JP5018143B2 - Design support method and system - Google Patents

Description

  The present invention relates to a method and system for supporting design of home appliances, OA products, and the like.

Conventionally, in product design, as a method of quantitatively evaluating the assembly time of component parts, for example, as disclosed in Patent Document 1, a method of analyzing the assembly operation of component parts of a product and calculating the assembly time for each part Has been proposed. This includes the step of previously converting about 50 kinds of assembly operations and the difficulty of assembling attributes, the step of analyzing the assembly operations and attributes of product components, and the analysis data according to equation (1). And an assembling time estimation method including an operation step for calculating the assembling time of each component from the assembling difficulty coefficient and a step for displaying the calculation result.
[Assembly time t _x ] = [t _{operation x} ] × [β _{attribute y1} ] × [β _{attribute y2} ] × (1)
Where t _{operation x} : assembly operation time when there is no attribute
β _{attribute y} : Ratio of the effect of assembly operation on assembly operation time (Assembly difficulty coefficient (attribute))
In addition, as a method for quantitatively evaluating the assembly failure occurrence rate, for example, as disclosed in Patent Document 2, a method of analyzing the assembly operation of product component parts and calculating the assembly failure occurrence rate for each component is proposed. Has been. This includes the step of pre-coefficientizing about 50 kinds of assembly operations and attribute assembly failure potentials, the step of analyzing the assembly operations and attributes of product components, and the analysis data according to equation (2). And an assembly failure occurrence rate estimation method comprising a calculation step of calculating the assembly failure occurrence rate of each part from the assembly failure coefficient, and a step of displaying the calculation result.
[Assembly failure occurrence rate u _x ] = [u _{operation x} ] × [θ _{attribute y1} ] × [θ _{attribute y2} ] × (2)
Here, u _{operation x} : assembly failure occurrence rate when there is no attribute θ _{attribute y} : ratio of influence of assembly operation attribute on assembly failure occurrence rate (assembly failure coefficient (attribute))
In addition, as a method of creating an improvement measure for solving the problem, for example, as described in Non-Patent Document 1, by selecting an item to be improved and a problem generated by the improvement from a binary table, a hint for the improvement measure A method for guiding the described pages has been proposed. This classifies past huge patent cases by items that want to be improved, such as “weight of moving object”, and items that deteriorate due to improvement, such as “intensity of moving object”. This is a summary of how the problem items that occurred in the case were resolved. First, create a binary table with “Improved items” vertically and “Deteriorated items” horizontally, and enter the number assigned to “Solution case” at the intersection. In the separate table, prepare a chart of the number and “solution case”. The designer first searches for a corresponding number from the binary table. Next, the solution case described in the number column is searched. Finally, referring to this solution, create an improvement structure.

JP 2003-39260 A JP-A-10-334151 “Matrix 2003: Updating the TRIZ Contradiction Matrix” (Darrell Mann, Simon Dewulf, Boris Zlotin, Alla Zusman, CREAX Press, Belgium, 2003)

  However, even if the assembly time and assembly failure occurrence rate can be estimated for each part, how does the assembly operation and attributes of the part affect the integrated assembly cost, which is the sum of assembly cost and assembly failure. However, there was a problem that the improvement target element could not be identified. Moreover, even if a part with a long assembly time or a part with a high assembly failure occurrence rate can be identified, a structure plan to improve them could not be created, and there was a case of getting stuck.

  Further, since Non-Patent Document 1 is intended to improve basic performance, it cannot be applied to shorten the assembly time or the assembly failure occurrence rate related to the assembly operation and attributes of specific parts. There was a problem.

  The object of the present invention is to support the creation of improvement measures for shortening assembly time and assembly failure in order to solve the above-mentioned problems, and to determine the priority of assembly time reduction measures and assembly failure reduction measures. It is to provide a design support method and its system.

  To achieve the above object, the present invention provides a design support for extracting an improvement guideline for shortening assembly time and an improvement guideline for reducing assembly defects in a design case targeted for improvement using a design support system. A method, a coefficient indicating the difficulty of assembling each assembly operation and attribute determined in a number of past design cases, a coefficient indicating an assembly failure potential, an assembly operation / attribute, and the assembly operation.・ Collect improvement guidelines for shortening the assembly time of attributes and improvement guidelines for reducing assembly defects and store them as a database of improvement guideline data that are related to each other and expanded hierarchically. Extract elements with long assembly time and elements with high assembly failure rate from parts, assembly operations and attributes, convert them into assembly costs and assembly loss costs, compare the importance, and need improvement To determine the elements, to extract the guidelines to improve this.

  According to the present invention, it is possible to extract improvement guidelines for shortening assembly time and reducing assembly defects by inputting assembly operation analysis data of a product to be improved.

  Embodiments according to the present invention will be described in detail with reference to the drawings.

First, a first embodiment of a design support system according to the present invention will be described.
FIG. 1 is a schematic configuration diagram showing an embodiment of a design support system according to the present invention. The design support system 1 according to the present invention includes an input unit 10, an output unit 20, a calculation unit 30, and a database unit 40. The input means 10 includes a keyboard 11, a mouse 12, and the like. The output unit 20 includes a display 21, a printing unit 22, and the like. The computing means 30 is composed of a CPU 31, a ROM 32, a RAM 33, and an input / output unit. The calculation means 30 and the display 21 constitute extraction extraction means.

  The database unit 40 includes an assembly difficulty coefficient database 41, an assembly time improvement guideline database 43, and an assembly time specific guideline construction database 45. The assembly failure coefficient database 42, the assembly failure improvement guideline database 44, and the assembly failure specific guideline construction database 46 are used in the second and subsequent embodiments. It is not used in this embodiment.

First, the assembly difficulty coefficient database 41, the assembly time improvement guideline database 43, and the specific assembly time guideline database 45 will be described. These databases are constructed in advance from past assembly results of products. FIG. 2 shows a construction flow of the databases 41 and 43 of this embodiment.
1-1. Assembly difficulty coefficient database 41
As shown in Fig. 2, from the assembly operation analysis result of the past product and the time required for the assembly operation, the assembly operation and the difficulty of assembling the attributes that assist / inhibit it are calculated as coefficients. Stored in the difficulty coefficient database 41.

First, in step S311 of FIG. 2, the past assembly operation of the product is analyzed. Here, as shown in FIG. 3, an analysis example of the operation of assembling the switching lever 52 with respect to the casing 51 of a certain electric device is shown. The attributes for assisting / inhibiting the assembling operation and the assembling operation of the casing 51 and the switching lever 52 are shown below.
(1) Move the casing 51 downward and place it on the assembly table.
(2) As shown in FIG. 3 [1], the switching lever 52 is moved downward. At this time, since the housing surface 51a is a design surface, it is necessary to take care not to damage it.
(3) As shown in FIG. 3 [2], the claw arm portion 53 of the switching lever 52 is shaped inward.
(4) As shown in FIG. 3 [3], the switching lever 52 is rotated to put the claw arm portion 53 into the housing 51. At this time, since the housing surface 51a is a design surface, it is necessary to take care not to damage it. Further, it is difficult to see the claw arm portion 53 and the coupling portion 54 inside the casing 51, so care is required.
(5) As shown in FIG. 3 [4], the switching lever 52 is press-fitted into the casing 51. At this time, the three claw arm portions 53 are fitted into the casing 51 at the same time.

As shown in Fig. 4 (a), using about 50 kinds of words and phrases prepared in advance, as shown in Fig. 4 (b), the above assembly operation analysis results are summarized as follows, and assembly operation analysis data And
(1) Part name: The part name is entered in the part / name column 611 as it is. In addition, the number of parts is described in the number field 612.
(2) Assembling operation: The assembling operation of each part is selected from preliminarily prepared assembling operation terms and described in the assembling operation / name column 613 in the order of appearance. Further, the number of repetitions of each assembling operation is described in the repetition number column 614.
(3) Attribute: An attribute associated with each assembling operation is selected from attribute terms prepared in advance and described in the attribute / name column 615. Further, the number of repetitions of each assembling operation is described in the repetition number column 616.

  Note that each part, assembly operation, and attribute used for the assembly operation analysis are collectively referred to as an assembly element.

  Next, in step S312 of FIG. 2, the assembling time for each pasting operation of the past product shown in FIG. 3 is measured. This actual measurement data is added to the operation time column 617 in FIG. Finally, the assembly operation analysis data and the assembly operation time shown in FIG.

  Next, in step S313 of FIG. 2, the design support system 1 calculates individual assembly operations and attribute assembly difficulty coefficients from the input assembly operation analysis data and the assembly operation time. The assembly difficulty coefficient of the assembly operation is determined by statistically calculating the assembly time of each assembly operation on the basis of the downward movement operation (no attribute). In addition, the attribute assembling difficulty coefficient is determined by statistically calculating the assembly time when a specific attribute accompanies each action and determining the ratio of the presence or absence.

The assembly time of the assembly-type product can be calculated as the sum of the assembly time for each component. The assembly time of each part can be calculated as the sum of the assembly times for each part assembly operation. The assembling time of each assembling operation is determined by the assembling operation and attributes. Therefore, the assembly time t _X of the assembly operation x is defined by the following equation.
(Equation 1)
[Assembly time t _x ] = [t _{operation x} ] × [β _{attribute y1} ] × [β _{attribute y2} ] × ・ ・ ・
Where t _{operation x} : assembly operation time when there is no attribute
β _{attribute y} : Ratio of the effect of assembly operation on assembly operation time (Assembly difficulty coefficient (attribute))
Furthermore, in order to dimensionless the assembling operation time t _{operation x,} the most assembling operation time is short the assembling operation time t _{operation x} [lower movement] t set of assembling operation value obtained by dividing _{under 0} The difficulty factor α is defined as _{motion x} .
(Equation 2)
[Assembly operation difficulty coefficient: α _{operation x} ] = [t _{operation x} ] / [t _{lower 0} ]
As shown in FIG. 5, from the assembly operation analysis results in various cases including the case of FIG. 3 and the actual measurement value of the assembly time for each assembly operation, the assembly difficulty coefficient α _{operation x} of the assembly _operation The attribute assembling difficulty coefficient β _{attribute y} is calculated.

First, the lower movement operation time t _{lower 0} that is a reference for estimating the assembly time is calculated by the following equation.
(Equation 3)
t _{lower 0} = (Σt _{lower i} ) / n
Next, an assembly difficulty coefficient α _{operation x} of each assembly _operation is calculated. For example, the assembly difficulty coefficient α _integer shaping operation is calculated by the following. First, the shaping operation time t _{adjustment 0} is calculated by the following equation.
(Equation 4)
t set ₀ = (Σt set _i ) / n
Thus, the assembly difficulty coefficient α _settling of the shaping operation, the following equation.
(Equation 5)
α _adjustment = t _{adjustment 0} / t _{lower 0}
Next, the assembling difficulty coefficient β _{attribute y} of the _{attribute y} is calculated from the ratio of the assembling times depending on the presence or absence of the attribute y. For example, the assembly difficulty coefficient β _meaning of the “design surface present” attribute is _expressed by the following equation.
(Equation 6)
β _meaning = (t ₁ / t ₀ + t ₂ / t ₀ + ...) / n
As described above, the assembly operation and attribute assembly difficulty coefficient can be calculated from the input assembly operation analysis result and the actual measurement data of the assembly operation. These are stored in the assembly difficulty coefficient database of FIG.
By storing the assembly difficulty coefficients for a large number of general products prepared in advance in the assembly difficulty coefficient database 41 in FIG. 2, steps S311, S312 and S313 in FIG. The design support system 1 can be used.

In addition, the assembly operation analysis and assembly operation time measurement are continuously performed, and the data is input to the design support system 1 to increase the number of samples, thereby setting a more reliable assembly difficulty coefficient. be able to.
In addition, when a product or assembly work environment has changed significantly, such as a product with a completely different size or production at an overseas factory, it was in that factory by entering the actual operation data of the assembly of that factory / product. The assembly difficulty coefficient can be set easily.
1-2. Assembly time improvement guideline database 43
As shown in FIG. 2, a generalized guideline for improving the assembly time is extracted for each assembling element and stored in the assembly time improvement guideline database 43. Note that the improvement guidelines for reducing assembly time and the improvement guidelines for reducing assembly defects often overlap, so here the stage for simultaneously extracting the assembly time reduction guideline and the assembly failure reduction guideline and storing them in the database Separate with.

  First, in step S331 of FIG. 2, past assembly time / assembly failure improvement cases are collected. In the “Past assembly time / Assembly defect improvement example” column in FIG. 6 (a), improvement examples of the ventilation fan, VTR, and electric device are shown. The assembly methods before improvement of each product and improvement examples are listed. In step S332 of FIG. 2, as shown in the assembling operation analysis column of FIG. 6A, the parts, assembling operations, and attributes of the collected assembling method before improvement of the collected improvement examples are analyzed. Finally, the past assembly time / assembly failure improvement case and assembly operation analysis data shown in FIG. 6 (a) are input to the design support system 1. Next, in step S333 of FIG. 2, the design support system 1 groups past improvement cases from the input past assembly time / assembly failure improvement cases and assembly operation analysis data.

FIG. 6 (b) shows the grouping result. The procedure is shown below.
(1) The design support system 1 extracts the last element of the input assembly operation analysis data of FIG. 6 (a) as a problem element to be improved.
(2) As shown in FIG. 6 (c), a task element / improvement keyword correspondence table in which task elements and keywords that frequently appear when improving the task elements are previously prepared is prepared. The improvement keywords are words and phrases used when abstracting improvement measures for the same problem element are accumulated in the database together with the problem elements each time. The design support system 1 classifies the input improvement examples shown in FIG. Next, the improvement examples of the same task element are classified by the improvement keywords related to the task element. Finally, as shown in FIG. 6 (b), the classification result is displayed on the display 21 of the design support system 1.
(3) In step S334 of FIG. 2, the designer first corrects the classification result. If there is an improvement case that does not have a corresponding improvement keyword, the designer incorporates it into another similar category. Also, if the classified improvement cases are clearly different from other similar classifications, they are included in a more appropriate classification.

  Next, the designer determines generalized improvement guidelines and specific improvement measures based on the grouped improvement cases. In particular, the improvement guideline is determined not to specify the target technical field so that it can be used in other technical fields. In Fig. 6 (b), for example, "ventilation fan motor" and "positioning bracket", etc., which are the target technical fields, are identified from an improvement example that shortens the assembly time of parts with long assembly time where "rotation" operation is a problem. Instead, group them with a generalized improvement guideline of “Assemble in a straight line”. Further, as a specific improvement measure, “widen fitting component tip”, “narrow fitting component tip” and the like are extracted.

As shown in FIG. 6 (d), the problem elements, the generalized improvement guideline, and the specific improvement measures shown in FIG. 6 (b) are stored in the design support system 1. Here, the improvement guideline regarding the assembly time is stored in the assembly time improvement guideline database 43 of FIG. Further, the improvement guideline regarding the assembly failure is stored in an assembly failure improvement database 44 shown in FIG.
1-3. Assembling time specific guidelines construction database 45
Since the improvement guideline stored in the assembly time improvement guideline database 43 is generalized by the algorithm described above, even if it is extracted by the algorithm described later, a specific image does not appear and it is difficult to judge the quality. Therefore, a specific improvement guideline is constructed by extracting related elements from the input assembly elements and supplementing necessary words and phrases. These algorithms are stored in the assembly time specific guideline construction database 45.

  For example, as an improvement guideline for the rotation operation of the switching lever in FIG. 3, “assemble by straight movement” from the general improvement guideline in FIG. 6 (d) stored in the assembly time improvement guideline database 43 is also a concrete improvement. As measures, it is possible to extract “[1] widen the fitting tip” and “[2] narrow the fitting tip”. However, this is too general and is not sufficient as an improvement guideline. Therefore, first, a phrase (part: switching lever) related to the assembly operation “rotation” is extracted from the assembly operation analysis data shown in FIG.

Using these, concrete improvement guidelines are constructed as follows.
In order to shorten the rotation time of the “switching lever”, the “switching lever” is assembled in a straight line motion.
[1] Widen the fitting end
[2] By narrowing the tip of the fitting part, this is a concrete guideline for generalized improvement: “Assemble in a straight line motion [1] Widen the fitting part tip [2] Narrow the fitting part tip” Can be specified.

  By the way, each database 41, 43, 45 does not need to be collected by the design support system 1, but may be collected by another design support system, transmitted to the design support system 1 via a network, and stored.

Next, in the design support system 1 according to the present invention, a first embodiment for performing an improved design that shortens the assembly time will be described. FIG. 7 is a diagram showing a first embodiment of a design support processing flow in the design support system 1. FIG. 8 shows the result of the assembling time influence index calculated inside the system from the input assembly operation analysis data. FIG. 9 is a diagram showing a first embodiment of the display 21. As shown in FIG. FIG. 10 (a) is a diagram showing an example of an improved structure created based on the improvement guideline displayed on the display 21 and its assembly operation analysis data. Further, FIG. 10 (b) is a diagram showing the improvement effect displayed on the display 21. FIG.
2-1. Assembly Operation Analysis Data Input In step S101 of FIG. 7, assembly operation analysis data is input to the design support system 1. For example, the assembly operation shown in Fig. 3 is analyzed into the parts that make up the product, the assembly operation of each component, and the attributes associated with the operation, and the assembly operation analysis data summarized in a table as shown in Fig. 4 (b) This is input to the design support system 1. In step S102 of FIG. 7, the design support system 1 displays the input assembly operation analysis data on the display 21 as shown in FIG.
2-2. Assembling time influence index calculation In step S103 of FIG. 7, the design support system 1 uses the coefficients of the respective assembly elements stored in the assembly difficulty coefficient database 41 as the coefficients of the respective elements of the input assembly operation analysis data. And the assembly time influence index of parts, assembly operations, and attributes is calculated. The product is composed of a plurality of parts. Parts are assembled by several assembly operations. Further, the assembling operation has an attribute that enables or inhibits this. Therefore, the difference in the assembly time of the entire product due to the presence or absence of these assembly elements is divided by the total assembly time, and a value multiplied by 100 is defined as an assembly time influence degree index.
(1) The difference in assembly time due to the presence or absence of one part can be regarded as the time required due to the presence of that part. Therefore, a value obtained by dividing the time difference by the total assembly time and multiplying by 100 is defined as a component index of the assembly time influence index.
(2) The difference in assembly time due to the presence or absence of one assembling operation can be regarded as the time required because of the assembling operation. Therefore, a value obtained by dividing the time difference by the total assembly time and multiplying by 100 is defined as an assembly operation index of the assembly time influence index.
(3) The difference in assembly time due to the presence or absence of one attribute can be regarded as the time required due to the presence of that attribute. Therefore, a value obtained by dividing the time difference by the total assembly time and multiplying by 100 is defined as an attribute index of the assembly time influence index.

In the case of assembling the switching lever shown in FIG. 3, the assembly time influence index is calculated as follows. Here, the assembly time of the entire product is assumed to be 100 seconds, and the standard part moving operation time t ₀ in this workplace is assumed to be 11 seconds.
(1) Assembling time influence index e of _adjusting operation of switching lever
[1] Switching lever shaping operation time t _adjustment × 2 = t _{down 0} × α _adjustment × 2 = 11 × 1.73 × 2 = 38 seconds
[2] assembling time effect index e _integer = (100- (100-38)) × 100/100 = 38
(2) Assembly time influence index e _times of rotation of the switching lever
[1] Rotating operation time of the switching lever t _{times Opinion} = t _{lower 0} × α _times × β _meaning × β _viewing = 11 × 2.63 × 1 × 1 = 29 seconds
[2] Assembly time influence index e _times = (100- (100-29)) × 100/100 = 29
(3) Assembly time influence index e of _{changeover lever eChangeover lever}
[1] Switching lever assembly operation time t _{Switching lever} = t _{Lower 0} + t _adjustment + t _Opinion + t _Fitting = 89 seconds
[2] Assembly time influence index e _{switching lever} = (100- (100-89)) x 100/100 = 89
FIG. 8 shows the calculation result of the assembly time influence degree index in this case. Since the switching lever has assembly operations such as shaping, rotation, and press fitting that are difficult to assemble, the assembly time influence index as a part is as high as 89. In this example, the assembly time influence index of each assembly element is displayed when the total assembly time is 100. The assembly time itself may be used instead of the assembly time influence index. Here, as shown in step S104 of FIG. 7, by displaying the calculated assembly time influence degree index on the display at this stage, as shown in step S105, the designer narrows down improvement targets and examines improvement. be able to.
2-3. Extraction of Improved Assembly Elements Needed In step S106 in FIG. 7, an assembly element that needs improvement is extracted from the calculated assembly time influence index.
In this case, the following three elements with high assembly time influence index were extracted.
(1) “Switching lever”
(2) “Shaping” operation of switching lever (3) “Rotating” operation of switching lever 2-4. Extraction of Generalized Improvement Measures As shown in FIG. 6 (d), which is stored in the assembly time improvement guideline database 43 extracted in step S107 of FIG. 7 and required improvement assembly elements (parts, assembly operation, attributes). From the element / improvement guideline data, extract the generalized improvement guideline that improves the elements requiring improvement. Examples of generalized improvement guidelines that have been extracted are shown below.
(1) Improvement required assembly elements (parts): “Switching lever”
→ Improvement guideline: “Dividing parts to be assembled and changing the assembly order [1] Assembling difficult-to-assemble parts last”
“Integrating with other parts [1] Outsert molding, [2] Elastic use of components”
(2) Improvement assembly element required (assembly operation): “Shaping”
→ Improvement guideline: “Making the shaping operation defective [1] Direct mounting on the board”
“Use assembly parts as jigs [1] Tap the engagement part”
(3) Improvement required assembly element (assembly operation): "Rotation"
→ Improvement guideline: "Assemble by straight operation [1] Widen the fitting tip, [2] Thin the fitting tip"
2-5. Specific improvement guideline construction In step S108 of FIG. 7, the assembly elements related to the above generalized improvement guideline are extracted from the specific improvement plan construction database 45 and supplemented with words, the specific improvement guideline is derived from the generalized improvement guideline. Build up. The following are examples of specific improvement guidelines that have been established.
(1) Generalization improvement guideline: “Dividing parts to be assembled and changing the assembly order [1] Assembling difficult-to-assemble parts last”
→ Related phrases: [Switching lever]
→ Specific improvement guidelines: “To reduce the assembly time of the [switch lever], [divide the parts to be assembled and change the assembly order [1] Assemble the difficult-to-assemble parts last.”
(2) Generalization improvement guideline: “Eliminate shaping operation”
→ Related terms: [Switch lever], [Shaping]
→ Specific improvement guideline: “[Shaping] operation of [Switching lever] is made unnecessary [1] Direct mounting on the board]”
(3) Generalization improvement guideline: “Assemble by straight operation [1] Widen the fitting end”
→ Related phrases: [Switch lever], [Rotation]
→ Specific improvement guideline: “To shorten the [Rotation] operation time of [Switching lever], assemble [Switching lever] by straight operation [1] Widen the fitting end”]
In step S109 of FIG. 7, as shown in FIG. 9, these specific improvement guidelines are displayed on the display 21 together with related assembly elements and assembly time influence degree indexes. That is, the selected part name, assembly operation name, attribute name and related assembly element, and assembly time influence degree index are displayed in the improvement required assembly element column 621 in FIG. Further, a specific improvement guideline for improving the selected element is displayed in the specific improvement guideline display field 622 of FIG.
2-6. Assembly time shortening improvement structure creation, assembly operation analysis As shown in FIG. 10 (a), in step S110 of FIG. 7, the designer refers to the specific improvement guideline of FIG. An improvement plan can be easily created. Further, in step S111 of FIG. 7, the created improvement plan assembly operation is analyzed, and the analysis data is input to the design support system 1.
(1) See improvement guideline 1-1 “Different parts to be assembled and change assembly order to reduce assembly time of switching lever [1] Assemble difficult-to-assemble parts last.” The following improvement structure plan can be created.
“The casing 51 is divided into upper and lower parts, and the assembly order is changed to the lower casing 511, the switching lever 521, and the upper casing 511a.” The assembling operation is as follows.
[1] Place the lower case 511 on the work table.
[2] Place the switching lever 521 on the lower case 511. At this time, since the surface of the lower case 511 is a design surface, attention is required for the assembling operation.
[3] Assemble the upper case 511a to the lower case 511.
(2) Improvement guideline 1-2 “Refer to [1] Outsert molding, [2] Elastic use of members” to reduce the assembly time of the switching lever. A structure plan can be created.
“A switch button 522 instead of the switch lever 52 is formed integrally with the casing 512.”
Due to the elasticity of the casing 512, the pressed switch button 522 is automatically restored. In this case, since the member that functions as the switching lever is formed at the stage of forming the casing 512, the assembling operation is not necessary.
(3) Improvement guideline 3-1 “To shorten the rotation time of the switching lever, assemble the switching lever by linear movement. [1] Widen the fitting end, [2] Narrow the fitting tip. The following improvement structure plan can be created.
“The tip 523a of the switching lever 523 is narrowed and assembled in a straight line motion”
The assembling operation is as follows.
[1] Place the lower case 513 on the work table.
[2] Move the switching lever 523 downward and place its tip 523a on the lower case 513. At this time, since the surface of the housing 513 is a design surface, attention is required for the assembling operation.
[3] Press the switching lever 523 into the housing 513. At this time, since the three tip portions 523a of the switching lever are simultaneously fitted, attention is required for the assembling operation.

In step S112 of FIG. 7, the design support system 1 displays the input assembly structure analysis data of the improved structure plan on the display 21 as shown in FIG.
2-7. Assembling time calculation In step S113 in FIG. 7, the assembly operation analysis data before improvement shown in FIG. 4 (b) input in step S101 in FIG. 7 and FIG. 10 (a) input in step S111 in FIG. Each assembly time is calculated from the assembly operation analysis data of the improved structure plan shown in FIG. 7 and the assembly difficulty coefficient DB 41 of FIG. The result is displayed on the display 21 as shown in FIG. In the example of FIG. 10 (b), a bar graph is used, but a numerical value or the like may be used. Further, in the example of FIG. 10 (b), it is shown as a percentage, but it may be a notation such as an assembly time. As a result, the designer can examine the specific structure in order from the improvement plan with the highest improvement effect, and can efficiently perform the improvement design.

  Next, a description will be given of a second embodiment in which the design support system 1 according to the present invention performs an improved design for reducing assembly defects.

  FIG. 1 is a schematic configuration diagram showing an embodiment of a design support system according to the present invention. The design support system 1 according to the present invention includes an input means 10, an output means 20, a calculation means 30, and a database section 40, as in the first embodiment.

  The database unit 40 includes an assembly failure coefficient database 42, an assembly failure improvement guideline database 44, and an assembly failure specific guideline construction database 46. Note that the assembly difficulty coefficient database 41, the assembly time improvement guideline database 43, and the specific assembly time guideline database 45 are not used in this embodiment.

First, the assembly failure coefficient database 42, the assembly failure improvement guideline database 44, and the assembly failure specific guideline construction database 46 will be described. These databases are constructed in advance from the past assembly failure occurrence results of products. FIG. 11 shows a construction flow of the databases 42 and 44 of the present embodiment.
1-1. Assembly failure coefficient database 42
As shown in Fig. 11, from the assembly failure results generated by the past assembly operation analysis results and the corresponding assembly operation results, the assembly operation and the assembly failure potential of the attribute that assists / inhibits it are used as coefficients. Calculate and store in the assembly failure coefficient database 42.

  First, in step S321 in FIG. 11, the past assembly operation of products is analyzed. Here, as in the first embodiment, as shown in FIG. 3, an analysis example of the assembling operation of the switching lever 52 with respect to the casing 51 of a certain electric device is shown. FIG. 12 shows the assembly operation analysis result. Next, in step S322 in FIG. 11, the assembly failure occurrence rate for each past product assembly operation shown in FIG. 3 is examined. This survey data is added to the assembly failure occurrence rate column 618 in FIG. Finally, the assembly operation analysis data and the assembly failure occurrence rate in FIG. 12 are input to the design support system 1. Next, in step S323 of FIG. 11, the design support system 1 calculates individual assembly operation and attribute assembly failure coefficients from the input assembly operation analysis data and the assembly failure occurrence rate. The assembly failure coefficient of the assembly operation is determined by statistically calculating the assembly failure occurrence rate of each assembly operation on the basis of the downward movement operation (no attribute). The attribute assembly failure coefficient is determined by statistically calculating an assembly failure occurrence rate when a specific attribute is associated with each operation, and by determining the ratio of the presence or absence.

The assembly failure occurrence rate of the assembly-type product can be calculated as the sum of the assembly failure occurrence rates for each component. The assembly failure occurrence rate of each component can be calculated as the sum of the assembly failure occurrence rates for each assembly operation of the component. The assembly failure occurrence rate of each assembly operation is determined by the assembly operation and attributes. Therefore, the assembly failure occurrence rate u _X of the assembly operation x is defined by the following equation.
(Equation 7)
[Assembly failure occurrence rate u _x ] = [u _{operation x} ] × [θ _{attribute y1} ] × [θ _{attribute y2} ] × ・ ・ ・
Here, u _{operation x} : assembly failure occurrence rate when there is no attribute θ _{attribute y} : ratio of influence of assembly operation attribute on assembly failure occurrence rate (assembly failure coefficient (attribute))
Furthermore, in order to dimensionless assembly failure rate u _{operation x,} the most the assembly failure rate is smaller Down Move Operation] The assembly failure rate u _{operation x} u assembling a divided by the _{below 0} It is defined as an _operation assembly failure coefficient γ _{operation x} .
(Equation 8)
[Assembly failure coefficient of assembly operation: γ _{operation x} ] = [u _{operation x} ] / [u _{down 0} ]
As shown in Fig. 13, from the assembly operation analysis results in various cases including the case of Fig. 12 and the actual value of the assembly failure occurrence rate for each assembly operation, the assembly failure coefficient γ _{operation x} of the assembly _operation And the attribute assembly failure coefficient β _{attribute y} are calculated.

First, the lower movement failure rate u _{lower 0} , which serves as a reference for the assembly failure rate, is calculated by the following equation.
(Equation 9)
u _{down 0} = (Σu _{down i} ) / n
Next, an assembly failure coefficient γ _{operation x} for each assembly _operation is calculated. For example, a shaping failure rate t _{integer 0,} is calculated by the following equation.
(Equation 10)
u set ₀ = (Σu set _i ) / n
Therefore, the assembly failure coefficient γ _adjustment of the shaping operation is expressed by the following equation.
(Equation 11)
γ _adjustment = u _{adjustment 0} / u _{lower 0}
Next, the assembly failure coefficient γ _{attribute y} of the _{attribute y} is calculated from the ratio of the assembly failure occurrence rate depending on the presence or absence of the attribute y. For example, the assembly failure coefficient θ _meaning of the “design surface present” attribute is _expressed by the following equation.
(Equation 12)
θ _meaning = (u _{meaning 1} / u _{bottom 0} + u _{meaning 2} / u _{times 0} + ...) / n
As described above, the assembly failure coefficient of the operation and the attribute can be calculated from the input assembly operation analysis result and the actual data of the assembly failure occurrence rate. These are stored in the assembly failure coefficient database 42 of FIG.
By storing assembly failure coefficients for many general products prepared in advance in the assembly failure coefficient database 42 in FIG. 11, design support can be achieved without performing steps S321, S322, and S323 in FIG. System 2 can be used.

  In addition, the assembly failure coefficient with higher reliability can be set by continuously inputting the assembly operation analysis result and the actual data of the assembly failure occurrence rate to increase the number of samples.

In addition, when a product or assembly work environment changes significantly, such as a product with a completely different size or production at an overseas factory, the factory and the product's assembly failure occurrence rate data can be entered to enter that factory. It is possible to easily set an assembly failure coefficient suitable for the above.
1-2. Assembly defect improvement guideline database 44
As shown in FIG. 11, a generalized guideline for reducing the assembly failure occurrence rate is extracted for each assembly element and stored in the assembly failure improvement guideline database 44. As described in the first embodiment, the improvement guideline for shortening the assembly time and the improvement guideline for reducing the assembly failure often overlap, so the assembly time reduction guideline and the assembly failure reduction guideline are At the same time, they are extracted and separated at the stage of storing in the database. Therefore, steps S331, S332, S333, and S334 in FIG. 2 are the same as steps S331, S332, S333, and S334 in FIG.

  In particular, the improvement guideline is determined not to specify the target technical field so that it can be used in other technical fields. In FIG. 6 (b), for example, from the example of improvement that reduces the assembly failure potential of parts with high assembly failure potential, where the attribute of “unable to see the joint” is a problem, the target technology field “ventilation fan” “motor” Without specifying the mounting bracket, “fixing screw”, etc., group by the generalized improvement guideline “rearrange the coupling part in the visible region”. This is extracted as a generalization improvement guideline.

As shown in FIG. 6 (d), the problem elements and the generalized improvement guidelines in FIG. 6 (b) are stored in the design support system 1. Here, the improvement guideline regarding the assembly failure is stored in the assembly failure improvement database 44 of FIG.
1-3. Assembly failure specific guidelines construction database 46
Since the improvement guideline stored in the assembly failure improvement guideline database 44 is generalized by the above-described algorithm, even if it is extracted by the algorithm described later, it is difficult to determine the quality because a specific image does not appear. Therefore, a specific improvement guideline is constructed by extracting related elements from the input assembly elements and supplementing necessary words and phrases. These algorithms are stored in the assembly failure specific guideline construction database 46.

  For example, as an improvement guideline for the attribute of “hard to see the joint” accompanying the rotation operation of the switching lever in FIG. 12, from the generalized improvement guideline in FIG. “Relocation to region” can be extracted. However, this is too general and is not sufficient as an improvement guideline. Therefore, first, from the assembly operation analysis data shown in FIG. 12, the words and phrases (parts: switching lever, assembly operation: rotation) related to the attribute “difficult to see the coupled portion” are extracted.

  Using these, a specific improvement plan is constructed as follows. In order to shorten the “rotation” operation time associated with the “switching lever” attribute “difficult to see the coupling part”, “rearrange the coupling part in the visible region”. ”Can be specifically identified.

  By the way, each database 42, 44, 46 does not need to be collected by the design support system 2, but may be collected by another design support system, transmitted to the design support system 1 via a network, and stored.

Next, a description will be given of a second embodiment in which the design support system 1 according to the present invention performs an improved design for reducing assembly defects. FIG. 14 is a diagram showing a second embodiment of the design support processing flow in the design support system 1. FIG. 15 shows the result of the assembly failure influence degree index calculated inside the system from the input assembly operation analysis data. FIG. 16 is a diagram showing a second embodiment of the display 21. As shown in FIG. FIG. 17 (a) is a diagram showing an example of an improved structure created based on the improvement guideline displayed on the display 21 and its assembly operation analysis data. Further, FIG. 17 (b) is a diagram showing the improvement effect displayed on the display 21. FIG.
2-1. Assembly Operation Analysis Data Input In step S201 of FIG. 14, assembly operation analysis data is input to the design support system 2. For example, the assembly operation shown in FIG. 3 is analyzed into the parts that make up the product, the assembly operation of each part, and the attributes associated with the operation, and is assembled into a table as shown in FIG. Is input to the design support system 2. In step S202 of FIG. 14, the design support system 2 displays the input assembly operation analysis data on the display 21 as shown in FIG.
2-2. Assembling failure influence degree index calculation In step S203 of FIG. 14, the design support system 2 calculates the coefficient of each element of the input assembly operation analysis data from the coefficient of each assembly element stored in the assembly failure coefficient database 42. Extract and calculate an assembly failure influence index for parts, assembly operations, and attributes. The product is composed of a plurality of parts. Parts are assembled by several assembly operations. Further, the assembling operation has an attribute that enables or inhibits this. Therefore, the difference in the assembly failure occurrence rate of the entire product due to the presence or absence of these assembly elements is divided by the overall assembly failure occurrence rate, and a value multiplied by 100 is defined as an assembly failure influence degree index.
(1) The difference in assembly failure occurrence rate due to the presence or absence of one component can be regarded as an assembly failure that occurs due to the presence of that component. Therefore, a value obtained by dividing the difference in the assembly failure occurrence rate by the total assembly failure occurrence rate and multiplying by 100 is defined as a component index of the assembly time influence degree index.
(2) A difference in assembly failure rate due to the presence or absence of one assembly operation can be regarded as an assembly failure that occurs due to the assembly operation. Therefore, a value obtained by dividing the difference in the assembly failure occurrence rate by the total assembly failure occurrence rate and multiplying by 100 is defined as an assembly operation index of the assembly failure influence degree index.
(3) A difference in assembly failure rate due to the presence or absence of one attribute can be regarded as an assembly failure that occurs due to the presence of that attribute. Therefore, a value obtained by dividing the difference in the assembly failure occurrence rate by the total assembly failure occurrence rate and multiplying by 100 is defined as an attribute index of the assembly failure influence degree index.

In the case of assembling the switching lever shown in FIG. 3, the assembly failure influence degree index is calculated as follows. Here, it is assumed that the assembly failure occurrence rate of the entire product is 100 ppm, and the assembly failure occurrence rate u ₀ generated during the standard part moving operation in this workplace is 1 ppm.
(1) of the rotation operation of the switching lever assembly bad influence index e _times
[1] Occurrence rate of assembly failure during rotating operation u _{times opinion} = u _{lower 0} × γ _times × θ _meaning × θ _view = 1 × 11 × 1 × 5.18 = 57 ppm
[2] Assembly failure effect index e _times = (100- (100-57)) × 100/100 = 57
(2) _viewed defective assembly influence index e of the coupling portion seen hardly attribute accompanying the rotation of the switching lever
[1] Assembly failure rate when there are no hard-to-see attributes
u _Kaii = u _{below 0} × _{γ times} × θ _meaning = 1 × 11 × 1 = 11ppm
[2] Assembly failure effect index e _times = (57-11) × 100/100 = 46
(3) Switching lever assembly failure influence index e _{Switching lever}
[1] Switching lever assembly malfunction occurrence rate u _{Switching lever} = u _{down 0} + u _adjustment + u _{times opinion} + u _{press fit} = 99ppm
[2] Assembly failure influence index e _{switching lever} = (100- (100-99)) x 100/100 = 99
FIG. 15 shows the calculation result of the assembly failure influence degree index in this case. The switch lever has an assembly operation with a high assembly failure potential such as rotation and press-fitting and a high attribute of assembly failure potential such as a design surface and difficult to see the joint, so the assembly failure impact index as a part is 99 is very high. In addition to the high assembly failure potential of the rotation operation itself, the rotation operation of the switching lever has a high attribute of assembly failure potential, such as the presence of a design surface and difficulty in seeing the coupling part. The impact index is as high as 57. In addition, it is difficult to see the coupling part during the rotation of the switching lever. In addition to the height of the assembly failure potential that is difficult to see the coupling part, it is an attribute that accompanies the rotation operation, and there is an attribute that the rotation operation has a design surface. As a result, the assembly failure impact index is as high as 46.

In this example, the failure influence index of each assembly element is displayed with the overall failure occurrence rate as 100. Note that the defect occurrence rate itself may be used instead of the defect influence index. Here, as shown in step S204 of FIG. 14, by displaying the calculated assembly defect influence degree index on the display at this stage, as shown in step S205, the designer narrows down improvement targets and examines improvement. be able to.
2-3. Extraction of improvement required assembly element In step S206 in FIG. 14, an assembly element that needs improvement is extracted from the calculated assembly failure influence degree index.
In this example, as shown in FIG. 15, the following three elements having a high assembly failure influence index were extracted.
(1) “Switching lever”
(2) “Rotating” operation of the switching lever (3) “Unable to see coupling” attribute associated with the rotating operation of the switching lever 2-4. Generalized improvement guideline extraction As shown in FIG. 6 (d), the improvement required assembly elements (parts, assembly operation, attributes) extracted in step S207 of FIG. 14 and the assembly failure improvement guideline database 44 are saved. From the element / improvement guideline data, extract the generalized improvement guideline that improves the elements requiring improvement. Examples of generalized improvement guidelines that have been extracted are shown below.
Improvement assembly elements (parts) required: “Switching lever”
→ Improvement guideline: “Dividing parts to be assembled and changing the assembly order [1] Assembling difficult-to-assemble parts last”
“Integrating with other parts [1] Outsert molding, [2] Elastic use of components”
Improving assembly elements required (assembly operation): "Rotation"
→ Improvement guideline: "Assemble by straight operation [1] Widen the fitting tip, [2] Thin the fitting tip"
[3] Improved assembly elements (attributes): “It is difficult to see the joint”
→ Improvement guideline: “Relocate the joint to the visible region”
2-5. Specific Improvement Guideline Construction In step S208 of FIG. 14, the assembly elements related to the above generalized improvement guideline are extracted from the specific improvement guideline construction database 46, and the phrase is supplemented to specify the specific improvement guideline from the generalized improvement guideline. Build up. The following are examples of specific improvement guidelines that have been established.
(1) Generalization improvement guideline: “Dividing parts to be assembled and changing the assembly order [1] Assembling difficult-to-assemble parts last”
→ Related phrases: [Switching lever]
→ Specific improvement guideline: “To reduce the assembly failure of the [switch lever], [divide the parts to be assembled and change the assembly order]”
(2) Generalization improvement guidelines: “[1] Outsert molding integrated with other parts, [2] Elastic use of members”
→ Related phrases: [Switching lever]
→ Specific improvement guideline: “To reduce assembly failure of [switch lever] [[Integrate with other parts [1] Outsert molding, [2] Use elastic components]”
(3) Generalization improvement guideline: “Assemble by straight operation [1] Widen the fitting end, [2] Narrow the fitting tip”
→ Related phrases: [Switch lever], [Rotation]
→ Specific improvement guideline: “To reduce assembly failure during [Rotation] operation of [Switching lever], [Assembly the [Switching lever] by [Straight-forward operation] [1] Widen the fitting end, [2 ] Narrow the fitting tip]
(4) Generalization improvement guideline: “Relocate the joint to the visible region”
→ Related phrases: [Switching lever], [Rotation], [Unable to see the joint]
→ Specific improvement guideline: “To re-arrange the [connection part] of the [switch lever] in the visible region in order to reduce the assembly failure during the [rotation] operation with the [hard to see] part of the [switch lever] ]
In step S209 of FIG. 14, as shown in FIG. 16, these specific improvement guidelines are displayed on the display 21 together with related assembly elements and assembly failure influence degree indexes. That is, the selected part name, assembly operation name, attribute name, related assembly element, and assembly failure influence degree index are displayed in the improvement required assembly element column 621 in FIG. Also, a specific improvement guideline for improving the selected element is displayed in the specific improvement guideline display field 622 of FIG.
2-6. Assembly defect reduction improvement structure creation, assembly operation analysis As shown in FIG. 17 (a), in step S210 of FIG. 14, the designer refers to the specific improvement guideline of FIG. 16 displayed on the display 21. An improvement plan can be easily created. Furthermore, in step S211 of FIG. 14, the assembly operation of the created improvement plan is analyzed, and the analysis data is input to the design support system 1.
(1) See improvement guideline 1-1 “Different parts to be assembled and change assembly order to reduce assembly failure of switching lever [1] Assemble difficult-to-assemble parts last” The following improvement structure plan can be created.
“The casing 51 is divided into upper and lower parts, and the assembly order is changed to the lower casing 511, the switching lever 521, and the upper casing 511a.” The assembling operation is as follows.
[1] Place the lower case 511 on the work table.
[2] Place the switching lever 521 on the lower case 511. At this time, since the surface of the lower case 511 is a design surface, attention is required for the assembling operation.
[3] Assemble the upper case 511a to the lower case 511.
(2) Improvement guideline 2-1 “To reduce assembly failure during rotation of the switching lever, assemble the switching lever by linear movement. [1] Widen the fitting end, [2] Insert the fitting tip. By referring to “Narrow”, the following improvement structure plan can be created.
“The tip 523a of the switching lever 523 is narrowed and assembled in a straight line motion”
The assembling operation is as follows.
[1] Place the lower case 513 on the work table.
[2] Move the switching lever 523 downward and place its tip 523a on the lower case 513. At this time, since the surface of the housing 513 is a design surface, attention is required for the assembling operation.
[3] Press the switching lever 523 into the housing 513. At this time, since the three tip portions 523a of the switching lever are simultaneously fitted, attention is required for the assembling operation.
(3) By referring to the improvement guideline 3-1 “Relocate the coupling portion of the switching lever in the visible region in order to reduce the assembly failure at the time of the rotation operation due to the hard-to-see attribute of the switching lever”, The following improvement structure plan can be created.
“Extend the tip 524a of the switching lever 524 and rearrange the coupling in the visible region”
The assembling operation is as follows.
[1] Place the lower case 514 on the work table.
[2] Move the switching lever 524 downward. At this time, since the surface of the housing 514 is a design surface, attention is required for the assembling operation.
[3] The claw arm portion 524a of the switching lever 524 is shaped inward.
[4] The switching lever 524 is rotated to put the claw arm portion 524a into the housing 514. At this time, since the housing surface is a design surface, it is necessary to consider so as not to be scratched. Note that the claw arm portion 524a and the coupling portion inside the housing 514 are rearranged in the visible region, so there is no need to pay attention.

In step S212 in FIG. 14, the design support system 1 displays the input operation analysis data of the improved structure plan on the display 21 as shown in FIG.
2-7. Assembling failure occurrence rate calculation In step S213 of FIG. 14, the assembly operation analysis data before improvement shown in FIG. 12 input in step S201 of FIG. 14 and FIG. 17A input in step S211 of FIG. Each assembly failure occurrence rate is calculated from the assembly operation analysis data of the improved structure plan shown and the assembly failure coefficient DB 42 in FIG. The result is displayed on the display 21 as shown in FIG. In the example of FIG. 17 (b), a bar graph is used, but a numerical value or the like may be used. Further, in the example of FIG. 10 (b), the percentage is shown, but a notation such as an assembly failure occurrence rate may be used. As a result, the designer can examine the specific structure in order from the improvement plan with the highest improvement effect, and can efficiently perform the improvement design.

Next, a third embodiment of the design support system according to the present invention will be described.
FIG. 1 is a schematic configuration diagram showing an embodiment of a design support system according to the present invention. The design support system 3 according to the present invention includes an input means 10, an output means 20, a calculation means 30, and a database unit 40. The input means 10 includes a keyboard 11, a mouse 12, and the like. The output unit 20 includes a display 21, a printing unit 22, and the like. The computing means 30 is composed of a CPU 31, a ROM 32, a RAM 33, and an input / output unit. The calculation means 30 and the display 21 constitute extraction extraction means. The database unit 40 includes an assembly difficulty coefficient database 41, an assembly failure coefficient database 42, an assembly time improvement guideline database 43, an assembly failure improvement guideline database 44, and an assembly time specific improvement guideline construction database 45. The assembly failure specific improvement guideline construction database 46 is configured.

Next, a description will be given of a third embodiment in which the design support system 1 according to the present invention performs an improved design that reduces the integrated assembly cost.
FIG. 18 is a diagram showing a third embodiment of the design support processing flow in the design support system 3. As shown in FIG. FIG. 19 shows the result of the integrated assembly cost influence index calculated inside the system from the input assembly operation analysis data. FIG. 20 is a diagram showing a third embodiment of the display 21. As shown in FIG. FIG. 21 (a) is a diagram showing an example of an improved structure created based on the improvement guideline displayed on the display 21 and its assembly operation analysis data. Furthermore, FIG. 21 (b) is a diagram showing the improvement effect displayed on the display 21. FIG.
1-1. Assembly Operation Analysis Data Input In step S301 of FIG. 18, assembly operation analysis data is input to the design support system 1. For example, the assembly operation shown in FIG. 3 is analyzed into the parts constituting the product, the assembly operation of each part, and the attributes associated with the operation, and the assembly operation analysis data is compiled into a table as shown in FIG. This is input to the design support system 1.
In step S302 of FIG. 18, the design support system 1 displays the input assembly operation analysis data on the display 21 as shown in FIG.
1-2. Integrated Assembly Cost Impact Index Calculation In step S303 of FIG. 18, the design support system 1 calculates an integrated assembly cost impact index according to the following procedure.
(1) The assembly difficulty coefficient of each element of the input assembly operation analysis data is extracted from the coefficient of each assembly element stored in the assembly difficulty coefficient database 41, and the component, assembly operation, attribute Calculate the assembly time influence index.
(2) The assembly cost influence degree for each assembly element is calculated from the calculated assembly time influence index and the assembly cost per unit time.
(3) The assembly failure coefficient of each element of the input assembly operation analysis data is extracted from the coefficient of each assembly element stored in the assembly failure coefficient database 42, and the assembly failure of parts, assembly operation, and attribute Calculate the impact index.
(4) From the calculated assembly failure influence degree index and the loss when the failure occurs, the assembly loss cost influence degree for each assembly element is calculated.
(5) The sum of the assembly cost and assembly loss cost of each assembly element is divided by the total of the total assembly cost and assembly loss cost, and a value multiplied by 100 is calculated as an integrated assembly cost impact index.

FIG. 19 shows the calculation result of the integrated assembly cost impact index in this case. The switch lever has an assembly operation that is difficult to assemble, such as shaping, rotation, press fitting, etc., and has an attribute of high assembly failure potential, such as difficult to see the joint and presence of a design surface. And very high. In this example, the total assembly cost impact index of each assembly element when the total assembly time is 100 is displayed. The integrated assembly cost itself may be used instead of the integrated assembly cost influence index. Also, as shown in step S304 in FIG. 18, by displaying the integrated assembly cost impact index on the display at this stage, the designer can narrow down the improvement target and consider improvement as shown in step S305. .
1-3. Extraction of Improved Assembly Elements Needed In step S306 in FIG. 18, an assembly element that needs improvement is extracted from the calculated integrated assembly cost impact index. In this case, the following three elements with high integrated assembly cost impact index were extracted.
(1) “Switching lever”
(2) “Shaping” operation of switching lever (3) “Rotating” operation of switching lever 1-4. Generalized improvement measure extraction and concrete improvement guideline construction In step S307 in FIG. 18, the generalized improvement guideline is extracted in the same manner as in the first and second embodiments. Further, in step S308 of FIG. 18, a specific improvement guideline is constructed in the same manner as in the first embodiment and the second embodiment. In step S309 of FIG. 18, as shown in FIG. 20, it is displayed on the display 21 together with the assembly elements and the assembly cost influence index related to these specific improvement guidelines.
1-5. Integrated assembly cost reduction improvement structure creation, assembly operation analysis As shown in Fig. 21 (a), in step S310 of Fig. 18, the designer refers to the specific improvement guideline of Fig. 20 displayed on the display 21. Can easily create an improvement plan. Further, in step S311 of FIG. 18, the created improvement plan assembly operation is analyzed, and the analysis data is input to the design support system 1.
(1) Refer to Improvement Guideline 1-1 “Dividing parts to be assembled and changing the assembly order to reduce the integrated assembly cost of the switching lever [1] Assembling difficult-to-assemble parts last” As a result, the following improvement structure plan can be created.

“The casing 51 is divided into upper and lower parts, and the assembly order is changed to the lower casing 511, the switching lever 521, and the upper casing 511a.” The assembling operation is as follows.
[1] Place the lower case 511 on the work table.
[2] Place the switching lever 521 on the lower case 511. At this time, since the surface of the lower case 511 is a design surface, attention is required for the assembling operation.
[3] Assemble the upper case 511a to the lower case 511.
(2) Improvement guideline 1-2 “Integrate with other parts to reduce the assembly cost of the switching lever.
By referring to [1] Outsert molding, [2] Elastic use of members, the following improved structure plan can be created.
“A switch button 522 instead of the switch lever 52 is formed integrally with the casing 512.”
Due to the elasticity of the casing 512, the pressed switch button 522 is automatically restored. In this case, since the member that functions as the switching lever is formed at the stage of forming the casing 512, the assembling operation is not necessary.
(3) Improvement guideline 3-1 “To reduce the integrated assembly cost associated with the rotation of the switching lever, assemble the switching lever in a straight line motion. [1] Widen the fitting end, [2] The fitting By referring to “Narrowing the tip”, the following improvement structure plan can be created.
“The tip 523a of the switching lever 523 is narrowed and assembled in a straight line motion”
The assembling operation is as follows.
[1] Place the lower case 513 on the work table.
[2] Move the switching lever 523 downward and place its tip 523a on the lower case 513. At this time, since the surface of the housing 513 is a design surface, attention is required for the assembling operation.
[3] Press the switching lever 523 into the housing 513. At this time, since the three tip portions 523a of the switching lever are simultaneously fitted, attention is required for the assembling operation.

In step S312 of FIG. 18, the design support system 1 displays the input assembly structure analysis data of the improved structure plan on the display 21 as shown in FIG.
1-6. Integrated assembly cost calculationIn step S313 of FIG. 18, the assembly operation analysis data before improvement shown in FIG. 4 (b) input in step S301 of FIG. 18 and FIG. 21 (a) input in step S311 of FIG. The assembly time and the assembly failure occurrence rate are calculated from the assembly operation analysis data of the improved structure plan shown in FIG. 18, the assembly difficulty coefficient DB 41 in FIG. 18, and the assembly failure coefficient DB in FIG. 18. Further, an integrated assembly cost is calculated by adding the assembly cost related to the assembly time and the assembly loss cost caused by the assembly failure. The result is displayed on the display 21 as shown in FIG. In the example of FIG. 21 (b), a bar graph is used, but a numerical value or the like may be used. Further, in the example of FIG. 21 (b), the percentage is shown as a percentage, but it may be a notation such as an integrated assembly cost. As a result, the designer can examine the specific structure in order from the improvement plan with the highest improvement effect, and can efficiently perform the improvement design.

1 is a schematic configuration diagram showing an embodiment of a design support system according to the present invention. It is a figure which shows the construction flow creation of the database regarding the assembly time reduction of one Embodiment of the design support system concerning this invention. It is sectional drawing which shows the assembly | attachment operation | movement of the switching lever of the electric equipment which is an example of the product design concerning this invention. It is a figure which shows the example of the list of the assembly | attachment operation | movement used for an assembly | attachment operation | movement analysis, and an attribute word / phrase. FIG. 4 is a diagram showing an assembly operation analysis result of the switching lever of the electric device shown in FIG. It is a figure which shows the data structure which calculates an assembly difficulty coefficient. It is a figure which shows the past assembly time / assembly failure improvement example, and an assembly operation | movement analysis example. It is a figure which shows the method of grouping the past assembly time / assembly failure improvement examples, and extracting the generalization improvement guideline as a superordinate concept. It is a figure which shows the improvement keyword used for the grouping of the past assembly time / assembly defect improvement example. It is a figure which shows the content of the assembly time improvement guideline database extracted from the past assembly time / assembly failure improvement example. It is a figure which shows the design support processing flow of one Embodiment of the design support system concerning this invention. FIG. 4 is a diagram showing an assembly time influence index calculation result for the assembly element of the electric device shown in FIG. FIG. 4 is a diagram showing assembly elements determined to require improvement of the electric device shown in FIG. 3 and their improvement guidelines. It is a figure which shows an example of the improvement structure plan and its assembly | attachment operation | movement analysis based on the assembly time improvement guideline of the electric equipment shown in FIG. It is a figure which shows an example of the improvement effect of the improvement structure plan based on the assembly time improvement guideline of the electric equipment shown in FIG. It is a figure which shows the design support processing flow of 2nd one Embodiment of the design support system concerning this invention. FIG. 4 is a diagram showing an assembly operation analysis result of the switching lever of the electric device shown in FIG. It is a figure which shows the data structure which calculates an assembly | attachment defect coefficient. It is a figure which shows the design support processing flow of 2nd one Embodiment of the design support system concerning this invention. FIG. 4 is a diagram showing a calculation result of an assembly failure influence degree index for the assembly element of the electric device shown in FIG. FIG. 4 is a diagram showing assembly elements determined to require improvement of the electric device shown in FIG. 3 and their improvement guidelines. It is a figure which shows an example of the improvement structure plan and its assembly | attachment operation | movement analysis based on the assembly defect improvement guideline of the electric equipment shown in FIG. It is a figure which shows an example of the improvement effect of the improvement structure plan based on the assembly defect improvement guideline of the electric equipment shown in FIG. It is a figure which shows the design support processing flow of 3rd Embodiment of the design support system concerning this invention. FIG. 4 is a diagram showing a result of calculating an integrated assembly cost influence index for the assembly elements of the electric device shown in FIG. FIG. 4 is a diagram showing assembly elements determined to require improvement of the electric device shown in FIG. 3 and their improvement guidelines. It is a figure which shows an example of the improvement structure plan and its assembly | attachment operation | movement analysis based on the integrated assembly cost improvement guideline of the electric equipment shown in FIG. It is a figure which shows an example of the improvement effect of the improvement structure plan based on the integrated assembly cost improvement guideline of the electric equipment shown in FIG.

Explanation of symbols

1 ... Design support system 10 ... Input means 20 ... Output means 30 ... Calculation means 40 ... Database

Claims (12)

A design support method for creating an improvement measure for shortening the assembly time of the product for a product design plan to be improved,
Save assembled difficulty with coefficients that stores the assembly difficulty coefficient is a coefficient in the database that indicates the number of degrees of assembling difficulty of the attributes with the design case the determined assembling operation and assembling operation based on the past Steps,
Based on the task element / improvement keyword table that accepts input of improvement examples and parts / assembly operations / attributes for shortening the assembly time of a large number of past design cases, and correlates the task elements with the improvement keywords. Issues that are developed hierarchically in a mutually related manner by grouping the improvement cases for each improvement keyword using the issue elements extracted from the improvement cases and accepting the input of improvement guidelines for the improvement cases that have been grouped An improvement guideline storing step for associating the component / assembly operation and attribute , which is an element, with the improvement guideline and storing them in the database,
In the product design plan, the input unit receives an input of various components associated with the product component, the assembly operation of the component, and the assembly operation;
An index indicating the degree of influence on the assembly time of the component of the design plan, the assembly operation of each component, and the combination of attributes associated with the assembly operation from the assembly difficulty coefficient read from the database A calculation step for calculating an assembly time influence index),
A selection step in which the selection means selects a combination of parts, assembly operations, and attributes having a high assembly time influence index; and
For the selected component, assembly operation, and attribute combination, the extraction means associates the improvement guideline related to any of the component, assembly operation, and attribute with the task element and the improvement guideline in the database. Extracting from the database based on ;
An improvement guideline constructing step, wherein the improvement guideline construction means constructs a specific improvement guideline from the extracted improvement guideline and the parts, assembly operations, and attributes related thereto,
A design support method characterized in that the output means includes at least an output step for outputting the constructed concrete improvement guideline. A design support method for creating an improvement plan for reducing an assembly failure of a product for an improvement target product design plan,
Multiple sets difficulty coefficient storage step with saving the defective assembly coefficient is a coefficient indicating the degree of assembly failure potential attributes with design case the determined assembling operation and assembling operation based on the database of past When,
Based on the task element / improvement keyword table that accepts input of improvement examples for reducing assembly defects and parts / assembly operations / attributes of many past design examples and associates task elements with improvement keywords. Issues that are developed hierarchically in a mutually related manner by grouping the improvement cases for each improvement keyword using the issue elements extracted from the improvement cases and accepting the input of improvement guidelines for the improvement cases that have been grouped An improvement guideline storing step for associating the component / assembly operation and attribute , which is an element, with the improvement guideline and storing them in the database,
In the product design proposal, the input unit receives an input of various attributes associated with the product component, the assembly operation of each component, and the assembly operation;
An index indicating the degree of influence on the assembly failure of the component of the design plan, the assembly operation of each component, and the attribute combination accompanying the assembly operation from the assembly failure coefficient read from the database A calculation step for calculating a defect influence index),
A selection step in which the selection means selects a combination of parts, assembly operations, and attributes having a high assembly defect influence index; and
For the selected component, assembly operation, and attribute combination, the extraction means associates the improvement guideline related to any of the component, assembly operation, and attribute with the task element and the improvement guideline in the database. Extracting from the database based on ;
An improvement guideline constructing step, wherein the improvement guideline construction means constructs a specific improvement guideline from the extracted improvement guideline and the parts, assembly operations, and attributes related thereto,
A design support method characterized in that the output means includes at least an output step for outputting the constructed concrete improvement guideline. A design support method for creating an improvement measure for reducing the assembly cost of the product for a product design plan to be improved,
And assembly difficulty coefficient is a coefficient indicating the degree of assembling difficulty of the attributes associated with the multiple operating assembling was determined design case based and assembling operations of the past, coefficient indicating the degree of assembly failure potential An assembling difficulty coefficient and an assembling defect coefficient storing step for storing the assembling defect coefficient in the database;
An issue element that receives input of improvement examples for reducing assembly time, improvement examples for reducing assembly defects, and parts / assembly operations / attributes in many past design examples, and associating issue elements with improvement keywords Based on the improvement keyword table, the improvement elements are grouped for each improvement keyword using the task elements extracted from the improvement case, and the input of the improvement guidelines for the improvement case that has been grouped is accepted. An improvement guideline storing step that associates the part / assembly operation and attributes , which are the task elements that are hierarchically developed with an attribute, and the improvement guideline and stores them in the database,
In the product design proposal, the input unit receives an input of various attributes associated with the product component, the assembly operation of each component, and the assembly operation;
The calculation means relates to the assembly time of the component of the design plan, the assembly operation of the component, and the attribute combination accompanying the assembly operation from the assembly difficulty coefficient and the assembly failure coefficient read from the database. A calculation step for calculating an index (integrated assembly cost influence index) indicating an influence on the integrated assembly cost obtained by adding the assembly cost and the assembly loss cost caused by the assembly failure;
A selection step in which the selection means selects a combination of parts, assembly operations, and attributes having a high integrated assembly cost resilience index; and
For the selected component, assembly operation, and attribute combination, the extraction means associates the improvement guideline related to any of the component, assembly operation, and attribute with the task element and the improvement guideline in the database. Extracting from the database based on ;
An improvement guideline constructing step, wherein the improvement guideline construction means constructs a specific improvement guideline from the extracted improvement guideline and the parts, assembly operations, and attributes related thereto,
A design support method characterized in that the output means includes at least an output step for outputting the constructed concrete improvement guideline. A design support system for creating an improvement plan for shortening the assembly time of the product for a product design plan to be improved,
Previously, a number of assembly difficulty coefficient is a coefficient indicating the degree of assembling difficulty of the attributes with the design case the determined assembling operation and assembling operation based on the past, improvements in order to shorten the set start-time A database in which data including assembly operations / attributes and improvement guidelines is stored, in which the guidelines are associated with the parts / assembly operations and attributes that are the subject elements, and are hierarchically expanded in relation to each other.
In the product design proposal, input means for inputting various attributes associated with product component parts, assembly operation of each part, and assembly operation;
Index indicating the degree of influence on the assembly time of the component of the design plan, the assembly operation of the component, and the attribute combination accompanying the assembly operation from the assembly difficulty coefficient read from the database (assembly time influence index) ) Calculating means),
A selection means for selecting a combination of a part having a high assembly time influence index, an assembly operation, and an attribute;
For the selected component, assembly operation, and attribute combination, the improvement guideline related to any of the component, assembly operation, and attribute is based on the association between the task element and the improvement guideline in the database. Extraction means for extracting from,
Improvement guideline construction means for constructing a specific improvement guideline from the extracted improvement guideline and the parts, assembly operations, and attributes related thereto,
A design support system comprising at least output means for outputting a concrete improvement guideline constructed. A design support system for creating an improvement measure for reducing the assembly failure of the product for a product design plan to be improved,
Previously, the defective assembly coefficient is a coefficient indicating the degree of assembly failure potential attributes associated with the past a number of operating assembling was determined design case based and assembling operations, improved guidance for the set elevational reduce defects A database in which data consisting of assembly operations / attributes and improvement guidelines are stored , which are associated with each other and parts / assembly operations and attributes as task elements, and are hierarchically expanded with mutual relations.
In the product design proposal, input means for inputting various attributes associated with product component parts, assembly operation of each part, and assembly operation;
An index indicating the degree of influence of the component of the design plan, the assembly operation of the component, and the combination of attributes associated with the assembly operation on the assembly failure from the assembly failure coefficient read from the database (assembly failure effect index) Computing means for calculating
A selection means for selecting a combination of parts, assembly operations, and attributes having a high assembly defect impact index,
For the selected component, assembly operation, and attribute combination, the improvement guideline related to any of the component, assembly operation, and attribute is based on the association between the task element and the improvement guideline in the database. Extraction means for extracting from,
Improvement guideline construction means for constructing a specific improvement guideline from the extracted improvement guideline and the parts, assembly operations, and attributes related thereto,
A design support system comprising at least output means for outputting a concrete improvement guideline constructed. A design support system for creating an improvement plan for reducing the assembly cost of the product for a product design plan to be improved,
The assembly operation coefficient determined based on a large number of past design examples in advance and the degree of difficulty in assembling the attribute accompanying the assembly operation, and the degree of assembly failure potential a defective assembly coefficient is a coefficient, the improvement guideline and the component-assembly operations and attributes is a challenge elements for improvement guideline and assembly defects reduced for reducing the set elevation time is associated with, each other to have an associated A database in which data consisting of assembly operations / attributes and improvement guidelines are stored,
In the product design proposal, input means for inputting various attributes associated with product component parts, assembly operation of each part, and assembly operation;
Assembly cost and assembly related to the assembly time of the component part of the design plan, the assembly operation of the component part, and the attribute combination accompanying the assembly operation from the assembly difficulty coefficient and assembly failure coefficient read from the database An arithmetic means for calculating an index (integrated assembly cost influence index) indicating an influence degree on the integrated assembly cost obtained by adding the assembly loss cost caused by the occurrence of a defect;
A selection means for selecting a combination of parts, assembly operations, and attributes having a high integrated assembly cost impact index; and
For the selected component, assembly operation, and attribute combination, the improvement measures related to any of the component, assembly operation, and attribute are determined based on the correspondence between the task element and the improvement guideline in the database. Extraction means for extracting from,
Improvement measure construction means for constructing a specific improvement guideline from the extracted improvement guideline and the related parts, assembly operations, and attributes related thereto,
A design support system comprising: an output means for outputting at least the constructed concrete improvement measures. In claim 1,
An input step in which the input means receives input of components of improvement measures created based on the presented improvement guidelines, assembly operation of each component, various attributes associated with the assembly operation,
An arithmetic step for calculating an assembling time from an assembling difficulty coefficient read from the database and a component part of the improvement measure, an assembling operation of each part, and an attribute accompanying the assembling operation;
A design support method, wherein the output means further includes an output step of outputting the calculated assembly time. In claim 2,
An input step in which the input means receives input of components of improvement measures created based on the presented improvement guidelines, assembly operation of each component, various attributes associated with the assembly operation,
An arithmetic step for calculating an assembly failure occurrence rate from the assembly failure coefficient read from the database and the component part of the improvement measure, the assembly operation of each part, and the attribute accompanying the assembly operation;
A design support method, wherein the output means further includes an output step of outputting the calculated assembly failure occurrence rate. In claim 3,
An input step in which the input means receives input of components of improvement measures created based on the presented improvement guidelines, assembly operation of each component, various attributes associated with the assembly operation,
An assembling cost and an assembling related to an assembling time from an assembling difficulty coefficient and an assembling failure coefficient read from the database, a component part of the improvement measure, an assembling operation of each part, and an attribute accompanying the assembling operation. A calculation step for calculating an integrated assembly cost obtained by adding an assembly loss cost caused by a defect; and
A design support method, wherein the output means further includes an output step of outputting the calculated integrated assembly cost. In claim 4,
Input means for inputting the components of the improvement measures created based on the presented improvement guidelines, the assembly operation of each component, and various attributes associated with the assembly operation;
A calculation means for calculating an assembly time from an assembly difficulty coefficient read from the database and components of the improvement measure, an assembly operation of each component, and an attribute associated with the assembly operation;
A design support system comprising output means for outputting the calculated assembly time. In claim 5,
Input means for inputting the components of the improvement measures created based on the presented improvement guidelines, the assembly operation of each component, and various attributes associated with the assembly operation;
A calculation means for calculating an assembly failure occurrence rate from the assembly failure coefficient read from the database, the component part of the improvement measure, the assembly operation of each part, and the attribute accompanying the assembly operation;
A design support system comprising output means for outputting the calculated assembly failure occurrence rate. In claim 6,
Input means for inputting the components of the improvement measures created based on the presented improvement guidelines, the assembly operation of each component, and various attributes associated with the assembly operation;
Generated by assembly cost and assembly failure related to assembly time based on assembly difficulty coefficient and assembly failure coefficient read from the database, components of the improvement measures, assembly operation of each part, and attributes associated with the assembly operation Computing means for calculating an integrated assembly cost obtained by adding the assembly loss cost to be
A design support system comprising output means for outputting the calculated integrated assembly cost.

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