CN112329952A - Method for evaluating maintenance convenience of automobile parts - Google Patents

Abstract

Translated fromChinese

本发明属于汽车技术领域，具体的说是一种汽车零部件维修方便性的评价方法。包括以下步骤：1、设定评价指标；2、按层次分析法构造判断矩阵，将10个评价指标归类整理，并且构造4个判断矩阵；3、填写判断矩阵；4、将判断矩阵样本扩充至1000份；5、计算1000份判断矩阵样本元素均值，并重新填写判断矩阵，记为均值判断矩阵；6、对均值判断矩阵的一致性进行检验；7、按检验通过的均值判断矩阵计算各评价指标权重；8、设定各项评价指标的评分标准；9、对待评价零件的各项指标进行评分；10、对各指标得分加权，得到零件维修方便性的综合得分。本发明是一种客观可量化的汽车零部件维修方便性评价方法，能辅助设计师优化设计方案。

The invention belongs to the technical field of automobiles, in particular to a method for evaluating the maintenance convenience of automobile parts. It includes the following steps: 1. Setting the evaluation index; 2. Constructing a judgment matrix according to the AHP method, classifying and sorting 10 evaluation indexes, and constructing 4 judgment matrices; 3. Filling in the judgment matrix; 4. Expanding the judgment matrix samples To 1000 copies; 5. Calculate the average value of the sample elements of the judgment matrix for 1000 copies, and re-fill the judgment matrix, which is recorded as the mean judgment matrix; 6. Check the consistency of the mean judgment matrix; 7. Calculate the average judgment matrix according to the test. Evaluation index weight; 8. Set the scoring standard of each evaluation index; 9. Score each index of the part to be evaluated; 10. Weight each index score to obtain a comprehensive score for the convenience of parts maintenance. The invention is an objective and quantifiable method for evaluating the maintenance convenience of auto parts, which can assist designers to optimize the design scheme.

Description

Method for evaluating maintenance convenience of automobile parts

Technical Field

The invention belongs to the technical field of automobiles, and particularly relates to an evaluation method for the maintenance convenience of automobile parts.

Background

With the continuous increase of the automobile holding capacity, the convenience of maintaining automobile parts is increasingly emphasized. The good maintenance convenience can reduce the waiting time of the customer, reduce the maintenance cost and contribute to improving the overall evaluation of the customer on the automobile.

The maintenance convenience of the automobile parts belongs to the inherent property, the quality degree of the automobile parts is locked when the product data is frozen, and the automobile parts are difficult to change. Although the automobile designer can consider the maintenance convenience in the design process, quantitative analysis cannot be performed due to the lack of quantitative indexes. Therefore, designers often only perform qualitative checking on the maintenance convenience, and cannot evaluate the quality degree and perform targeted design improvement.

At present, when the maintenance convenience of the parts is considered, an automobile designer usually determines the maintenance convenience of the parts by adopting a qualitative analysis and subjective judgment mode. For example, key indexes affecting the maintenance convenience, such as visibility, accessibility and the like, are listed first, and then the corresponding indexes of the part to be evaluated are subjectively scored within a good-medium-poor range. Due to different abilities and experiences of designers, evaluation criteria of different designers for the same index may be different, so that scores of different designers for the maintenance convenience of the same part may be different. Meanwhile, qualitative analysis is difficult to assist designers to define the optimization direction of the scheme, so that the optimal design scheme is difficult to obtain.

Disclosure of Invention

The invention provides an evaluation method for the maintenance convenience of automobile parts, which can assist designers to optimize a design scheme and solve the problem that quantitative analysis cannot be carried out due to the lack of quantitative indexes in the prior art.

The technical scheme of the invention is described as follows by combining the attached drawings:

a method for evaluating the maintenance convenience of automobile parts comprises the following steps:

step one, setting an evaluation index;

comprises repeatable disassembly B1, weight B2, disassembly step number B3, disassembly torque B4, peripheral component disassembly step number B5, visibility B6, operation space B7, maintenance person number B8, special equipment requirement B9 and fatigue degree B1010 indexes;

step two, constructing a judgment matrix according to an analytic hierarchy process, classifying and sorting 10 evaluation indexes, and constructing 4 judgment matrices;

step three, selecting workers to fill in the judgment matrixes respectively according to requirements of an analytic hierarchy process;

expanding the judgment matrix sample to 1000 parts;

calculating 1000 judgment matrix sample element mean values, and re-filling the judgment matrix to be recorded as a mean value judgment matrix;

step six, checking the consistency of the mean judgment matrix;

step seven, calculating the weight of each evaluation index according to the mean judgment matrix passing the inspection;

step eight, setting scoring standards of all evaluation indexes;

step nine, according to the scoring standard of step eight, scoring each index of the part to be evaluated;

and step ten, weighting the scores of all the indexes to obtain a comprehensive score of the maintenance convenience of the part.

The specific method of the second step is as follows:

the 10 indexes are divided into 3 types of first-level indexes, specifically, a part attribute A1 index, a scheme attribute A2 index and an environment attribute A3 index;

wherein the part attribute indicators include a repeatable disassembly B1, a weight B2, a disassembly step number B3, and a disassembly torque B4;

the project attribute indexes comprise a perimeter disassembly step number B5, visibility B6 and an operation space B7;

the environment attribute indexes comprise a maintenance person number B8, a special equipment requirement B9 and a fatigue degree B10; and 4 judgment matrixes, namely a primary index judgment matrix, a part attribute judgment matrix, a scheme attribute judgment matrix and an environment attribute judgment matrix, are constructed according to the classification.

The concrete method of the third step is as follows:

the number of the workers is not less than 5.

The concrete method of the fourth step is as follows:

according to the bootstrap method, the judgment matrix samples are expanded to 1000 parts by using a computer programming means.

The concrete method of the seventh step is as follows:

the weights of repeatable disassembly, weight, disassembly steps, disassembly moment, disassembly steps of the peripheral parts, visibility, operation space, the number of maintenance personnel, special equipment requirements and fatigue degree are 0.0483, 0.0199, 0.0107, 0.0096, 0.1666, 0.1522, 0.1206, 0.2027, 0.2166 and 0.0528 in sequence.

The concrete method of the step eight is as follows:

repeatable detachability scoring criteria: the repeated disassembly is 100 minutes, and the repeated disassembly is 40 minutes;

weight scoring criteria: counting the weight of a certain vehicle part, and arranging the parts in ascending order, wherein the first 15%, the first 50% and the first 95% of all weight data are scoring nodes, (0,23] g is 100 points, (23,193.3] g is 80 points, (193.3,6803.5] g is 60 points, (6803.5, + ∞ ] g is 40 points;

disassembling step number scoring standard: counting the disassembly steps of a certain vehicle part, and arranging the disassembly steps in an ascending order, wherein the first 15%, the first 50% and the first 95% of all the disassembly steps are scoring nodes, the steps of 0 and 2 are 100 minutes, the steps of 2 and 4 are 80 minutes, the steps of 4 and 17 are 60 minutes, and the steps of 17 and + ∞are40 minutes;

the disassembly torque scoring standard is as follows: counting the disassembly torque of a certain vehicle part, and arranging the disassembly torque in ascending order, wherein the first 15%, the first 50% and the first 95% of all the disassembly torques are scoring nodes, (0,21] N.m is 100 points, (21,65] N.m is 80 points, (65,229] N.m is 60 points, (229, + ∞ N.m is 40 points;

peripheral part disassembly step number scoring standard: the synchronous disassembly step number scoring standard is that the (0, 2) step is 100 minutes, the (2, 4) step is 80 minutes, the (4, 17) step is 60 minutes, and the (17, infinity) step is 40 minutes;

operating space scoring criteria: and performing assembly simulation on the operation tool based on the CATIA assembly design module. Alpha is the maximum movement angle of the torque wrench, alpha is more than or equal to 60 degrees and is 100 minutes, alpha is more than or equal to 30 degrees and less than 60 degrees and is 80 minutes, and alpha is more than 0 degrees and less than 30 degrees and is 60 minutes;

the maintenance person number scoring standard is as follows: 100 points for 1 person, 80 points for 2 persons, 60 points for 3 persons, and 40 points for more than 3 persons;

special equipment requirement scoring standard: the required special equipment is 100 minutes and 40 minutes;

the fatigue degree scoring standard is as follows: analyzing the human body posture by a RULA method by utilizing a CATIA ergonomic design and analysis module, wherein the green color is 100 minutes, the yellow color is 80 minutes, the orange color is 60 minutes, and the red color is 40 minutes

Visibility scoring criteria: based on a CATIA ergonomic design and analysis module, static simulation of operation postures of maintenance personnel is carried out, an Open Vision Window command is applied to observe a target part, a visual range is divided into 3 areas I II III, the areas are distributed as shown in figure 1, the number of all the target parts falling in the areas I is 100, the number of parts of the target part falling in the areas I and II is 80, the number of parts of the target part falling in the areas III is 60, and the number of parts of the target part not falling in a visual Window is 40.

The invention has the beneficial effects that:

1) the invention sets the evaluation index weight according to a large amount of sample data, and is objective;

2) the evaluation standard grading of each evaluation index of the invention can be quantized, and no main observation evaluation item exists;

3) the evaluation result of the invention is presented by numerical value, which is convenient for comparing the maintenance convenience among different parts;

4) the method can be applied to the product research and development stage, and helps designers to identify the problem of convenience in maintenance in advance.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the contents of the embodiments of the present invention and the drawings without creative efforts.

FIG. 1 is a flow chart of the operation of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, a method for evaluating the maintenance convenience of an automobile part includes the following steps:

step one, setting an evaluation index;

comprises repeatable disassembly B1, weight B2, disassembly step number B3, disassembly torque B4, peripheral component disassembly step number B5, visibility B6, operation space B7, maintenance person number B8, special equipment requirement B9 and fatigue degree B1010 indexes;

step two, constructing a judgment matrix according to an analytic hierarchy process, classifying and sorting 10 evaluation indexes, and constructing 4 judgment matrices;

the 10 indexes are divided into 3 types of first-level indexes, specifically, a part attribute A1 index, a scheme attribute A2 index and an environment attribute A3 index; wherein the part attribute indicators include a repeatable disassembly B1, a weight B2, a disassembly step number B3, and a disassembly torque B4;

the project attribute indexes comprise a perimeter disassembly step number B5, visibility B6 and an operation space B7;

the environment attribute indexes comprise a maintenance person number B8, a special equipment requirement B9 and a fatigue degree B10; and 4 judgment matrixes, namely a primary index judgment matrix, a part attribute judgment matrix, a scheme attribute judgment matrix and an environment attribute judgment matrix, are constructed according to the classification. Specifically, as shown in tables 1 to 5:

TABLE 1 evaluation index Classification Table

TABLE 2 first-level index decision matrix

TABLE 3 part Attribute decision matrix

TABLE 4 scheme Attribute decision matrix

TABLE 5 Environment Attribute decision matrix

Step three, selecting workers to fill in the judgment matrixes respectively according to requirements of an analytic hierarchy process;

the number of the workers is not less than 5.

Expanding the judgment matrix sample to 1000 parts;

according to the bootstrap method, the judgment matrix samples are expanded to 1000 parts by using a computer programming means.

Calculating 1000 judgment matrix sample element mean values, and re-filling the judgment matrix to be recorded as a mean value judgment matrix;

step six, checking the consistency of the mean judgment matrix;

step seven, calculating the weight of each evaluation index according to the mean judgment matrix passing the inspection;

the weights of repeatable disassembly, weight, disassembly steps, disassembly moment, disassembly steps of the peripheral parts, visibility, operation space, the number of maintenance personnel, special equipment requirements and fatigue degree are 0.0483, 0.0199, 0.0107, 0.0096, 0.1666, 0.1522, 0.1206, 0.2027, 0.2166 and 0.0528 in sequence.

Step eight, setting scoring standards of all evaluation indexes;

repeatable detachability scoring criteria: the repeated disassembly is 100 minutes, and the repeated disassembly is 40 minutes;

weight scoring criteria: counting the weight of a certain vehicle part, and arranging the parts in ascending order, wherein the first 15%, the first 50% and the first 95% of all weight data are scoring nodes, (0,23] g is 100 points, (23,193.3] g is 80 points, (193.3,6803.5] g is 60 points, (6803.5, + ∞ ] g is 40 points;

disassembling step number scoring standard: counting the disassembly steps of a certain vehicle part, and arranging the disassembly steps in an ascending order, wherein the first 15%, the first 50% and the first 95% of all the disassembly steps are scoring nodes, the steps of 0 and 2 are 100 minutes, the steps of 2 and 4 are 80 minutes, the steps of 4 and 17 are 60 minutes, and the steps of 17 and + ∞are40 minutes;

the disassembly torque scoring standard is as follows: counting the disassembly torque of a certain vehicle part, and arranging the disassembly torque in ascending order, wherein the first 15%, the first 50% and the first 95% of all the disassembly torques are scoring nodes, (0,21] N.m is 100 points, (21,65] N.m is 80 points, (65,229] N.m is 60 points, (229, + ∞ N.m is 40 points;

peripheral part disassembly step number scoring standard: the synchronous disassembly step number scoring standard is that the (0, 2) step is 100 minutes, the (2, 4) step is 80 minutes, the (4, 17) step is 60 minutes, and the (17, infinity) step is 40 minutes;

operating space scoring criteria: and performing assembly simulation on the operation tool based on the CATIA assembly design module. Alpha is the maximum movement angle of the torque wrench, alpha is more than or equal to 60 degrees and is 100 minutes, alpha is more than or equal to 30 degrees and less than 60 degrees and is 80 minutes, and alpha is more than 0 degrees and less than 30 degrees and is 60 minutes;

the maintenance person number scoring standard is as follows: 100 points for 1 person, 80 points for 2 persons, 60 points for 3 persons, and 40 points for more than 3 persons;

special equipment requirement scoring standard: the required special equipment is 100 minutes and 40 minutes;

the fatigue degree scoring standard is as follows: analyzing the human body posture by a RULA method by utilizing a CATIA ergonomic design and analysis module, wherein the green color is 100 minutes, the yellow color is 80 minutes, the orange color is 60 minutes, and the red color is 40 minutes

Visibility scoring criteria: based on a CATIA ergonomic design and analysis module, static simulation of operation postures of maintenance personnel is carried out, an Open Vision Window command is applied to observe a target part, a visual range is divided into 3 areas I II III, the areas are distributed as shown in figure 1, the number of all the target parts falling in the areas I is 100, the number of parts of the target part falling in the areas I and II is 80, the number of parts of the target part falling in the areas III is 60, and the number of parts of the target part not falling in a visual Window is 40.

Step nine, according to the scoring standard of step eight, scoring each index of the part to be evaluated;

and step ten, weighting the scores of all the indexes to obtain a comprehensive score of the maintenance convenience of the part.

Examples

The convenience of maintenance of a luxury brand class C driver seat is evaluated by taking the luxury brand class C driver seat as a research object.

Step one, setting an evaluation index;

step two, constructing a judgment matrix according to an analytic hierarchy process, classifying and sorting 10 evaluation indexes, and constructing 4 judgment matrices;

step three, selecting workers to fill in the judgment matrixes respectively according to requirements of an analytic hierarchy process, wherein the judgment matrixes are shown in tables 6 to 25;

TABLE 6 staff 1 level index decision matrix

TABLE 7 staff 1 part Attribute decision matrix

TABLE 8 staff 1 schema Attribute decision matrix

TABLE 9 staff 1 Environment Attribute decision matrix

TABLE 10 staff 2 level index decision matrix

TABLE 11 staff 2 part Attribute decision matrix

TABLE 12 staff 2 schema attributes decision matrix

TABLE 13 staff 2 Environment Attribute decision matrix

TABLE 14 staff 3 level index decision matrix

TABLE 15 staff 3 part Attribute decision matrix

TABLE 16 staff 3 schema attributes decision matrix

TABLE 17 staff 3 Environment Attribute decision matrix

TABLE 18 staff 4 level index decision matrix

TABLE 19 staff 4 part Attribute decision matrix

TABLE 20 staff 4 schema attributes decision matrix

TABLE 21 staff 4 Environment Attribute decision matrix

TABLE 22 staff 5 level index decision matrix

TABLE 23 staff 5 part Attribute decision matrix

TABLE 24 staff 5 schema attributes decision matrix

TABLE 25 staff 5 Environment Attribute decision matrix

Expanding the judgment matrix sample to 1000 parts;

according to bootstrap method, the computer programming means is used to expand the judgment matrix sample to 1000 parts

Calculating 1000 judgment matrix sample element mean values, re-filling the judgment matrix, and recording as a mean value judgment matrix, which is specifically shown in tables 26-29;

table 26 first-level index mean judgment matrix

Table 27 part attribute mean judgment matrix

TABLE 28 scheme Attribute mean decision matrix

Table 29 environment attribute mean judgment matrix

Step six, checking the consistency of the mean judgment matrix, specifically as shown in tables 30-33;

table 30 first-level index mean judgment matrix consistency test

TABLE 31 part Attribute mean determination matrix consistency test

TABLE 32 scheme Attribute mean determination matrix consistency test

TABLE 33 Environment Attribute mean determination matrix consistency test

Step seven, calculating the weight of each evaluation index according to the mean judgment matrix passing the inspection;

the weights of repeatable disassembly, weight, disassembly steps, disassembly moment, disassembly steps of the peripheral parts, visibility, operation space, the number of maintenance personnel, special equipment requirements and fatigue degree are 0.0483, 0.0199, 0.0107, 0.0096, 0.1666, 0.1522, 0.1206, 0.2027, 0.2166 and 0.0528 in sequence.

Step eight, setting scoring standards of all evaluation indexes;

step nine, according to the scoring standard of step eight, scoring each index of the driver seat, as shown in table 34 specifically;

table 34 score of each index of driver's seat

Step ten, weighting the scores of all the indexes to obtain a comprehensive score 94.458 for the convenience of maintenance of the driver seat.

In conclusion, the hierarchical level and the judgment matrix are constructed by utilizing an analytic hierarchy process, the sample capacity is enlarged by utilizing a bootstrap method, the weight of each evaluation index is obtained through calculation, meanwhile, the scoring standards of the evaluation indexes are set one by adopting methods such as mathematical statistics, CATIA assembly simulation, ergonomic analysis and qualitative analysis, and finally, the score of the convenience in maintaining the automobile parts is obtained through weighted calculation by combining the weight and the scoring standards of the evaluation indexes.

Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (6)

1. The method for evaluating the maintenance convenience of the automobile parts is characterized by comprising the following steps of:

step one, setting an evaluation index;

comprises repeatable disassembly B1, weight B2, disassembly step number B3, disassembly torque B4, peripheral component disassembly step number B5, visibility B6, operation space B7, maintenance person number B8, special equipment requirement B9 and fatigue degree B1010 indexes;

step two, constructing a judgment matrix according to an analytic hierarchy process, classifying and sorting 10 evaluation indexes, and constructing 4 judgment matrices;

step three, selecting workers to fill in the judgment matrixes respectively according to requirements of an analytic hierarchy process;

expanding the judgment matrix sample to 1000 parts;

calculating 1000 judgment matrix sample element mean values, and re-filling the judgment matrix to be recorded as a mean value judgment matrix;

step six, checking the consistency of the mean judgment matrix;

step seven, calculating the weight of each evaluation index according to the mean judgment matrix passing the inspection;

step eight, setting scoring standards of all evaluation indexes;

step nine, according to the scoring standard of step eight, scoring each index of the part to be evaluated;

and step ten, weighting the scores of all the indexes to obtain a comprehensive score of the maintenance convenience of the part.

2. The method for evaluating the maintenance convenience of the automobile parts according to claim 1, wherein the specific method in the second step is as follows:

the 10 indexes are divided into 3 types of first-level indexes, specifically, a part attribute A1 index, a scheme attribute A2 index and an environment attribute A3 index;

wherein the part attribute indicators include a repeatable disassembly B1, a weight B2, a disassembly step number B3, and a disassembly torque B4;

the project attribute indexes comprise a perimeter disassembly step number B5, visibility B6 and an operation space B7;

the environment attribute indexes comprise a maintenance person number B8, a special equipment requirement B9 and a fatigue degree B10; and 4 judgment matrixes, namely a primary index judgment matrix, a part attribute judgment matrix, a scheme attribute judgment matrix and an environment attribute judgment matrix, are constructed according to the classification.

3. The method for evaluating the maintenance convenience of the automobile parts according to claim 1, wherein the concrete method of the third step is as follows:

the number of the workers is not less than 5.

4. The method for evaluating the ease of repairing automobile parts according to claim 1, wherein the concrete method of the fourth step is as follows:

according to the bootstrap method, the judgment matrix samples are expanded to 1000 parts by using a computer programming means.

5. The method for evaluating the maintenance convenience of the automobile parts according to claim 1, wherein the concrete method of the seventh step is as follows:

the weights of repeatable disassembly, weight, disassembly steps, disassembly moment, disassembly steps of the peripheral parts, visibility, operation space, the number of maintenance personnel, special equipment requirements and fatigue degree are 0.0483, 0.0199, 0.0107, 0.0096, 0.1666, 0.1522, 0.1206, 0.2027, 0.2166 and 0.0528 in sequence.

6. The method for evaluating the ease of repairing automobile parts according to claim 1, wherein the concrete method of the step eight is as follows:

repeatable detachability scoring criteria: the repeated disassembly is 100 minutes, and the repeated disassembly is 40 minutes;

weight scoring criteria: counting the weight of a certain vehicle part, and arranging the parts in ascending order, wherein the first 15%, the first 50% and the first 95% of all weight data are scoring nodes, (0,23] g is 100 points, (23,193.3] g is 80 points, (193.3,6803.5] g is 60 points, (6803.5, + ∞ ] g is 40 points;

disassembling step number scoring standard: counting the disassembly steps of a certain vehicle part, and arranging the disassembly steps in an ascending order, wherein the first 15%, the first 50% and the first 95% of all the disassembly steps are scoring nodes, the steps of 0 and 2 are 100 minutes, the steps of 2 and 4 are 80 minutes, the steps of 4 and 17 are 60 minutes, and the steps of 17 and + ∞are40 minutes;

the disassembly torque scoring standard is as follows: counting the disassembly torque of a certain vehicle part, and arranging the disassembly torque in ascending order, wherein the first 15%, the first 50% and the first 95% of all the disassembly torques are scoring nodes, (0,21] N.m is 100 points, (21,65] N.m is 80 points, (65,229] N.m is 60 points, (229, + ∞ N.m is 40 points;

peripheral part disassembly step number scoring standard: the synchronous disassembly step number scoring standard is that the (0, 2) step is 100 minutes, the (2, 4) step is 80 minutes, the (4, 17) step is 60 minutes, and the (17, infinity) step is 40 minutes;

operating space scoring criteria: and performing assembly simulation on the operation tool based on the CATIA assembly design module. Alpha is the maximum movement angle of the torque wrench, alpha is more than or equal to 60 degrees and is 100 minutes, alpha is more than or equal to 30 degrees and less than 60 degrees and is 80 minutes, and alpha is more than 0 degrees and less than 30 degrees and is 60 minutes;

the maintenance person number scoring standard is as follows: 100 points for 1 person, 80 points for 2 persons, 60 points for 3 persons, and 40 points for more than 3 persons;

special equipment requirement scoring standard: the required special equipment is 100 minutes and 40 minutes;

the fatigue degree scoring standard is as follows: analyzing the human body posture by a RULA method by utilizing a CATIA ergonomic design and analysis module, wherein the green color is 100 minutes, the yellow color is 80 minutes, the orange color is 60 minutes, and the red color is 40 minutes

Visibility scoring criteria: based on a CATIA ergonomic design and analysis module, static simulation of operation postures of maintenance personnel is carried out, an Open Vision Window command is applied to observe a target part, a visual range is divided into 3 areas I II III, the areas are distributed as shown in figure 1, the number of all the target parts falling in the areas I is 100, the number of parts of the target part falling in the areas I and II is 80, the number of parts of the target part falling in the areas III is 60, and the number of parts of the target part not falling in a visual Window is 40.

Images