Abstract:
Methods and systems for weight-based identification of three dimensional (3D) printed parts. Various embodiments disclosed herein may permit reliable processing of 3D printed parts to effectively scale a 3D printing service to large volumes of orders for 3D printed parts.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 13/708,135, titled “WEIGHT-BASED IDENTIFICATION OF THREE DIMENSIONAL PRINTED PARTS,” filed on Dec. 7, 2012, which is a continuation of U.S. patent application Ser. No. 13/455,286 titled “WEIGHT-BASED IDENTIFICATION OF THREE DIMENSIONAL PRINTED PARTS,” filed on Apr. 25, 2012, each of which is hereby incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     1. Field of the Disclosure 
     The present disclosure relates generally to three dimensional (3D) printing and processing of 3D printed parts. More specifically, embodiments of this disclosure relate to methods and systems for identification of 3D printed parts. 
     2. Description of Background 
     3D printing generally refers to the process of creating a 3D part from a 3D model by printing material layers to create the 3D part. A 3D model from which a 3D part is printed may be any 3D-printable digital model such as a computer-aided design (CAD) model. On-demand 3D printing of custom 3D models has become possible in recent years. For example, there are online services that offer custom 3D printing services. For instance, the online provider Shapeways provides custom 3D printing services wherein customers may upload custom 3D models, select materials and order 3D printed parts to be built from the selected materials. 
     SUMMARY OF INVENTION 
     In a typical on-demand 3D printing process, a 3D model, such as a custom model uploaded by a customer submitting an order, may be assigned to a manufacturer based on the ordered material, shipping location of the customer and available capacity at the manufacturer. The manufacturer may analyze the 3D model to determine whether it is 3D-printable. If the model is printable on a 3D printer, the manufacturer may accept the 3D model and queue it for production planning. Production planning plans 3D print runs, i.e. the build of 3D models. After production planning, one or more 3D parts based on the 3D model may be scheduled to be built inside a tray. Other 3D parts to be built based on other 3D models may also be assigned to the same tray. For example, a tray may be used to build 50-800 3D parts from various 3D models. The tray is then assigned to a 3D printer. After 3D printing, the tray contains multiple 3D printed parts, and these 3D parts may correspond to different 3D models and may also correspond to different customer orders. Therefore, each of the 3D printed parts in a typical tray must be identified so that the parts may be correctly distributed and shipped to customers. As the demand for 3D printing services continues to grow, manufacturers of 3D printed parts need to efficiently process large numbers of 3D printed parts. The identification of a 3D printed part may be achieved by identifying the corresponding 3D model which was used to print that part, thereby matching the 3D printed part with the corresponding 3D model. The process of identifying 3D printed parts within each tray used for 3D printing may be referred to as tray sorting. 
     Tray sorting is particularly challenging when large numbers of 3D printed parts are to be identified. Typically, an operator of the manufacturing facility identifies each 3D printed part within a tray based on a contact sheet made for that tray. A contact sheet is made per tray that is to be sorted. The contact sheet for a tray may include images associated with 3D models assigned to that tray, i.e. 3D models used to build the 3D parts in that tray. The operator identifies each 3D printed part by visually matching the part to an image listed on the contact sheet. 
     The contact sheet may also include a barcode associated with each 3D model. Upon identifying a 3D printed part, the operator may scan a barcode associated with the matching 3D model for that part, so as to update the status of the part in a computer system and to generate an order card for that part. 
     According to one aspect of the invention, it is appreciated that approaches of identifying 3D printed parts is both time consuming and unreliable. For example, a large number of images corresponding to a large number of 3D models may be listed on the contact sheet, thereby making it difficult for the operator to quickly and reliably identify the correct match for a given 3D printed part. Therefore, there is a need to identify 3D printed parts efficiently and reliably in order to effectively scale a 3D printing service to process large volumes of orders for 3D printed parts. 
     Aspects and embodiments disclosed herein are directed to providing methods and systems for weight-based identification of 3D printed parts. Various embodiments of the present invention relate to methods and systems that enable efficient and reliable identification of 3D printed parts. Some embodiments may be implemented on a computer system and may provide a convenient user interface to an operator of a manufacturing facility that supplies large quantities of 3D printed parts. According to some embodiments, a system may automatically select a subset of 3D models that may match a 3D printed part based on the weight of the part and theoretical weights computed for each 3D model based on the volume of the 3D model and the density of the material used to print the part. Compared to the typical process where the operator uses a contact sheet to identify the 3D printed parts, some methods and systems of the present disclosure may speed up the process of identifying the parts and increase the identification reliability. 
     One aspect of the present disclosure is directed to providing a computer-implemented method for weight-based identification of a three dimensional (3D) printed part, the 3D printed part being printed from a 3D model using a preselected material, the method comprising acts of receiving, by a computer system, an indication of a weight of the 3D printed part; calculating, by the computer system, a plurality of theoretical weights for a plurality of 3D models, each theoretical weight being calculated for a respective 3D model based on a volume of the respective 3D model and a density of the preselected material; comparing the indication of the weight to the plurality of theoretical weights; and selecting a subset of the plurality of 3D models based on a result of the comparing act, the subset having a size less than a total number of the plurality of 3D models. In one embodiment, the act of selecting a subset may further include an act of selecting a 3D model to include in the subset responsive to an act of determining that a deviation of the theoretical weight of the 3D model from the indication of the weight of the 3D printed part does not exceed a predetermined threshold value. In one embodiment, the method may further comprise an act of sorting the subset based on a respective value of deviation of a respective theoretical weight of each 3D model within the subset from the indication of the weight of the 3D printed part. In one embodiment, the method may further comprise an act of receiving the size of the subset. 
     In one embodiment, the method may further comprise acts of outputting the subset and receiving a selection of the 3D model corresponding to the 3D printed part from the subset. In one embodiment, the method may further comprise generating a label for the 3D printed part based on the selection of the 3D model. The label may include at least one of a barcode, a model number of the 3D model and an order number for the 3D printed part. 
     In one embodiment, the method may further comprise acts of receiving a selection of a tray, the 3D printed part being one of a plurality of 3D printed parts built inside the tray, and selecting the plurality of 3D models based on the selection of the tray. The method may further comprise removing a 3D model corresponding to an identified 3D printed part from the plurality of 3D models. 
     Another aspect of the present disclosure is directed to providing a system for weight-based identification of a three dimensional (3D) printed part, the 3D printed part being printed from a 3D model using a preselected material, the system comprising a memory; and a processing unit coupled to the memory, wherein the processing unit is operative to receive an indication of a weight of the 3D printed part; calculate a plurality of theoretical weights for a plurality of 3D models, each theoretical weight being calculated for a respective 3D model based on a volume of the respective 3D model and a density of the preselected material; compare the indication of the weight to the plurality of theoretical weights; and select a subset of the plurality of 3D models in response to comparing the indication of the weight to the plurality of theoretical weights, the subset having a size less than a total number of the plurality of 3D models. In one embodiment, the processing unit being operative to select a subset further includes the processing unit being operative to select a 3D model for inclusion in the subset responsive to a determination that a deviation of the theoretical weight of the 3D model from the indication of the weight of the 3D printed part does not exceed a predetermined threshold value. In one embodiment, the processing unit is further operative to sort the subset based on a respective value of deviation of a respective theoretical weight of each 3D model within the subset from the indication of the weight of the 3D printed part. In one embodiment, the processing unit is further operative to receive the size of the subset. 
     In one embodiment, the processing unit is further operative to output the subset and receive a selection of the 3D model corresponding to the 3D printed part from the subset. In one embodiment, the system may further comprise a printer configured to print a label for the 3D printed part based on the selection of the 3D model. 
     In one embodiment, the processing unit is further operative to receive a selection of a tray, the 3D printed part being one of a plurality of 3D printed parts built inside the tray, and select the plurality of 3D models based on the selection of the tray. In one embodiment, the processing unit is further operative to remove a 3D model corresponding to an identified 3D printed part from the plurality of 3D models. 
     Another aspect of the present disclosure is directed to providing a computer-readable storage medium that stores a set of instructions which when executed perform a method for weight-based identification of a three dimensional (3D) printed part, the 3D printed part being printed from a 3D model using a preselected material, the method executed by the set of instructions comprising receiving an indication of a weight of the 3D printed part; calculating a plurality of theoretical weights for a plurality of 3D models, each theoretical weight being calculated for a respective 3D model based on a volume of the respective 3D model and a density of the preselected material; comparing the indication of the weight to the plurality of theoretical weights; and selecting a subset of the plurality of 3D models based on a result of comparing, the subset having a size less than a total number of the plurality of 3D models. 
     Another aspect of the present disclosure is directed to providing a method for weight-based identification of a three dimensional (3D) printed part, the 3D printed part being printed from a 3D model using a preselected material, the method comprising acts of weighing the 3D printed part to generate an indication of a weight of the 3D printed part; calculating a plurality of theoretical weights for a plurality of 3D models, each theoretical weight being calculated for a respective 3D model based on a volume of the respective 3D model and a density of the preselected material; comparing the indication of the weight to the plurality of theoretical weights; and selecting a subset of the plurality of 3D models based on a result of the comparing act, the subset having a size less than a total number of the plurality of 3D models. In one embodiment, the selecting act further includes an act of selecting the subset responsive to an act of determining that a deviation of a theoretical weight of a 3D model from the indication of the weight of the 3D printed part does not exceed a predetermined threshold value. The method may further comprise an act of sorting the subset based on a respective value of deviation of a respective theoretical weight of each 3D model within the subset from the indication of the weight of the 3D printed part. The method may further comprise an act of selecting the size of the subset. 
     In one embodiment, the method may further comprise an act of cleaning the 3D printed part prior to the weighing act. In one embodiment, the 3D printed part may be one of a plurality of 3D printed parts built inside a tray, the plurality of 3D models corresponding to the plurality of 3D printed parts built inside the tray. 
     In one embodiment, the method may further comprise an act of identifying the 3D model corresponding to the 3D printed part from the subset of the plurality of 3D models. In one embodiment, the identifying act may further include an act of visually comparing at least one 3D model in the subset to the 3D printed part. In one embodiment, the method may further comprise an act of adding a label to the 3D printed part following the identifying act. The method may further comprise an act of routing the 3D printed part to one or more locations in response to the identifying act. 
     Still other aspects, embodiments, and advantages of these exemplary aspects and embodiments are discussed in detail below. Embodiments disclosed herein may be combined with other embodiments in any manner consistent with at least one of the principles disclosed herein, and references to “an embodiment,” “some embodiments,” “an alternate embodiment,” “various embodiments,” “one embodiment” or the like are not necessarily mutually exclusive and are intended to indicate that a particular feature, structure, or characteristic described may be included in at least one embodiment. The appearances of such terms herein are not necessarily all referring to the same embodiment. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Various aspects of at least one embodiment are discussed below with reference to the accompanying figures, which are not intended to be drawn to scale. The figures are included to provide illustration and a further understanding of the various aspects and embodiments, and are incorporated in and constitute a part of this specification, but are not intended as a definition of the limits of the invention. In the figures, each identical or nearly identical component that is illustrated in various figures is represented by a like numeral. For purposes of clarity, not every component may be labeled in every figure. In the figures: 
         FIG. 1  is a flow chart illustrating an exemplary embodiment of a process for weight-based identification of 3D printed parts according to aspects of the present invention; 
         FIG. 2  is a display illustrating one example of a user interface including a listing of trays in a computer system implementing weight-based identification of 3D printed parts according to aspects of the present invention; 
         FIG. 3  is a display illustrating one example of a user interface for outputting a subset of 3D models in a computer system implementing weight-based identification of 3D printed parts according to aspects of the present invention; 
         FIG. 4  is a display illustrating one example of a user interface for generating an order card in a computer system implementing weight-based identification of 3D printed parts according to aspects of the present invention; 
         FIG. 5  illustrates one example of a label for a 3D printed part according to aspects of the present invention; 
         FIG. 6  is a flow chart illustrating an exemplary process of interacting with a user of the computer implemented user interfaces in  FIGS. 3, 4 and 5 ; 
         FIG. 7  is a block diagram illustrating one example of a general purpose computer system which may execute a software implementing weight-based identification of 3D printed parts according to aspects of the present invention; and 
         FIG. 8  is a diagram illustrating one example of a storage system of the general purpose computer system in  FIG. 7 . 
     
    
    
     DETAILED DESCRIPTION 
     Aspects and embodiments are directed to providing efficient and reliable methods for identification of 3D printed parts based on weight. Other aspects and embodiments are directed to systems that implement identification of 3D printed parts based on weight. Efficiency and reliability may be achieved by providing embodiments that enable automatically selecting a subset of 3D models that may correspond to a 3D printed part, based on the weight of the 3D printed part. 
     It is to be appreciated that embodiments of the methods and apparatuses discussed herein are not limited in application to the details of construction and the arrangement of components set forth in the following description or illustrated in the accompanying drawings. The methods and apparatuses are capable of implementation in other embodiments and of being practiced or of being carried out in various ways. Examples of specific implementations are provided herein for illustrative purposes only and are not intended to be limiting. In particular, acts, elements and features discussed in connection with any one or more embodiments are not intended to be excluded from a similar role in any other embodiment. 
     Also, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. Any references to embodiments or elements or acts of the systems and methods herein referred to in the singular may also embrace embodiments including a plurality of these elements, and any references in plural to any embodiment or element or act herein may also embrace embodiments including only a single element. The use herein of “including,” “comprising,” “having,” “containing,” “involving,” and variations thereof is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. References to “or” may be construed as inclusive so that any terms described using “or” may indicate any of a single, more than one, and all of the described terms. Any references to front and back, left and right, top and bottom, upper and lower, and vertical and horizontal are intended for convenience of description, not to limit the present systems and methods or their components to any one positional or spatial orientation. 
     Referring to  FIG. 1 , there is illustrated one example of a process  100  for weight-based identification of 3D printed parts according to aspects disclosed herein. Process  100  may be fully or partially implemented in a computer system. In one example, process  100  may be executed by a set of instructions that may be stored on a computer readable storage medium. Process  100  may be implemented, for instance, in software, hardware, or combination thereof used by an operator of a manufacturing facility to efficiently identify 3D printed parts. 
     At block  102  of process  100  in  FIG. 1 , a tray to be sorted is selected. Tray sorting generally refers to identifying 3D printed parts in each tray after the parts are built in the tray. The tray may include one or more 3D printed parts built based on one or more 3D models. The one or more 3D printed parts in a tray may also correspond to one or more customer orders. In one example, the tray may be selected by a user or operator and the selection of the tray may be input to the computer system implementing weight-based identification. In some embodiments, selecting a tray at block  102  may include selecting or identifying a material and a density of the material used for 3D printing in that tray. In one embodiment, the computer system may be configured to automatically identify the material and associated density used for 3D printing in a selected tray, for example, by retrieving stored material and associated density corresponding to the selected tray. A list of 3D printing materials may be stored in the computer system. Density may also be stored in the computer system as a material property for each 3D printing material. 
     Still referring to  FIG. 1 , at block  104  of process  100 , theoretical weights may be calculated for one or more 3D models. In the embodiment shown in  FIG. 1 , the 3D models for which theoretical weights are calculated may include all the 3D models assigned to the tray selected at block  102 . A 3D model assigned to a tray may be used to build a corresponding 3D part in that tray. In one embodiment, selecting a tray at block  102  may result in selection of one or more 3D models assigned to the selected tray for use at block  104 . 
     In one practical example, a group of 1000 3D models that are assigned to a single tray selected at block  102  may be selected for use at block  104 . However, the one or more 3D models used at block  104  may generally include any of the 3D models that were used to print 3D parts in any tray. 
     A theoretical weight for a 3D model at block  104  may be calculated by multiplying the volume of the 3D model by the density of the material used to print the 3D model in the selected tray. In one example, the density of the material may be automatically identified upon selecting a tray at block  102 . In one embodiment, block  104  may be performed only once per selected tray. If the selected tray includes 3D parts made from different materials, block  104  may be performed for each 3D printed part based on the density of the material used to print that part. 
     At block  106  of process  100 , a 3D printed part that was built in the selected tray may be weighed. In one example, the 3D printed part may be weighed by using a scale. The 3D printed part is weighed after cleaning the part to eliminate any residual weight. Cleaning may be performed prior to selecting the tray at block  102  or prior to weighing the 3D part at block  106 . In other embodiments, if cleaning does not precede weight-based identification, the process of weight-based identification may compensate for an estimated weight of residue. 
     In one embodiment, a 3D printed part from the selected tray may be weighed by a user or operator and the weight may be input to the computer system implementing weight-based identification. At block  108 , the weight of the 3D printed part may be compared to the theoretical weights calculated for one or more 3D models. In one embodiment, the comparison may include calculating, for each 3D model used at block  104 , a value representing a deviation of the theoretical weight of the 3D model from the weight of the 3D printed part provided at block  106 . In one example, the values may be absolute values. The comparison may further include checking, for each 3D model used at block  104 , whether a value representing a deviation of its theoretical weight from the weight of the 3D printed part is within a predetermined threshold value of deviation from the weight of the 3D printed part. 
     At block  110  of process  100 , a subset of 3D models may be selected from one or more models used at block  104 . The number of 3D models in the subset may be less than the total number of 3D models used at block  104 . The number of 3D models in the subset, i.e. the size of the subset, may be predetermined. In one example, the size may be selected by a user of the weight-based identification process. The subset of 3D models is selected based on comparing, at block  108 , the weight of the 3D printed part with the theoretical weights of one or more 3D models. In one example, a 3D model may be selected for inclusion in the subset of 3D models if a value of deviation of its theoretical weight from the weight of the 3D printed part is within a predetermined threshold value of deviation. 
     In one embodiment, selecting a subset of 3D models in at block  110  may further include sorting the 3D models within the subset. Sorting the subset of 3D models may be included within block  110  or as a separate block of process  100 . In one example, the 3D models in the subset may be sorted based on values of deviation of their respective theoretical weights from the weight of the 3D printed part. For example, the subset may be sorted such that the first 3D model in the sorted subset has the smallest value or amount of deviation from the weight of the 3D printed part, thereby being the closest match to the 3D printed part based on weight. 
     In a computer implementation of process  100 , the selected subset of 3D models may at least partially be output or presented to a user or operator. In one example, a first subset of 3D models may be presented to the user. Upon receiving a request from the user for more 3D models that may match the 3D printed part, a next subset of 3D models may be presented to the user. The user may switch between viewing the different subsets and may select one or more 3D models for viewing. At block  112  of process  100 , the 3D model that corresponds to the 3D printed part is identified. Block  112  may include comparing 3D models in the subset of block  110  to the 3D printed part. In one embodiment, the comparison may include visual comparison to identify the 3D model that matches the 3D printed part. In one example, the subset of 3D models at block  110  may only include a single 3D model, and at block  112 , the selected 3D model may be confirmed to match the 3D printed part. 
     Once the 3D model from which the 3D printed part has been printed is identified at block  112 , a label corresponding to the 3D printed part may be generated at block  114 . The label may include information identifying the 3D printed part. For example, the label may be an order card and may include customer order information, a barcode, the 3D model number that matches the 3D printed part and a code for the material used to print the part (e.g., as shown in  FIG. 5  and discussed further below). 
     The label may also include a storage bin number corresponding to the 3D printed part. Generating the label may include printing the label and may also include affixing or adding the label to the 3D printed part or a packaging thereof. In some embodiments, process  100  may further include removing an identified 3D printed part from the tray and removing a 3D model corresponding to the identified 3D printed part from the set of one or more 3D models used in process  100 . Removing 3D models from the set of one or more 3D models used for weight based identification of 3D printed parts in a tray may increase the efficiency of weight based identification over time. In some embodiments, process  100  may further include updating a status of the 3D printed part. For example, in a computer system implementation, the status of the 3D printed part may be updated to indicate that the part has been identified or to indicate that a label has been printed for the part. The 3D printed part may be routed to one or more locations using the label. For example, the 3D printed part may be routed from the manufacturing facility to a distribution center, where it may be collected along with any other 3D printed parts from the same customer order and shipped to the customer. 
       FIG. 2  illustrates a user interface  120  including a listing of trays in a computer system implementing weight-based identification of 3D printed parts according to aspects of the present disclosure. In one example, interface  120  may be in the form of a table, as shown in  FIG. 2 . The interface may include a listing of trays as shown in column  122 . Column  124  lists a date of 3D printing corresponding to each tray. As shown, the listing of trays in column  122  may be sorted by dates of 3D printing in column  124 . In one example, the last tray emerging from the 3D printing process may be listed first. 
     Column  126  lists number of items corresponding to each tray. In one example, the number of items in a tray may correspond to the number of 3D printed parts built in that tray. In another example, the number of items may correspond to a sum of the quantity of production orders assigned to that tray, where a production order is a request to produce one or more copies of a 3D part from a single 3D model. Column  128  of interface  120  lists a weight-based sorting feature available for trays that are not yet sorted. In one example, a weight-based sorting feature corresponding to a tray may be selected to launch a computer implemented method for weight-based identification of 3D printed parts in the corresponding tray. In another example, a tray may be selected from the listing of trays that are available for weight-based sorting. Selecting a tray may launch another user interface for weight-based identification of 3D printed parts in the selected tray. 
       FIG. 3  illustrates a user interface  130  for weight-based sorting of a selected tray  132 . The tray  132  may be selected using the interface  120  in  FIG. 2 . Interface  130  provides an input cell  134  to receive a value indicative of the weight of the 3D printed part. In one example, an operator may enter the weight of a 3D printed part. In another example, a system including the user interface  130  may be configured to obtain a weight of a 3D printed part. 
     The user interface  130  may provide a button  136  configured to launch weight-based identification of the 3D printed part corresponding to the entered weight. In one embodiment, clicking on button  136  may result in performing process  100  at blocks  106  and  108  in  FIG. 1 . The weight entered in input cell  134  may be compared to one or more of theoretical weights calculated for one or more 3D models assigned to the selected tray  132 . In response to the comparison, a subset of 3D models having theoretical weights that are closest matches to the weight entered in input cell  134  may be selected. Each 3D model in the selected subset may be displayed or output in a respective 3D model window  138  of the user interface  130 . In one example, the 3D model windows  138  may be thumbnails. Each 3D model window  138  may include a zoom button  140  configured to launch the 3D model in a larger overlay window. Each 3D model window  138  may also include a 3D model viewer button  142  configured to launch a 3D viewer application. 
     The number of 3D model windows  138  displayed on the user interface  130  may be selected from a menu  144  including predetermined choices. In one example, the predetermined number of 3D models to be output may be chosen to be one of 6, 24 and 60 3D models. However, any other number may be provided for selection in menu  144 . In the example shown in  FIG. 3 , 6 3D models are selected, thereby resulting in the display of the 6 3D model windows  138 . In one embodiment, the user interface  130  may be configured to receive as input any number representing the size of the subset of 3D models, wherein the number is less than the total number of 3D models assigned to the selected tray  132 . The user interface  130  may also include buttons  146  and  148  configured to switch between displaying a first subset and a second subset of 3D models selected based on the weight in input cell  134 . In one example, the selected subset of 3D models may be sorted such that the first subset of 3D models that are displayed in user interface  130  more closely match the weight in input cell  134  compared to the second subset of 3D models. 
     A user may identify the 3D model that matches the 3D printed part having a weight entered in input cell  134  from a displayed subset of 3D model windows  138  in  FIG. 3 . Once the 3D model corresponding to the 3D printed part is identified, the user may request generating a label for the part.  FIG. 4  shows one example of a user interface  150  for printing an order card for an identified 3D printed part. The order card may include identifying information for the part. The order card may be generated and displayed in an area  152  of the user interface  150 . The user interface  150  may also provide an interface  154  for updating the status of the 3D printed part. After identifying a 3D printed part, the number of parts left to be identified in a single tray may be reduced. In one example, the number of items corresponding to a tray, as shown in column  126  of  FIG. 2 , may be reduced as 3D printed parts are identified in that tray. 
       FIG. 5  illustrates one example of an order card printed as a label  156 . The label  156  includes a barcode  158 . In one example, the barcode corresponds to the 3D model that matches the 3D printed part. Label  156  also includes a section  159  having information identifying the 3D printed part. The identifying information may include a customer order number, production order information, a material code corresponding to the material used to 3D print the part, and a 3D model number corresponding to the part. In other examples, the label may include other identifying data. 
       FIG. 6  is a flow chart illustrating a computer implemented process  160  of interacting with a user of a weight-based identification system having the user interfaces in  FIGS. 3, 4 and 5 . At block  162 , a list of trays to be sorted may be output, for example, by providing the user interface  120  and a listing of trays as shown in column  122  of  FIG. 2 . At block  164 , a selection of a tray may be received from a user. For example, the user may select a tray for weight-based sorting using the user interface  120  in  FIG. 2 . In response to selecting a tray, process  160  may include launching a user interface  130  as shown in  FIG. 3 , for weight-based sorting of the selected tray. 
     At block  166  of process  160 , a weight of a 3D printed part built in the tray may be received. The weight may be received using, for example, the input cell  134  in  FIG. 3 . Process  160  may include, at block  168 , outputting a subset of 3D models that are closest matches to the 3D printed part having the input weight. Additional subsets of 3D printed parts may be output at block  170 . For example, buttons  146  and  148  of the user interface  130  in  FIG. 3  may be used to output additional subsets of 3D models and to switch among displaying the different subsets of 3D models. Process  160  may include receiving a selection of a 3D model from a subset of 3D models at block  172 . For example, a 3D model displayed in a 3D model window  138  of user interface  130  may be selected. A 3D model may be selected for viewing. Selecting a 3D model may include visually comparing the 3D model to the 3D printed part and identifying the 3D model corresponding to the part. 
     At block  174  of process  160 , an order card may be generated for the identified part. For example, an order card may be generated using the interface  150  of  FIG. 5 . Generating an order card may include printing the order card. Process  160  may further include updating the status of the identified 3D printed part at block  176 . For example, interface  154  of  FIG. 4  may be used at block  176 . In some embodiments, process  160  may further include removing a 3D model corresponding to the identified 3D printed part from one or more 3D models used for weight based identification. Embodiments of the processes disclosed herein, such as process  100  in  FIG. 1  and process  160  in  FIG. 6  may be implemented in a software system that supports the production process for 3D printing at a manufacturing facility. The software system may generally allow tracking of 3D printed parts through the production process and may support processes involved in handling 3D printed parts. For example, the software system may support handling of 3D model files, creating production plans and sending shipments of 3D printed parts to distribution centers. The user interfaces  120 ,  130  and  150  may be provided to facilitate interaction with an operator of the manufacturing facility. 
     Processes described above are merely illustrative embodiments of systems for weight-based identification of 3D printed parts. Such illustrative embodiments are not intended to limit the scope of the present invention, as any of numerous other implementations for performing the invention. None of the claims set forth below are intended to be limited to any particular implementation of a process of weight-based identification, unless such claim includes a limitation explicitly reciting a particular implementation. 
     Processes associated with various embodiments, acts thereof and various embodiments and variations of these methods and acts, individually or in combination, may be defined by computer-readable signals tangibly embodied on a computer-readable medium, for example, a non-volatile recording medium, an integrated circuit memory element, or a combination thereof. Such signals may define instructions, for example, as part of one or more programs that, as a result of being executed by a computer, instruct the computer to perform one or more of the methods or acts described herein, and/or various embodiments, variations and combinations thereof. Such instructions may be written in any of a plurality of programming languages, for example, Java, Visual Basic, C, C#, or C++, Fortran, Pascal, Eiffel, Basic, COBOL, etc., or any of a variety of combinations thereof. The computer-readable medium on which such instructions are stored may reside on one or more of the components of a general-purpose computer described above, and may be distributed across one or more of such components. 
     The computer-readable medium may be transportable such that the instructions stored thereon can be loaded onto any computer system resource to implement the aspects of the present invention discussed herein. In addition, it should be appreciated that the instructions stored on the computer-readable medium, described above, are not limited to instructions embodied as part of an application program running on a host computer. Rather, the instructions may be embodied as any type of computer code (e.g., software or microcode) that can be employed to program a processor to implement the above-discussed aspects of the present invention. 
     Various embodiments according to the invention may be implemented on one or more computer systems. These computer systems may be, for example, general-purpose computers such as those based on Intel PENTIUM-type processor, Motorola PowerPC, Sun UltraSPARC, Hewlett-Packard PA-RISC processors, or any other type of processor. It should be appreciated that one or more of any type computer system may be used to partially or fully automate weight-based identification of 3D printed parts according to various embodiments of the invention. Further, the software design system may be located on a single computer or may be distributed among a plurality of computers attached by a communications network. 
     The computer system may include specially-programmed, special-purpose hardware, for example, an application-specific integrated circuit (ASIC). Aspects of the invention may be implemented in software, hardware or firmware, or any combination thereof. Further, such methods, acts, systems, system elements and components thereof may be implemented as part of the computer system described above or as an independent component. 
     A computer system for weight-based identification of 3D printed parts may be a general-purpose computer system that is programmable using a high-level computer programming language. The computer system may be also implemented using specially programmed, special purpose hardware. In a computer system there may be a processor that is typically a commercially available processor such as the well-known Pentium class processor available from the Intel Corporation. Many other processors are available. Such a processor usually executes an operating system which may be, for example, the Windows NT, Windows 2000 (Windows ME), Windows XP, Windows Vista or Windows 7 operating systems available from the Microsoft Corporation, MAC OS Snow Leopard, MAC OS Snow Lion operating systems available from Apple Computer, the Solaris Operating System available from Sun Microsystems, or UNIX available from various sources. Many other operating systems may be used. 
     The processor and operating system together define a computer platform for which application programs in high-level programming languages are written. It should be understood that the invention is not limited to a particular computer system platform, processor, operating system, or network. Also, it should be apparent to those skilled in the art that the present invention is not limited to a specific programming language or computer system. Further, it should be appreciated that other appropriate programming languages and other appropriate computer systems could also be used. 
     One or more portions of the computer system may be distributed across one or more computer systems coupled to a communications network. These computer systems also may be general-purpose computer systems. For example, various aspects of the invention may be distributed among one or more computer systems configured to provide a service (e.g., servers) to one or more client computers, or to perform an overall task as part of a distributed system. For example, various aspects of the invention may be performed on a client-server system that includes components distributed among one or more server systems that perform various functions according to various embodiments of the invention. These components may be executable, intermediate (e.g., IL) or interpreted (e.g., Java) code which communicate over a communication network (e.g., the Internet) using a communication protocol (e.g., TCP/IP). 
     It should be appreciated that the invention is not limited to executing on any particular system or group of systems. Also, it should be appreciated that the invention is not limited to any particular distributed architecture, network, or communication protocol. 
     Various embodiments of the present invention may be programmed using an object-oriented programming language, such as SmallTalk, Java, C++, Ada, or C# (C-Sharp). Other object-oriented programming languages may also be used. Alternatively, functional, scripting, and/or logical programming languages may be used. Various aspects of the invention may be implemented in a non-programmed environment (e.g., documents created in HTML, XML or other format that, when viewed in a window of a browser program, render aspects of a graphical-user interface (GUI) or perform other functions). Various aspects of the invention may be implemented as programmed or non-programmed elements, or any combination thereof. 
     Further, on each of the one or more systems that include one or more components of a system for weight-based identification of 3D printed parts, each of the components may reside in one or more locations on the system. For example, different portions of the components of a system for weight-based identification of 3D printed parts may reside in different areas of memory (e.g., RAM, ROM, disk, etc.) on the system. Each of such one or more systems may include, among other components, a plurality of known components such as one or more processors, a memory system, a disk storage system, one or more network interfaces, and one or more busses or other internal communication links interconnecting the various components. 
     Systems and processes disclosed herein for weight-based identification of 3D printed parts, such as a system including user interfaces  120 ,  130  and  150  in  FIGS. 2, 3 and 4 , may be implemented on a computer system described below in relation to  FIGS. 7 and 8 . 
     A system having user interfaces  120 ,  130  and  150  in  FIGS. 2, 3 and 4  is merely an illustrative embodiment of the weight-based identification system. Such an illustrative embodiment is not intended to limit the scope of the invention, as any of numerous other implementations of the system, for example, are possible and are intended to fall within the scope of the invention. None of the claims set forth below are intended to be limited to any particular implementation of the system unless such claim includes a limitation explicitly reciting a particular implementation. 
     Various aspects of the invention may be implemented as specialized software executing in a general-purpose computer system  180  such as that shown in  FIG. 7 . The computer system  180  may include a processor  182  connected to one or more memory devices  184 , such as a disk drive, memory, or other device for storing data. Memory  184  is typically used for storing programs and data during operation of the computer system  180 . Components of computer system  180  may be coupled by an interconnection mechanism  186 , which may include one or more busses (e.g., between components that are integrated within a same machine) and/or a network (e.g., between components that reside on separate discrete machines). The interconnection mechanism  186  enables communications (e.g., data, instructions) to be exchanged between system components of system  180 . Computer system  180  also includes one or more input devices  188 , for example, a keyboard, mouse, trackball, microphone, touch screen, and one or more output devices  190 , for example, a printing device, display screen, and/or speaker. In addition, computer system  180  may contain one or more interfaces (not shown) that connect computer system  180  to a communication network (in addition or as an alternative to the interconnection mechanism  186 . 
     The storage system  192 , shown in greater detail in  FIG. 8 , typically includes a computer readable and writeable nonvolatile recording medium  194  in which signals are stored that define a program to be executed by the processor or information stored on or in the medium  194  to be processed by the program. The medium may, for example, be a disk or flash memory. Typically, in operation, the processor causes data to be read from the nonvolatile recording medium  194  into another memory  196  that allows for faster access to the information by the processor than does the medium  194 . This memory  196  is typically a volatile, random access memory such as a dynamic random access memory (DRAM) or static memory (SRAM). It may be located in storage system  192 , as shown, or in memory system  184 , not shown. The processor  182  generally manipulates the data within the integrated circuit memory  184 ,  196  and then copies the data to the medium  194  after processing is completed. A variety of mechanisms are known for managing data movement between the medium  194  and the integrated circuit memory element  184 ,  196 , and the invention is not limited thereto. The invention is not limited to a particular memory system  184  or storage system  192 . 
     Although computer system  180  is shown by way of example as one type of computer system upon which various aspects of the invention may be practiced, it should be appreciated that aspects of the invention are not limited to being implemented on the computer system as shown in  FIG. 7 . Various aspects of the invention may be practiced on one or more computers having a different architecture or components that that shown in  FIG. 7 . 
     Computer system  180  may be a general-purpose computer system that is programmable using a high-level computer programming language. Computer system  180  may be also implemented using specially programmed, special purpose hardware. In computer system  180 , processor  182  is typically a commercially available processor such as the well-known Pentium class processor available from the Intel Corporation. Many other processors are available. Such a processor usually executes an operating system which may be, for example, the Windows NT, Windows 2000 (Windows ME), Windows XP, Windows Vista or Windows 7 operating systems available from the Microsoft Corporation, MAC OS Snow Leopard, MAC OS Snow Lion operating systems available from Apple Computer, the Solaris Operating System available from Sun Microsystems, or UNIX available from various sources. Many other operating systems may be used. 
     The processor and operating system together define a computer platform for which application programs in high-level programming languages are written. It should be understood that the invention is not limited to a particular computer system platform, processor, operating system, or network. Also, it should be apparent to those skilled in the art that the present invention is not limited to a specific programming language or computer system. Further, it should be appreciated that other appropriate programming languages and other appropriate computer systems could also be used. 
     One or more portions of the computer system may be distributed across one or more computer systems (not shown) coupled to a communications network. These computer systems also may be general-purpose computer systems. For example, various aspects of the invention may be distributed among one or more computer systems configured to provide a service (e.g., servers) to one or more client computers, or to perform an overall task as part of a distributed system. For example, various aspects of the invention may be performed on a client-server system that includes components distributed among one or more server systems that perform various functions according to various embodiments of the invention. These components may be executable, intermediate (e.g., IL) or interpreted (e.g., Java) code which communicate over a communication network (e.g., the Internet) using a communication protocol (e.g., TCP/IP). 
     It should be appreciated that the invention is not limited to executing on any particular system or group of systems. Also, it should be appreciated that the invention is not limited to any particular distributed architecture, network, or communication protocol. 
     Various embodiments of the present invention may be programmed using an object-oriented programming language, such as SmallTalk, Java, C++, Ada, or C# (C-Sharp). Other object-oriented programming languages may also be used. Alternatively, functional, scripting, and/or logical programming languages may be used. Various aspects of the invention may be implemented in a non-programmed environment (e.g., documents created in HTML, XML or other format that, when viewed in a window of a browser program, render aspects of a graphical-user interface (GUI) or perform other functions). Various aspects of the invention may be implemented using various Internet technologies such as, for example, the well-known Common Gateway Interface (CGI) script, PHP Hyper-text Preprocessor (PHP), Active Server Pages (ASP), HyperText Markup Language (HTML), Extensible Markup Language (XML), Java, JavaScript, Asynchronous JavaScript and XML (AJAX), Flash, and other programming methods. Various aspects of the invention may be implemented as programmed or non-programmed elements, or any combination thereof. 
     Having described above several aspects of at least one embodiment, it is to be appreciated various alterations, modifications, and improvements will readily occur to those skilled in the art. Such alterations, modifications, and improvements are intended to be part of this disclosure and are intended to be within the scope of the invention. Accordingly, the foregoing description and drawings are by way of example only, and the scope of the invention should be determined from proper construction of the appended claims, and their equivalents.