Systems and methods for computer-aided design analysis

Abstract

According to some embodiments, a system, method, and computer program code are provided for analyzing embodied carbon associated with the manufacturing of a part.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 443,375, filed January 31, 2023, the contents of which are incorporated herein by reference in their entirety for all purposes. [Background technology]

[0002] Manufacturers are becoming increasingly concerned about the environmental impact of their products and processes, in part because many countries have passed sustainability regulations requiring manufacturers and brands to reduce their carbon footprint, and in part because many consumers are willing to pay a premium for environmentally friendly products.

[0003] Unfortunately, it is difficult for manufacturers to assess a product's carbon footprint during the design and planning stages. The production of each part of a product impacts the environment in different ways. The materials selected, the process choices, and even the location of the factory each affect the carbon dioxide equivalents (CO2) associated with the part. 2e ") (referred to herein as "embodied carbon"). Evaluating each of these variables can be very complex, and becomes even more complex when analyzed in conjunction with evaluating the manufacturing costs of a part. It would be desirable to provide a system and method that allows manufacturers to simulate the expected cost and quantity of embodied carbon, and to evaluate how changes in material selection, design, manufacturing process, and manufacturing location could affect those costs and quantities of embodied carbon. Summary of the Invention [Means for solving the problem]

[0004] The features and advantages of the exemplary embodiments, and the manner in which they are achieved, will become more readily apparent from the following detailed description taken in conjunction with the accompanying drawings.

[0005] Throughout the drawings and detailed description, unless otherwise noted, the same drawing reference numerals should be understood to refer to the same elements, features, and structures, and the relative size and depiction of those elements may be exaggerated or adjusted for clarity, illustration, and / or convenience. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 illustrates a design system according to some embodiments. [Figure 2A] ~ [Figure 2C] FIG. 1 illustrates a process according to some embodiments. [Figure 3A] ~ [Figure 3I] FIG. 1 illustrates a user interface according to some embodiments. [Figure 4] FIG. 1 illustrates components of a design system according to some embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0007] In the following description, specific details are set forth to provide a thorough understanding of various exemplary embodiments. It should be understood that various modifications to the embodiments will be readily apparent to those skilled in the art, and that the general principles presented herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Furthermore, in the following description, numerous details are set forth for purposes of explanation. However, those skilled in the art will understand that embodiments may be practiced without such specific details. Furthermore, in certain instances, well-known structures or processes are not shown or described to avoid obscuring the description with unnecessary detail. Thus, the present disclosure is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0008] Designers of manufactured parts are often unaware of factors that can affect the embodied carbon associated with the production of their parts. It is becoming increasingly important for companies to consider the carbon footprint of their product manufacturing. Unfortunately, comparing processes, materials, and manufacturing locations—all of which affect the monitoring impact of a part's production—can be complex and difficult. For example, calculating embodied carbon from the materials used to manufacture a part can be challenging. To calculate the rough mass required to manufacture a part, users must understand the manufacturing process used as well as the stock materials required to manufacture the part. Rough mass (also referred to herein as "raw mass") is difficult to calculate accurately because it can vary depending on the manufacturing process used. For example, the mass of a finished machined part may be only 5–20% of the initial rough mass of the materials used, whereas the finished mass of a cast part may be around 95% of the rough mass. Furthermore, manufacturing processes may involve various steps, or "routings." As an example, a die casting manufacturing process may include steps that perform machining, milling, cutting, or drilling. Each of these steps affects the embodied carbon of the manufactured part. Each step may use different machines and may also affect the cycle time of the manufactured part. Each machine may have different energy consumption requirements. Because all of these variables affect the embodied carbon of the manufacturing process, calculating the embodied carbon of the manufactured part becomes very complex and specialized.

[0009] According to some embodiments, systems, methods, and computer program code are provided for analyzing embodied carbon associated with the manufacturing of parts. The embodiments enable embodied carbon to be efficiently calculated for various manufacturing processes, for various materials, in various geographic locations, thereby enabling users to analyze various scenarios and combinations of variables. The systems and methods for designing for sustainability provided by the embodiments enable users to easily calculate embodied carbon for various design choices, processes, materials, and manufacturing locations, thereby enabling sustainable choices to be made. Furthermore, the embodiments enable such embodied carbon analysis to be performed in conjunction with cost analysis, thereby enabling users to compare the cost and embodied carbon of various scenarios. The embodiments provide improvements in the art of part design and analysis, thereby improving systems, methods, and computer program code for analyzing part designs.

[0010] According to some embodiments, a part designer or other user can interact with the system to compare numerous different part manufacturing scenarios to identify a desirable combination of cost and embodied carbon. These different scenarios can be quite complex and require analysis of four key variables, each of which includes several data points and subvariables. These four key variables are the geometry and shape of the part, the material used in manufacturing the part, the process used in manufacturing the part, and the specific location of the factory selected for manufacturing the component. According to some embodiments, the system can output cost and embodied carbon information to the user through a user interface, which allows the user to select a combination of the four key variables that results in a desired balance of cost and embodied carbon.

[0011] For convenience and ease of explanation, certain terms are used herein. For example, the terms "process" or "process type" generally refer to the type of manufacturing process used to manufacture a part (or, using embodiments of the present invention, to analyze a part for possible manufacturing using one or more process types). For example, various process types may include die casting, injection molding, machining, or sheet metal bending or fabrication (although one skilled in the art will understand that other process types may also be used to manufacture a part, and these process types are used as examples herein). Embodiments allow a user to compare costs associated with manufacturing a part using various process types, as well as compare embodied carbon from manufacturing a part using various process types.

[0012] As used herein, the term "cycle time" generally refers to the time it takes one or more machines to operate to produce a part using a given process type. Different process types require different cycle time calculations. For example, the cycle time for a part made using a machining process type can be complex, including the sum of the cutting times for each operating step of the machining process. This cycle time can also include the operating times of multiple process steps using different machines. Various cycle time calculations are discussed in more detail below.

[0013] As used herein, the term "material" when describing a manufactured part refers to the raw materials used in manufacturing, such as different types of plastics (e.g., for injection molding) and different types of metals (e.g., for machining, sheet metal, or various types of casting).

[0014] Another (smaller) contributor to embodied carbon in the manufacture of a part is the embodied carbon associated with the manufacturing process itself ("process carbon" or "process-embodied carbon"). As will be explained in more detail below, process carbon depends to some extent on the selected factory location. The factory location determines the "grid mix" associated with the factory (and associated process). As used herein, the term "grid mix" refers to information associated with the mix of power sources used by factories operating in a given geographic location. For example, the "grid mix" of a factory in one location may consist primarily of electricity from coal-fired power plants, while the "grid mix" of a factory in another geographic location may include electricity from renewable energy sources. To calculate the total embodied carbon in a process, the present invention uses the different "grid mixes" associated with the use of different factories.

[0015] Before describing the features of the present invention in detail, a non-limiting illustrative example will be provided. In this illustrative example, a company seeks to manufacture a component for a piece of equipment. The component is a heat sink, which will ultimately be mounted to another component to dissipate heat. The company has a set of computer-aided design (CAD) drawings of the heat sink, which define its dimensions and shape. The CAD drawings include a model stored in a file, which includes a rendering / visualization of the heat sink (e.g., the visualization shown as part 306 in FIG. 3B ). In addition to the structural design (or geometric shape) of the heat sink, the CAD file may contain additional attributes, which may be stored in metadata in the CAD file itself or in a part object paired with the CAD file. The company then seeks to select a manufacturer to make the heat sink according to the requirements specified in the CAD file.

[0016] Knowing the specifications the heat sink must meet (which are defined in the CAD file), a company can then consider different manufacturing processes, geographic locations of manufacturers, and materials to manufacture the part in a cost-effective manner while also reducing the embodied carbon associated with manufacturing the part.

[0017] A company wants to keep manufacturing costs low (so that machines incorporating heat sinks can be sold at a reasonable profit). Additionally, the company wants the manufacturing of heat sinks to be sustainable (i.e., reduce the amount of embodied carbon emissions caused by the manufacturing of heat sinks). Embodiments allow a company to import or otherwise provide a design described in a CAD file to a design system for analysis. The design system of the present invention allows a company (i.e., a user or representative of the company) to interact with the design system to analyze various scenarios and arrive at a manufacturing recipe that achieves a desired balance between cost and embodied carbon. Various possible outcomes may include scenarios with different materials, different manufacturing processes, and different locations in the manufacturing facility. The company can interact with the design system to adjust these various variables to arrive at a manufacturing recipe that achieves a desired balance between cost and embodied carbon. The selected recipe may then be communicated to the manufacturer to begin manufacturing the part. This illustrative example will be referenced later in conjunction with various figures to explain features of the present invention.

[0018] Referring initially to FIG. 1 , a block diagram illustrates various components of the system of the present invention. The system 100 illustrated in FIG. 1 includes a design system 104, which receives a computer-aided design (“CAD”) model to analyze aspects of a part to be manufactured. The CAD model may be provided in the form of one or more files provided by a user operating a user device 102 in communication with the design system 104 and may be uploaded or otherwise transferred to a design service 106 via an interface 108. The design service 106 may include a number of rules and computer program code configured to analyze the CAD model and perform processes described further herein. The CAD model may also be provided in the form of one or more files retrieved via the interface 108 from a design data repository 110. For example, the design data repository 110 may be a product lifecycle management (PLM) system. For example, many part designers or other companies may use PLM systems to manage CAD files. In some embodiments, interface 108 of design system 104 may be configured to interface with or otherwise receive data from various PLM systems (e.g., to translate or convert data from the PLM systems into data that can be manipulated by design system 104). While a single user device 102, design data repository 110, and design system 104 are shown in FIG. 1 , those skilled in the art will appreciate that in actual applications, multiple user devices, design data repositories, and / or design systems may be provided. For example, as described further herein, multiple user devices 102 and multiple design data repositories 110 may provide part design data to design system 104 for analysis.

[0019] Information from each CAD model (or data from design data repository 110) defines one or more parts to be manufactured. After obtaining this data, design system 104 may be configured to perform an analysis of various aspects of the part (part material, manufacturing process, and manufacturer location) to generate embodied carbon estimates for several different manufacturing options for the part and to generate manufacturing cost estimates for each of those different manufacturing options. Design system 104 may operate on a local computing device or on a remote hosted device (or network of computing devices).

[0020] Upon receiving the design data from interface 108, design service 106 identifies one or more geometric features of interest of the part and performs operations on those one or more geometric features to recommend modifications to improve the design with respect to manufacturability as well as cost and embodied carbon. For example, design service 106 may recommend reducing the number of tools required, changing specialized tooling processes to more standard processes, shortening production time, reducing production costs, reducing raw materials required for the part, changing the geographic location where the part is manufactured which affects costs or embodied carbon due to local labor rates and electrical grid mix, etc.

[0021] The design service 106 may present information to a user through one or more user interfaces. The user interfaces may allow a user to change one or more manufacturing variables to see the effect on cost and embodied carbon. According to some embodiments, a user can arrive at a desired balance between cost and embodied carbon by running different "scenarios" with different variables and comparing the results of the different scenarios.

[0022] According to some embodiments, design system 104 uses data associated with various manufacturing processes to perform various analyses associated with manufacturing a part (e.g., performing a comparative analysis between die casting a part and machining a part). In part, such analyses may use data associated with various manufacturing processes received from one or more databases (e.g., process database 120). Design system 104 may also use data from one or more databases (e.g., factory database 130) to perform analyses associated with estimating cycle times for manufacturing a part. For example, cycle times associated with manufacturing a part may vary depending on the material or process used to manufacture the part, and each of these different cycles may consume different amounts of electricity. Design system 104 may also use data from one or more databases (e.g., materials database 140) to perform analyses associated with estimating amounts of embodied carbon associated with various materials that may be used to manufacture the part. While the term “database” is used to refer to databases 120-140, data may be stored in or retrieved from other types of information sources or data storage devices, as will be readily understood by those skilled in the art upon reading this disclosure. For example, the data may be obtained as a file or feed from an application programming interface.

[0023] According to some embodiments, process database 120 may contain data associated with various processes. Each manufacturing process may include, for example, various process feasibility checks for each process required to manufacture a part (e.g., minimum bend radius, maximum thickness, material type, achievable tolerances, consumables required for the process), modifications to cycle time based on the selected material type (e.g., adjustment factors to cutting speed based on material cutting conditions), and power requirements for each stage of the process cycle time. In some embodiments, process database 120 consists of several lookup tables to retrieve this information by process type.

[0024] According to some embodiments, the factory database 130 may include regionalized factory data for multiple geographic regions. For example, the factory data 130 may include economic and machine-related data associated with factories in various regions, such as data for determining factory overhead allocation rates (e.g., electricity rates, gas rates, rental rates, insurance rates, and additional support allocations), machine parameters (e.g., machine cost, size, life, and maintenance factors) for performing feasibility assessments and calculating machine overhead allocation rates, additional machine parameters (e.g., machine spindle power, traverse speed, and tool change time) for facilitating calculation of process cycle times, industry sector wage rates by skill level, and electrical embodied carbon factors for particular factories or geographic regions.

[0025] According to some embodiments, materials database 140 may contain detailed material information for hundreds of different material compositions, including several different stock types, hundreds of individual stock sizes, and their associated process data. This data may include material property data (e.g., material type, specific heat capacity, and material hardness) for performing feasibility assessments, material cost data for each material and for the specific stock type (if required) for manufacturing the part, and material embodied carbon factors for each material.

[0026] The design system 104 may generate one or more analysis results and / or recommendations that enable a user to select a desired manufacturing method for producing the part (including, for example, recommendations regarding the process to be used, the geographic location where the part should be manufactured, and the material to be used). In some embodiments, these recommendations may be generated in conjunction with other manufacturing recommendations to enable improvements in cost, efficiency, and sustainability.

[0027] 2A-2C illustrate processes 200, 250, and 280 that may be implemented by design system 104 (along with other components of system 100) according to some embodiments. The processes 200, 250, and 280 of FIGS. 2A-2C are described in conjunction with various user interface illustrations shown in FIGS. 3A-3I. The user interfaces of FIGS. 3A-3I are for illustrative purposes only; those skilled in the art will readily appreciate upon reading this disclosure that other user interface configurations may be used to interact with the systems of the present invention. The user interfaces of FIGS. 3A-3I may be accessed, for example, from a web browser on user device 102, displayed on the display of user device 102, and configured to receive input from a user operating user device 102 (e.g., via a keyboard, cursor, mouse, touchscreen, or other input device associated with user device 102).

[0028] Process 200 may begin with a request from a user operating user device 102, for example. The user may be a manufacturing engineer or other designer seeking to evaluate aspects of a manufactured part (or components thereof) to determine whether the part can be manufactured in a more sustainable manner. Processing begins at 202, where one or more CAD files or part objects are provided to a design system. For example, a user operating user device 102 may interact with a user interface, such as user interface 302 of FIG. 3A. User interface 302 (and the user interfaces shown in FIGS. 3B-3I) may be displayed, for example, on display device 300 of user device 102. As shown in FIG. 3A, the user may be prompted to upload a CAD model (e.g., in the form of one or more CAD files), select an existing (already uploaded) CAD model, or identify the location of the CAD model in terms of a location (e.g., a PLM location within design data repository 110). In some embodiments, the user may also be able to select an existing project (which may require, for example, an already uploaded or identified CAD model that has already been analyzed to create one or more embodied carbon and cost scenarios). The term "scenario" is used herein to refer to data associated with a part being analyzed by the system of the present invention (using certain input variables selected by the user). The term "project" is used herein to refer to data associated with a part being analyzed by the system of the present invention in one or more "scenarios" (each scenario may have different input variables selected by the user).

[0029] Upon receiving the CAD file, the design system 104 may perform a process to analyze the part design. Processing continues at 204, where the design system 104 prompts the user (in a user interface presented to the user on the display screen of the user device 102) to select one or more process groups to be used to manufacture the part. Generally, as used herein, a "process group" is a collection of manufacturing processes that share a common understanding of feature recognition and material morphology. For example, the user may be prompted to select whether an analysis should be performed if the part were manufactured using a die casting process or a machining process. In some embodiments, the selectable types of process groups are identified by the design system 104 during the initial analysis of the CAD file, thereby preventing the user from selecting a process group that is incompatible with the part design.

[0030] An example of a user interface that allows a user to select one or more process groups (and other input variables) is shown in FIG. 3B. As shown in FIG. 3B, display 300 displays several menu options available for selection by the user, including production scenario menu group 310, tolerance menu group 330, process and machine options menu group 340, cost menu group 350, and sustainability menu group 370. These menu groups are shown for illustrative purposes only; other groups or groupings may be used, as would be readily understood by one of ordinary skill in the art upon reading this disclosure. When production scenario menu group 310 is selected (as shown in FIG. 3B), several input options are presented to the user (displayed as items 312, 314, 316, 318, and 320 on the left side of display 300) while a rendering of part 306 is displayed in visualization area 304. The rendering of part 306 is generated by design system 104 based on the CAD file uploaded in 202. In some embodiments, the visualization area 304 includes several controls that allow a user to interact with the rendering of the part 306 (e.g., to zoom, pan, rotate, or otherwise inspect the part).

[0031] Processing at 204 may include a user interacting with display 300 to select a process group at 312. In this illustrative example, the heat sink is compatible with die casting, so die casting is presented to the user as a process group option (and selected by the user in FIG. 3B ). Some die-cast parts also require machining operations, so selected by the user in the example of FIG. 3B . In some embodiments, display 300 of FIG. 3B is created by design system 104 based at least in part on an analysis of the CAD model, retrieving process data from process database 120. For example, this processing may include determining whether the part is compatible with a given manufacturing process and, if so, including that process as an option available for selection by the user at 312. According to some embodiments, the compatibility of the part with a process is determined based on a feasibility assessment by design system 104. In some embodiments, a user's ability to select from among several compatible manufacturing processes may also be determined by user permissions (e.g., the system may impose license restrictions based on whether the user has a license for a manufacturing process).

[0032] Once the user selects the desired process group attributes, processing continues at 206, where the design system 104 receives a selection of raw material types (input 318) to be used to manufacture the part. In some embodiments, multiple options may be selected, and the same part may be analyzed to calculate the embodied carbon of producing the same part using different types of materials. For example, if the part is to be manufactured using nylon, embodiments allow the user to select from a list of nylon types (e.g., using nylon 6 (30% glass)) and other nylon types compatible with the process group. In this illustrative example, the user selects to analyze the manufacture of a heat sink using aluminum (more specifically, aluminum ANSI AL380.0). In some embodiments, an input at 318 allows the user to select from a calculated list of compatible materials. The calculated list of compatible materials is determined by the design system 104 based on the analysis of the CAD model and the selected process group (e.g., based on input received from the user at 312). This prevents the user from being presented with material options that are incompatible with the design or the selected process.

[0033] Once these selections are made, processing may proceed to 208, where the user provides other relevant information (e.g., the quantity of parts to be produced in various scenarios, the size of each run or batch, etc.) This information is used by design system 104 to calculate the embodied carbon as well as the cost.

[0034] Once the user has selected information identifying the desired process group, material, desired quantity, and batch size, processing continues at 210, where the design system 104 prompts the user to select a factory location where the part (using the process group selected at 204) will be manufactured. According to some embodiments, the selected factory location may be a “digital” or “virtual” location that the design system 104 simulates using a digital twin or digital model of the factory in the corresponding geographic location. According to some embodiments, selecting a digital factory location causes the design system 104 to use various sustainability parameters. For example, selecting a digital factory location causes the design system 104 to retrieve factory data from the factory database 130, including local electricity costs and regional CO2 emissions estimates (e.g., expressed in kg CO2 / kWh). As an illustrative example, if a digital factory location is selected in China, the CO2 emissions may be equivalent to approximately 1.02 kg CO2 / kWh, whereas for a digital factory location in the United States, the CO2 emissions may be equivalent to approximately 0.5 kg CO2 / kWh. In some embodiments, the estimate is based on the current electricity mix for the region (e.g., coal, natural gas, nuclear, hydro, or renewables). The selection of the digital factory location may also affect other estimates generated by the design system 104.

[0035] 3B, the user may be presented with a drop-down menu 314 from which to select a desired digital factory. The options available to the user may vary depending on the process group selected at 312, as well as other information associated with the CAD model based on analysis by the design system 104. For example, some processes and designs may not be compatible with some factory locations.

[0036] Once the user selects the desired factory location, processing continues at 212, where the design system 104 receives information identifying one or more process routing attributes. Combinations of various parts with various manufacturing processes may require various process routings (essentially sub-routines of the selected manufacturing process). For example, a part (e.g., a heat sink in the illustrative example) may be die-cast (as selected in step 204 and shown at 312 in FIG. 3B). However, based on the part's design, several process routings may be required to finish the part. These process routings may be determined by the design system 104 (based on the selected process and the CAD model) and are referred to herein as "computed routings." They may also include one or more pre-configured "process overrides," which may modify one or more steps or sub-steps. Generally, as used herein, a process override is a user-specified deviation from the design system 104's default assumptions. Referring again to the illustrative example, the primary process selected for the heat sink is "die casting," but design system 104 may determine that there are several sub-processes or steps that are required.

[0037] An example of a procedure is a collection of steps used in a manufacturing process (e.g., a procedure may include one or more of stock machining, perimeter cutting, 3-axis milling, sawing, or bulk milling). These steps may be required to resize raw material to a size suitable for die casting. The selection of a process procedure has a direct impact on both the embodied carbon of the process and the cost of the part. For example, the more steps in a process procedure a part requires, the more additional energy may be consumed (thereby increasing the embodied carbon of the process). Furthermore, if raw material requires significant machining or other cutting to reduce its size, the more waste may be generated (and the more cost and embodied carbon may be generated). Embodiments allow these variables to be easily analyzed using the system of the present invention. According to some embodiments, the options available to the user (e.g., at 316 in FIG. 3B) are determined by the design system 104 based on the CAD model and the selected process group (312 in FIG. 3B). The process data may be retrieved by the design system 104 from the process data 120.

[0038] With these selections and additional information, processing continues at 214, where design system 104 operates to perform an analysis. In some embodiments, an analysis is performed for each combination of selections. Generally, processing at 214 includes calculating the material embodied carbon and the process embodied carbon (the sum of which represents the total embodied carbon for that scenario). According to some embodiments, processing at 214 further includes determining the costs of each scenario (e.g., these approximately equal the material costs, tooling and setup costs, manufacturing process costs, assembly costs, and labor costs for each scenario). Calculating each of these values ​​may be an iterative process requiring process data from process database 120, factory data from factory database 130, and material data from materials database 140.

[0039] According to some embodiments, the embodiment performs a calculation of the rough mass required to manufacture a part in a given scenario. This calculation depends on several factors and is affected by the selected process group, process sequence, and material. The following describes the calculation of rough mass for various process groups. If a part is selected to be manufactured by injection molding, the calculation of the part's rough mass is based on dividing the part's "finished mass" by its "utilization rate." The "utilization rate" is calculated as "utilization rate = (1 - material waste rate) x molding efficiency," where efficiency is based on the machine used (the efficiency is retrieved from process data 120 and factory data 130) (and is typically equal to 0.95). The material waste rate is expressed as a percentage and is the difference between the "runner rate" and the "regrind allowance." The regrind allowance may default to 0.25, may be retrieved from factory data 130, or may be entered as a user-specified value. The runner rate is a function of the runner volume, the number of cavities in the part, and the part volume. The number of cavities and part volume of a part are calculated by the design system 104 based on a CAD model of the part. In injection molding, "runners" are channels cut into the mold that allow material (such as plastic) to flow from the nozzle into the cavity (mold). The "runner volume" is calculated by the design system 104 based on the CAD model of the part and information about the machine being used (retrieved from process data 120 and factory data 130). The "finished mass" of the part is calculated based on the product of the "part volume" and the "material density." The part volume is calculated by the design system 104 based on the CAD model of the part and the material density of the selected material (entered in step 206). The material density may be retrieved from the material database 140. In this manner, embodiments enable efficient and accurate calculation of the rough mass of an injection-molded part.

[0040] In a scenario where a part to be manufactured is selected to use a machining process, the selection of the appropriate material stock is a key controlling factor in the calculation of the rough mass (and therefore the embodied carbon calculation for the scenario). The analysis at 214 includes a process to ensure that the appropriate material stock is selected and analyzed. This includes a process to determine the appropriate material stock alignment and cross-section. Embodiments automatically determine the most likely stock configuration and alignment direction. The design system 104 analyzes the part geometry (from the CAD model) and evaluates possible stock axis directions and cross-sections from those directions. In some embodiments, a user may be able to view the selected stock axis directions and cross-sections by interacting with the visualization area 304 of the display 300 (e.g., shown in FIG. 3B). In some embodiments, a user may override the stock configuration and alignment recommended by the design system 104. The design system 104 uses several rules to determine the stock configuration and alignment of the part. For example, if the part is round, a round cross-section may be assigned (allowing for the selection of a round stock material). If the part is approximately flat and round, a rectangular cross-section may be assigned to the part (and plate stock may be selected for use in the analysis). Rules applied by the design system 104 may determine which plate stock may be used based on the selected machine and factory. For example, the selected factory or machine may have a maximum acceptance limit for round stock and / or a maximum stock thickness compared to the diameter of the round cross-section. These parameters define which stock material may be used in a given factory or machine (and may be retrieved, for example, from factory data 130). The selection of an input stock material appropriate for the selected factory / machine in a scenario can have a significant impact on the embodied carbon for the production of the part. Another factor is the size and tolerance of the stock machining material.

[0041] In some embodiments, the design system 104 uses the concept of machining stock allowance when determining the initial stock size required for machining a given part. Stock allowance is a small amount of excess material added to the finished part dimensions to accommodate any machining (material removal) required to meet material quality, tolerance, or finish requirements. Stock allowance may be specified in the CAD model of the part and analyzed by the design system 104. A non-zero stock allowance may be required to drive the rough and finish machining of the part. A zero value for stock allowance means that the “as supplied” stock surface is sufficient for the finished part and no additional machining is required to meet the given quality, tolerance, or surface finish requirements. The design system 104 determines the ideal stock size required for the part based on the dimensions of the finished part, as well as the amount of material needed to meet any specified stock allowance (both of which are determined from the CAD model of the part). In some embodiments, if design system 104 determines that non-hex stock is appropriate for a part, design system 104 selects stock with a minimum standard thickness greater than or equal to the ideal thickness. This selection includes data from materials data 140.

[0042] In some embodiments, the concept of “virtual” stock may be used in situations where actual stock is not available. Using the concept of “virtual” stock allows for analysis to be performed to determine whether stock may be appropriate for the part, even if the stock is not currently available. In some embodiments, the design system 104 uses rules to apply default stock allowances. These rules may determine minimum and maximum stock allowance values. In some embodiments, in situations where the stock material is a rectangular bar, a square bar, or a plate, a stock allowance percentage may be applied. The stock allowance percentage may be a percentage of the cross-sectional height of the part. In situations where the stock material is a round bar or a circular tube, the stock allowance percentage is a percentage of the outer diameter of the cross-section of the part. The design system 104 may apply other rules to determine the stock allowance for the part.

[0043] If the scenario indicates that the part to be manufactured uses sheet metal, processing at 214 includes an analysis specific to that material and the associated manufacturing process. For example, the material cost of a sheet metal part is based on the rough mass required to make the part. Raw material utilization is equal to the finished mass of the part divided by the rough mass ("rough mass" includes all material scrap). There are several methods that the design system 104 can use to calculate sheet metal material utilization. These methods may be based on the process used to assemble the part using sheet metal. For example, if the scenario indicates that the material to be used is sheet metal and the selected manufacturing process is progressive die, the design system 104 may calculate material utilization using a true part shape nesting (TPSN) algorithm. This algorithm maximizes material utilization and minimizes waste by finding the tightest nesting of the part using the actual perimeter of the blank (the blank perimeter is determined from the process data 120 and factory data 130). For progressive die processes, the TPSN algorithm uses an optimized strip nesting algorithm. In this algorithm, parts are nested in rows, with all parts in a row having a uniform orientation. In a scenario where the material is sheet metal and the process is another type of hard tool procedure (other than progressive die), the design system 104 may use rectangular nesting by default. This method uses the minimum enclosing rectangle of the blank (determined from process data 120 and factory data 130) to account for the length and width orientation of the material.

[0044] According to some embodiments, a user may be allowed to specify a desired method for calculating utilization rates for parts assembled from sheet metal. For example, a user may be able to select “rectangular nesting,” “true part nesting,” “machine default nesting,” or “override.” In some embodiments, the design system 104 may allow a user to select “rectangular nesting” if parts are rectangularly nested in the lengthwise or widthwise orientation on the sheet. The design system 104 may allow a user to select “true part nesting” if the selected manufacturing process is a progressive die. In this nesting, the actual perimeter of the part is used to determine the nesting, and the design system 104 performs an analysis testing various rotations of the part. The design system 104 may allow a user to select “machine default nesting,” which uses the machine’s average material utilization rate (determined from the process data 120 and factory data 130). The design system 104 may also allow a user to “override” these nesting rates and instead use a fixed utilization rate value specified by the user.

[0045] The design system 104 performs several other analyses to calculate cost and embodied carbon. This is done by analyzing the part design (from the CAD model information) and the selected materials, processes, and locations. For example, the design system 104 may determine whether pilot holes should be drilled to assemble the part (and the size of those pilot holes). Once the design system 104 performs these (and other) analyses to calculate the rough mass of the part, the embodied carbon in this scenario is calculated by multiplying the calculated rough mass by the material's carbon factor (retrieved from materials data 140). In this way, embodiments consider all processes associated with creating the stock material, which leads to an accurate calculation of the part's embodied carbon. The design system 104 uses the rough mass to calculate the part's "material embodied carbon."

[0046] The design system 104 also performs several determinations to estimate the cycle time associated with manufacturing a part in a desired scenario. The cycle time for manufacturing a part varies depending on the process group selected in the scenario. For example, a part manufactured using a machining process may require several cycle times that make up the overall cycle time. A machining process may include cutting time (the time during which material is cut into a certain shape or size). The cutting portion of the cycle time may have multiple steps, each of which includes engagement time and rapid move time. Engagement time is the time during which the tool or part is rotating (or otherwise moving). Rapid move time is the time during which the tool or part is positioned (during which neither the tool nor the part is rotating). Each of these requires complex calculations and several rules based on data retrieved from the process data 120 and factory data 130, as well as the selected process and procedures. For a machining process, engagement time consists of "chip making time" and "non-chip making time." Each of these times is dependent on the particular process and machines used and may be calculated by design system 104 (with reference to data from process data 120 and factory data 130). Once the overall cycle time for a given scenario has been calculated, embodiments utilize factory data 130 to calculate the electrical carbon factor for that scenario. The electrical carbon factor is expressed in kg CO 2eThe energy consumption may be expressed in kWh / kWh and generally depends on cycle time, machine data, and factory location (which has an associated "grid mix"). As mentioned above, a factory location may be a virtual model of a factory at a geographic location. The virtual model may include energy data that defines the grid mix associated with that location. Once the manufacturing (or "process") embodied carbon for the production of a part has been calculated, an estimate of the total embodied carbon may be calculated (this is done by summing the material embodied carbon, process embodied carbon, and all logistics embodied carbon associated with the scenario). In some embodiments, the logistics embodied carbon associated with a scenario may be a user-defined value. For example, a user may know what their logistics embodied carbon is and may enter that value. As a default, a zero value may be entered.

[0047] The design system 104 also operates to calculate the cost of the scenario (with reference to cost calculation rules and data from the process data 120, factory data 130, and material data 140), which includes material costs, labor costs, and tooling costs.

[0048] Processing continues at 216, where design system 104 presents the results of the analysis to the user (e.g., in a user interface format, spreadsheet format, or the like). As an example, the user may be presented with a user interface such as that shown in FIG. 3C via display 300, which shows the results of the analysis of a given scenario. In display 300 of FIG. 3C, the user is presented with a spreadsheet-style display of data showing the results of the analysis of one scenario. The data in FIG. 3C shows the results of an analysis of a heat sink, a die-cast part requiring four processing steps (melting, high-pressure die-casting, trimming, and milling) in the selected sequence. A factory in China was selected for the analyzed scenario. Design system 104 calculates the total embodied carbon (measured in kg CO ) for the scenario to produce each heat sink. 2e ) is predicted to be 0.63, with 0.52 for material-embodied carbon, 0.11 for process-embodied carbon, and 0.00 for logistics-embodied carbon. Furthermore, design system 104 calculates that the total burdened cost per manufactured heat sink for the scenario is predicted to be $1.77. In some embodiments, the user may be able to view and / or download a detailed breakdown of the cost data (e.g., showing the manufacturing time for each process and a detailed breakdown of the cost data). In some embodiments, the user may select the scenario presented at 216 as the final scenario to be used in production. In some embodiments, the user may interact with design system 104 to have a specification of the selected scenario sent to the manufacturer to be used in producing parts according to that scenario. In some embodiments, the specification of the selected scenario may be sent to a user device 102 associated with the manufacturer.

[0049] According to some embodiments, a user may compare results from multiple scenarios to select a scenario that provides a desired balance of low embodied carbon and low cost. Referring to FIG. 2B, process 250 illustrates an analysis sequence that can be used to analyze various part manufacturing scenarios. Process 250 may be performed by a user operating user device 102 and interacting with design system 104. At 252, the user performs an initial analysis of the part (e.g., according to process 200 of FIG. 2A). At 254, the user saves the initial scenario results for the part. Design system 104 stores the scenario results for later retrieval and analysis. The user may then input information to modify one or more variables of the scenario to create a new scenario at 256. For example, the user may select a different process group, a different factory location, a different process sequence, a different material, or a different production quantity or batch size. Processing continues at 258, where design system 104 stores the updated scenario results for later retrieval and analysis. The processes at 256 and 258 may be repeated as needed by the user to input different combinations of variables for analysis.

[0050] Processing continues at 260, where the design system 104 displays to the user a comparison of various scenarios for manufacturing the part. As described above, each scenario may be saved by the user, and each scenario may require the selection of one or more different input variables (e.g., the user may modify the process group, factory location, material selection, etc.). Embodiments allow the user to view the results of each of these different scenarios. For example, with reference to FIG. 3H, processing at 260 may require the design system 104 to present the user with a display 300 showing the results of each scenario in chart form. The display 300 may include an area 390 that lists the execution of various scenarios on the selected part, as well as an area 392 that displays the results of each scenario. In the display 300 of FIG. 3H, the user can click, hover the cursor over, or otherwise select a particular scenario in the list of scenarios 390 to view more details about that scenario (e.g., hovering over a scenario may cause a modal or window showing the variables selected in each scenario to overlay a portion of the display 300). Area 392 allows the user to select the data to output on the graph for each scenario. For example, the user may select to display total burdened cost data and total embodied carbon for each scenario. Various cost options may include material costs, labor costs, equipment costs, etc. Various embodied carbon options may include total embodied carbon, material embodied carbon, process embodied carbon, logistics embodied carbon, etc. In this illustrative example, the user may determine that scenario 3 achieves the user's desired balance of low cost and relatively low embodied carbon. By presenting the user with such a scenario comparison display, embodiments allow the user to efficiently compare highly complex scenarios.The user can interact with the results to determine which scenario produces the desired result (e.g., the user can balance the embodied carbon of each scenario against the cost of each scenario to better select the scenario that matches the desired result). In some embodiments, the user can interact with design system 104 to select one of the scenarios as the final scenario to use in manufacturing the part. In some embodiments, design system 104 can send the selected scenario to the manufacturer to manage manufacturing of the part according to the selected scenario.

[0051] According to some embodiments, the design system 104 may be configured to automatically analyze user-entered data to ensure that the user selects valid combinations of materials, processes, and factory locations (or to allow the user to select only valid combinations). Furthermore, the design system 104 may be configured to automatically suggest alternative materials, processes, or factory locations that may result in either cost or embodied carbon reduction. For example, with reference to FIG. 2C , in some embodiments, process 280 may be performed after a user executes a scenario requiring a specific selection of materials. At 282, the design system 104 performs a process to analyze the material selection (and other selected attributes). At 284, the design system 104 determines whether one or more alternative materials (e.g., materials compatible with the part design) are available. At 286, the design system 104 presents the user with a user interface listing the alternative materials. For example, referring again to FIG. 3E , the user may navigate to the user interface presenting the alternative materials from item 375 (a user interface area showing the relative material carbon effects for one or more alternative materials). If the user wishes to analyze alternative materials in more detail, the user may click on the area (or button) associated with item 375 and may be presented with the user interface 300 shown in FIG. 3I. As shown in FIG. 3I, the user interface lists one or more alternative materials with different carbon emissions and costs in area 380. The user may be presented with the materials analyzed in the current scenario and a list of possible alternative materials. The user may select to analyze one or more of the alternative materials, which causes the design system 104 to perform an analysis using the criteria already entered and the newly selected materials.

[0052] Referring again to FIG. 2C , if the user selects one or more alternative materials at 288, processing proceeds to 290, where alternative scenarios are executed using the selected alternative materials. In this manner, embodiments readily enable a user to generate and compare multiple scenarios using materials (or other inputs) that may result in different costs or carbon impacts. While an exemplary user interface is shown in which alternative materials are automatically identified by the design system 104, the system may also automatically identify other alternatives (e.g., plant locations, process groups, etc.). In this manner, embodiments readily enable a user to review highly complex comparisons of scenarios requiring highly complex analysis of multiple variables, thereby enabling selection of a scenario that achieves a desired balance between carbon impact and cost.

[0053] According to some embodiments, a user may be provided with several options and interfaces when creating or evaluating a scenario. For example, referring again to FIG. 3B , the user may be presented with an option 309 to save the current scenario. Additionally, the user may be presented with an option 308 to view part details. An illustrative user interface that may be displayed to a user who selects to view part details is shown in FIG. 3G . In display 300 of FIG. 3G , the user is presented with a tabular display of the process steps associated with the selected process group for the part. Continuing with this illustrative example, the illustrated process steps are for a heat sink die casting process in a digital factory in China. As shown, the die casting process for this part in this scenario includes four processes: melting, high-pressure die casting, trimming, and 3-axis milling. Display 300 of FIG. 3G shows embodied carbon information associated with each of these process steps.

[0054] The user may also be able to view cost information for the current scenario. For example, referring to FIG. 3C, the illustrated display 300 may be displayed to a user who selects cost menu item 350. The user may also be able to view sustainability information for the current scenario. For example, referring to FIG. 3D, the illustrated display 300 may be displayed to a user who selects sustainability menu item 370. In some embodiments, sustainability menu item 370 may be presented as a single display or may be split into multiple displays (as shown in FIGS. 3D-3F). In display 300 of FIG. 3D, the user is shown a sustainability screen displaying an embodied carbon summary 372 for the current scenario (which includes information indicating how many of the evaluated processes lack sustainability information, as well as information indicating the calculated embodied carbon). The user may select to compare (309) the current scenario to other scenarios.

[0055] With reference to FIG. 3E, a user who selects to view material embodied carbon information may be presented with a display 300 showing the material embodied carbon for the current scenario. With reference to FIG. 3F, a user who selects to view manufactured embodied carbon information may be presented with a display 300 showing the manufactured embodied carbon for the current scenario. As shown, a table showing the manufactured embodied carbon for each step in the procedure may also be presented. In this illustrative example, the melting and trimming steps account for the majority of the embodied carbon for the manufacturing step. Other displays, interfaces, and analyses may be provided to the user, as would be readily understood by one of ordinary skill in the art upon reading this disclosure.

[0056] FIG. 4 illustrates a computing system 400 that may be configured to function as the design system 104 of FIG. 1 , according to an example embodiment. For example, the computing system 400 may be a database node, a server, a cloud platform, a user device, etc. In some embodiments, the computing system 400 may be distributed across multiple devices. Referring to FIG. 4 , the computing system 400 includes a network interface 410, a processor 420, an output 430, and a storage device 440 (e.g., in-memory). Although not shown in FIG. 4 , the computing system 400 may also include or be electronically connected to other components (e.g., a display, an input unit, a receiver, a transmitter, a persistent disk, and the like). The processor 420 may control the other components of the computing system 400.

[0057] The network interface 410 may transmit and receive data via the Internet, a private network, a public network, an enterprise network, etc. The network interface 410 may be a wireless interface, a wired interface, or a combination thereof. The processor 420 may include one or more processing devices, each including one or more processing cores. In some examples, the processor 420 is a multi-core processor or multiple multi-core processors. Furthermore, the processor 420 may be fixed or reconfigurable.

[0058] The output 430 may output data to an embedded display of the computing system 400, an externally connected display, a display connected to the cloud platform, another computing device (e.g., a display used with the user device 102 and / or a display used with the design data source 110), and the like. For example, the output 430 may include a port, interface, cable, wire, board, and / or the like having input / output capabilities. The network interface 410, the output 430, or a combination thereof may interact with applications running on other devices. The storage device 440 is not limited to a particular storage device and may include any known memory device (e.g., RAM, ROM, hard disk, and the like), which may or may not be included in a cloud environment. The storage device 440 may store software modules or other instructions that may be executed by the processor 420 to implement the methods 200, 250, and 280 shown in FIG. 2 .

[0059] According to various embodiments, processor 420 may receive an image containing a geometric design of a part. This image may include a technical model, such as CAD, or the like. Processor 420 may be configured to analyze the technical model to perform the processes described herein. Additionally, output 430 may output information regarding various embodied carbon methods of manufacturing the part to a user interface.

[0060] As will be understood from the foregoing specification, the above-described examples of the present disclosure may be implemented using computer programming or computer engineering techniques, including computer software, firmware, hardware, or any combination or subset thereof. Any of the resulting programs having computer-readable code may be embodied or provided in one or more non-transitory computer-readable media, thereby creating a computer program product (i.e., article of manufacture) in accordance with the described examples of the present disclosure. For example, the non-transitory computer-readable medium may be, but is not limited to, a fixed drive, a diskette, an optical disk, a magnetic tape, a flash memory, an external drive, a semiconductor memory (e.g., read-only memory (ROM), random access memory (RAM)), and / or any other non-transitory transmission and / or reception medium (e.g., the Internet, cloud storage, the Internet of Things (IoT), or other communications network or link). An article of manufacture containing the computer code may be made and / or used by executing the code directly from one medium, by copying the code from one medium to another, or by sending the code over a network.

[0061] Computer programs (also referred to as programs, software, software applications, "apps," or code) may include machine instructions for a programmable processor and may be implemented in a high-level procedural programming language and / or an object-oriented programming language, and / or an assembly / machine language. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, cloud storage, Internet of Things, and / or device (e.g., magnetic disk, optical disk, memory, programmable logic device (PLD)) used to provide machine instructions and / or data to a programmable processor (this includes machine-readable media that receive machine instructions as machine-readable signals). However, "machine-readable medium" and "computer-readable medium" do not include transitory signals. The term "machine-readable signal" refers to any signal that can be used to provide machine instructions and / or any other type of data to a programmable processor.

[0062] The above process descriptions and illustrations should not be construed herein as implying a fixed order in which the process steps are performed. Rather, the process steps may be performed in any order possible, including performing at least some steps simultaneously. While the present disclosure has been described in connection with specific examples, it should be understood that various changes, substitutions, and modifications apparent to those skilled in the art may be made to the embodiments of the present disclosure without departing from the spirit and scope of the present disclosure, as set forth in the appended claims.

Claims

1. 1. A computing system comprising: The computing system includes a processor, the processor comprising: receiving a computer-aided design (CAD) model and a request to perform an analysis of at least a first part described by the CAD model; receiving information identifying a manufacturing scenario, the scenario including process group, factory location, and material selection results; calculating embodied carbon for the manufacturing scenario based on the information identifying the manufacturing scenario, the embodied carbon including material embodied carbon, process embodied carbon, and total process embodied carbon; presenting information associated with the embodied carbon of the manufacturing scenario to a user; and configured to: Computing system.

2. The processor further comprises: The computing system of claim 1 configured to store the information associated with the embodied carbon of the manufacturing scenario.

3. The processor further comprises: receiving information identifying a second manufacturing scenario associated with the at least first part, the second manufacturing scenario including information updating values ​​for at least one of (i) the process group, (ii) the factory location, and (iii) the material; calculating a second embodied carbon for the manufacturing scenario based on the information identifying the second manufacturing scenario, the second embodied carbon including a second material embodied carbon, a second process embodied carbon, and a second total process embodied carbon; presenting to a user information associated with the second embodied carbon of the second manufacturing scenario; and configured to: The computing system of claim 2 .

4. The processor further comprises: The computing system of claim 3 , configured to store the information associated with the second embodied carbon of the second manufacturing scenario.

5. The processor further comprises: The computing system of claim 1 , configured to calculate an estimated cost of producing the at least first part using the manufacturing scenario based on the information identifying the manufacturing scenario.

6. The processor further comprises:

5. The computing system of claim 4, configured to generate an interface for display to a user operating a user device comparing the embodied carbon in the manufacturing scenario and the second manufacturing scenario.

7. The processor further comprises: automatically determining at least a first alternative material compatible with the at least first part based on the information identifying the manufacturing scenario; generating an interface for display to a user operating a user device, the interface presenting information associated with the at least first alternative material; The computing system of claim 1 configured to:

8. The processor further comprises:

8. The computing system of claim 7, further configured to receive from the user a selection of the at least a first alternate material and a request to create a further manufacturing scenario, the further manufacturing scenario including the process group, the factory location, and the selection of the at least a first alternate material.

9. The processor further comprises:

10. The computing system of claim 8, configured to generate an interface for display to a user operating a user device comparing the embodied carbon in the manufacturing scenario and the further manufacturing scenario.

10. 1. A method of operating a design system, comprising: receiving a computer-aided design (CAD) model, the CAD model describing at least a first part; receiving a request to perform an analysis of the at least a first part; receiving information identifying a manufacturing scenario, the scenario including selected process groups, selected factory locations, and selected materials; calculating embodied carbon for the manufacturing scenario based on the information identifying the manufacturing scenario, the embodied carbon including material embodied carbon, process embodied carbon, and total process embodied carbon; causing information associated with the embodied carbon of the manufacturing scenario to be displayed to a user; A method comprising:

11. storing the information associated with the embodied carbon of the manufacturing scenario. The method of claim 10 further comprising:

12. receiving information identifying a second manufacturing scenario associated with the at least first part, the second manufacturing scenario including information updating values ​​for at least one of (i) the process group, (ii) the factory location, and (iii) the material; calculating a second embodied carbon for the manufacturing scenario based on the information identifying the second manufacturing scenario, the second embodied carbon including a second material embodied carbon, a second process embodied carbon, and a second total process embodied carbon; causing information associated with the second embodied carbon of the second manufacturing scenario to be displayed to a user; The method of claim 11 further comprising:

13. storing the information associated with the second embodied carbon of the second manufacturing scenario. The method of claim 12 further comprising:

14. calculating an estimated cost of producing the part using the scenario based on the information identifying the manufacturing scenario; The method of claim 10 further comprising:

15. generating an interface for display to the user comparing the embodied carbon of the manufacturing scenario with the embodied carbon of the second manufacturing scenario; The method of claim 13 further comprising:

16. automatically determining at least a first alternative material compatible with the at least a first part based on the information identifying the manufacturing scenario; generating an interface for display to a user operating a user device, the interface presenting information associated with the at least a first alternative material; The method of claim 10 further comprising:

17. receiving from the user a selection of the at least a first alternate material and a request to create a further manufacturing scenario, the further manufacturing scenario including the process group, the factory location, and the selection of the at least a first alternate material; 17. The method of claim 16, further comprising:

18. generating an interface for display to a user operating a user device comparing the embodied carbon of the manufacturing scenario and the further manufacturing scenario; 20. The method of claim 17, further comprising:

19. causing information associated with the manufacturing scenario to be transmitted to a manufacturer for use in manufacturing the part. The method of claim 10 further comprising:

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