WO2003079239A2

WO2003079239A2 - Automatic incorporation of material and process standards for optimized dimensional managemenet

Info

Publication number: WO2003079239A2
Application number: PCT/US2003/007192
Authority: WO
Inventors: Michael V. Reasoner
Original assignee: Eltekon Engineered Solutions
Priority date: 2002-03-11
Filing date: 2003-03-11
Publication date: 2003-09-25
Also published as: WO2003079239A3; AU2003253914A1; WO2003079239A8; AU2003253914A8

Abstract

A product design process automatically accesses standardized data during the design process to ensure that material standards, manufacturing process standards, and other associated tolerance standards set forth by the relevant industry are met by the product design. This proactive approach optimizes the design process by satisfying material and manufacturing standards in the early design stages, resulting in significant cost reductions and expedited component design times. Additionally, the process automatically performs a failure analysis and generates a failure occurrence ranking that predicts potential failures per predetermined quantity. The process automatically and continuously adjusts design features until the potential failures-per-predetermined quantity is less than an associated failure limit. Thus, the process automatically generates an optimized component design that satisfies both the predetermined industry standards and failure limits.

Description

AUTOMATIC INCORPORATION OF MATERIAL AND PROCESS STANDARDS FOR OPTIMIZED DIMENSIONAL MANAGEMENT

BACKGROUND OF THE INVENTION This invention relates to a method for streamlining component design processes by automatically incorporating material and process standards to optimize dimensional management.

Designing a new component can be a time consuming and expensive process. Even redesigning an existing component for a different application involves significant cost and time requirements. Often several design iterations are required before a component meets the minimum design requirements. Potential component areas of failure during this design process are not mathematically identified and/or automatically ranked according to order of importance. Thus, design changes made during this design iteration process are often guesses made by engineers. For example, one potential component area of failure can be affected by many different tolerance ranges called out for that specific area of the component. Should all tolerance ranges be adjusted, should only certain tolerances be changed and if so, which ones should be changed? These questions are difficult to answer.

Often, to eliminate a potential area of failure, all tolerance ranges are identified as critical and are narrowed, which significantly increases component cost and inspection time. Further, if all or some of the tolerance ranges are narrowed, certain manufacturing processes might not even be able to achieve these ranges. Thus, it is desirable to have a method that identifies, in a mathematical output format, which tolerances should be changed to eliminate or reduce the affects of the potential component area of failure.

Even w hen a final d esign i s a chieved, t his d esign m ay n ot b e t he o ptimal design from a material cost or inspection investment aspect. Further, the final design may not take into account tolerance and material specifications that are standardized for different manufacturing or material processes, h other words, even though a design may meet all of the fit, form, and function requirements there may be additional design improvements that will be required to achieve certain manufacturing or material processing standards. Traditionally, engineers have guessed at tolerances that are relative to any manufacturing or material process such as injection molding, die casting, stamping, machining, powdered metal, rubber extrusion, rubber curing, etc. There is information available to engineers through suppliers, engineering societies, and other similar sources, for tolerance standards for these manufacturing and material processes. However, obtaining this information from the respective source and properly utilizing, maintaining, and updating this information across the industry is difficult.

Further, in a traditional design process, the engineer is not only guessing at the tolerance itself but is also guessing at a proper dimensional orientation for each tolerance. Tool makers, injection molders, and part suppliers are attempting to achieve these speculative tolerances as well as trying to achieve these tolerances in a dimensional orientation that may not be optimal for the component design. Thus, the step of determining the equations, tolerances, and dimensional orientation is a critical step for design optimization for the failure mode effects analysis and final component outputs. If this critical step is done incorrectly with tolerances selected without manufacturing considerations, then the optimization cycle for the failure mode effects analysis and the final outputs for the designed component may not be achievable by the selected manufacturing process, i.e. the tolerances may be tighter than what the manufacturing process can deliver.

Thus, it is desirable to provide a method and apparatus that optimizes component design by automatically incorporating industry tolerance, material, and process standards to reduce design time and cost, as well as overcoming the other above-mentioned deficiencies with current methods.

SUMMARY OF THE INVENTION

The subject design process satisfies predetermined industry standards to optimize dimensional management by automatically linking to standardized reference data for material standards, manufacturing standards, tolerance tables, and other s imilar r eference material. B y u sing t his r eference m aterial i n e arly d esign stages, product design time and cost is significantly reduced. In one disclosed embodiment, the method includes the following steps. A set of output equations is generated to define fit, form, and function for a component that has a plurality of component characteristics. The component characteristics can include material, manufacturing process, or other similar characteristics. The output equations are entered into a computer readable medium via an input device associated with a microprocessor and are stored in an electronic format. An initial dimensioning scheme is determined for the component based on the output equations. A plurality of component dimensions are identified and a tolerance range is associated with each component dimension. The initial dimensioning scheme is also stored in an electronic format. At least one reference table is automatically accessed via an electronic link after the initial dimensioning scheme has been determined. The reference table includes a plurality of standardized data relating to at least one of the component characteristics. A numerical value is assigned to at least one of the tolerance ranges based on the standardized data to generate an initial set of component tolerance ranges that satisfy predetermined industry standards.

In one embodiment, the step of accessing the reference table data can be selectively bypassed under certain predetermined conditions. If a bypass attempt is made, a security measure is automatically activated. The security measure requires the steps of manually entering a predetermined identifier, comparing the predetermined identifier to a predetermined secured identifier, and permitting the bypass w hen t he c omparison o f t he p redetermined i dentifier t o t he p redetermined secured identifier satisfies a predetermined condition.

In one embodiment, a failure analysis is automatically performed to generate a failure occurrence ranking indicating a potential number of failures per predetermined quantity for each output. The initial set of component tolerance ranges is automatically and continuously adjusted such that each potential number of failures per predetermined quantity is less than an associated failure limit for each output. Thus, an optimized set of tolerance ranges is automatically g enerated that satisfies both predetermined industry standards and the associated failure limit for each output. These and other features of the present invention can be best understood from the following specifications and drawings, the following of which is a brief description.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 is a perspective view, partially cut away, of an exemplary component designed according to the subject invention.

Figure 2 is a cross-sectional view of the component shown in Figure 1 including a dimensional tolerance designation. Figure 3 is an example of an occurrence table.

Figure 4 is an example of a design for failure mode and effects analysis (DFMEA) output generated by the subject invention.

Figure 5 is an example of a table defining severity evaluation criteria.

Figure 6 is a flowchart for the subject inventive method. Figure 7 is a flowchart for the bypass function.

Figure 8 is one example of industry standardized reference data.

Figure 9 is another example of industry standardized reference data.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT The subject invention is directed toward a method for streamlining component design processes by automatically incorporating predefined industry standards into a component design. The subject invention relates to the method and apparatus for dimensional design management disclosed in co-pending application 10/177,275 filed on June 21, 2002 and herein incorporated by reference. The subject invention can also be utilized with a method for automatically determining product inputs by optimizing dimensional management in a design process disclosed in co-pending application 10/346,440 filed on January 17, 2003 and herein incorporated by reference.

An example of a component assembly that is designed according to the subject invention is shown in Figure 1. It should be understood that this assembly, as shown in Figure 1, is simply one example of a component that could be designed according to the subject invention, as the subject inventive design process could be used to design any mechanical, electrical, or electro-mechanical component or could be used for civil engineering projects. Further, it should be understood that the subject inventive design process could be used to design a single component having component outputs specific to the component or could be used to design a component assembly or sub-assembly having component outputs specific to individual components in the assembly and/or component outputs specific to the overall assembly.

The component assembly of Figure 1 shows a retaining mechanism 10 including a housing 12 and retaining pin 14. The housing 12 includes a central bore 16 that receives the pin 14. The bore 16 includes an increased diameter portion 18 that transitions to narrower diameter portions 20 on either side of the increased diameter portion 18. The retaining pin 14 includes a longitudinal body 22 with a resilient center flange portion 24 extending out radially from the body 22. As the retaining pin 14 is pushed into the bore 16, the flange portion 24 snaps into the increased diameter portion 18 such that the pin 14 cannot be easily withdrawn from the bore 16.

An initial dimensioning tolerance scheme for the retaining mechanism 10 is shown in Figure 2. The initial dimensioning tolerance scheme includes a plurality of initial dimensional tolerances TOL1, TOL2, TOL3, TOL4, TOL5 that are defined as inputs. When a component, such as the retaining mechanism 10, is to be designed or redesigned there are basic rules that are required. Rules can vary according to design requirements and design needs, and are tied to the inputs. These rules preferably include contribution, sensitivity, occurrence, and severity evaluations. These rules are used to define significant characteristics (SCs) and critical characteristics (CCs) for inputs. These SCs and CCs are linked to the production world for inspection procedures, manpower planning, and level of risk evaluations.

Further, each SC and CC has a specific Contribution requirement and/or Sensitivity requirement that must be met. As is well known in the art, Contribution relates to tolerance and Sensitivity relates to magnitude. Preferably, to qualify as either a SC or CC, predetermined Contribution and Sensitivity requirements should be m et, h owever, it s hould b e u nderstood t hat q ualification as a S C or C C c ould involve simply meeting one of a Contribution or Sensitivity requirement. The discussion below describes SCs and CCs that must meet both Contribution and Sensitivity requirements simply as one example.

These Contribution and Sensitivity requirements are statistical evaluations and are defined by ranges or limits. To qualify as an SC for a dimension "x" identified by one of the rules, an example set of criteria may include the following: a Contribution of 60% > x > 30%; a Sensitivity of .6 > x > .3; and a defective parts per million (DDPM) > 1000. To qualify as a CC for dimension "x," an example set of criteria may include the following: a Contribution of x > 60%; a Sensitivity of x > .6; and no DDPM requirement for qualification. Once the list of SCs and CCs is determined, the design outputs for the component are determined for modeling. For example, if the component is a retaining mechanism, the outputs can include snap-in, engagement requirements, low lash, minimum clearance for all features, overall packaging size, etc. These outputs can be mathematically determined or graphically determined based on the various tolerances, i.e. inputs, of different dimensions of the component. These outputs can be any fit, form, or function of the component.

Preferably, the outputs are mathematically determined with equations being derived for each of the outputs based on the initial dimensioning tolerance scheme. Examples o f s everal o utputs O UTA, O UTB, O UTC a re s hown i n F igure 2. T he equation for determining OUTA is as follows:

Once the equations are determined and entered into the program along with the SCs and CCs requirements for the inputs, a mathematical engine generates a Contribution and a Sensitivity calculation for each input and generates a Defective Parts Per Million (DPPM) or Defective Parts Per Opportunity (DPPO) calculation for each output. These calculations are statistical determinations that are made by methods well known in the art and will not be discussed in detail. The Sensitivity and C ontribution c alculations a re c ompared t o t he s pecified S C a nd C C r ules for each of the inputs and the specified DDPM rules for each output. This comparison is then used to determine whether the input meets the definition of a SC or a CC, or to determine whether the input does not qualify for either a SC or CC. The following example shows how this determination is made. The discussion below describes SCs and CCs that must meet both Contribution and

Sensitivity requirements simply as one example, it should be understood that qualification as a SC or CC could involve simply meeting one of a Contribution or Sensitivity requirement.

Assume that the SC for a certain dimension "x" is defined by a Contribution of 60% > x > 30%, a Sensitivity of .6 > x > .3, and a DDPM > 1000. Also assume that the CC for dimension "x" is defined by a Contribution of x > 60% and a Sensitivity of x > .6. It should be understood that "x" can be any specified dimension that is related to the tolerance inputs used to determine the outputs. Also assume that OUT A, OUTB, and OUTC each include tolerances that affect the dimension "x". The mathematical engine uses the SC, CC, and equations to generate a Contribution and Sensitivity calculation for each of the tolerances TOL1, TOL2, TOL3, TOL4, TOL5, and a DDPM calculation that affects each output equation. An example of the math modeling outputs is as follows:

OUTA

Contribution of TOL1 is 65% Sensitivity ofTOLl is .7 DPPM₍OUTA) = 1000

OUTB

Contribution of TOL3 is 40% Sensitivity of TOL3 is .35

OUTC

Contribution of TOL2 is 25% Sensitivity of TOL2 is .1 DPPM₍ouτc) = 10 Based on the SC and CC definitions above, TOL1 for OUTA would qualify as a CC because the Contribution of 65% is greater than 60% and the Sensitivity of .7 is greater than .6. TOL3 for OUTB would qualify as a SC because the Contribution of 60% is greater than 30% but less than 60%, the Sensitivity of .35 is greater than .3 but less than .6, and the DPPM is greater than 1000. TOL2 for OUTC would not qualify as either a SC or CC because the Contribution of 25% is less than 30%, the Sensitivity of .1 is less than .3, and the DPPM is less than 1000. Once the DPPM rale has been satisfied, then the Contribution and Sensitivity calculations are performed and reviewed to determine whether the input qualifies as a significant characteristic SC. Thus, the subject invention mathematically identifies SCs and CCs and relates this information directly back to the specific inputs.

The DPPM calculation is compared to a predetermined reference chart to determine risk of failure. The reference chart is known as an Occurrence Table. An example of such a table is shown in Figure 3. Each calculated DPPM number is compared to the table and is assigned a degree of risk. Referring to the example above, for OUTA the DPPM of 1000 is assigned a risk of 4, which indicates that failures would be occasional. The same degree of risk would also be assigned to OUTB. OUTC w ith a DPPM o f 10 i s a ssigned a r isk o f 1 , w hich i ndicates t hat failures would be unlikely. The subject invention then automatically exports the SCs and CCs for each input and the DDPMs for each output into a Design for Failure Mode and Effects Analysis (DFMEA) output comprising a predetermined format. Preferably, this output is generated as an output table that identifies the potential cause(s)/mechanism(s) of failure for each input associated with each output. The table p referably i ncludes t he following c olumns: ( 1) Item Function; ( 2) P otential Failure Mode; (3) Potential Effects of Failure; (4) Severity; (5) Class; (6) Potential Causes/Mechanisms of Failure; and (7) Occurrence. An example of this table output format is shown in Figure 4. It should be understood that this is just one preferred version of the table format and that the table could include fewer or more columns of information as determined by user requirements. It should also be understood that several of the columns indicated above are user defined so the number and description of columns could vary depending upon the user. Further, while an output table format is preferred, the output could be in the form of an output file that could be imported into any desired software program. The output file would include data similar to that described above.

In a typical DFMEA table output format, the Item/Function column lists the outputs in rows, e.g. snap-in, nose engages, low lash, etc. The Potential Failure Mode column is typically user defined in the initial software and lists potential failures relating to the outputs, e.g. does not snap in, nose does not engage, high lash etc. While the Potential Failure mode is typically user defined it can be optionally generated automatically. The Potential Effects of Failure is preferably user defined and includes the result of the potential failures, e.g., component fails to operate, component noise due to vibration etc. The Potential Effects of Failure is preferably a user defined table that is incorporated into the software.

A Severity table is also defined within the software and includes a ranking system use to assign a severity ranking to the outputs. An example of a Severity Evaluation Criteria table is shown in Figure 5. A severity ranking for each output is generated based on occurrence (generated by the DDPM evaluation for each output) to further identify significant characteristics. Critical characteristics typically are not identified/weighted by an occurrence evaluation, however, occurrence is used to mathematically identify significant characteristics by criteria including a contribution with sensitivity weighted by occurrence. In other words, a critical characteristic automatically is assigned a high severity ranking while the severity ranking of a significant characteristic is determined based on occurrence.

An example of some of the user defined columns in table of Figure 5 include "Effects" and "Criteria: Severity of Effect." The severity rules to determine the level of severity and to identify significant characteristics are shown in the "Rules" column and the severity ranking, as determined by the DPPM occurrence, is shown in the "Rank" column. For example, if the severity is 7 and the occurrence is greater than 4, then the input is identified as an SC, assuming any Contribution and Sensitivity requirements that may apply have also been met. The severity ranking of 7 is described as having a "High" effect. CCs typically do not need to meet an occurrence requirement. If CC requirements are met, then based on the table of Figure 5, the associated output would automatically be assigned a 9 or 10 ranking in severity. The severity ranking of the SCs are weighted by the occurrence as shown in the "Very High" to "Low" range in the table. Thus, each output having SC identified inputs is given a severity ranking based on certain Contribution, Sensitivity, and occurrence requirements.

The Class column shows the designation of CC, SC, or neither SC nor CC, i.e. blank, for each input associated with each output. The Occurrence column is a failure/severity ranking t hat i s d etermined from t he D PPM and r eference t able a s described above. As described above, the subject invention identifies which inputs are SCs

(weighted by occurrence as determined from DDPMs) and CCs, automatically associates a probability of failure occurrence ranking with each output, automatically determines which inputs are the most influential to the outputs, and automatically exports these results into the desired DFMEA table format. The Potential Causes/Mechanisms of Failure column includes the listing of the most influential inputs associated with each of the outputs. The determination of which inputs are influential is based on which inputs are identified as SCs and CCs and what the associated occurrence rank is. The subject invention has the option of listing every input associated with every output in the Potential Causes/Mechanisms of Failure column, however, to minimize the output to the DFMEA table the subject invention preferably determines which inputs are most influential to each output and only lists the inputs in the DFMEA table that have the most influence on the associated output, including all CCs and using the DPPM as the distinguishing factor for the SCs. The subject invention further automatically assigns a predetermined cause of failure level to each of the inputs listed in the Potential Causes/Mechanisms of Failure column. An example of one predetermined cause of failure level identification system uses two levels to identify the inputs that may require tolerance changes and assigns a Level 2 or Level 1 designation. The requirements that define when a Level 2 or Level 1 designation is appropriate are predefined and can vary depending upon the component and the type of application the component or component assembly is being used in. For example, in the DFMEA table shown in Figure 4, the most influential input for the nose snap-in output is TOL4, which has been determined to be a CC with an occurrence ranking of 4. Further, TOL4 has been designated as a Level 2. Another input that affects the nose snap-in output is TOL1, which is designated as a Level 1 and does not qualify as either a CC or SC. Also since the output has a low occurrence ranking and no input qualified for SC or CC, the subject invention can optionally not list this input as an influential input since the occurrence value in conjunction with contribution and/or sensitivity do not satisfy the given rules.

For every tolerance/dimension input that is in an output equation, a SC/CC identifier will be assessed for qualification, an occurrence ranking will be assigned for the output, a Level 1 or 2 designation will be assigned, and a severity value will be assessed for the output based on the SC/CC/ occurrence evaluations. Not every Level 1 or 2 will be designated as a CC or SC and not every input will necessarily be shown for each output. As described above, while the subject invention does determine the SC, CC, DPPM and associated severity value, and predetermined cause of failure level, not all of this information is necessarily shown in the DFMEA output table. To reduce the number of rows displayed in the table, the subject invention automatically identifies which inputs are the most influential for each output. There may be two influential inputs, ten influential inputs, or only one influential input for any one of the outputs. Thus, the number of rows listing inputs associated with an output may vary for each output, i.e. nose snap-in may have three rows while lash may only have one row.

Thus, the subject invention automatically ties occurrence of output to the SC and CC inputs and to severity, which makes it easy to determine which dimension/tolerances inputs could be revised to reduce the occurrences. For example, because TOL4 was identified as a CC with an overall occurrence of 4 for the nose snap-in output, to reduce the occurrence TOL4 can be changed, the component can be selectively re-dimensioned, the output spec can be increased, or a design change may be implemented to possibly reduce the occurrence level associated with nose snap-in. If a simple change is made, i.e. TOL4 is made tighter, then the same nose snap-in output equation is used. The mathematical engine recalculates, automatically identifies the influential inputs, and automatically exports this information to the DFMEA table output or into an output file for importation into a d esired s oftware program. If a m ore c omplicated c hange is m ade, i .e. t he component is re-dimensioned or changed, then the equations for the output equations m ay h ave t o be r e-determined b ased on t he n ew d imensioning s cheme. Once this is done, the mathematical engine re-calculates, automatically identifies the influential inputs, and automatically exports this information to the DFMEA table output or into an output file for importation into a desired software program. Based on the information supplied in the DFMEA, the component design can be optimized to reduce cost. Thus, the subject invention optimizes specifications and dimensioning schemes to achieve the least amount of variation for a component or component assembly design and documents this through the DFMEA. The information generated during the design optimization process can also be used to create template drawings in addition to identifying CCs and SCs in relation to the specific dimensioning scheme.

In the past, SCs and CCs were randomly selected based on historical data, personal experience, etc. These arbitrary designations of SC and CC for multiple inputs in a component or component assembly resulted in increased manufacturing costs and time/cost for inspection. To be able to mathematically identify which dimension inputs are actually SCs and CCs is a huge cost savings. To further be able to automatically associate each input with a risk associated to the outputs (i.e. occurrence) and to automatically generate a DFMEA output table incorporating this information significantly reduces design time while also providing a more accurate DFMEA based upon mathematical principles which is used by manufacturing to generate a more robust process and safer assembly procedures.

Predetermined input parameters, such as available packaging space and/or general fit, form, and function requirements, are specified for a component. Designers and engineers then determine the design specifics for the component based on these input parameters. Once the supplier has gone through the process described above, the input parameters can be easily accommodated and can be changed/varied to accommodate similar components for similar applications. The information such as the optimized output equations, occurrence levels, and optimized dimensions can then be exported into a window-based program to solve for t he i nputs. I nputs are u ser i dentified and c an i nclude i nputs s uch a s b olthole diameter, overall component length, etc. Then certain dimensions or input parameters can be selectively modified to determine the effect on the inputs. Or, optionally, the inputs can be selectively modified to determine the effect on the inputs.

Further, the subject invention automatically accesses standardized data during the design process to ensure that material standards, manufacturing process standards, and other associated tolerance standards set forth by the relevant industry are met by the product design. This proactive approach optimizes the design process by satisfying material and manufacturing standards in the early design stages, resulting in significant cost reductions and expedited component design times.

This unique dimensional management process is outlined in Figure 6. As discussed above, certain initial predetermined rules, requirements, and data for the component design are entered into the program via an input device 30 to begin the dimensional management process at 40. Next, as discussed above, the dimensional scheme is optimized and any SCs or CCs are identified at 50. Then, for each output, a range is determined based on the TOL ranges for each tolerance/dimension used in the equation for that output. Thus, the ranges are determined mathematically based on the equations that were optimized during the process described above. The range establishes the upper and lower worst case limits.

During the optimization process, the system automatically links to industry standardized reference data at 60. This data, which will be discussed in greater detail below, includes material, manufacturing process, and associated tolerance information that has been accepted across the relevant industry. The data is used to help set tolerance ranges at 70 so that once the optimization process has been completed, the component will not only have an optimized design but will also meet all material and process standards for manufacturing purposes. Once the tolerance range is determined, then the equations can be re-written to solve for the inputs at 80.

Example: A component has been designed according to the above process and the overall length was 500 mm. Now the user wants the same component but wants the component to be 600 mm in overall length. The equations can be automatically re-calculated with an overall length of 600 mm to identify potential causes/mechanisms of failure.

In the past, the ranges were determined by guessing, which could result in a combination of equations that may not have a solution. The subject invention automatically determines the appropriate industry standardized reference data for each respective range and automatically links to that data so that manufacturing and material standards are taken into account for range selection. Further, the subject invention uses this data and automatically and mathematically establishes the ranges to result in a combination of equations that can be re-written to solve for the inputs. These equations and ranges can be incorporated into a user interface at 90, such as a windows based program, where a user can selectively modify dimensions, inputs, or outputs to determine overall effect on potential risks of failure.

Further, once the dimensions of the component have been optimized, the data can be exported into a computer aided drafting (CAD) based drawing program 100 to automatically draw the component at 110. The component can be drawn in three- dimensional solid modeling format or wireframe format. It should be understood that any type of microprocessor 112 can be used to compile the input data, generate the desired output and tolerance range information and transmit the information to an output device 114 such as the user interface or CAD system.

Under certain situations, it may be desirable to bypass the step of automatically accessing the standardized reference data. If a bypass request is entered by a user than a security process is activated. This is shown in greater detail in Figure 7. An initial dimensioning scheme is determined with an initial set of tolerances at 120. There is an automatic link to the appropriate standardized data at 130. A bypass request, indicated at 140, can be initiated either prior to the automatic link or in response to the automatic link. Once the bypass request is initiated, a security measure is activated at 150. The security measure could be a password requirement, approval from a manager, or other similar measure. Once the security measure has been satisfied, the user can simply enter a tolerance range or have a range automatically entered that may not meet an industry standard range at 160. If the bypass is not initiated, the process proceeds with setting the tolerance range based on industry standards at 170. Once the initial range is determined the process continues with optimization at 180, i.e. the tolerance range can be further refined in response to failure analysis or component redesign requests. The method for automatically incorporating the predetermined industry standards to optimize dimensional management in the design process includes the following steps. The initial set of output equations is generated to define fit, form, and function for the component. The component has a plurality of predetermined component characteristics. These characteristics include the material that will be used to form the component, the manufacturing process, which will be used to make the component, and other similar characteristics known in the art. As discussed above, the initial dimensioning scheme for the component will be determined based on the output equations and will include identification of a plurality of component dimensions with a tolerance range associated with each component dimension. An electronic link to at least one reference table will be automatically accessed to assist with tolerance range determination. The reference table will include a plurality of standardized data relating to at least one of the component characteristics. A numerical value is then assigned to the tolerance ranges based on the standardized data to generate an initial set of component tolerance ranges that satisfy predetermined industry standards.

Examples of different types of ISO standardized reference data are shown in Figures 8 and 9. Figure 8 shows a tolerance table for dimension ranges with associated grades o f t olerances. Figure 9 s hows an e quivalence t able for s urface roughness scales. The data from these tables is automatically accessed, when appropriate, and i s u sed t o s et b ase t olerance r ange v alues. T he t ables shown i n Figures 8 and 9 are simply examples, it should be understood that the industry standardized reference data could also include other similar types of data known in the art.

For example, one of the predetermined component characteristics is the manufacturing process that will be used to make the component. One of the reference tables will include tolerance data that is achievable by the manufacturing process. Another example of a component characteristic is the material that will be used to form the component. The reference data will include a material standards table with a plurality of tolerance ranges specific to the predetermined material. The subject invention will automatically identify at least one appropriate reference table for each of the component characteristics. A numerical value will be assigned to all of the tolerance ranges based on the standardized data to generate the initial set of component tolerance ranges that satisfy predetermined industry standards.

As discussed above, failure analysis is also performed to identify potential critical areas of component failure. The initial set of component tolerance ranges is automatically adjusted to reduce the number of potential critical areas of component failure. For example, a failure occurrence ranking is generated that indicates a potential number of failures per predetermined quantity for each output. The initial set of component tolerance ranges is automatically and continuously adjusted such that each potential number of failures per predetermined quantity is less than an associated failure limit for each output. Thus, an optimized set of tolerance ranges is generated that satisfies both the predetermined industry standards and the associated failure limit for each output.

Once an initial set of optimized tolerance ranges is generated, adjustments can be made to solve for the inputs. The method for automating inputs includes the following steps. All fit, form, and function equations, i.e., the output equations including output and input variables with the best dimensioning scheme determined, should be generated according to the process described above. This best dimensioning scheme should then be applied to a print, i.e. engineering drawing, of the component. The best dimensioning scheme is determined through the least variation added to the fit, form, and function equations, which is determined and verified as the equations are being written according to the process detailed above.

Next, users need to define a set of modifiable inputs that will drive automation. These modifiable inputs are inputs that can be changed or varied such as hole size or component thickness, for example, to accommodate an increase/decrease in component size for light/heavy duty applications, respectively, or to accommodate changes in overall packaging size. Then, based on engineering experience, successful "nominal" limits should be determined for each nominal fit, form, and function equation, i.e. output equation. In other words, from the list of output equations determined above, the user defines what "nominal" is the desired value for the specific output equation. The estimated nominal ranges are then automatically established for the output equations with the "nominal" value preferably being at the center of the range. Once the nominal limits or ranges are applied, the user must proceed with the following steps. First, the user should determine what nominal output limits can be met at one time (simultaneous equations). If all of the nominal output limits cannot be met with simultaneous equations, then the user must determine which nominal output limits can be shifted to allow for the simultaneous equations to be solved. Second, the user should determine how many nominal inputs are still undefined due to lack of equations, i.e., how many nominal inputs are undefined because there are not enough equations to solve for all of the nominal inputs. Third, based on previous engineering experiences and experiences with successful component/assembly r elationships, the u ser must e stablish g eometric r elationships between the nominal inputs until each undefined nominal input can be defined through the equations. The program will automatically prompt the user to enter these specific relationships. It should be understood that these relationships are additional output equations that are needed to solve for the remaining unidentified nominal inputs but were not necessarily identified in the output equation process explained above. These additional output equations are referred to here as geometric relationships simply for identification purposes.

With any realistic changes to the defined modifiable inputs, all nominal input dimensions can now be automated once the steps described above have been successfully performed. The user must then add tolerances to each of the automated nominal values and run the fit, form, and function calculations to determine acceptable tolerances for each value.

Although a preferred embodiment of this invention has been disclosed, a worker of ordinary skill in this art would recognize that certain modifications would come within the scope of this invention. For that reason, the following claims should be studied to determine the true scope and content of this invention.

Claims

1. A method for automatically incorporating predetermined industry standards to optimize dimensional management in a design process comprising the steps of:

(a) generating a s et o f o utput e quations to d efine fit, form, and function for a component having a plurality of component characteristics and storing the output equations in an electronic format;

(b) determining an initial dimensioning scheme for the component based on the output equations of step (a) including identifying a plurality of component dimensions, associating a tolerance range with each component dimension, and storing the initial dimensioning scheme in an electronic format;

(c) automatically accessing an electronic link to at least one reference table including a plurality of standardized data relating to at least one of the component characteristics during step (b); and

(d) assigning a numerical value to at least one of the tolerance ranges based on the standardized data accessed during step (c) to generate an initial set of component tolerance ranges that satisfy predetermined industry standards.

2. The method of claim 1 including the step of selectively bypassing step (c) under certain predetermined conditions.

3. The method of claim 2 including the step of activating a security measure when an attempt to bypass step (c) is made.

4. The method of claim 3 wherein activation of the security measure further requires the steps of manually entering a predetermined identifier, comparing the predetermined identifier to a predetermined secured identifier, and permitting a bypass of step (c) when the comparison of the predetermined identifier to the predetermined secured identifier satisfies a predetermined condition.

5. The method of claim 4 including the step of requiring entry of the predetermined identifier each time a bypass is requested.

6. The method of claim 4 wherein the predetermined identifier is a pre- assigned password unique to each user and the predetermined secured identifier comprises a list of acceptable passwords.

7. The method of claim 1 wherein one of the component characteristics comprises at least one manufacturing process used to produce the component and the at least one reference table set forth in step (c) further comprises at least one tolerance table including at least one tolerance range that is achievable by the manufacturing process.

8. The method of claim 1 wherein one of the component characteristics comprises at least one predetermined material used to form the component and the at least one reference table set forth in step (c) further comprises at least one material standards table including a plurality of tolerance ranges specific to the predetermined material.

9. The method of claim 1 further including the step of automatically identifying at least one appropriate reference table for each of the component characteristics prior to step (c).

10. The method of claim 1 wherein step (d) is automatically performed without user input.

11. The method of claim 1 wherein step (d) further includes assigning a numerical value to all of the tolerance ranges based on the standardized data accessed during step (c) to generate the initial set of component tolerance ranges that satisfy predetermined industry standards.

12. The method of claim 1 including the step of automatically performing a failure analysis to identify potential critical areas of component failure subsequent to step (d) and automatically adjusting the initial set of component tolerance ranges to reduce the number of potential critical areas of component failure.

13. The method of claim 1 including the steps of automatically performing a failure analysis and generating a failure occurrence ranking indicating a potential number of failures per predetermined quantity for each output subsequent to step (d) and further including the steps of (e) automatically and continuously adjusting the initial set of component tolerance ranges such that each potential number of failures per predetermined quantity is less than an associated failure limit for each output; and (f) automatically generating an optimized set of tolerance ranges that satisfy both predetermined industry standards and the associated failure limit for each output.

14. A computer readable medium storing a computer program, which when executed by a computer performs the steps of:

(a) receiving a set of output equations to define fit, form, and function for a component having a plurality of component characteristics; (b) determining an initial dimensioning scheme for the component based on the output equations of step (a) including identifying a plurality of component dimensions and associating a tolerance r ange with each component dimension;

(c) automatically accessing at least one reference table including a plurality of standardized data relating to at least one of the component characteristics during step (b);

(d) assigning a numerical value to at least one of the tolerance ranges based on the standardized data accessed during step (c);

(e) generating an initial set of component tolerance ranges that satisfy predetermined industry standards to optimize dimensional management in a component design process.

15. The computer readable medium of claim 14, which when executed by the computer performs the additional steps of: selectively bypassing step (c) under certain predetermined conditions.

16. The computer readable medium of claim 15, which when executed by the computer performs the additional steps of: activating a security measure when an attempt to bypass step (c) is made.

17. The computer readable medium of claim 16, which when executed by the computer performs the additional steps of: manually entering a predetermined identifier when the security measure is activated; comparing the predetermined identifier to a predetermined secured identifier; and permitting a bypass of step (c) when the comparison of the predetermined identifier to the predetermined secured identifier satisfies a predetermined condition.

18. The computer readable medium of claim 14, which when executed by the computer performs the additional steps of: automatically identifying at least one appropriate reference table for each of the component characteristics prior to step (c).

19. The computer readable medium of claim 14, which when executed by the computer performs the additional steps of: automatically performing step (d) without user input.

20. The computer readable medium of claim 14, which when executed by the computer performs the additional steps of:

(f) automatically performing a failure analysis and g enerating a failure occurrence ranking indicating a potential number of failures per predetermined quantity for each output subsequent to step (e); and

(g) automatically and continuously adjusting the initial set of component tolerance ranges such that each potential number of failures per predetermined quantity is less than an associated failure limit for each output; and

(h) automatically generating an optimized set of tolerance ranges that satisfy both predetermined industry standards and the associated failure limit for each output.