gap" can refer to a single gap (e.g., gap 116) or one or more of the gaps (e.g., gaps 116).

[0052]

[0069] In instances where mating surfaces of joined parts may change shape during assembly, embodiments of the system 100 consider the assembled shapes of the parts and predict the gap shape based on the manufactured shapes of the parts. In one or more embodiments, the system 100 facilitates proactively removing the first deformation 162 from the first shape 146 of the first part 106 during the predictive assembly process. In one or more embodiments, the system 100 facilitates proactively removing the second deformation 262 from the second shape 246 of the second part 110 during the predictive assembly process.

[0053]

[0070] Embodiments of the system 100 and method 1000, 2000 disclosed herein enable prediction of the dimension 114 of the gap 116. The gap 116 is formed between the first mating surface 118 and the second mating surface 120. The prediction of the dimension 114 of the gap 116 is performed using approximations of the first assembled shape 176 of the first part 106 and / or the second assembled shape 276 of the second part 110 (e.g., the final shape after the joining process 194). Such prediction of the dimension 114 of the gap 116 enables proactive and / or predictive modifications to the manufacturing process, if necessary, when the dimension 114 of the gap 116 is larger than an allowable dimension based on manufacturing specifications or manufacturing tolerances. Accordingly, embodiments of the system 100 and method 1000, 2000 disclosed herein improve the speed, cost, and efficiency of manufacturing and reduce the amount of waste associated with non-conforming parts.

[0054]

[0071] In one or more embodiments, the system 100 includes an assembly planner 210. The assembly planner 210 compares (e.g., is configured or adapted to compare) a prediction of the dimension 114 of the gap 116 to a gap threshold 214. The assembly planner 210 also recommends (e.g., is configured or adapted to recommend) an operation 212 based on a comparison of the gap 116 (e.g., the dimension 114) to the gap threshold 214.

[0055]

[0072] For purposes of this disclosure, as used herein, gap threshold 214 refers to a specific limit or point that must be met before a decision or action is taken. Gap threshold 214 may refer to any measurable parameter or characteristic of the gap or space between mating surfaces of parts and may be based on manufacturing design, specifications, and / or tolerances. As one example, gap threshold 214 is a dimensional threshold (e.g., dimensional threshold 216) that represents the maximum allowable distance (e.g., gap size) between mating surfaces of parts after they are joined.

[0056]

[0073] In instances where the predicted dimension 114 of the gap 116 is equal to or less than the dimension threshold 216 of the gap threshold 214, the operation 212 (e.g., recommended by the assembly planner 210) may proceed to join the parts and assemble the object 180 ( FIG. 1 ). However, in instances where the predicted dimension 114 of the gap 116 is equal to or greater than the dimension threshold 216 of the gap threshold 214, the operation 212 (e.g., recommended by the assembly planner 210) may be to rework the process before manufacturing the parts, or before joining the parts and before assembling the object 180.

[0057]

[0074] In one or more embodiments, the operation 212 recommended by the assembly planner 210 includes joining the first part 106 and the second part 110 when the dimension 114 of the gap 116 is less than or equal to the gap threshold 214.

[0058]

[0075] In one or more embodiments, the operations 212 recommended by the assembly planner 210 include reworking at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214. In these embodiments, the reworking includes remanufacturing or manufacturing a new instance of the first part 106 and / or the second part 110.

[0059]

[0076] In one or more examples, the actions 212 recommended by the assembly planner 210 include redesigning at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214. In these examples, the redesigning includes making changes to the design, specifications, and / or tolerances of the first part 106, the second part 110, and / or the structural assembly (e.g., the object 180) including the first part 106 and the second part 110.

[0060]

[0077] In one or more embodiments, the actions 212 recommended by the assembly planner 210 include repairing at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214. In these embodiments, the repairing includes modifying at least one of the first mating surface 118 of the first part 106 and / or the second mating surface 120 of the second part 110, such as by sanding or other surface finishing, to reduce or eliminate the gap 116.

[0061]

[0078] 3 illustrates one embodiment of an aircraft 1200. In one or more embodiments, the aircraft 1200 includes a fuselage 1218 (e.g., main body) and wings 1220 attached to the fuselage 1218. The aircraft 1200 includes a propulsion system 1208 (e.g., engines) attached to the wings 1220, for example. The fuselage 1218 has a nose 1222 and a tail 1224. The fuselage 1200 includes a horizontal stabilizer 1228 and a vertical stabilizer 1226 attached to the tail 1224.

[0062]

[0079] 1 and 3 , in one or more embodiments, fuselage 1218 is an example of object 180. Fuselage 1218 includes an exterior barrel 1230 and an interior frame 1232. In these embodiments, barrel 1230 is an example of first part 106, and frame 1232 is an example of second part 110. Frame 1232 is coupled to barrel 1230 and serves as a support structure for fuselage 1218. It can be appreciated that before frame 1232 is coupled to barrel 1230, an initial shape of barrel 1230 may exhibit deformation 162 due to the size and weight of barrel 1230. After frame 1232 is coupled to barrel 1230, barrel 1230 may have a final shape that is different from the initial shape.

[0063]

[0080] In one or more embodiments, wing 1220 is an example of object 180. Wing 1220 may also be referred to as a wing structure or a wing box. Wing 1220 includes an exterior panel assembly 1234 and an interior stiffener assembly 1236. Panel assembly 1234 includes several panels and may also be referred to as a wing skin. Stiffener assembly 1236 includes several spars, ribs, etc. In these embodiments, panel assembly 1234 is an example of first component 106, and stiffener assembly 1236 is an example of second component 110. Stiffener assembly 1236 is coupled to panel assembly 1234 and serves as a support structure for wing 1220. Before stiffener assembly 1236 is coupled to panel assembly 1234, the initial shape of panel assembly 1234 may exhibit deformation 162 due to the size and weight of panel assembly 1234. After the stiffener assembly 1236 is coupled to the panel assembly 1234, the panel assembly 1234 may have a final shape that is different from its initial shape.

[0064]

[0081] 4 shows an example of a portion of an object 180 formed by a first part 106 coupled to a second part 110. When the first part 106 coupled to the second part 110 is coupled together, the first mating surface 118 and the second mating surface 120 come together. When the first part 106 coupled to the second part 110 is coupled together and the first mating surface 118 and the second mating surface 120 come together, some gaps 116 may be formed between the first mating surface 118 and the second mating surface 120.

[0065]

[0082] 5 diagrammatically illustrates an example of a gap 116 formed between a first nominal model 124 and a second nominal model 224 and between a first mating surface 118 and a second mating surface 120 represented by the first nominal model 124 and the second nominal model 224. In the illustrated embodiment, the first nominal model 124 represents the first part 106, such as at least a portion of the first mating surface 118 after assembly of the object 180 (e.g., before the joining process 194). The second nominal model 224 represents the second part 110, such as at least a portion of the second mating surface 120 after assembly of the object 180 (e.g., before the joining process 194). As shown, the gap 116 between the first mating surface 118 and the second mating surface 120 is within (e.g., less than) an acceptable gap threshold 214 determined based on the design specifications and / or tolerances of the object 180.

[0066]

[0083] 6 diagrammatically illustrates an example of a dimension 114 of a gap 116 between a first model 104 and a second model 108 and between a first mating surface 118 and a second mating surface 120 represented by the first model 104 and the second model 108. In the illustrated example, the first model 104 represents the first part 106, such as at least a portion of the first mating surface 118, as manufactured but prior to assembly of the object 180 (e.g., prior to the joining process 194). The second model 108 represents the second part 110, such as at least a portion of the second mating surface 120, as designed but prior to assembly of the object 180 (e.g., prior to the joining process 194). As illustrated, the gap 116 between the first mating surface 118 and the second mating surface 120 is outside of (e.g., greater than) an acceptable gap threshold 214 determined based on the design specifications and / or tolerances of the object 180.

[0067]

[0084] In one or more embodiments, the first model 104 represents the first part 106 and the first mating surface 118 in a first initial shape 174 (e.g., the shape before the joining process 194). In one or more embodiments, the second model 108 represents the second part 110 and the second mating surface 120 in a second initial shape 274 (e.g., the shape before the joining process 194).

[0068]

[0085] As one example, the first initial shape 174 includes the first deformation 162 and the first waviness 184 in the first shape 146 ( FIG. 1 ). For example, the first part 106 is flexible and experiences some degree of the first deformation 162 (e.g., global variation in the first configuration 198), and the first mating surface 118 includes the first waviness 184 (e.g., local variation in the surface profile). The first waviness 184 is represented by the first model 104.

[0069]

[0086] As one example, the second initial shape 274 includes a second deformation 262 and a second waviness 284 in the second shape 246. For example, the second part 110 is flexible and experiences some degree of the second deformation 262 (e.g., a global variation in the second configuration 298), and the second mating surface 120 includes a second waviness 284 (e.g., a local variation in the surface profile). The second waviness 284 is represented by the second model 108.

[0070]

[0087] As another example, the second initial shape 274 does not include the second deformation 262 and the second undulation 284 within the second shape 246. For example, the second part 110 is rigid and does not experience the second deformation 262, and the second mating surface 120 does not include the second undulation 284.

[0071]

[0088] As another example, the second initial shape 274 does not include the second deformation 262 in the second shape 246, but includes the second undulation 284 in the second shape 246. For example, the second part 110 is rigid and does not experience the second deformation 262, and the second mating surface 120 includes the second undulation 284.

[0072]

[0089] 6 , the gap 116 formed between the first mating surface 118 and the second mating surface 120 after the bonding process 194 is represented by the space between the representations of the first mating surface 118 and the second mating surface 120 in the first model 104 and the second model 108. The dimension 114 of the gap 116 is estimated or calculated by the linear distance between the first mating surface 118 and the second mating surface 120 as represented in the first model 104 and the second model 108. In this illustrative example, it can be understood that the dimension 114 of the gap 116 shown at this level of modeling may be larger than the dimension 114 of the gap 116 that actually exists when the object 180 is assembled (e.g., after the bonding process 194).

[0073]

[0090] 7 diagrammatically illustrates one embodiment of the first model 104 and the second model 108. In one or more embodiments, a first space 200 between the first mating surface 118 and the second mating surface 120, represented by a dashed line for the first model 104, represents an area or distance between the first mating surface 118 and the second mating surface 120 associated with or formed by a first deformation 162 (e.g., global variation in the first configuration 198) in the first shape 146 of the first part 106. Similarly, in one or more embodiments, a second space 204 between the first mating surface 118 and the second mating surface 120, represented by a dashed line for the second model 108, represents an area or distance between the first mating surface 118 and the second mating surface 120 associated with or formed by a second deformation 262 (e.g., global variation in the second configuration 298) in the second shape 246 of the second part 110.

[0074]

[0091] Generally, first space 200 and / or second space 204 are closed or otherwise eliminated after assembly of object 180 or accordingly (e.g., after joining process 194 of first part 106 and second part 110). Therefore, any predicted dimension 114 of gap 116 must account for such spaces that are eliminated after assembly. Therefore, it is desirable to estimate dimension 114 of gap 116 without first deformation 162 in first shape 146 of first part 106 and / or second deformation 262 in second shape 246 of second part 110. The system 100 advantageously facilitates removing the first deformation 162 and / or the second deformation 262 from the calculation of the dimension 114 of the gap 116 formed between the first mating surface 118 and the second mating surface 120 after the first part 106 and the second part 110 are bonded together (e.g., after the joining process 194).

[0075]

[0092] 8 diagrammatically illustrates an example of a first modified nominal model 190, a second modified nominal model 290, and a dimension 114 of a gap 116 between a first mating surface 118 and a second mating surface 120 represented by the first modified nominal model 190 and the second modified nominal model 290. In the illustrated example, the first modified nominal model 190 represents the first part 106, such as at least a portion of the first mating surface 118 after assembly of the manufactured object 180 (e.g., after the joining process 194). The second modified nominal model 290 represents the second part 110, such as at least a portion of the second mating surface 120 after assembly of the manufactured object 180 (e.g., after the joining process 194). Therefore, the predicted gap 116 between the first mating surface 118 and the first mating surface 120 more accurately represents the actual gap that will be formed between the first mating surface 118 and the second mating surface 120 after assembly of the object 180 compared to using the first nominal model 124 and the second nominal model 224 (Figure 5) or the first model 104 and the second model 108 (Figure 6).

[0076]

[0093] This example illustrates an analysis process used to estimate (predict) the size 114 of the gap 116 between the first mating surface 118 and the second mating surface 120, such as used in the predictive assembly process or new proactive predictive assembly process disclosed herein. In the illustrated example, the first deformation 162 (e.g., global variation in the first configuration 198) in the first shape 146 of the first part 106 and / or the second deformation 262 (e.g., global variation in the second configuration 298) in the second shape 246 of the second part 110 have been removed from the analysis process. As a result, only the first waviness 184 (e.g., local variation in the surface profile) in the first shape 146 of the first mating surface 118 and the second waviness 284 in the second shape 246 of the second mating surface 120 are considered when determining the size 114 of the gap 116.

[0077]

[0094] As will be described in more detail herein, in one or more embodiments, prediction of the gap 116 is achieved by replacing the first model 104 with a first modified nominal model 190 representing the first part 106 and / or by replacing the second model 108 with a second modified nominal model 290 representing the second part 110.

[0078]

[0095] In these illustrative examples, first modified nominal model 190 represents first part 106, such as at least a portion of first mating surface 118. In one or more illustrative examples, first modified nominal model 190 is first nominal model 124 as modified by first waviness deviation 134 extracted from first model 104. In one or more illustrative examples, first modified nominal model 190 represents first part 106, and thus first mating surface 118, as manufactured but after assembly of object 180 (e.g., after joining process 194).

[0079]

[0096] The second model 108 represents the second part 110, such as at least a portion of the second mating surface 120. In one or more embodiments, the second modified nominal model 290 is the second nominal model 224 as modified by the second waviness deviation 234 extracted from the second model 108. The second modified nominal model 290 represents the second part 110, and thus the second mating surface 120, as manufactured but after assembly of the object 180 (e.g., after the joining process 194).

[0080]

[0097] In one or more embodiments, the first modified nominal model 190 represents the first part 106 and the first mating surface 118 in the first assembled shape 176 (e.g., the final shape after the joining process 194), which does not include the first deformation 162, but does include the first waviness 184 in the first shape 146. As an example, the first deformation 162 (e.g., global variations in the first configuration 198) in the first shape 146 of the first part 106, represented by the first shape 200 ( FIG. 7 ), has been removed (as would be introduced by the joining process 194), and the first mating surface 118 includes the first waviness 184 (e.g., local variations in the surface profile), which is represented by the first modified nominal model 190.

[0081]

[0098] In one or more embodiments, the second modified nominal model 290 represents the second part 110 and the second mating surface 120 in the second assembled shape 276 (e.g., the final shape after the joining process 194), which does not include the second deformation 262 but does include the second waviness 284 in the second shape 246. As an example, the second deformation 262 (e.g., global variations in the second configuration 298) in the second shape 246 of the second part 110 represented by the second shape 204 ( FIG. 7 ) has been removed (as would be induced by the joining process 194), and the second mating surface 120 includes the second waviness 284 (e.g., local variations in the surface profile), which is represented by the second modified nominal model 290.

[0082]

[0099] In other examples, the second model 108 represents the second part 110 and the second mating surface 120 in the second assembled shape 276 (e.g., the final shape after the joining process 194), which may not include the second deformation 262 but may include the second undulation 284 in the second shape 246. As one example, the second part 110 is rigid and does not experience the second deformation 262, and the second mating surface 120 does not include the second undulation 284.

[0083]

[0100] The gap 116 that will be formed between the first mating surface 118 and the second mating surface 120 is represented by the space between the representations of the first mating surface 118 and the second mating surface 120 in the first modified nominal model 190 and the second modified nominal model 290, respectively. In one or more embodiments, the dimension 114 of the gap 116 is estimated or calculated by the linear distance between the first mating surface 118 and the second mating surface 120 as represented in the first modified nominal model 190 and the second modified nominal model 290.

[0084]

[0101] In the illustrated example of the predictive assembly process or the new proactive predictive assembly process, it can be seen that the size 114 of the gap 116 predicted by the process (referred to herein as the predictive size 188 shown in FIG. 2 ) is substantially equal to the size 114 of the gap 116 that will actually be present when the object 180 is assembled (e.g., after the bonding process 194). Accordingly, a determination related to a defect or non-conformity can be made preemptively based on comparing the predicted gap 116 to an acceptable or possible gap threshold 214.

[0085]

[0102] Referring to FIG. 2 , in one or more embodiments, the model analyzer 112 identifies (e.g., is configured or adapted to identify) a first overall deviation 122 in a normal direction 150 between the first model 104 of the first part 106 and the first nominal model 124.

[0086]

[0103] In one or more embodiments, the model analyzer 112 determines (e.g., is configured or adapted to determine) a second overall deviation 222 in the normal direction 150 between the second model 108 of the second part 110 and a second nominal model 224.

[0087]

[0104] In one or more embodiments, the model analyzer 112 performs (e.g., is configured or adapted to perform) a best-fit alignment (also referred to as a best-fit analysis 186 ) between the first model 104 of the first part 106 and the first nominal model 124 to identify the first overall deviation 122 .

[0088]

[0105] In one or more embodiments, the model analyzer 112 performs (e.g., is configured or adapted to perform) a best-fit alignment (e.g., best-fit analysis 186 ) between the second model 108 of the second part 110 and the second nominal model 224 to identify the second overall deviation 222 .

[0089]

[0106] In one or more embodiments, the model analyzer 112 determines (eg, is configured or adapted to determine) a first overall dimension 164 of the first overall deviation 122 in the normal direction 150 .

[0090]

[0107] In one or more embodiments, the model analyzer 112 determines (eg, is configured or adapted to determine) a second overall dimension 264 of the second overall deviation 222 in the normal direction 150 .

[0091]

[0108] For purposes of this disclosure, the first nominal model 124 and / or the second nominal model 224 refer to computer-aided design (CAD) models of the first part 106 and the second part 110, respectively, which represent the nominal or design shapes of the first part 106 and the second part 110 and thus the first mating surface 118 and the second mating surface 120, respectively. The first shape 146 of the first part 106 represented in the first nominal model 124 may be understood to be free of the first deformation 162 (global variations in the first shape 198) or the first waviness 184 (local variations in the surface profile). Similarly, the second shape 246 of the second part 110 represented in the second nominal model 224 may be understood to be free of the second deformation 262 (global variations in the second shape 298) or the second waviness 284 (local variations in the surface profile).

[0092]

[0109] 9-12 diagrammatically illustrate several examples of the disclosed predictive assembly analysis process. The several examples described and illustrated are directed to the process as applied to the first part 106. However, in one or more examples, the process described and illustrated in FIGS. 9-12 may equally be applied to the second part 110. Thus, the several examples described and illustrated in FIGS. 9-12 are not limited to application or implementation to the first part 106. Thus, references to a "first" instance may equally be applied to a "second" instance. A full description of the application of the predictive assembly analysis process to the second part 110 is omitted for purposes of brevity and avoidance of redundancy, and does not limit the application of the process.

[0093]

[0110] 9 graphically illustrates one example of a first total deviation 122 in a normal direction 150 between the first model 104 and the first nominal model 124 of the first part 106. In one or more embodiments, the first total deviation 122 in the normal direction 150 between the first model 104 (e.g., as-built state) and the first nominal model 124 (e.g., design state) is obtained by performing a best-fit analysis 186, such as a least-squares alignment, of the first mating surface 118 represented in the first model 104 and the first mating surface 118 represented in the first nominal model 124. The first total deviation 164 is represented by or calculated as a value 130 (e.g., a linear distance measurement in the normal direction 150) relative to the XYZ coordinate system 126.

[0094]

[0111] 2, in one or more embodiments, system 100, such as computer 148 executing instructions 170, includes a user interface (UI) 202. The graphical representation of first overall deviation 122 and overall dimension 164 of first overall deviation 122 shown in FIG. 9 is one example of a graphical representation displayed to a user by UI 202.

[0095]

[0112] In one or more embodiments, the first overall deviation 122 includes both large-scale (e.g., gross or global) shape differences and small-scale surface variations. The large-scale shape variations represent a first morphology 198 and are referred to herein as first shape deviations 132. The small-scale surface variations represent a first waviness 184 and are referred to herein as first waviness deviations 134. As disclosed herein, the system 100 advantageously enables the dimension 114 of the gap 116 to be formed between the first mating surface 118 and the second mating surface 120 to be determined based solely on the small-scale variations (e.g., the first waviness 184 and the second waviness 284).

[0096]

[0113] In one or more embodiments, the model analyzer 112 maps (e.g., is configured or adapted to map) the first total deviation 122 from the XYZ coordinate system 126 to the UVW coordinate system 128, whereby the value 130 of the first total dimension 164 of the first total deviation 122 is represented along the W-axis 152 of the UVW coordinate system 128. In one or more embodiments, the coordinate mapping 192 includes any suitable conformal mapping or charting technique.

[0097]

[0114] FIG. 10 graphically illustrates one example of the first total deviation 122 as mapped from the XYZ coordinate system 126 ( FIG. 9 ) to the UVW coordinate system 128. In one or more embodiments, data representing the first total deviation 122 is transformed (e.g., charted or mapped) from x, y, z coordinate points to u, v, w coordinate points. By using a two-dimensional (2D) coordinate system, the u, v coordinates represent locations on the first part 106, and the w coordinate represents deviations from the nominal shape. This operation effectively removes the “designed shape” from the first part 106. The w-axis 152 is thereby the only deviation from the designed shape. The graphical representation of the first total deviation 122 and the overall dimension 164 of the first total deviation 122 shown in FIG. 10 is one example of a graphical representation displayed to the user by the UI 202.

[0098]

[0115] 2 , in one or more embodiments, the model analyzer 112 filters (e.g., is configured or adapted to filter) values ​​130 of the first overall dimension 164 of the first overall deviation 122 into a first shape deviation 132 and a first waviness deviation 134. In one or more embodiments, the system 100, such as a computer 148 executing instructions 170, includes a filter 154 that performs the filtering process. In one or more embodiments, the model analyzer 112 filters the values ​​130 using a low-pass filter 156. In one or more embodiments, the model analyzer 112 filters the values ​​130 using a robust Gaussian regression filter 158. In one or more embodiments, the filter 154, such as the low-pass filter 156 or the robust Gaussian regression filter 158, is run on the u, v, w point cloud to filter the data into a first shape 198 and a first waviness 184. Since the designed curvature has been effectively removed, a linear regression function (e.g., a planar regression) is selected and used for local fitting.

[0099]

[0116] 11 graphically illustrates an example of a first shape deviation 132 and a value 130 of a first feature dimension 166 as mapped to the UVW coordinate system 128 and filtered from the first overall dimension 164 of the first overall deviation 122. As shown in the illustrated embodiment, the value 130 of the first feature dimension 166 of the first shape deviation 132 ( FIG. 11 ) is approximately equal to the value 130 of the first overall dimension 164 of the first overall deviation 122 ( FIG. 10 ) because the global variation in the first feature 198 (first shape deviation 132) due to the first deformation 162 represents a large portion of the first overall deviation 122 from the design shape. The graphical representation of the first shape deviation 132 and the first feature dimension 166 of the first shape deviation 132 shown in FIG. 11 is an example of a graphical representation displayed to the user by the UI 202.

[0100]

[0117] Substantially similar operations and embodiments can be used to obtain the values ​​130 of the second feature deviation 232 and the second feature dimension 266 as mapped to the UVW coordinate system 128 and filtered from the second overall dimension 264 of the second overall deviation 222.

[0101]

[0118] 12 graphically illustrates one example of a first waviness deviation 134 and a value 130 of a first waviness dimension 168 as mapped to a UVW coordinate system 128 and filtered from the first overall dimension 164 of the first overall deviation 122. As shown in the illustrative example, the value 130 of the first waviness dimension 168 of the first waviness deviation 134 ( FIG. 12 ) is several orders of magnitude smaller than the value 130 of the first overall dimension 164 of the first overall deviation 122 ( FIG. 10 ) because local variations in the first waviness 184 (first waviness deviation 134) due to small-scale variations in the surface profile of the first mating surface 118 represent a small portion of the first overall deviation 122 from design shape. The graphical representation of the first waviness deviation 134 and the first waviness dimension 168 of the first waviness deviation 134 shown in FIG. 12 is one example of a graphical representation displayed to the user by the UI 202.

[0102]

[0119] 2 , in one or more embodiments, the model analyzer 112 modifies (e.g., is configured or adapted to modify) the first nominal model 124 by the first waviness deviation 134. The first nominal model 124, once modified by the first waviness deviation 134, represents the first mating surface 118 of the first part 106 after the first part 106 and the second part 110 are bonded together. The first nominal model 124, once modified by the first waviness deviation 134, is also referred to herein as a first modified nominal model 190. In one or more embodiments, the model analyzer 112 maps (e.g., is configured or adapted to map) the first waviness deviation 134 from the UVW coordinate system 128 to the XYZ coordinate system 126. The value 130 of the first waviness dimension 168 of the first waviness deviation 134 is thereby expressed as a first distance 160 relative to the first nominal model 124 .

[0103]

[0120] 13 graphically illustrates an example of a first waviness deviation 134 mapped from the UVW coordinate system 128 (FIG. 12) back to the XYZ coordinate system 126, and a value 130 of a first waviness dimension 168 expressed as a first distance 160 in a normal direction 150 relative to the first nominal model 124. In one or more embodiments, the data representing the first waviness deviation 134 is altered (e.g., charted or mapped) from u, v, w coordinate points back to x, y, z coordinate points. The calculated first waviness 184 in the w-coordinate is used as a first distance 160 to be added to or subtracted from the first nominal model 124 to estimate one or more dimensions 114 of one or more gaps 116 that will be formed between the first mating surface 118 and the second mating surface 120 after the first part 106 and the second part 110 are bonded together (e.g., after the joining process 194). The graphical illustration of the first waviness deviation 134 and the first waviness dimension 168 as the first distance 160 shown in FIG. 13 is one example of a graphical representation displayed to the user by the UI 202.

[0104]

[0121] 2 , in one or more embodiments, the system 100 includes a measurement system 136. The measurement system 136 generates first data 138 that represents at least a portion of the first mating surface 118 of the first part 106 and / or that is used in the first model 104. The measurement system 136 generates second data 140 that represents at least a portion of the second mating surface 120 of the second part 110 and / or that is used in the second model 108. The first data 138 and the second data 140 are generated before the first part 106 and the second part 110 are joined together and the first mating surface 118 and the second mating surface 120 are mated.

[0105]

[0122] In one or more embodiments, the measurement system 136 includes or takes the form of a scanning device. The scanning device is used to scan the first part 106, such as at least a portion of the first mating surface 118, and generate the first data 138. The measurement system 136 includes or takes the form of a scanning device. The scanning device is used to scan the second part 110, such as at least a portion of the second mating surface 120, and generate the second data 140. The scanning device may take the form of, for example, without limitation, a laser system, an optical measurement device, or some other type of system. The laser system may be, for example, a laser radar scanner. The optical measurement device may be, for example, a three-dimensional optical measurement device. In another exemplary embodiment, the measurement system 136 takes the form of a photogrammetry system.

[0106]

[0123] In one or more embodiments, the first part 106 and the second part 110 may be manufactured and / or measured (e.g., scanned) at different locations. Accordingly, in one or more embodiments, the measurement system 136 includes two or more scanning devices, each one collocated with or dedicated to a manufacturing or measurement environment associated with a respective one of the first part 106 and the second part 110.

[0107]

[0124] 1 and 2 , in one or more embodiments, the first data 138 includes data or 3D shape information about a first shape 146, e.g., a first initial shape 174 of the first part 106 and thus the first mating surface 118. In one or more embodiments, the second data 140 includes data or 3D shape information about a second shape 246, e.g., a second initial shape 274 of the second part 110 and thus the second mating surface 120.

[0108]

[0125] 2 , in one or more embodiments, the first data 138 and the second data 140 take the form of three-dimensional point clouds. In one example, the first data 138 takes the form of a first three-dimensional point cloud. This point cloud has a density sufficient to capture the first shape 146 of the first part 106 and thus the first mating surface 118 with a desired level of accuracy. Similarly, the second data 140 takes the form of a second three-dimensional point cloud. This point cloud has a density sufficient to capture the second shape 246 of the second part 110 and thus the second mating surface 120 with a desired level of accuracy.

[0109]

[0126] 2 and 16, in one or more embodiments, the model generator 102, the model analyzer 112, and the assembly planner 210 take the form of program code 918 executed by the data processing system 900.

[0110]

[0127] 1-13, below are several embodiments of a system 100 according to the present disclosure. System 100 includes several elements, features, and components. Not all elements, features, and / or components described or illustrated in an embodiment are required in that embodiment. Some or all of the elements, features, and / or components described or illustrated in one embodiment may be combined in various ways with other embodiments without necessarily including other elements, features, and / or components described in those other embodiments, even if one or more such combinations are not explicitly described or illustrated by an embodiment herein.

[0111]

[0128] In one or more embodiments, the system 100 includes a model generator 102, a model analyzer 112, and an assembly planner 210. The model generator 102 generates a first model 104 of the first part 106 and a second model 108 of the second part 110 before the first part 106 and the second part 110 are bonded together.

[0112]

[0129] In one or more embodiments, the model analyzer 112 analyzes the first model 104 and the second model 108 to determine a dimension 114 of a gap 116 between a first mating surface 118 of the first part 106 and a second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together.

[0113]

[0130] In one or more embodiments, the model analyzer 112 filters out the first deformation 162 of the first part 106 and / or the second deformation 262 of the second part 110 before the first part 106 and the second part 110 are bonded together. The model analyzer 112 also identifies (e.g., calculates a prediction of) a dimension 114 of the gap 116 between the first mating surface 118 of the first part 106 and the second mating surface 120 of the second part 110.

[0114]

[0131] In one or more embodiments, the assembly planner 210 recommends operations 212 based on a comparison of the gaps 116 to a gap threshold 214. In one or more embodiments, the assembly planner 210 recommends operations 212 based on the size 114 of the gaps 116.

[0115]

[0132] In one or more embodiments, when the size 114 of the gap 116 is less than or equal to the gap threshold 214, the operations 212 that may be recommended by the assembly planner 210 include joining the first part 106 and the second part 110 together. In one or more embodiments, when the size 114 of the gap 116 is greater than the gap threshold 214, the operations 212 recommended by the assembly planner 210 include at least one of reworking at least one of the first part 106 and the second part 110, redesigning at least one of the first part 106 and the second part 110 when the size 114 of the gap 116 is greater than the gap threshold 214, and repairing at least one of the first part 106 and the second part 110 when the size 114 of the gap 116 is greater than the gap threshold 214.

[0116]

[0133] In one or more embodiments, the model analyzer 112 modifies the first nominal model 124 of the first part 106 by the first waviness deviation 134. The model analyzer 112 modifies the second nominal model 224 of the second part 110 by the second waviness deviation 234. The first modified nominal model 190 represents the first mating surface 118 of the first part 106 after the first part 106 and the second part 110 are bonded together. The second modified nominal model 290 represents the second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together. The dimension 114 of the gap 116 is determined using the first modified nominal model 190 and the second modified nominal model 290.

[0117]

[0134] In one or more embodiments, the model analyzer 112 determines a first total deviation 122 in a normal direction between the first model 104 of the first part 106 and the first nominal model 124. The model analyzer 112 determines a second total deviation 222 in a normal direction between the second model 108 of the second part 110 and the second nominal model 224. The first waviness deviation 134 is derived from the first total deviation 122. The second waviness deviation 234 is derived from the second total deviation 222.

[0118]

[0135] In one or more embodiments, the model analyzer 112 performs a best-fit alignment between the first model 104 and the first nominal model 124 of the first part 106 to identify the first overall deviation 122. The model analyzer 112 performs a best-fit alignment between the second model 108 and the second nominal model 224 of the second part 110 to identify the second overall deviation 222.

[0119]

[0136] In one or more embodiments, the model analyzer 112 determines a first overall dimension 164 of the first overall deviation 122 in the normal direction. The model analyzer 112 determines a second overall dimension 264 of the second overall deviation 222 in the normal direction.

[0120]

[0137] In one or more embodiments, the model analyzer 112 maps the first total deviation 122 from the XYZ coordinate system 126 to the UVW coordinate system 128, such that a first value of the first total dimension 164 of the first total deviation 122 is represented along the W-axis 152. In one or more embodiments, the model analyzer 112 maps the second total deviation 222 from the XYZ coordinate system 126 to the UVW coordinate system 128, such that a second value of the second total dimension 264 of the second total deviation 222 is represented along the W-axis 152.

[0121]

[0138] In one or more embodiments, the model analyzer 112 filters the first value of the first overall dimension 164 of the first overall deviation 122 into the first shape deviation 132 and the first waviness deviation 134. In one or more embodiments, the model analyzer 112 filters the second value of the second overall dimension 264 of the second overall deviation 222 into the second shape deviation 232 and the second waviness deviation 234.

[0122]

[0139] In one or more embodiments, the model analyzer 112 maps the first waviness deviation 134 from the UVW coordinate system 128 to the XYZ coordinate system 126, whereby a first value of a first waviness dimension 168 of the first waviness deviation 134 is represented as a first distance 160 to the first nominal model 124. In one or more embodiments, the model analyzer 112 maps the second waviness deviation 234 from the UVW coordinate system 128 to the XYZ coordinate system 126, whereby a second value of a second waviness dimension 268 of the second waviness deviation 234 is represented as a second distance 260 to the second nominal model 224.

[0123]

[0140] 14 , in one or more embodiments, a method 1000 includes generating 1002 a first model 104 of a first part 106. The method 1000 includes generating 1004 a second model 108 of a second part 110. The steps 1002 of generating the first model 104 and 1004 of generating the second model 108 are performed before the first part 106 and the second part 110 are bonded together. The method 1000 includes a step 1006 of filtering out a first variant 162 of the first part 106 and a second variant 262 of the second part 110 that exist before the first part 106 and the second part 110 are bonded together. The method 1000 includes a step 1008 of identifying (e.g., predicting) a dimension 114 of a gap 116 that will exist between a first mating surface 118 and a second mating surface 120 after the first part 106 and the second part 110 are bonded together. The method 1000 includes a step 1010 of comparing the dimension 114 of the gap 116 against a gap threshold 214. The method 1000 includes a step 1012 of recommending an operation 212 based on the prediction of the dimension 114 of the gap 116.

[0124]

[0141] In one or more embodiments, step 1006 of filtering out deformations of at least one of the first part 106 and the second part 110 before the first part 106 and the second part 110 are bonded together is one embodiment of analyzing the first model 104 and the second model 108 of the disclosed predictive assembly analysis process (e.g., method 2000).

[0125]

[0142] 15 , in one or more embodiments, a method 2000 includes a step 2006 of generating a first model 104 of a first part 106. The method 2000 includes a step 2008 of generating a second model 108 of a second part 110. The steps 2006 of generating the first model 104 and 2008 of generating the second model 108 are performed before the first part 106 and the second part 110 are bonded together.

[0126]

[0143] In one or more embodiments, the method 2000 includes a step 2010 of analyzing the first model 104 and the second model 108 to determine a dimension 114 of the gap 116 between the first mating surface 118 of the first part 106 and the second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together. In one example, the method 2000 includes a step 2032 of determining (e.g., calculating) the dimension 114 of the gap 116 between the first mating surface 118 of the first part 106 and the second mating surface 120 of the second part 110 based on the analysis performed on the first model 104 and the second model 108.

[0127]

[0144] In one or more embodiments, the method 2000, such as the analyzing step 2010, includes a step 2012 of identifying (e.g., calculating) a first overall deviation 122 in the normal direction 150 between the first model 104 and the first nominal model 124 of the first part 106. In one or more embodiments, the analyzing step 2010 also includes a step 2012 of identifying (e.g., calculating) a second overall deviation 222 in the normal direction 150 between the second model 108 and the second nominal model 224 of the second part 110.

[0128]

[0145] In one or more embodiments, the method 2000, such as the identifying step 2012, includes a step 2014 of performing a best fit alignment between the first model 104 and the first nominal model 124 of the first part 106 to identify the first overall deviation 122. In one or more embodiments, the identifying step 2012 includes a step 2014 of performing a best fit alignment between the second model 108 and the second nominal model 224 of the second part 110 to identify the second overall deviation 222.

[0129]

[0146] In one or more embodiments, the method 2000, such as the analyzing step 2010, includes a step 2016 of identifying (e.g., calculating) a first overall dimension 164 of the first overall deviation 122 in the normal direction 150. In one or more embodiments, the analyzing step 2010 includes a step 2016 of identifying (e.g., calculating) a second overall dimension 264 of the second overall deviation 222 in the normal direction 150.

[0130]

[0147] In one or more embodiments, the method 2000, such as the analyzing step 2010, includes a step 2018 of mapping the first total deviation 122 from the XYZ coordinate system 126 to the UVW coordinate system 128 such that the value of the first total dimension 164 of the first total deviation 122 is represented along the W-axis 152. In one or more embodiments, the analyzing step 2010 includes a step 2018 of mapping the second total deviation 222 from the XYZ coordinate system 126 to the UVW coordinate system 128 such that the value of the second total dimension 264 of the second total deviation 222 is represented along the W-axis 152.

[0131]

[0148] In one or more embodiments, the method 2000, such as the analyzing step 2010, includes a step 2020 of filtering values ​​of the first overall dimension 164 of the first overall deviation 122 into a first shape deviation 132 and a first waviness deviation 134. In one or more embodiments, the analyzing step 2010 includes a step 2020 of filtering values ​​of the second overall dimension 264 of the second overall deviation 222 into a second shape deviation 232 and a second waviness deviation 234.

[0132]

[0149] In one or more embodiments, according to method 2000, filtering 2020 is performed using or includes a step 2022 or performing a low pass filter 156. In one or more embodiments, according to method 1000, filtering 2020 is performed using or includes a step 2024 or performing a robust Gaussian regression filter 158.

[0133]

[0150] In one or more embodiments, the method 2000, such as the analyzing step 2010, includes a step 2026 of modifying the first nominal model 124 by the first waviness deviation 134. The first nominal model 124 modified by the first waviness deviation 134 thereby represents the first mating surface 118 of the first part 106 after the first part 106 and the second part 110 are bonded together. In one or more embodiments, the analyzing step 2010 includes a step 2026 of modifying the second nominal model 224 by the second waviness deviation 234. The second nominal model 224 modified by the second waviness deviation 234 thereby represents the second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together.

[0134]

[0151] In one or more embodiments, the dimension 114 of the gap 116 is determined using the first modified nominal model 190 and the second modified nominal model 290 .

[0135]

[0152] In one or more embodiments, the method 2000, such as the modifying step 2026, includes a step 2028 of mapping the first waviness deviation 134 from the UVW coordinate system 128 to the XYZ coordinate system 126 such that a value of the first waviness dimension 168 of the first waviness deviation 134 is expressed as a first distance 160 relative to the first nominal model 124. In one or more embodiments, the modifying step 2026 includes a step 2028 of mapping the second waviness deviation 234 from the UVW coordinate system 128 to the XYZ coordinate system 126 such that a value of the second waviness dimension 268 of the second waviness deviation 234 is expressed as a second distance 260 relative to the second nominal model 224.

[0136]

[0153] In one or more embodiments, the modifying step 2026 includes adding 2030 the first distance 160 to and / or subtracting 2030 the first distance 160 from the first nominal model 124, such that the first modified nominal model 190 represents the first part 106 having the first assembled shape 176, thereby providing at least a portion of the dimension 114 of the gap 116. In one or more embodiments, the modifying step 2026 includes adding 2030 the second distance 260 to and / or subtracting 2030 the second distance 260 from the second nominal model 224, such that the second modified nominal model 290 represents the second part 110 having the second assembled shape 276, thereby providing at least a portion of the dimension 114 of the gap 116.

[0137]

[0154] In one or more embodiments, the method 2000 includes generating 2002 first data 138 representing at least a portion of the first mating surface 118 of the first part 106. The generating 2002 first data 138 is performed before the first part 106 and the second part 110 are bonded together. The first model 104 is generated using the first data 138.

[0138]

[0155] In one or more embodiments, the method 2000 includes generating 2004 second data 140 representing at least a portion of the second mating surface 120 of the second part 110. The generating 2004 second data 140 is performed before the first part 106 and the second part 110 are bonded together. The second model 108 is generated using the second data 140.

[0139]

[0156] In one or more embodiments, the method 2000 includes recommending 2034 an operation 212 based on a comparison of the gap 116 (e.g., the dimension 114) to the gap threshold 214. In one or more embodiments, the operation 212 includes joining the first part 106 and the second part 110 when the dimension 114 of the gap 116 is less than or equal to the gap threshold 214. In one or more embodiments, the operation 212 includes reworking at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214. In one or more embodiments, the operation 212 includes redesigning at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214. In one or more embodiments, the operation 212 includes repairing at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214 .

[0140]

[0157] In one or more embodiments, the method 1000 includes bonding the first part 106 and the second part 110 together. In one or more embodiments, the bonding is performed using a bonding process 194, whereby the first mating surface 118 and the second mating surface 120 are mated. In one or more embodiments, several gaps 116 are formed between the first mating surface 118 and the second mating surface 120. In these embodiments, the dimensions 114 of the gaps 116 are less than the gap threshold 214, whereby the object meets assembly and / or clearance requirements according to the design, specifications, and / or tolerances.

[0141]

[0158] 2, 14, and 15, in one or more embodiments, method 1000 and / or method 2000 are implemented using computer 148. For example, method 1000 and / or method 2000 are computer-implemented methods. In one or more embodiments, system 100 is a computer-implemented system configured or adapted to implement method 1000 and / or method 2000.

[0142]

[0159] 3, a portion of aircraft 1200 is also disclosed. The portion of aircraft 1200 is manufactured using system 100 and / or according to method 1000 or method 2000.

[0143]

[0160] 16 , by way of example, the present disclosure is also directed to a computer program product 922. The computer program product 922 includes a non-transitory computer-readable medium 920 that includes program code 918. The program code 918, when executed by one or more processors 904, causes the one or more processors 904 to perform operations.

[0144]

[0161] In one or more embodiments, the process includes generating a first model 104 of the first part 106 from the first data 138 before the first part 106 is bonded to the second part 110. The process includes generating a second model 108 of the second part 110 from the second data 140 before the second part 110 is bonded to the first part 106.

[0145]

[0162] In one or more embodiments, the process includes filtering out the first variant 162. In one or more embodiments, the process includes filtering out the second variant 262.

[0146]

[0163] In one or more embodiments, the process includes analyzing the first model 104 and the second model 108 to determine a dimension 114 of a gap 116 between a first mating surface 118 of the first part 106 and a second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together.

[0147]

[0164] In one or more embodiments, the process includes determining a first overall deviation 122 in the normal direction 150 between the first model 104 and the first nominal model 124 of the first part 106. In one or more embodiments, the process includes determining a second overall deviation 222 in the normal direction 150 between the second model 108 and the second nominal model 224 of the second part 110.

[0148]

[0165] In one or more embodiments, the process includes performing a best-fit alignment between the first model 104 and the first nominal model 124 of the first part 106 to identify the first overall deviation 122. In one or more embodiments, the process includes performing a best-fit alignment between the second model 108 and the second nominal model 224 of the second part 110 to identify the second overall deviation 222.

[0149]

[0166] In one or more embodiments, the process includes determining a first overall dimension 164 of the first overall deviation 122 in the normal direction 150. In one or more embodiments, the process includes determining a second overall dimension 264 of the second overall deviation 222 in the normal direction 150.

[0150]

[0167] In one or more embodiments, the process includes mapping the first total deviation 122 from the XYZ coordinate system 126 to the UVW coordinate system 128, whereby a value of the first total dimension 164 of the first total deviation 122 is represented along the W-axis 152. In one or more embodiments, the process includes mapping the second total deviation 222 from the XYZ coordinate system 126 to the UVW coordinate system 128, whereby a value of the second total dimension 264 of the second total deviation 222 is represented along the W-axis 152.

[0151]

[0168] In one or more embodiments, the process includes filtering values ​​of the first overall dimension 164 of the first overall deviation 122 into a first shape deviation 132 and a first waviness deviation 134. In one or more embodiments, the process includes filtering values ​​of the second overall dimension 264 of the second overall deviation 222 into a second shape deviation 232 and a second waviness deviation 234.

[0152]

[0169] In one or more embodiments, the filtering is performed using a low pass filter 156. In one or more embodiments, the filtering is performed using a robust Gaussian regression filter 158.

[0153]

[0170] In one or more embodiments, the process includes mapping the first waviness deviation 134 from the UVW coordinate system 128 to the XYZ coordinate system 126, whereby a value of a first waviness dimension 168 of the first waviness deviation 134 is represented as a first distance 160 relative to the first nominal model 124. In one or more embodiments, the process includes mapping the second waviness deviation 234 from the UVW coordinate system 128 to the XYZ coordinate system 126, whereby a value of a second waviness dimension 268 of the second waviness deviation 234 is represented as a second distance 260 relative to the second nominal model 224.

[0154]

[0171] In one or more embodiments, the process includes modifying the first nominal model 124 by the first waviness deviation 134 (e.g., the first distance 160). The first nominal model 124 modified by the first waviness deviation 134 (e.g., the first modified nominal model 190) thereby represents the first mating surface 118 of the first part 106 after the first part 106 and the second part 110 are bonded together. In one or more embodiments, the process includes modifying the second nominal model 224 by the second waviness deviation 234 (e.g., the second distance 260). Thereby, the second nominal model 224 (e.g., second modified nominal model 290) modified by the second waviness deviation 234 represents the second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together.

[0155]

[0172] In one or more embodiments, the process includes analyzing the first modified model 190 and the second modified model 290 to determine a dimension 114 of a gap 116 between a first mating surface 118 of the first part 106 and a second mating surface 120 of the second part 110 after the first part 106 and the second part 110 are bonded together.

[0156]

[0173] In one or more embodiments, the process recommends an operation 212 based on a comparison of the gap 116 to a gap threshold 214. In one or more embodiments, the operation 212 includes joining the first part 106 and the second part 110 when the dimension 114 of the gap 116 is less than or equal to the gap threshold 214. In one or more embodiments, the operation 212 includes reworking at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214. In one or more embodiments, the operation 212 includes redesigning at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214. In one or more embodiments, the operation 212 includes repairing at least one of the first part 106 and the second part 110 when the dimension 114 of the gap 116 is greater than the gap threshold 214.

[0157]

[0174] 2, in one or more embodiments, system 100 may be implemented using software, hardware, firmware, or a combination thereof. When software is used, the operations performed by system 100 may be implemented using, for example, but not limited to, program code configured to execute on a processor unit. When firmware is used, the operations performed by system 100 may be implemented using, for example, but not limited to, program code and data stored in persistent memory for execution on a processor unit.

[0158]

[0175] When hardware is employed, the hardware may include one or more circuits that operate to perform the operations performed by system 100. Depending on the implementation, the hardware may take the form of a circuit system, an integrated circuit, an application specific integrated circuit (ASIC), a programmable logic device, or some other suitable type of hardware device configured to perform any number of operations.

[0159]

[0176] A programmable logic device may be configured to perform particular operations. The device may be permanently configured to perform these operations or may be reconfigurable. A programmable logic device may take the form of, for example, but not limited to, a programmable logic array, a programmable array logic device, a field programmable logic array, a field programmable gate array, or some other type of programmable hardware device.

[0160]

[0177] In some embodiments, the steps and processes performed by system 100 may be performed using organic components integrated with inorganic components. In some cases, the steps and processes may be performed entirely by non-human organic components. For example, organic semiconductor circuits may be used to perform these steps and processes.

[0161]

[0178] 16, in one or more embodiments, computer 148 (FIG. 2) takes the form of a data processing system 900. In one or more embodiments, data processing system 900 includes a communications framework 902 that facilitates communications between at least one processor 904, one or more storage devices 916, such as memory 906 and / or persistent storage 908, a communications unit 910, an input / output unit 912 (I / O unit), and a display 914. In this embodiment, communications framework 902 takes the form of a bus system.

[0162]

[0179] Processor 904 functions to execute instructions 170 (FIG. 2) for software that may be loaded into memory 906. In one or more embodiments, processor 904 may be several processors, a multi-processor core, or some other type of processor, depending on the particular implementation.

[0163]

[0180] Memory 906 and persistent storage 908 are examples of storage device 916. A storage device is any piece of hardware that can store information, such as, but not limited to, data, program code in a functional form, or other suitable information, temporarily, persistently, or both. Storage device 916 may also be referred to as a computer-readable storage device in one or more embodiments. Memory 906 may be, for example, a random access memory or any other suitable volatile or non-volatile storage device. Persistent storage 908 may take various forms depending on the particular implementation.

[0164]

[0181] For example, persistent storage 908 may comprise one or more components or devices. For example, persistent storage 908 may be a hard drive, a solid-state hard drive, a flash memory, a rewritable optical disk, a rewritable magnetic tape, or some combination thereof. The media used by persistent storage 908 may also be removable. For example, a removable hard drive may be used for persistent storage 908.

[0165]

[0182] The communication unit 910 provides for communication with other systems or devices, such as the measurement system 136 or other computer systems. In one or more embodiments, the communication unit 910 is a network interface card.

[0166]

[0183] Input / output unit 912 allows for input and output of data to and from other devices that may be connected to data processing system 900. As one example, input / output unit 912 provides a connection for user input via at least one of a keyboard, a mouse, or some other suitable input device. Additionally, input / output unit 912 may send output to a printer. Display 914 provides a mechanism for displaying information to a user. For example, user interface 202 may be displayed to a user by display 914.

[0167]

[0184] Instructions for at least one of the operating system, applications, and programs (e.g., instructions 170) may be located in storage device 916, which may be in communication with processor 904 through communications framework 902. The processes of various embodiments may be performed by processor unit 904 using computer-implemented instructions that may be located in a memory (such as memory 906).

[0168]

[0185] The instructions 170 may be referred to as program code, computer usable program code, or computer readable program code, which may be read and executed by a processor in processor unit 904. The program code in different embodiments may be embodied in different physical or computer readable storage media, such as memory 906 or persistent storage 908.

[0169]

[0186] In one or more embodiments, program code 918 is located in a functional form on a selectively removable computer readable medium 920 and may be loaded onto or transmitted to data processing system 900 for execution by processor 904. In one or more embodiments, program code 918 and computer readable medium 920 form computer program product 922. In one or more embodiments, computer readable medium 920 is computer readable storage medium 924.

[0170]

[0187] In one or more embodiments, computer readable storage media 924 is a physical or tangible storage device used to store program code 918 rather than a medium that propagates or transmits program code 918.

[0171]

[0188] Alternatively, program code 918 may be transmitted to data processing system 900 using a computer readable signal medium. The computer readable signal medium may be, for example, a propagated data signal embodied with program code 918. For example, the computer readable signal medium may be at least one of an electromagnetic signal, an optical signal, or any other suitable type of signal. These signals may be transmitted over at least one communications link, such as wireless communications links, fiber optic cable, coaxial cable, a wire, or any other suitable type of communications link.

[0172]

[0189] The different components illustrated for data processing system 900 are not meant to provide architectural limitations to the manner in which different embodiments may be implemented. Different embodiments may be implemented in a data processing system including components in addition to or instead of those illustrated for data processing system 900. Other components illustrated in FIG. 16 may differ from the illustrated embodiments. Different embodiments may be implemented using any hardware device or system capable of running program code 918.

[0173]

[0190] Additionally, various components of computer 148 and / or data processing system 900 may be described as modules. For purposes of this disclosure, the term “module” may include hardware, software, or a combination of hardware and software. As one example, a module may include one or more circuits configured to perform or implement the described functions or operations of the processes described herein (e.g., method 1000 and / or method 2000). As another example, a module may also include a processor, a storage device (e.g., memory), and a computer-readable storage medium having instructions that, when executed by the processor, cause the processor to perform or implement the described functions. In one or more examples, a module takes the form of program code 918 and computer-readable medium 920 that together form computer program product 922. In one or more examples, model generator 102, model analyzer 112, and / or assembly planner 210 are implemented as modules.

[0174]

[0191] 17 and 18 , several embodiments of system 100, method 1000, method 2000, and / or computer program product 922 described herein may be related to or used in the context of aircraft manufacturing and service method 1100, as illustrated in the flow diagram of Figure 17, and aircraft 1200, as illustrated generally in Figure 18. For example, aircraft 1200 and / or aircraft manufacturing and service method 1100 may include object 180 ( Figure 1 ), such as fuselage 1218, wing 1220, etc., produced using system 100 and / or according to method 1000 or 2000.

[0175]

[0192] 3 and 18 , which illustrate embodiments of an aircraft 1200. The aircraft 1200 includes an airframe 1202 having an interior 1206. The aircraft 1200 includes a plurality of onboard systems 1204 (e.g., high-level systems). Examples of the onboard systems 1204 of the aircraft 1200 include a propulsion system 1208, a hydraulic system 1212, an electrical system 1210, and an environmental system 1214. In other examples, the onboard systems 1204 also include one or more control systems 1216 coupled to the airframe 1202 of the aircraft 1200, such as flaps, spoilers, ailerons, slats, rudder, elevators, and trim tabs. In still other examples, the onboard systems 1204 also include one or more other systems, such as, but not limited to, a communications system, an avionics system, a software distribution system, a network communications system, a passenger information / entertainment system, a guidance system, a radar system, and a weapons system. Aircraft 1200 may include various other structures assembled using system 100 and / or methods 1000, 2000.

[0176]

[0193] 17 , during pre-production of the aircraft 1200, aircraft manufacturing and service method 1100 includes specification and design 1102 of the aircraft 1200 and materials procurement 1104. During production of the aircraft 1200, component and subassembly manufacturing 1106 and system integration 1108 of the aircraft 1200 occur. The aircraft 1200 then undergoes certification and delivery 1110 before being placed into service 1112. Routine maintenance and service 1114 includes modifying, reconfiguring, refurbishing, etc., one or more systems of the aircraft 1200.

[0177]

[0194] Each of the processes of aircraft manufacturing and service method 1100 shown in Figure 17 may be performed or carried out by a system integrator, a third party, and / or an operator (e.g., a customer). For purposes of this specification, a system integrator may include, but is not limited to, any number of aircraft manufacturers and major system subcontractors, a third party may include, but is not limited to, any number of vendors, subcontractors, and suppliers, and an operator may be an airline, leasing company, military entity, service organization, etc.

[0178]

[0195] The system 100 and methods 1000 and 2000 shown and described herein may be employed during any one or more stages of the aircraft manufacturing and service method 1100 illustrated in the flow diagram shown in Figure 17. In one example, parts of the aircraft 1200 may be predictively assembled using the system 100 and / or in accordance with the methods 1000 or 2000 during component and subassembly manufacturing 1106 and / or system integration 1108. Furthermore, parts of the aircraft 1200 may be predictively assembled using the system 100 and / or in accordance with the methods 1000 and 2000 during service 1112 of the aircraft 1200. Parts of the aircraft 1200 may also be predictively assembled using the system 100 and / or in accordance with the methods 1000 and 2000 during system integration 1108 and certification and delivery 1110. Similarly, parts of aircraft 1200 may be predictively assembled using system 100 and / or according to methods 1000 , 2000 while aircraft 1200 is in service 1112 and during maintenance and service 1114 .

[0179]

[0196] The foregoing detailed description refers to the accompanying drawings, which illustrate specific embodiments described by the present disclosure. Other embodiments having different structures and steps do not depart from the scope of the present disclosure. Like reference numerals may represent the same feature, element, or component in various drawings. Throughout this disclosure, any of a plurality of items may be referred to individually as that item, and a plurality of items may be referred to collectively as items (plural) and may be represented by like reference numerals. Furthermore, as used herein, a feature, element, component, or step preceded by the term "a" or "an" should be understood not to exclude a plurality of features, elements, components, or steps, unless expressly stated to exclude it.

[0180]

[0197] Illustrative, non-exhaustive examples of the inventive subject matter according to the present disclosure may be, but are not necessarily, claimed. Reference herein to an "example" means that one or more features, structures, elements, components, properties, and / or operational steps described in connection with the example are included in at least one aspect, embodiment, and / or implementation of the subject matter according to the present disclosure. Thus, the phrases "one example," "another example," "one or more examples," and similar phrases used throughout this disclosure may, but do not necessarily, refer to the same example. Furthermore, subject matter characterizing any one of the examples may, but does not necessarily, include subject matter characterizing any other example. Furthermore, subject matter characterizing any one of the examples may, but does not necessarily, be combined with subject matter characterizing any other example.

[0181]

[0198] As used herein, a system, apparatus, device, structure, article, element, component, or hardware that is "configured to" perform a particular function is, in fact, capable of performing that particular function without any modification, rather than merely having the potential to perform that particular function after further modification. In other words, a system, apparatus, device, structure, article, element, component, or hardware that is "configured" to perform a particular function is specifically selected, created, implemented, utilized, programmed, and / or designed for the purpose of performing that particular function. As used herein, "configured to" refers to an existing characteristic of a system, apparatus, device, structure, article, element, component, or hardware that enables the system, apparatus, device, structure, article, element, component, or hardware to perform a particular function without further modification. For the purposes of this disclosure, a system, apparatus, device, structure, article, element, component, or hardware that is described as "configured" to perform a particular function may additionally or alternatively be described as "adapted" and / or "operating" to perform that function.

[0182]

[0199] Unless otherwise indicated, terms such as "first," "second," "third," etc. are used herein merely as designators and are not intended to impose any sequential, positional, or hierarchical requirements on the items to which these terms refer. Furthermore, a reference to, e.g., a "second" item does not require or preclude the presence of, e.g., a "first" or lower-numbered item and / or, e.g., a "third" or higher-numbered item.

[0183]

[0200] As used herein, the phrase "at least one of" used in conjunction with listed items means that various combinations of one or more of the listed items may be used, and that only one of each listed item may be required. For example, "at least one of item A, item B, and item C" may include, but is not limited to, "item A," or "item A and item B." This example may also include item A, item B, and item C, or item B and item C. In other examples, "at least one of" may be, for example, but is not limited to, "two item A, one item B, and ten item C," "four item B, and seven item C," and other suitable combinations. As used herein, the phrase "and / or" and the indicia " / " include any and all combinations of one or more of the associated listed items.

[0184]

[0201] For purposes of this disclosure, the terms "coupled," "coupling," and similar terms refer to two or more elements that are coupled, connected, fastened, attached, connected, in communication with, or otherwise associated (e.g., mechanically, electrically, fluidly, optically, electromagnetically) with one another. In various examples, these elements may be directly associated or indirectly associated. For example, element A may be directly associated with element B. As another example, element A may be associated with element B, e.g., through another element C. It should be understood that not all relationships between the various disclosed elements are necessarily depicted. Thus, other couplings than those shown in the figures may exist.

[0185]

[0202] As used herein, the term "approximately" refers to or describes a condition that is close to, but not exactly, a specified condition that still performs a desired function or achieves a desired result. As an example, the term "approximately" refers to a condition that is within an acceptable predetermined tolerance or precision, such as within 10% of the specified condition. However, the term "approximately" does not exclude a condition that is exactly the specified condition. As used herein, the term "substantially" refers to a condition that is essentially a specified condition that performs a desired function or achieves a desired result.

[0186]

[0203] The above-referenced Figures 1-13, 16, and 18 may depict functional elements, features, or components thereof and do not necessarily suggest any particular structure. Accordingly, modifications, additions, and / or omissions may be made to the illustrated configurations. Furthermore, those skilled in the art will recognize that not all elements, features, and / or components described and shown in the above-referenced Figures 1-13, 16, and 18 need be included in every embodiment, and not all elements, features, and / or components described herein are necessarily shown in each illustrative embodiment. Accordingly, some of the elements, features, and / or components described and shown in Figures 1-13, 16, and 18 may be combined in various ways without necessarily including other features described and shown in Figures 1-13, 16, and 18, other figures, and / or the accompanying disclosure, although such combinations are not explicitly set forth herein. Similarly, additional features not limited to the examples presented may be combined with some or all of the features shown and described herein. Unless expressly stated otherwise, the schematic diagrams of the embodiments set forth in FIGS. 1-13, 16, and 18 above are not intended to imply architectural limitations with respect to the example embodiments. Rather, it is to be understood that one example configuration is depicted, as may be appropriately modified. Accordingly, modifications, additions, and / or omissions may be made to the illustrated configuration. Furthermore, elements, features, and / or components that serve similar, or at least substantially similar, purposes are labeled with similar reference numerals in each of FIGS. 1-13, 16, and 18, and such elements, features, and / or components may not be described in detail herein when referring to each of FIGS. 1-13, 16, and 18. Similarly, not all elements, features, and / or components are labeled with reference numerals in each of FIGS. 1-13, 16, and 18, although their associated reference numerals may be used consistently herein.

[0187]

[0204] In the above-referenced Figures 14, 15, and 17, multiple blocks may represent operations, steps, and / or portions thereof, and the lines connecting various blocks do not imply any particular order or dependency of the operations or portions thereof. It should be understood that not all dependencies between the various disclosed processes are necessarily depicted. Figures 14, 15, and 17, and the accompanying disclosure describing the operations disclosed herein, should not be construed as necessarily dictating the order in which operations should be performed. Rather, although one exemplary order is shown, it should be understood that the sequence of operations can be changed where appropriate. Accordingly, modifications, additions, and / or omissions may be made to the illustrated operations, and certain operations may be performed in a different order or simultaneously. Additionally, those skilled in the art will recognize that it is not necessary to perform all of the operations described.

[0188]

[0205] Furthermore, throughout this specification, references to features, advantages, or similar language as used herein do not imply that all of the features and advantages that may be realized in the examples disclosed herein should or are in any single example. Rather, language referring to features and advantages is understood to mean that the particular feature, advantage, or characteristic described in connection with an example is included in at least one example. Thus, descriptions of features, advantages, and similar language as used throughout this disclosure may, but do not necessarily, refer to the same single example.

[0189]

[0206] The described features, advantages, and characteristics of one embodiment may be combined in any suitable manner in one or more other embodiments. Those skilled in the art will recognize that the embodiments described herein may be practiced without one or more of the specific features or advantages of a particular example. In other cases, additional features and advantages may be recognized in certain examples that may not be present in all examples. Moreover, while various embodiments of system 100, method 1000, method 2000, and computer program product 922 have been shown and described, modifications will occur to those skilled in the art upon reading this specification. The present application includes such modifications and is limited only by the scope of the claims.

Claims

1. A system (100), comprising: a model generator (102) for generating a first model (104) of a first part (106) and a second model (108) of a second part (110) before the first part (106) and the second part (110) are bonded together; a model analyzer (112) that analyzes the first model (104) and the second model (108) to identify a size (114) of a gap (116) between a first mating surface (118) of the first component (106) and a second mating surface (120) of the second component (110) after the first component (106) and the second component (110) are joined together; and A system (100) comprising an assembly planner (210) that recommends operations (212) based on a comparison of the gap (116) to a gap threshold (214).

2. 2. The system of claim 1, wherein the operation recommended by the assembly planner comprises joining the first part and the second part together when the dimension of the gap is less than or equal to the gap threshold.

3. 2. The system of claim 1, wherein the operations recommended by the assembly planner include reworking at least one of the first part and the second part when the dimension of the gap is greater than the gap threshold.

4. 2. The system of claim 1, wherein the actions recommended by the assembly planner include redesigning at least one of the first part and the second part when the dimension of the gap is greater than the gap threshold.

5. 2. The system of claim 1, wherein the operations recommended by the assembly planner include repairing at least one of the first component and the second component when the dimension of the gap is greater than the gap threshold.

6. The model analyzer (112) modifying a first nominal model (124) of the first part (106) by a first waviness deviation (134); and modifying a second nominal model (224) of the second part (110) by a second waviness deviation (234); a first modified nominal model (190) representing the first mating surface (118) of the first part (106) after the first part (106) and the second part (110) are bonded together; a second modified nominal model (290) representing the second mating surface (120) of the second part (110) after the first part (106) and the second part (110) are bonded together; 2. The system of claim 1, wherein the dimension of the gap is determined using the first modified nominal model and the second modified nominal model.

7. The model analyzer (112) determining a first overall deviation (122) in a normal direction between the first model (104) and the first nominal model (124) of the first part (106); and determining a second overall deviation (222) in the normal direction between the second model (108) and the second nominal model (224) of the second part (110); the first waviness deviation (134) is derived from the first total deviation (122); The system (100) of claim 6, wherein the second waviness deviation (234) is derived from the second total deviation (222).

8. The model analyzer (112) performing a best-fit alignment between the first model (104) and the first nominal model (124) of the first part (106) to identify the first overall deviation (122); and 8. The system (100) of claim 7, further comprising: performing the best-fit alignment between the second model (108) and the second nominal model (224) of the second part (110) to identify the second overall deviation (222).

9. The model analyzer (112) determining a first overall dimension (164) of the first overall deviation (122) in the normal direction; determining a second overall dimension (264) of the second overall deviation (222) in the normal direction; mapping the first total deviation (122) from the XYZ coordinate system (126) to the UVW coordinate system (128) such that the first total dimension (164) of the first total deviation (122) is represented along the W axis (152); mapping the second total deviation (222) from the XYZ coordinate system (126) to the UVW coordinate system (128) such that the second total dimension (264) of the second total deviation (222) is represented along the W axis (152); filtering the first overall dimension (164) of the first overall deviation (122) into a first shape deviation (132) and a first waviness deviation (134); and 9. The system of claim 8, further comprising filtering the second overall dimension of the second overall deviation into a second shape deviation and a second waviness deviation.

10. The model analyzer (112) mapping the first waviness deviation (134) from the UVW coordinate system (128) to the XYZ coordinate system (126) such that a first waviness dimension (168) of the first waviness deviation (134) is expressed as a first distance (160) relative to the first nominal model (124); and 10. The system (100) of claim 9, further comprising: mapping the second waviness deviation (234) from the UVW coordinate system (128) to the XYZ coordinate system (126) such that a second waviness dimension (268) of the second waviness deviation (234) is expressed as a second distance (260) relative to the second nominal model (224).

11. 2. The system of claim 1, further comprising a measurement system for generating first data representing at least a portion of the first mating surface of the first component and second data representing at least a portion of the second mating surface of the second component before the first mating surface and the second mating surface are mated.

12. 2. The system of claim 1, wherein the model generator, the model analyzer, and the assembly planner take the form of program code executed by a data processing system.

13. A method (1000) for predictive assembly, comprising: generating a first model (104) of the first part (106) and a second model (108) of the second part (110) before the first part (106) and the second part (110) are bonded together; analyzing the first model (104) and the second model (108) to determine a size (114) of a gap (116) between a first mating surface (118) of the first component (106) and a second mating surface (120) of the second component (110) after the first component (106) and the second component (110) are bonded together; and A method (1000) comprising recommending an action (212) based on a comparison of the gap (116) to a gap threshold (214).

14. 14. The method (1000) of claim 13, wherein the operation (212) comprises joining the first part (106) and the second part (110) together when the dimension (114) of the gap (116) is less than or equal to the gap threshold (214).

15. 14. The method (1000) of claim 13, wherein the operation (212) includes reworking at least one of the first part (106) and the second part (110) when the dimension (114) of the gap (116) is greater than the gap threshold (214).

16. 14. The method (1000) of claim 13, wherein the operation (212) includes redesigning at least one of the first part (106) and the second part (110) when the dimension (114) of the gap (116) is greater than the gap threshold (214).

17. 14. The method (1000) of claim 13, wherein the operation (212) includes repairing at least one of the first component (106) and the second component (110) when the dimension (114) of the gap (116) is greater than the gap threshold (214).

18. modifying a first nominal model (124) of the first part (106) by a first waviness deviation (134); and further comprising modifying a second nominal model (224) of the second part (110) by a second waviness deviation (234); a first modified nominal model (190) representing the first mating surface (118) of the first part (106) after the first part (106) and the second part (110) are bonded together; a second modified nominal model (290) representing the second mating surface (120) of the second part (110) after the first part (106) and the second part (110) are bonded together; 14. The method (100) of claim 13, wherein the dimension (114) of the gap (116) is determined using the first modified nominal model (190) and the second modified nominal model (290).

19. determining a first overall deviation (122) in a normal direction between the first model (104) and the first nominal model (124) of the first part (106); determining a second overall deviation (222) in a normal direction between the second model (108) and the second nominal model (224) of the second part (110); performing a best-fit alignment between the first model (104) and the first nominal model (124) of the first part (106) to identify the first overall deviation (122); performing the best-fit alignment between the second model (108) and the second nominal model (224) of the second part (110) to identify the second overall deviation (222); determining a first overall dimension (164) of the first overall deviation (122) in the normal direction; determining a second overall dimension (264) of the second overall deviation (222) in the normal direction; mapping the first total deviation (122) from the XYZ coordinate system (126) to the UVW coordinate system (128) such that the first total dimension (164) of the first total deviation (122) is represented along the W axis (152); mapping the second total deviation (222) from the XYZ coordinate system (126) to the UVW coordinate system (128) such that the second total dimension (264) of the second total deviation (222) is represented along the W axis (152); filtering the first overall dimension (164) of the first overall deviation (122) into a first shape deviation (132) and the first waviness deviation (134); filtering the second overall dimension (264) of the second overall deviation (222) into a second shape deviation (232) and a second waviness deviation (234); mapping the first waviness deviation (134) from the UVW coordinate system (128) to the XYZ coordinate system (126) such that a first waviness dimension (168) of the first waviness deviation (134) is expressed as a first distance (160) relative to the first nominal model (124); and 20. The method (1000) of claim 18, further comprising mapping the second waviness deviation (234) from the UVW coordinate system (128) to the XYZ coordinate system (126) such that a second waviness dimension (268) of the second waviness deviation (234) is expressed as a second distance (260) relative to the second nominal model (224).

20. A non-transitory computer-readable medium (920) comprising program code (918), which, when executed by one or more processors (904), causes the one or more processors (904) to perform steps, including: generating a first model (104) of the first part (106) from the first data (138) before the first part (106) is bonded to the second part (110); generating a second model (108) of the second part (110) from second data (140) before the second part (110) is bonded to the first part (106); determining a first overall deviation (122) in a normal direction between the first model (104) and a first nominal model (124) of the first part (106); determining a second overall deviation (222) in the normal direction between the second model (108) and a second nominal model (224) of the second part (110); performing a best-fit alignment between the first model (104) and the first nominal model (124) of the first part (106) to identify the first overall deviation (122); performing the best-fit alignment between the second model (108) and the second nominal model (224) of the second part (110) to identify the second overall deviation (222); determining a first overall dimension (164) of the first overall deviation (122) in the normal direction; determining a second overall dimension (264) of the second overall deviation (222) in the normal direction; mapping the first total deviation (122) from the XYZ coordinate system (126) to the UVW coordinate system (128) such that the first total dimension (164) of the first total deviation (122) is represented along the W axis (152); mapping the second total deviation (222) from the XYZ coordinate system (126) to the UVW coordinate system (128) such that the second total dimension (264) of the second total deviation (222) is represented along the W axis (152); filtering the first overall dimension (164) of the first overall deviation (122) into a first shape deviation (132) and a first waviness deviation (134); filtering the second overall dimension (264) of the second overall deviation (222) into a second shape deviation (232) and a second waviness deviation (234); mapping the first waviness deviation (134) from the UVW coordinate system (128) to the XYZ coordinate system (126) such that a first waviness dimension (168) of the first waviness deviation (134) is expressed as a first distance (160) relative to the first nominal model (124); mapping the second waviness deviation (234) from the UVW coordinate system (128) to the XYZ coordinate system (126) such that a second waviness dimension (268) of the second waviness deviation (234) is expressed as a second distance (260) relative to the second nominal model (224); modifying the first nominal model (124) of the first part (106) by the first waviness deviation (134) so ​​that a first modified nominal model (190) represents a first mating surface (118) of the first part (106) after the first part (106) and the second part (110) are bonded together; modifying the second nominal model (224) of the second part (110) by the second waviness deviation (234) so ​​that a second modified nominal model (290) represents a second mating surface (120) of the second part (110) after the first part (106) and the second part (110) are bonded together; analyzing the first modified nominal model (190) and the second modified nominal model (290) to determine a size (114) of a gap (116) between the first mating surface (118) of the first component (106) and the second mating surface (120) of the second component (110) after the first component (106) and the second component (110) are bonded together; and recommending an action (212) based on a comparison of the gap (116) to a gap threshold (214), the action (212) comprising: bonding the first part (106) and the second part (110) together when the dimension (114) of the gap (116) is less than or equal to the gap threshold (214); reworking at least one of the first part (106) and the second part (110) when the dimension (114) of the gap (116) is greater than the gap threshold (214); redesigning at least one of the first part (106) and the second part (110) when the dimension (114) of the gap (116) is greater than the gap threshold (214); and and repairing at least one of the first component (106) and the second component (110) when the dimension (114) of the gap (116) is greater than the gap threshold (214).

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