Patent Publication Number: US-2018032638-A1

Title: Surface Analysis Systems and Methods of Generating a Comparator Surface Reference Model of a Multi-Part Assembly Using the Same

Description:
TECHNICAL FIELD 
     Embodiments described herein generally relate to surface analysis systems and, more specifically, methods and systems for generating a comparator surface reference model of a multi-part assembly, such as a vehicle. 
     BACKGROUND 
     When designing and manufacturing products, such as vehicles, reference models of the products may be created to provide a quality control reference. However, comparing a product having many parts with many surfaces to a reference model may be time consuming and inefficient. 
     Accordingly, a need exists for systems and methods for generating comparator surface reference models that include a subset of the part surfaces of a product. 
     SUMMARY 
     In one embodiment, a surface analysis system includes one or more processors, one or more memory modules communicatively coupled to the one or more processors, and machine readable instructions stored in the one or more memory modules that cause the surface analysis system to perform at least the following when executed by the one or more processors: identify one or more visible surface segments of a first part of a first multi-part assembly. The one or more visible surface segments of the first part are located unobstructed from at least one discrete observation location within an observation environment. The second part includes one or more hidden surface segments located obstructed from at least one discrete observation location within the observation environment. Further, at least one hidden surface segments of the second part is positioned adjacent and unobstructed from the first part. The machine readable instructions stored in the one or more memory modules further cause the surface analysis system to classify the one or more visible surface segments of the first part as comparator surfaces of the first multi-part assembly, determine a segment spacing distance between at least one hidden surface segment of the second part and the first part; classify the one or more hidden surface segments of the second part positioned adjacent and unobstructed from the first part that have a segment spacing distance less than or equal to a threshold spacing distance as one or more comparator surfaces of the first multi-part assembly, and generate a comparator surface reference model corresponding with the one or more comparator surfaces of the first multi-part assembly. 
     In another embodiment, a method of generating a comparator surface reference model of a first multi-part assembly includes identifying one or more visible surface segments of a first part of a first multi-part assembly. The one or more visible surface segments of the first part are located unobstructed from at least one discrete observation location within an observation environment. The second part includes one or more hidden surface segments located obstructed from at least one discrete observation location within the observation environment. Further, at least one hidden surface segment of the second part is positioned adjacent and unobstructed from the first part. The method further includes classifying the one or more visible surface segments of the first part as one or more comparator surfaces of the first multi-part assembly, determining a segment spacing distance between at least one hidden surface segments of the second part and the first part, classifying the one or more hidden surface segments of the second part positioned adjacent and unobstructed from the first part that have a segment spacing distance less than or equal to a threshold spacing distance as one or more comparator surfaces of the first multi-part assembly, and generating, using one or more processors, a comparator surface reference model corresponding with the one or more comparator surfaces of the first multi-part assembly. 
     In yet another embodiment, a surface analysis system includes one or more processors, one or more memory modules communicatively coupled to the one or more processors, and machine readable instructions stored in the one or more memory modules that cause the surface analysis system to perform at least the following when executed by the one or more processors: identify one or more visible surface segments of a first part of a multi-part assembly that further includes a second part. The one or more visible surface segments of the first part are located unobstructed from at least one discrete observation location within an observation environment. The second part includes one or more hidden surface segments located obstructed from at least one discrete observation location within the observation environment. Further, at least one hidden surface segment of the second part is positioned adjacent and unobstructed from the first part. The machine readable instructions stored in the one or more memory modules further cause the surface analysis system to determine a segment spacing distance between at least one hidden surface segments of the second part and the first part, compare, using the one or more processors, the segment spacing distance with a threshold spacing distance, compare, using the one or more processors, the one or more visible surface segments of the first part with a reference model of the multi-part assembly, and compare, using the one or more processors, the one or more hidden surface segments of the second part that are positioned adjacent and unobstructed from the first part and have a segment spacing distance less than or equal to the threshold spacing distance with the reference model of the multi-part assembly. 
     These and additional features provided by the embodiments of the present disclosure will be more fully understood in view of the following detailed description, in conjunction with the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The embodiments set forth in the drawings are illustrative and exemplary in nature and not intended to limit the disclosure. The following detailed description of the illustrative embodiments can be understood when read in conjunction with the following drawings, where like structure is indicated with like reference numerals and in which: 
         FIG. 1  schematically depicts an surface analysis system, according to one or more embodiments shown and described herein; 
         FIG. 2  depicts an example multi-part assembly comprising a vehicle, according to one or more embodiments shown and described herein; 
         FIG. 3  schematically depicts a cross-section of a first part and a second part of the multi-part assembly of  FIG. 2 , according to one or more embodiments shown and described herein; 
         FIG. 4  schematically depicts a comparator surface reference model of the first part and the second part of  FIG. 3 , according to one or more embodiments shown and described herein; 
         FIG. 5  depicts a flow diagram of a method of generating a comparator surface reference model using the surface analysis system, according to one or more embodiments shown and described herein; 
         FIG. 6  schematically depicts a cross-section of a first part and a second part of a second multi-part assembly, according to one or more embodiments shown and described herein; 
         FIG. 7  schematically depicts part models of the first part and the second part of  FIG. 6  overlaid with the comparator surface reference model of  FIG. 4 , according to one or more embodiments shown and described herein; and 
         FIG. 8  depicts a flow diagram of a method of comparing surfaces of a multi-part assembly with a reference model of the multi-part assembly using the surface analysis system, according to one or more embodiments shown and described herein. 
     
    
    
     DETAILED DESCRIPTION 
     The embodiments disclosed herein include a surface analysis system for generating a comparator surface reference model of a multi-part assembly, for example, a vehicle. In operation, the surface analysis system identifies visible surface segments of one or more parts and classifies the visible surface segments as comparator surfaces. The visible surface segments comprise the surface segments of the multi-part assembly that are positioned unobstructed from at least one observation location in an observation environment. For example, the at least one observation location may comprise a location where a head of an observer may be positioned at least once during an observation period. The surface analysis system may also classify hidden surface segments of the multi-part assembly that are positioned unobstructed from an adjacent part and located within a threshold segment spacing distance from the adjacent part. Further, the surface analysis system may generate a comparator surface reference model of the comparator surfaces of the multi-part assembly. The comparator surface reference model may be used for quality control and includes only a subset of the multi-part assembly, providing a simple and efficient quality control model for design and manufacture of multi-part assemblies. The surface analysis system and will now be described in more detail herein with specific reference to the corresponding drawings. 
     Referring now to  FIG. 1 , an embodiment of a surface analysis system  100  is schematically depicted. The surface analysis system  100  includes one or more processors  102 . Each of the one or more processors  102  may be any device capable of executing machine readable instructions. Accordingly, each of the one or more processors  102  may be a controller, an integrated circuit, a microchip, a computer, or any other processing device. For example, the one or more processors  102  may be processors of a computing device  105 . The one or more processors  102  are coupled to a communication path  104  that provides signal interconnectivity between various components of the surface analysis system  100 . Accordingly, the communication path  104  may communicatively couple any number of processors  102  with one another, and allow the components coupled to the communication path  104  to operate in a distributed computing environment. As used herein, the term “communicatively coupled” means that coupled components are capable of exchanging data signals with one another such as, for example, electrical signals via conductive medium, electromagnetic signals via air, optical signals via optical waveguides, and the like. 
     Accordingly, the communication path  104  may be formed from any medium that is capable of transmitting a signal such as, for example, conductive wires, conductive traces, optical waveguides, or the like. In some embodiments, the communication path  104  may facilitate the transmission of wireless signals, such as WiFi, Bluetooth, and the like. Moreover, the communication path  104  may be formed from a combination of mediums capable of transmitting signals. In one embodiment, the communication path  104  comprises a combination of conductive traces, conductive wires, connectors, and buses that cooperate to permit the transmission of electrical data signals to components such as processors, memories, sensors (e.g., sensors  112  described herein), input devices, output devices, and communication devices. Accordingly, the communication path  104  may comprise a vehicle bus, such as for example a LIN bus, a CAN bus, a VAN bus, and the like. Additionally, it is noted that the term “signal” means a waveform (e.g., electrical, optical, magnetic, mechanical or electromagnetic), such as DC, AC, sinusoidal-wave, triangular-wave, square-wave, vibration, and the like, capable of traveling through a medium. 
     Moreover, the surface analysis system  100  includes one or more memory modules  106  coupled to the communication path  104 . The memory modules  106  may be one or more memory modules of the computing device  105 . Further, the one or more memory modules  106  may comprise RAM, ROM, flash memories, hard drives, or any device capable of storing machine readable instructions such that the machine readable instructions can be accessed by the one or more processors  102 . The machine readable instructions may comprise logic or algorithm(s) written in any programming language of any generation (e.g., 1GL, 2GL, 3GL, 4GL, or 5GL) such as, for example, machine language that may be directly executed by the processor, or assembly language, object-oriented programming (OOP), scripting languages, microcode, etc., that may be compiled or assembled into machine readable instructions and stored on the one or more memory modules  106 . Alternatively, the machine readable instructions may be written in a hardware description language (HDL), such as logic implemented via either a field-programmable gate array (FPGA) configuration or an application-specific integrated circuit (ASIC), or their equivalents. Accordingly, the methods described herein may be implemented in any conventional computer programming language, as pre-programmed hardware elements, or as a combination of hardware and software components. 
     As depicted in  FIG. 1 , the surface analysis system  100  may include a reference model library  125 , which may be stored in the one or more memory modules  106 . The reference model library  125  may store one or more reference models corresponding with a multi-part assembly  160  ( FIGS. 2 and 3 ). The reference models stored within the reference model library  125  may comprise two-dimensional reference models (e.g., drawings) and three dimensional reference models. Further, the reference models stored within the reference model library  125  may comprise reference models of both the multi-part assembly  160  and individual parts  162  ( FIGS. 2 and 3 ) of the multi-part assembly  160 . Further, reference models, for example, comparator surface reference models  180  ( FIG. 4 ) generated by the surface analysis system  100  may be stored in the reference model library  125 . In operation, reference models, such as the comparator surface reference model  180 , may be compared with various iterations of the multi-part assembly  160 , for example, compared with part models of one or more parts  162  of the various iterations of the multi-part assembly  160  generated by scanning the part  162 , for example, using a scanner  111 . As used herein “iterations” of the multi-part assembly  160  reference to multiple versions or copies of the same multi-part assembly  160 . For example, when the multi-part assembly  160  comprises a vehicle  150  ( FIG. 2 ), each iteration of the vehicle  150  refers to a single vehicle and multiple iterations refer to multiples of the same vehicle  150 , e.g., the same make and model of the vehicle  150 . 
     Referring still to  FIG. 1 , the surface analysis system  100  includes one or more scanners  111  communicatively coupled to the one or more processors  102 . The one or more scanners  111  are configured to capture surface data from real-world surfaces, such as surfaces  170  ( FIGS. 2 and 3 ) of the multi-part assembly  160 . The surface data may comprise surface contour data. In some embodiments, the one or more scanners  111  may comprise three-dimensional scanners, two-dimensional scanners, or a combination thereof. As a non-limiting example, the one or more scanners  111  may capture surface contour data from one or more surfaces of a vehicle  150  ( FIG. 2 ). The one or more scanners  111  generally capture surface contour data by scanning the targeted surfaces with a scanning sensor (e.g. an optical sensor, a laser, a radar array, or a LiDAR array). From the surface contour data, the one or more processors  102  may execute point cloud logic or other scanning logic to generate a part model of the one or more parts  162  of the multi-part assembly  160 . In operation, the part models generated by scanning the one or more surfaces  170  of the parts  162  with the scanners  111  may be compared to the reference models of the reference model library  125 , for example, the comparator surface reference model  180 . 
     Referring still to  FIG. 1 , the surface analysis system  100  comprises a display  108  for providing visual output such as, visual depictions of scanned parts, part models, reference models, or the like. The display  108  is coupled to the communication path  104 . Accordingly, the communication path  104  communicatively couples the display  108  to other components of the surface analysis system  100 . The display  108  may include any medium capable of transmitting an optical output such as, for example, a cathode ray tube, light emitting diodes, a liquid crystal display, a plasma display, or the like. In some embodiments, the display  108  may comprise a display of the computing device  105 . Moreover, the display  108  may be a touchscreen that, in addition to providing optical information, detects the presence and location of a tactile input upon a surface of or adjacent to the display. Accordingly, each display may receive mechanical input directly upon the optical output provided by the display. 
     The surface analysis system  100  may further comprise tactile input hardware  110  coupled to the communication path  104  such that the communication path  104  communicatively couples the tactile input hardware  110  to other components of surface analysis system  100 . The tactile input hardware  110  may be any device capable of transforming mechanical, optical, or electrical signals into a data signal capable of being transmitted with the communication path  104 . Specifically, the tactile input hardware  110  may include any number of movable objects that each transform physical motion into a data signal that can be transmitted to over the communication path  104  such as, for example, a button, a switch, a knob, a microphone or the like. Further, in some embodiments, the tactile input hardware  110  may be integrated with and/or connected to the computing device  105 . 
     Referring now to  FIGS. 1 and 2 , the surface analysis system  100  further comprises one or more sensors  112 , for example, one or more of an image sensor  114 , a proximity sensor  116 , and/or a motion capture sensor  118 . In operation, each of the one or more sensors  112  may be configured to generate data regarding a location (e.g., a spatial location) and, in some embodiments, an orientation of an object, for example, a head  122  of an observer  120  positioned in an observation environment  130 . In some embodiments, the surface analysis system  100  may further comprise one or more tracking markers  115  configured to be worn by the observer  120 . In operation, the one or more tracking markers  115  may interact with the one or more sensors  112  to generate data regarding a location and/or orientation of the observer  120  (e.g., the head  122  of the observer  120 ). 
     The image sensor  114  is coupled to the communication path  104  such that the communication path  104  communicatively couples the image sensor  114  to other components of the surface analysis system  100 . The image sensor  114  may comprise any imaging device configured to capture image data of the observation environment  130  and the observer  120  positioned in the observation environment  130 . The image data may digitally represent at least a portion of the observation environment  130  or the observer  120 , for example, the head  122  of the observer  120 . In operation, the image sensor  114  may interact with the one or more tracking markers  115  when the one or more tracking markers  115  are worn by the observer  120 , to determine the location of the observer  120  (e.g., the spatial location of the head  122  of the observer  120 ) and, in some embodiments, the orientation of the head  122  of the observer  120  (e.g., a pointing direction of a face  124  of the observer  120 ). 
     The image sensor  114  may comprise any sensor operable to capture image data, such as, without limitation, a charged-coupled device image sensors or complementary metal-oxide-semiconductor sensors capable of detecting optical radiation having wavelengths in the visual spectrum, for example. The image sensor  114  may be configured to detect optical radiation in wavelengths outside of the visual spectrum, such as wavelengths within the infrared spectrum. In some embodiments, two or more image sensors  114  are provided to generate stereo image data capable of capturing depth information. Moreover, in some embodiments, the image sensor  114  may comprise a camera, which may be any device having an array of sensing devices (e.g., pixels) capable of detecting radiation in an ultraviolet wavelength band, a visible light wavelength band, or an infrared wavelength band. 
     Still referring to  FIGS. 1 and 2 , the proximity sensor  116  is communicatively coupled to the communication path  104  such that the communication path  104  communicatively couples the proximity sensor  116  to other components of the surface analysis system  100 . The proximity sensor  116  may be any device capable of outputting a proximity signal indicative of a proximity of an object to the proximity sensor  116 . In some embodiments, the proximity sensor  116  may include a laser scanner, a capacitive displacement sensor, a Doppler effect sensor, an eddy-current sensor, an ultrasonic sensor, a magnetic sensor, an optical sensor, a radar sensor, a sonar sensor, or the like. Some embodiments may not include the proximity sensor  116 . In operation, the proximity signal may be used to determine the location of the observer  120  and in some embodiments, the orientation of the observer  120 . For example, the proximity sensor  116  may interact with the one or more tracking markers  115  when the one or more tracking markers  115  are worn by the observer  120 , to determine the location of the observer  120  (e.g., the spatial location of the head  122  of the observer  120 ) and, in some embodiments, the orientation of the head  122  of the observer  120  (e.g., the pointing direction of the face  124  of the observer  120 ). 
     Further, the motion capture sensor  118  is communicatively coupled to the communication path  104  such that the communication path  104  communicatively couples the motion capture sensor  118  to other components of the surface analysis system  100 . The motion capture sensor  118  comprises one or more sensors that are wearable by the observer  120  and are configured to measure the spatial location and/or the orientation of the observer  120 . For example, the motion capture sensor  118  may comprise an inertial sensor having an inertial measurement unit (IMU). For example, the IMU may include a gyroscope, a magnetometer, and an accelerometer. Further, the motion capture sensor  118  may comprise one or more RF sensors configured to transmit an RF signal regarding the spatial location and/or orientation of the head  122  of the observer  120 . Moreover, the motion capture sensor  118  may comprise one or more magnetic sensors configured to transmit a magnetic signal regarding the spatial location and/or orientation of the head  122  of the observer  120 . 
     As depicted in  FIG. 2 , the one or more sensors  112  and/or one or more tracking markers  115  may be coupled to a wearable device  140  configured to be worn by the observer  120 , for example, eyeglasses  142 , headwear  144 , or any other wearable device configured to monitor the position and/or orientation of the head  122  of the observer  120 . Further, the one or more tracking markers  115  may be directly coupled to the observer  120 , for example, using an adhesive or a fastening mechanism. As a non-limiting example, the one or more sensors  112 , for example, image sensors  114  and/or proximity sensors  116  may be positioned in the observation environment  130  apart from the observer  120  and the one or more tracking markers  115  may be positioned on the head  122  of the observer  120  using the wearable device  140  or by directly coupling the one or more tracking markers  115  to the head  122  of the observer  120 . As another non-limiting example, the motion capture sensors  118  may be coupled to the observer  120  and/or the wearable device  140  and may measure the location and/or orientation of the head of the observer  120  without use of additional sensors  112 . In operation, the sensors  112  may monitor the observer  120 , for example, by monitoring the tracking markers  115  and may generate sensor data regarding the location and or orientation of the head of the observer  120 . 
     Still referring to  FIG. 2 , an example multi-part assembly  160  comprising a vehicle  150  is depicted. The multi-part assembly  160  may be positioned in the observation environment  130 . The multi-part assembly  160  (e.g., the vehicle  150 ) includes one or more parts  162  each comprising one or more surfaces  170 . For example, the one or more parts  162  may comprise one or more vehicle parts positioned in the interior of the vehicle  150 , such as a seat  154 , a dashboard  158 , a steering wheel  152 , a central storage console  155 , one or more interior panels, a vehicle floor, or the like. Further, the one or more parts  162  may comprise one or more exterior vehicle parts, for example, one or more exterior vehicle panels. While the multi-part assembly  160  is described herein as comprising the vehicle  150  and the one or more surfaces  170  are described as vehicle part surfaces, it should be understood that the surface analysis system  100  may analyze surfaces in any multi-part assembly  160 . 
     Referring also to  FIG. 3 , a cross-section of two parts  162  of the multi-part assembly  160  is depicted, for example, a first part  164  and a second part  166 . The first part  164  and the second part  166  may comprise any two parts of the multi-part assembly  160 , such as adjacent parts. As an example, the first part  164  and the second part  166  may comprise two panel portions of the dashboard  158  the vehicle  150 . Further, the first part  164  and the second part  166  may be located in the observation environment  130 , which comprises one or more discrete observation locations  135 . The one or more discrete observation locations  135  are locations within the observation environment  130  from which the observer  120  may view the multi-part assembly  160 . When the multi-part assembly  160  comprises the vehicle  150  of  FIG. 2 , the one or more discrete observation locations  135  may comprise any location within the vehicle  150  or outside the vehicle  150 , where the head  122  of the observer  120  may be located. 
     Referring still to  FIG. 3 , the parts  162  of the multi-part assembly  160  may each comprise one or more visible surface segments  172  and/or one or more hidden surface segments  174 . The one or more visible surface segments  172  are segments of the one or more surfaces  170  that are positioned unobstructed from at least one discrete observation point  135  within the observation environment  130 . The one or more hidden surface segments  174  are segments of the one or more surfaces  170  of that are not visible to the observer  120  and may be obstructed from each discrete observation point  135 . For example, the one or more hidden surface segments  174  may comprise surface segments that face away from the one or more discrete observation points  135  and/or surface segments that are blocked from view from the one or more discrete observation points  135 , e.g., by other parts  162 . The visible surface segments  172  and the hidden surface segments  174  may comprise any length. Further, an individual part  162  may comprise both visible surface segments  172  and hidden surface segments  174 . For example, the first part  164  comprises first visible surface segments  172   a  and first hidden surface segments  174   a.  Further, the second part  166  comprises second visible surface segments  172   b  and second hidden surface segments  174   b.  In  FIG. 3 , the visible surface segments  172  are depicted with a dot-dash crosshatch pattern and the hidden surface segments  174  are depicted with a standard crosshatch pattern. 
     Further, portions of the hidden surface segments  174  may include interacting hidden surface segments  176  that are positioned unobstructed from an adjacent part  162 . For example, first interacting hidden surface segments  176   a  of the first part  164  comprise portions of the first hidden surface segments  174   a  of the first part  164  that face the second part  166  without any obstructions positioned therebetween. Further, second interacting hidden surface segments  176   b  of the second part  166  comprise portions of the second hidden surface segments  174   b  of the second part  166  that face the first part  164  without any obstructions positioned therebetween. In some embodiments, as described below, the surface analysis system  100  may scan the first part  164  and the second part  166  using the scanner  111  to generate one or more part models of the first part  164  and the second part  166 . It is noted that in some embodiments, the one or more processors  102  execute scanning logic to cause the one or more scanners  111  to scan the first part  164  and the second part  166 . In other embodiments, the first part  164  and the second part  166  may be manually scanned with the one or more scanners  111 . In operation, to determine which of the hidden surface segments  174  comprise interacting hidden surface segments  176 , the surface analysis system  100  may generate one or more visibility polygons extending from the one or more portions along the hidden surface segments  174 . Moreover, information regarding the interacting hidden surface segments  176  may be stored in the one or more memory modules  106 . 
     Referring now to  FIG. 3 , the multi-part assembly  160  further comprises segment spacing distances D extending between hidden surface segments  174  and parts  162  positioned adjacent the hidden surface segments  174 . For example, the segment spacing distances D may extend between the first hidden surface segments  174   a  of the first part  164  and the second hidden surface segments  174   b  of the second part  166 . Further, the individual spacing distances D may extend between a discrete measurement location  175  of the first hidden surface segment  174   a  of the first part  164  and a corresponding discrete measurement location  175 ′ of the second hidden surface segment  174   b  of the second part  166 . Each segment spacing distance D may extend orthogonal from the discrete measurement location  175  of the hidden surface segment  174  of the first part  164  and the corresponding discrete measurement location  175 ′ of the second part  166 . Further, in some embodiments, the segment spacing distances D may extend outward from each discrete measurement location  175  in a plurality of directions. 
     As a non-limiting example,  FIG. 3  depicts three segment spacing distances D extending between three discrete measurement locations  175 ,  175 ′ of the first part  164  and the second part  166 . A first segment spacing distance D 1  extends between a first discrete measurement location  175   a  of the first part  164  and a first corresponding discrete measurement location  175   a ′ of the second part  166 . A second segment spacing distance D 2  extends between a second discrete measurement location  175   b  of the first part  164  and a second corresponding discrete measurement location  175   b ′ of the second part  166 . Further, a third segment spacing distance D 3  extends between a third discrete measurement location  175   c  and a third corresponding discrete measurement location  175   c ′ of the second part  166 . While the segment spacing distance D is depicted at three discrete measurement locations  175 ,  175 ′, it may be desired to determine the segment spacing distance D along a continuous length of each of the hidden surface segments  174 . 
     Referring now to  FIG. 4 , an example comparator surface reference model  180  of the multi-part assembly  160  is depicted. The comparator surface reference model  180  comprises a first comparator reference surface  182  corresponding with surfaces  170  of the first part  164  and a second comparator reference surface  184  corresponding with the surfaces  170  of the second part  166 . In particular, the comparator surface reference model  180  is a reference model of one or more comparator surfaces of the multi-part assembly  160 . Comparator surfaces are a subset of the surfaces  170  of the multi-part assembly  160  that meet preset criteria. For example, the comparator surfaces may comprise the visible surface segments  172  of the one or more parts  162  of the multi-part assembly  160  and interacting hidden surface segments  176  of the hidden surface segments  174  that comprise a segment spacing distance D that is less than a threshold segment spacing distance. In operation, when comparing the multi-part assembly  160  to a reference model, it may be efficient to generate comparator surface reference models  180  of the multi-part assembly  160  that comprise comparator reference surfaces  182 ,  184  corresponding with the surfaces  170  of the multi-part assembly  160  that meet the criteria of a comparator surface. Moreover, it may be efficient to compare only a portion of the surfaces  170  of the multi-part assembly  160  to the reference model, for example, compare only the surfaces  170  of the multi-part assembly  160  that meet the criteria of a comparator surface with the reference model. 
     Referring also to  FIG. 5  a flow chart  10  depicting a method for generating the comparator surface reference model  180  of the multi-part assembly  160  is illustrated. The flow chart  10  depicts a number of method steps illustrated by boxes  12 - 20 . Though the method is described below with respect to the first part  164  and the second part  166 , the method may be used to generate comparator surface reference models  180  of any multi-part assembly  160  having any number of parts  162 . Further, while the steps of the method are described below in a particular order, it should be understood that other orders are contemplated. 
     Referring now to  FIGS. 1-5 , at box  12 , the method for generating the comparator surface reference model  180  includes first identifying one or more visible surface segments  172 . In some embodiments, the one or more visible surface segments  172  may be identified by monitoring the observer  120  positioned in the observation environment  130  using the one or more sensors  112 . As depicted in  FIG. 2 , the observer  120  may be the driver  121  of the vehicle  150  or the passenger  123  of the vehicle  150 . In operation, the one or more sensors  112  may monitor the observer  120  for an observation period, measure one or more locations of the head  122  of the observer  120  within the observation environment  130  and, in some embodiments, measure the orientation of the head  122  of the observer  120  within the observation environment  130 . Each measured location of the head  122  of the observer  120  may correspond with an individual discrete observation point  135  within the observation environment  130 . 
     Using this head location data, the one or more processors  102  may identify the visible surface segments  172 . In particular, the visible surface segments  172  comprise the surfaces  170  of the one or more parts  162  that are positioned unobstructed from at least one discrete observation point  135 . Non-limiting example methods and systems for identifying the one or more visible surface segments  172  are described in U.S. application Ser. No. 15/221,012 titled “Surface Analysis Systems and Methods of Identifying Visible Surfaces Using the Same,” filed Jul. 27, 2016, hereby incorporated by reference. 
     In some embodiments, the visible surface segments  172  may be identified based on surface data stored in the one or more memory modules  106 . The visible surface segments  172  may also be identified based on user input received by the tactile input hardware  110 . Further, the visible surface segments  172  may be identified by the one or more sensors  112  without monitoring the observer  120 . For example, the one or more sensors  112  may scan or otherwise generate surface data of the multi-part assembly  160  based on sensor signals and output sensor data to the one or more processors  102 . The one or more processors  102  may use the sensor data to determine the one or more visible surface segments  172 . The remaining surfaces  170  of the first part  164  and the second part  166  comprise the one or more hidden surface segments  176 . 
     Next, at box  14 , the surface analysis system  100  may determine the segment spacing distance D between the one or more hidden surface segments  174  of the first part  164  and the second part  166 . For example, by scanning each part  162  with the scanner  111  to generate a part model of each part  162  and/or by accessing data regarding the one or more parts  162  stored in the one or more memory modules  106 . The segment spacing distance D may be measured and determined at the plurality of discrete measurement locations  175 ,  175 ′, which may be spaced along the surfaces  170  of the first part  164  and the second part  166  between about 0.05 mm and about 10 cm apart. In some embodiments, the segment spacing distance D may be measured along a continuous length of each of the hidden surface segments  174 . Further, the segment spacing distance D, for example, the first segment spacing distance D 1 , the second segment spacing distance D 2 , and the third segment spacing distances D 3 , may be compared to the threshold segment spacing distance. The threshold spacing distance may be preset and stored in the one or more memory modules  106 . The threshold segment spacing distance may comprise any preset distance, for example, between about 0.05 cm and about 50 cm, for example, 0.1 cm 0.25 cm, 0.5 cm, 0.75 cm, 1 cm, 2 cm, 5 cm, 10 cm, 25 cm, or the like. For example, in some embodiments, the threshold spacing distance may comprise less than about 10 cm, less than about 5 cm, less than about 2 cm, less than about 1 cm, less than 0.5 cm, less than 0.1 cm or the like. 
     Next, at box  16  the surface analysis system  100  may classify segments of the surfaces  170  as comparator surfaces. In particular, the surface analysis system  100  may classify the one or more visible surface segments  172  as comparator surfaces, for example, the first visible surface segments  172   a  of the first part  164  and the second visible surface segments  172   b  of the second part  166 . Further, the surface analysis system  100  may classify the one or more hidden surface segments  174  that are positioned unobstructed from an adjacent part (e.g., interacting hidden surface segments  176   a,    176   b  of the first part  164  and the second part  166 ) and comprise a segment spacing distance D that is less than or equal to the threshold spacing distance, as comparator surfaces. In the example depicted in  FIG. 3 , the first segment spacing distance D 1  and the second segment spacing distance D 2  are less than the threshold spacing distance and the third segment spacing distance D 3  is greater than the threshold spacing distance. As such, the hidden surface segments  174  at the first discrete measurement locations  175   a    175   a ′ of the first part  164  and the second part  166  are comparator surfaces and the hidden surface segments  174  at the second discrete measurement locations  175   b,    175   b ′ of the first part  164  and the second part  166  are classified as comparator surfaces. However, hidden surface segments  174  at the third discrete measurement locations  175   c    175   c ′ of the first part  164  and the second part  166  are not classified as comparator surfaces. 
     At box  18 , surface analysis system  100  may generate a comparator surface reference model  180  corresponding with the multi-part assembly  160 . As depicted in  FIG. 4 , the comparator surface reference model  180  comprises a first comparator reference surface  182  corresponding with the comparator surfaces of the first part  164  and a second comparator reference surface  184  corresponding with the comparator surfaces of the second part  166 . In some embodiments, the comparator surface reference model  180  comprises a two-dimensional representation of the comparator surfaces of the multi-part assembly  160  and in other embodiments, the comparator surface reference model  180  comprises a three-dimensional representation of the comparator surfaces of the multi-part assembly  160 . 
     Further, at box  20 , the surface analysis system  100  may use the comparator surface reference model  180  to analyze additional multi-part assemblies  160 . In operation, the surface analysis system  100  may compare the comparator surface reference model  180  of the multi-part assembly  160  with additional iterations of the multi-part assembly  160 , for example, to determine one or more offsets  265  ( FIGS. 6 and 7 ) between each multi-part assembly  160  and the comparator surface reference model  180 . This comparison may be used for quality control. Referring now to  FIGS. 6 and 7 , a second multi-part assembly  260  comprising one or more parts  262  including a first part  264  and a second part  266  is depicted. The second multi-part assembly  260  comprises an additional iteration of the multi-part assembly  160  of  FIG. 3 . Further, as depicted in  FIG. 6 , the second multi-part assembly  260  may comprise the one or more offsets  265 , which comprise one or more segments of the surface of the first part  264  and/or the second part  266  that deviate from the reference model of the multi-part assembly  160 , for example, the comparator surface reference model  180 . The one or more offsets  265  may be indicative of one or more flaws in the second multi-part assembly  260 . While the one or more offsets  265  are described with respect to the example second multi-part assembly  260 , it should be understood that any iteration of the multi-part assembly  160  may comprise the one or more offsets  265 . 
     In operation, the first part  264  and the second part  266  of the second multi-part assembly  260  may be scanned using the scanner  111  to generate scanning data, which may be output to the one or more processors  102 . As depicted in  FIG. 7 , based on the scanning data, the one or more processors  102  may generate a first part model  294  of the first part  264  and a second part model  296  of the second part  266 . Further, the surface analysis system  100  may compare the first part model  294  and the second part model  296  with the comparator surface reference model  180  to determine the one or more offsets  265  between the second multi-part assembly  260  and the comparator surface reference model  180 . In some embodiments, the surface analysis system  100  may also determine a maximum deviation E of each of the one or more offsets  265 . 
     Referring now to  FIG. 8 , a flow chart  50  depicting a method for comparing the one or more surfaces  170  of the multi-part assembly  160  with a reference model is illustrated. The flow chart  50  depicts a number of method steps illustrated by boxes  52 - 58 . In the method depicted by flow chart  50 , the surface analysis system  100  may determine the surfaces  170  of the multi-part assembly  160  to identify and classify as comparator surfaces, using the methods and criteria described above with respect to the flow chart  10  of  FIG. 5 . Once the comparator surfaces have been identified, the comparator surfaces may be compared to a reference model of the multi-part assembly  160 , for example, a reference model of the full multi-part assembly  160 . 
     At box  52 , the method includes first identifying one or more visible surface segments  172 , as described above with respect to  FIG. 5 . Next, at box  54 , the surface analysis system  100  may determine the segment spacing distance D between the one or more hidden surface segments  174  of the first part  164  and the second part  166 , as described above with respect to  FIG. 5 . At box  56 , the segment spacing distance D may be compared to the threshold segment spacing distance. Next, the surface analysis system  100  may classify the visible surface segments  172  and the one or more hidden surface segments  174  that are positioned unobstructed from an adjacent part (e.g., interacting hidden surface segments  176   a,    176   b  of the first part  164  and the second part  166 ) and comprise a segment spacing distance D that is less than or equal to the threshold spacing distance, as comparator surfaces. 
     Further, at box  58 , the surface analysis system  100 , for example, the one or more processors  102 , may compare the surfaces  170  that meet the criteria of comparator surfaces, (e.g., the visible surface segments  172  and the hidden surface segments  174  that are unobstructed from an adjacent part  162  and have a segment spacing distance D that is less than or equal to the threshold spacing distance) with the reference model, for example, a reference model of the full multi-part assembly  160 . In some embodiments, part models of the surfaces  170  that meet the criteria of comparator surfaces may be generated, for example, using the scanner  111 , and these part models may be compared with the reference model of the full multi-part assembly  160  to determine the one or more offsets  265  between the surfaces  170  of the multi-part assembly  160  classified as comparator surfaces and the reference model. In this method, instead of generating the comparator surface reference model  180  to increase quality control efficiency, the surface analysis system  100  compares the surfaces  170  of the multi-part assembly  160  that are classified as comparator surfaces with the reference model of the full multi-part assembly  160  to provide a different method of increasing quality control efficiency. 
     It should be understood that embodiments described herein provide for surface analysis systems and methods for a comparator surface reference model corresponding with the one or more comparator surfaces of a multi-part assembly. In operation, the surface analysis system may identify one or more visible surface segments of a first part of a multi-part assembly and classify the one or more visible surface segments as comparator surfaces. The surface analysis system may also classify one or more hidden surface segments positioned unobstructed from an adjacent part and comprising a segment spacing distance from the adjacent part as comparator surfaces. Once the comparator surfaces have been identified, the surface analysis system may generate the comparator surface reference model. The comparator surface reference model provides an efficient model for quality control. For example, the surface analysis system may compare additional iterations of the multi-part assembly to the comparator surface reference model to determine deviations between the comparator surface reference model and the additional iterations of the multi-part assembly. 
     It is noted that the terms “substantially” and “about” may be utilized herein to represent the inherent degree of uncertainty that may be attributed to any quantitative comparison, value, measurement, or other representation. These terms are also utilized herein to represent the degree by which a quantitative representation may vary from a stated reference without resulting in a change in the basic function of the subject matter at issue. 
     While particular embodiments have been illustrated and described herein, it should be understood that various other changes and modifications may be made without departing from the spirit and scope of the claimed subject matter. Moreover, although various aspects of the claimed subject matter have been described herein, such aspects need not be utilized in combination. It is therefore intended that the appended claims cover all such changes and modifications that are within the scope of the claimed subject matter.