A physical design method for assembly process based on user cognition

Abstract

The present invention relates to an assembly process expression design method for assisting manual assembly, specifically an assembly process materialization design method based on the cognitive differences among individual assembly users. This method first analyzes the cognitive differences of users in the process and explores their demand patterns, determines the user demand characteristics of the assembly process, and based on this, conducts materialization design on the assembly process, establishes an assembly process materialization instruction library, providing theoretical and data support for the materialized process instruction push-assisted guided assembly prototype system; secondly, constructs the association relationship between individual users and the materialized process, develops a materialized process instruction push-assisted guided assembly prototype system based on the cognitive differences of users, and completes the verification of the usability and applicability of the assembly process materialization design method based on user cognition. In this way, the assembly guidance system can push assembly guidance instruction information that matches the assembly process cognitive level of the assembly workers according to the needs of the assembly workers, accurately relieve the cognitive pressure of the assembly workers, and thus further improve the assembly efficiency and assembly quality in the manual assembly process of complex and major products.

Description

[0001] Field of the Invention

[0002] The present invention relates to a method for expressing and designing an assembly process for assisting manual assembly, specifically a method for physically designing an assembly process based on the cognitive differences among individual assembly users, which can be used to assist and guide an assembly system. The present invention relates to knowledge theories of user cognitive psychology, multimedia technology, augmented reality technology, etc. Technical Background

[0003] Under the background of the era of intelligent manufacturing, the high-performance assembly of major complex products such as aero-engines, which is digitalized, informatized, and intelligent, has attracted extensive research by scholars at home and abroad. By using technologies such as multimedia digitization, three-dimensional visualization, and augmented reality in the manual assembly process of major products, the digital model information is integrated with the assembly site, and the assembly guidance information is displayed more intuitively and accurately to more efficiently solve problems such as high error rates and low efficiency in the manual assembly process. These new types of auxiliary assembly technology methods can display all the assembly process instruction information at the assembly site, and the content expression method is becoming more and more intuitive and vivid, but their applicability at the assembly site is not strong. There are problems such as the disconnection between the assembly guidance with the assistance of multimedia 3D animation electronic displays and the assembly operation process of the workers at the assembly site, discomfort when wearing the augmented reality glasses during the operation by the assembly workers, and interference with the attention of experienced assembly workers by the assembly guidance information.

[0004] The inventor found that mainly due to the following deficiencies still existing in the process of assisting and guiding assembly with current display technologies such as multimedia digitization, three-dimensional visualization, and augmented reality:

[0005] There is a problem of single guidance scheme in the assembly guidance process. The existing assembly guidance system is for all assembly workers, and the same assembly guidance scheme is adopted during the assembly operation process, including the content and form of the assembly process instruction information. However, the experience levels of the assembly worker group are not the same, and the familiarity of assembly workers with different experience levels with the assembly process and assembly tasks is also different. If an assembly guidance scheme adapted to their needs is not formulated according to the needs of assembly workers with different experience levels, it will affect the reading and understanding of the assembly guidance information by some assembly operators, resulting in the problem of weak applicability of the assembly guidance system.

[0006] The above problems restrict the development of the auxiliary guidance technology in the field of complex and major product assembly, making the efficiency and quality of the assembly guidance method fail to reach the expected ideal effect. In the case where the expression of the assembly process instruction information seriously does not match the needs of the assembly workers, there will even be a situation where the auxiliary guidance efficiency based on technologies such as multimedia digital, three-dimensional stereoscopic, and augmented reality is not higher than that of the traditional drawing-based assembly process manual. In order to improve the applicability of the assembly guidance process instruction information on-site, it is a very important task to conduct targeted design of the assembly process instruction expression with the assembly guidance display information as the goal.

[0007] Content of the Invention

[0008] Aiming at the problems of weak applicability such as single existing form, weak emphasis, and weak pertinence of the auxiliary guidance assembly process information, the present invention proposes an assembly process physical design method based on the cognitive differences among individual users. First, by analyzing the cognitive differences of users in the process and exploring their demand laws, the user demand characteristics of the assembly process are determined, and based on this, the assembly process is physically designed to establish an assembly process physical instruction library, providing theoretical and data support for the physical process instruction push-assisted guidance assembly prototype system; secondly, the association relationship between the individual user and the physical process is constructed, and the physical process instruction push-assisted guidance assembly prototype system based on the user cognitive differences is developed to complete the verification of the usability and applicability of the assembly process physical design method based on the user cognition. In this way, the assembly guidance system can push the assembly guidance instruction information that matches the assembly process cognitive level of the assembly workers according to their needs, accurately relieve the cognitive pressure of the assembly workers, and thus further improve the assembly efficiency and assembly quality in the manual assembly process of complex and major products.

[0009] In order to improve the applicability of the auxiliary guidance assembly system on-site during assembly, the present invention provides an assembly process physical design method based on user cognition. It is characterized by the following steps:

[0010] Step 1: Design of the user assembly guidance interaction experiment. By means of the user interaction experiment method, compare the cognitive differences among individual users in the assembly process, understand their expression needs for the assembly process, and conduct the experimental design with the user experience level and the assembly process expression method as the prediction factors for the user process cognitive differences, which is divided into 5 steps:

[0011] Step 1.1: Divide the user experience level into two types: novice users and experienced users, and divide the assembly process expression methods into four types: text, pictures, animations, and videos;

[0012] Step 1.2: Select the experimental assembly task, and determine the assembly key points as the basis for judging the assembly correctness. At the same time, express the assembly process of the assembly task in the above four ways to guide the users in the assembly;

[0013] Step 1.3: Taking the multi-factor repeated measures experiment as the experimental model, conduct the experimental group design. The influence of the user experience level is studied through the between-group design, and the influence of the expression method of the assembly process instructions is studied through the within-group design method;

[0014] Step 1.4: Design the methods for observing and recording user behaviors during the experiment, the NASA-TLX questionnaire, the interest tendency questionnaire, and the content of the in-depth interview;

[0015] Step 1.5: Design the implementation process of the user assembly guidance interaction experiment, and the process is as follows: 1) Conduct the pre-test of the user experience experiment; 2) Recruit, group, and train the participants; 3) Conduct the assembly process of the user experience experiment and record; 4) Fill in the questionnaire of the user experience experiment; 5) Conduct the in-depth interview of the user experience experiment; 6) Organize and summarize the data;

[0016] Step 2: Implement the user assembly guidance interaction experiment. According to the experimental process in Step 1.5, enable users with different experience levels to conduct the assembly interaction experience experiment, and obtain the experimental task data completed by the users from 5 aspects: the assembly time, assembly accuracy rate, assembly load interest tendency, and subjective feelings of the users when completing the assembly experiment task. During the experimental implementation process, through the observation and record of user behaviors, obtain the objective performance of the assembly users in terms of assembly time, assembly accuracy rate, and operation behaviors during the assembly process; quantitatively evaluate the assembly load of the assembly users during the assembly process through the NASA-TLX questionnaire; obtain the subjective experience feelings of the assembly users, such as their preferences for the process expression methods and their experiences and expectations for the expression of the assembly process instructions, through the interest tendency questionnaire and the in-depth interview;

[0017] Step 3: Analyze the data of the user assembly guidance interaction experiment. Use the repeated trial analysis model to analyze the cognitive differences of users with different experience levels in the guiding process instructions, mainly by analyzing the performances of users with 2 experience levels under 4 conditions of the process instruction expression methods, that is, the subjective and objective data analysis of the assembly time, assembly accuracy rate, assembly load, interest tendency, and experience feelings of the assembly users when completing the experimental tasks; it is mainly divided into 3 steps:

[0018] Step 3.1: Based on the experimental data obtained in Step 2, use SPSS to analyze whether there are significant differences in the assembly time, assembly accuracy rate, assembly load, and interest tendency of users with different experience levels using different assembly guidance expression methods by using the general linear repeated measures data analysis model;

[0019] Step 3.2: Compare the average error values of the assembly time, assembly accuracy rate, and subjective and objective data of assembly load obtained in the above Step 2 through two comparison methods, that is, the performance comparison of two users with different experience levels under the guidance of the expression methods of 4 assembly process instructions respectively, and the performance comparison of two users with different experience levels in completing the assembly tasks under the guidance of the expression method of the same assembly process instruction; at the same time, in terms of the interest tendency selection, compare the number of times of the expression method tendency selection of two users with different experience levels;

[0020] Step 3.3: Based on the analysis and comparison results of the above Step 3.1 and Step 3.2, obtain the ranking of the assembly guidance effects of the 4 expression methods for novice users and experienced users in terms of assembly time, assembly accuracy rate, assembly load, and interest tendency respectively; in terms of assembly time, the expression method with a shorter assembly guidance time ranks higher. In terms of assembly accuracy rate, the expression method with a higher assembly guidance accuracy rate ranks higher. In terms of assembly load, the expression method with a smaller assembly guidance load ranks higher. In terms of interest tendency, the expression method with a larger number of times of tendency selection ranks higher; in the above 4 aspects, when there are significant differences in the use of different assembly guidance expression methods by users with different experience levels, the rankings of the assembly guidance effects of the 4 expression methods for novice users and experienced users are different, otherwise, they are the same;

[0021] Step 4: Analysis of the requirements of users for the assembly guidance process instructions. Based on the results obtained in Step 3.3 and combined with the user experience, analyze the requirements of novice users and experienced users for the information quantity and intuitive vividness of the process instruction expression, which are divided into the following 3 steps:

[0022] Step 4.1: Assembly accuracy rate and assembly time are important factors affecting assembly efficiency. According to the characteristics of the user experience level, novice users should first refer to the performance results in terms of assembly accuracy rate, while experienced users should first refer to the performance results in terms of assembly time;

[0023] Step 4.2: Let the participating users rate the information quantity and intuitive vividness of the 4 expression methods, and it is obtained that in terms of information quantity, the 4 expression methods can all control the size. In terms of intuitive vividness, the video and animation are the most intuitive and vivid; the pictures are the second, and the text is the weakest;

[0024] Step 4.3: Combining the user experience, analyze the requirements of two users with different experience levels for the information quantity and intuitive vividness of the process instruction expression, and it is obtained that novice users have a greater demand for the information quantity of the process instruction expression, and also have a relatively strong demand for the intuitiveness and vividness of the content; during the assembly process, the information quantity and intuitiveness of the guidance process instructions required by experienced users will both decrease relatively, which is related to the user's familiarity with the assembly operation and user preferences, and it is not the requirement rule that the less the information quantity, the simpler and better;

[0025] Step 5: Based on the demand laws of assembly users for assembly processes with different experience levels, construct an assembly user portrait. Stratify this user group according to the familiarity of assembly operators with assembly operations, comprehensively describe them according to their interest tendencies, complete the construction of the portrait of assembly process users, and determine the demand characteristics of different levels of users for the expression of assembly process instructions from three aspects: the amount of information, the intuitive vividness of content expression, and the selection of interest tendencies.

[0026] Step 6: Based on the demand characteristics of each level of assembly users for the expression of process instructions in Step 5, combined with the evaluation of assembly process expression methods in Step 4.2, obtain assembly knowledge and carry out the physical design of the assembly process, which is divided into 2 steps:

[0027] Step 6.1: Obtain assembly knowledge through methods such as assembly process manuals and on-site assembly teaching, which is the object-oriented for the physical design of the assembly process;

[0028] Step 6.2: According to the relevant principles of visual language presentation, for the demand characteristics of different levels of users for the expression of assembly process instructions in Step 5, combined with the evaluation results of assembly process expression methods in Step 4.2, design corresponding physical assembly process instructions and construct a physical assembly process instruction library;

[0029] Step 7: Construct the association relationship between user individuals and physical processes. By designing user level tests, evaluation and division schemes, match the user process demand characteristics corresponding to user individuals, so as to be associated with the physical assembly process instructions in Step 6.2;

[0030] Step 8: Establish a prototype system for pushing physical process instructions. Based on the system development framework and the theoretical guidance of the association relationship between user individuals and physical processes, build the physical process instruction push system platform from both virtual and physical environments, and complete the verification of the usability and applicability of the physical design method of assembly processes based on user cognition.

[0031] Compared with the assembly instruction information presented under the existing auxiliary guidance assembly technology, the main advantages of the present invention are as follows: By means of an assembly process physical design method that analyzes the cognitive differences among individual users, the present invention constructs an assembly process user demand feature model, and conducts physical design on the assembly process, thereby establishing an assembly process physical instruction library. By developing a physical process instruction push prototype system to push assembly guidance instruction information that matches the assembly process cognitive level of assembly workers according to their needs, the problems of inaccurate, incomplete description and single guidance scheme of the existing assembly guidance instruction information are solved. Centering on the assembly user, the cognitive pressure of the assembly site workers on the guidance instruction information is reduced in a more accurate way, thereby improving the applicability of the assembly guidance system, and providing a solution idea for further improving the assembly efficiency and assembly quality of the manual assembly process of complex and major products. Brief Description of the Drawings

[0032] Figure 1 It is an assembly process physical design scheme based on user cognition;

[0033] Figure 2 It is a flowchart for analyzing the user demands of the assembly process;

[0034] Figure 3 It is a comparison chart of the cognitive differences of assembly process users;

[0035] Figure 4 It is an evaluation of multimedia expression methods;

[0036] Figure 5 It is the user demand characteristics of the assembly process;

[0037] Figure 6 It is the physical design process of the assembly process;

[0038] Figure 7 It is the acquisition of assembly process knowledge; [[ID=3I]]

[0039] Figure 8 It is the relevant principles of visual language presentation;

[0040] Figure 9 It is an example of an assembly process physical instruction library for the low-pressure turbine rotor blades of an aeroengine;

[0041] Figure 10 It is the association relationship between the individual user and the physical process;

[0042] Figure 11 It is the development framework of the physical process instruction push prototype system;

[0043] Figure 12 It is the construction of the physical process instruction push system platform.

[0044] 8. Implementation Examples

[0045] The present invention will be further described below in conjunction with specific embodiments and the accompanying drawings:

[0046] In this embodiment, taking the guiding system for assisting the assembly of the low-pressure turbine rotor blades of an aero-engine as an example, based on the physical design method of the assembly process based on user cognition, the following steps are adopted:

[0047] As Figure 1 shown, a guiding assembly system for assistance, based on the physical design scheme of the assembly process based on user cognition. First, through user experience experiments, the analysis of user process cognition differences and the exploration of demand laws are completed; then, combined with the user portrait construction method, the expression demand characteristics of the user's individual process instruction information are further constructed; then, based on the user's process demand characteristics, combined with methods such as the acquisition of process knowledge, physical expression evaluation, and visual presentation design for physical design; the association relationship between the user individual and the physical process is constructed, the physical process instruction push scheme design is completed, and the prototype system is built and deployed from both software and hardware aspects to realize the on-demand push of the physical assembly instructions. It includes the following steps:

[0048] Step 1: As Figure 2 shown, design the user assembly guiding interaction experiment. The experimental design is carried out with the user experience level and the assembly process expression method as the prediction factors for user process cognition differences. The specific steps are as follows:

[0049] Step 1.1: Divide the user experience level into two types: novice users and experienced users, and divide the assembly process expression methods into four types: text, picture, animation, and video;

[0050] Step 1.2: Select the assembly process of the second-stage blades of the low-pressure turbine of the aero-engine as an example. (A laboratory assembly model has been constructed according to the physical characteristics of the assembly), determine the work steps 4 and 5 of this process as the experimental assembly tasks, and determine the assembly key points as the basis for judging the assembly correctness. At the same time, express the assembly process of the assembly task in the above four ways to guide the user for assembly;

[0051] Step 1.3: As shown in Table 1, take the multi-factor repeated measurement experiment as the experimental model to conduct the experimental group design, which includes both between-group design components and within-group design components. The user experience level analysis is based on rows. Analyze the influence of the user experience level by comparing conditions 1 and 5, 2 and 6, 3 and 7, 4 and 8 respectively, and analyze the influence of the assembly guiding expression method by comparing conditions 1, 2, 3, and 4, and conditions 5, 6, 7, and 8. As shown in Table 2, use the Latin square balance to process the experimental sequence groups to avoid the learning effect and fatigue effect during the experiment;

[0052] Step 1.4: Observe and record user behavior through experimental recordings. Design the NASA-TLX questionnaire and interest preference questionnaire (see Appendix 1 and Appendix 2). In-depth interview questions will focus on users' experiences with using the four assembly process instruction expressions to guide the completion of assembly tasks.

[0053] Step 1.5: Design the implementation process of the user assembly guided interaction experiment, which includes: 1) user experience experiment pre-test; 2) participant recruitment, grouping, and training; 3) user experience experiment assembly process and record keeping; 4) user experience experiment questionnaire completion; 5) user experience experiment in-depth interviews; 6) data collation and summary;

[0054] Step 2: Implement the user assembly guidance interaction experiment. According to the experimental process in step 1.5, let users with different experience levels conduct the assembly interaction experience experiment. The specific steps are as follows:

[0055] Step 2.1: Pre-test the user experience experiment. Find two students with aviation background to pre-test the entire user experience experiment process. If any loopholes or problems are found, make timely corrections.

[0056] Step 2.2: Recruitment, grouping and training of participants. A total of 32 participants were recruited to participate in the experiment. They were randomly divided into two groups, each with 16 participants. One group consisted of novice users (who became novice users after later training) and the other group consisted of experienced users (same as above). They completed the assembly task under four assembly guidance expression conditions (the order of conditions is shown in step 1.3). By controlling the training duration of the participants, users with two levels of assembly experience were obtained. The novice user group was given a brief introduction to the installation of secondary rotor blade-related components, processes, etc. (physical site, no paper manual), with an introduction time of 5-10 minutes, so that they had a general understanding of the assembly process; the experienced user group used the traditional paper assembly manual + physical site experience guidance method to intensively train the basic knowledge and assembly process of the entire blade assembly for 30-40 minutes.

[0057] Step 2.3: User experience and recording of the experimental assembly process. During the subject's assembly process, an experimental assistant recorded the entire process of the subject completing the assembly task to record the subject's assembly operation time, movements, and behavior.

[0058] Step 2.4: Complete the User Experience Experiment Questionnaire. Participants completed a NASA-TLX questionnaire after completing each assembly task under each assembly process instruction presentation method. After completing all four assembly process instruction presentation methods, they completed a questionnaire on preference ranking for assembly process instruction presentation methods. This meant each participant completed the questionnaire five times. After completing each assembly task under each assembly instruction presentation method, participants rested for two minutes to relieve fatigue.

[0059] Step 2.5: In-depth interviews for user experience experiment. After completing the assembly task, in-depth interviews are conducted with the assembly users. During this process, the interviewer records their feelings and remarks and records the whole process for subsequent collation.

[0060] Step 2.6: Data collation and induction. After the experiment, the correctness of the assembly operations of the subjects is judged according to the key points of the assembly task, and the time taken by the subjects to complete the assembly task under each assembly guidance expression method is recorded (all in the experimental data record form), and the interview records are sorted out and summarized.

[0061] Step 3: As Figure 2 shown, data analysis of the user assembly guidance interaction experiment. The repeated trial analysis model is used to analyze the cognitive differences of users with different experience levels in guiding process instructions. It mainly analyzes the performance of two types of users with different experience levels under four process instruction expression methods, that is, the subjective and objective data analysis of the assembly time, assembly accuracy rate, assembly load, interest tendency, and experience feelings of the assembly users to complete the experimental tasks; it is mainly divided into three steps:

[0062] Step 3.1: Based on the experimental data obtained in Step 2, use the general linear repeated measurement data analysis model in SPSS to analyze whether there are significant differences in assembly time, assembly accuracy rate, assembly load, and interest tendency among users with different experience levels using different assembly guidance expression methods;

[0063] Step 3.2: Compare the average error values of the subjective and objective data of the assembly time, assembly accuracy rate, and assembly load obtained in Step 2 above through two comparison methods, that is, the performance comparison of two types of users with different experience levels under the guidance of four assembly process instruction expression methods and the performance comparison of two types of users with different experience levels to complete the assembly task under the guidance of the same assembly process instruction expression method; at the same time, in terms of interest tendency selection, compare the number of times of expression method tendency selection of two types of users with different experience levels;

[0064] Step 3.3: Through the analysis and comparison in Steps 3.1 and 3.2 above, the rankings of the assembly effects of novice users and experienced users on the four expression methods are obtained in terms of assembly time, assembly accuracy rate, assembly load, and interest tendency, as Figure 3 shown;

[0065] Step 4: Analysis of the requirements for user assembly guidance process instructions. Based on the results obtained in Step 3.3 and combined with the user experience feelings, analyze the requirements of novice users and experienced users for the information quantity and intuitive vividness of the process instruction expression. The specific steps are as follows:

[0066] Step 4.1: Assembly accuracy and assembly time are important factors affecting assembly efficiency. Based on the user's experience level, novice users should first refer to the performance results for assembly accuracy, while experienced users should first refer to the performance results for assembly time.

[0067] Step 4.2: If Figure 4 As shown in the figure, based on the test users' ratings on the information content and intuitive vividness of the four expression methods, it was found that in terms of information content, the four expression methods can control the size, and in terms of intuitive vividness, videos and animations are the most intuitive and vivid; pictures are second, and text is the weakest;

[0068] Step 4.3: Based on user experience, we analyzed the requirements of users with different experience levels for the amount of information and the intuitiveness and vividness of process instructions. We found that novice users have a greater demand for the amount of information in process instructions, as well as stronger demand for intuitiveness and vividness. Experienced users, on the other hand, require less information and less intuitiveness during the assembly process. This is related to the user's familiarity with assembly operations and their preferences, and does not necessarily mean that less information and more simplicity are better.

[0069] Step 5: Based on the demand patterns of assembly users with different experience levels for assembly process, construct assembly user portraits. According to the assembly operator's familiarity with assembly operations, the user group is stratified, and their familiarity with assembly operations is divided into low, medium, and high. The assembly user group is further divided into three assembly user levels: beginner, medium, and advanced. The user's interest tendency is comprehensively described to complete the construction of the portraits of the three assembly user levels, see Appendix 3; the demand characteristics of different levels of users for the expression of assembly process instructions are determined from the three aspects of information volume, intuitive vividness, and interest tendency, such as Figure 5 shown.

[0070] Step 6: Figure 6 As shown in the figure, based on the requirements of assembly users at all levels for process instruction expression in step 5, combined with the evaluation of assembly process expression in step 4.2, assembly knowledge is acquired and the materialized design of the assembly process is carried out. The specific steps are as follows:

[0071] Step 6.1: If Figure 7 As shown, assembly knowledge is acquired through assembly process manuals and assembly on-site teaching, which serves as the object-oriented materialized design of assembly process;

[0072] Step 6.2: Present sensory, functional, and relevant principles based on visual language, such as Figure 8 As shown, for the demand characteristics of assembly process instructions expressed by users at different levels in step 5, combined with the evaluation results of assembly process expression in step 4.2, the corresponding assembly process materialization instructions are designed, and the assembly process materialization instruction library is constructed as shown in Figure 9as shown;

[0073] Step 7: As Figure 10 shown, establish the correlation between the user individual and the materialized process. Design the user level test, evaluation and division plan. Investigate, test and evaluate the assembly operation users in the form of answering questions and scoring from three aspects: the understanding of the assembly process knowledge by the operator, the proficiency in the assembly operation process and the on-the-job assembly duration, see Appendix 4; after testing, classify the assembly level and determine the characteristics according to the obtained scores. If the test score is below 70% of the total score, classify it as a primary assembly user; if the test score is 70% - 90% of the total score, classify it as an intermediate assembly user; if the test score is above 90% of the total score, classify it as a high-level assembly user, and match the user process requirement characteristics corresponding to the user individual, so as to be associated with the assembly process materialization instruction in Step 6.2;

[0074] Step 8: Establish a prototype system for pushing materialized process instructions. As Figure 11 shown, based on the system development framework and the theoretical guidance of the correlation between the user individual and the materialized process, build the materialized process instruction push system platform from both virtual and physical environments, as Figure 12 shown, and complete the verification of the usability and applicability of the assembly process materialization design method based on user cognition.

[0075] Table 1 Experimental Group Design

[0076]

[0077]

[0078] Table 2 Experimental Sequence Group Treatment

[0079]

[0080] The 4 appendix files used in this embodiment are as follows:

[0081] Appendix 1: NASA-TLX Questionnaire

[0082] NASA-TLX Questionnaire Design

[0083] Part 1:

[0084] Please make marks on the six measurement scales according to your own situation in the execution of the assembly task.

[0085] 1. Mental Demand: How do you think the assembly guidance expression requires mental effort and cognitive activities?

[0086]

[0087] 2. Physical effort required: How do you think the use of this assembly guidance expression affects the physical activity required?

[0088]

[0089] 3. Time required: Do you feel time pressure when using this assembly guidance expression to complete the task?

[0090]

[0091] 4. Personal performance: How do you think you performed in completing the task using this assembly guidance expression?

[0092]

[0093] 5. Degree of effort: To achieve the performance level you just self-assessed, how much effort did you spend during the completion process?

[0094]

[0095] 6. Degree of frustration: What was your level of frustration during the entire task when using this assembly guidance expression?

[0096]

[0097] Part Two:

[0098] In the following 15 groups, compare every two items and select the one that has the greatest impact on the task completion performance in each group.

[0099] 7. Under this assembly guidance expression, which do you think has a greater impact on the task completion performance?

[0100] A. Mental effort required

[0101] B. Physical effort required

[0102] 8. Under this assembly guidance expression, which do you think has a greater impact on the task completion performance?

[0103] A. Time required

[0104] B. Degree of frustration

[0105] 9. Under this assembly guidance expression, which do you think has a greater impact on the task completion performance?

[0106] A. Degree of effort

[0107] B. Personal performance

[0108] 10. Under this assembly guidance expression, which do you think has a greater impact on the task completion performance?

[0109] A, Degree of effort

[0110] B, Physical strength requirement

[0111] 11. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0112] A, Mental demand

[0113] B, Degree of frustration

[0114] 12. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0115] A, Physical strength requirement

[0116] B, Time requirement

[0117] 13. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0118] A, Personal performance

[0119] B, Physical strength requirement

[0120] 14. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0121] A, Mental demand

[0122] B, Degree of effort

[0123] 15. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0124] A, Degree of frustration

[0125] B, Physical strength requirement

[0126] 16. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0127] A, Time requirement

[0128] B, Personal performance

[0129] 17. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0130] A, Degree of effort

[0131] B, Time requirement

[0132] 18. Under this assembly guidance expression, what do you think has a great impact on the task completion performance?

[0133] A, Time requirement

[0134] B. Mental needs

[0135] 19. Under this assembly guidance expression, what do you think has a great impact on the task completion score?

[0136] A. Personal performance

[0137] B. Mental needs

[0138] 20. Under this assembly guidance expression, what do you think has a great impact on the task completion score?

[0139] A. Degree of frustration

[0140] B. Personal performance

[0141] 21. Under this assembly guidance expression, what do you think has a great impact on the task completion score?

[0142] A. Degree of effort

[0143] B. Degree of frustration

[0144] 22. Which level of user do you belong to?

[0145] A. Novice user

[0146] B. Experienced user

[0147] 23. The assembly guidance expression you used this time is

[0148] A. Text

[0149] B. Picture

[0150] C. Animation

[0151] D. Video

[0152] Appendix 2: Interest Tendency Questionnaire

[0153] Design of the Interest Tendency Questionnaire for Assembly Guidance Expressions

[0154] 1. Your user level is:

[0155] A. Novice user

[0156] B. Experienced user

[0157] 2. Based on your current assembly level, please rank the following 4 expressions according to your assembly guidance experience?

[0158] A. Text

[0159] B. Picture

[0160] C. Animation

[0161] D. Video

[0162] Appendix 3: Assembly User Profile Construction

[0163] Table 1 User portrait - primary assembly user

[0164]

[0165]

[0166]

[0167] Table 2 User portrait - intermediate assembly users

[0168]

[0169]

[0170] Table 3 User portrait - advanced assembly users

[0171]

[0172]

[0173] Appendix 4: Assembly User Level Test Questions

[0174] Evaluation of the experience level of operators assembling low-pressure turbine rotor blades for aircraft engines

[0175] Please answer carefully based on your actual situation

[0176] 1. Have you ever learned about the assembly process of aircraft engine rotor blades?

[0177] A. Very little understanding (score: 6)

[0178] B. Some understanding, but not very understanding (score: 8)

[0179] C. Very familiar with relevant knowledge (score: 10)

[0180] 2. Do you know how many stages there are in the assembly of rotor blades?

[0181] A. Level 1 (score: 0)

[0182] B. Level 2 (score: 0)

[0183] C. Level 3 (score: 5)

[0184] D. Don’t know (score: 0)

[0185] 3. Do you know which stage of blades should be installed first during the rotor blade assembly process?

[0186] A, Level 1 (Score: 0)

[0187] B, Level 2 (Score: 5)

[0188] C, Level 3 (Score: 0)

[0189] D, Don't know (Score: 0)

[0190] 4. Do you know what components, auxiliary materials, tools and equipment are involved in the rotor blade assembly process?

[0191] A, Not clear (Score: 0)

[0192] B, Rotor assembly (Score: 1)

[0193] C, Blade (Score: 1)

[0194] D, Snap ring assembly (Score: 1)

[0195] E, Labyrinth gland protection sleeve (Score: 1)

[0196] F, Shoulder protection pad (Score: 1)

[0197] G, Cleaning cloth (Score: 0.5)

[0198] H, Frame (Score: 0.5)

[0199] I, Nylon hammer (Score: 1)

[0200] J, Nylon rod (Score: 1)

[0201] K, Aluminum rod (Score: 1)

[0202] L, Toothpick (Score: 0.5)

[0203] M, Sign pen (Score: 0.5)

[0204] 5. Do you know how to remove the snap ring assembly during the secondary blade assembly?

[0205] A, Directly remove the snap ring assembly by hand (Score: 0)

[0206] B, Knock on the snap ring boss with a sign pen to remove it (Score: 5)

[0207] C, Pad an aluminum rod at the boss of the snap ring assembly and knock on the aluminum rod with a nylon hammer to disassemble and remove the snap ring assembly (Score: 5)

[0208] D, Don't know (Score: 0)

[0209] 6. Do you know which parts of the components need to be protected when assembling the blades?

[0210] A. Hub Grate (Score: 5)

[0211] B. Clamping ring boss (score: 0)

[0212] C. Blade shoulder root (score: 5)

[0213] D. Don’t know (score: 0)

[0214] 7. Do you know how to determine the position of the first blade during the blade assembly process?

[0215] A. Set a random slot as the starting point and insert the blade at the arrow position of the blade weight vector diagram into the slot (score: 0)

[0216] B. The arrow position of the blade weight vector diagram should be installed at the unbalanced light point position marked on the secondary disk edge (score: 10)

[0217] C. Don’t know (score: 0)

[0218] 8. When installing the secondary blades, how should the blades be placed?

[0219] A. Insert the blades into the corresponding slots clockwise according to the blade marking numbers until all the blades are inserted (score: 0)

[0220] B. Randomly insert the blades into the corresponding slots according to their numbered markings until all the blades are inserted (score: 0)

[0221] C. Insert the blade into the corresponding disc slot, and then install the next adjacent blade in the same way clockwise according to the blade number until all blades are installed (score: 10)

[0222] D. Don’t know (score: 0)

[0223] 9. Do you know how to install the blades into the disc slot?

[0224] A. Place the nylon rod on the blade edge plate and hit the nylon rod with a nylon hammer to assemble the blade (score: 5)

[0225] B. Use a nylon hammer to hit the blade edge plate to assemble the blade (score: 0)

[0226] C. Don’t know (score: 0)

[0227] 10. Do you know that when installing the second-stage rotor blades:

[0228] A. The second-stage rotor blades are assembled as a whole. Adjacent blade shoulders are prone to interference and should be assembled slowly (score: 10)

[0229] B. The second-stage rotor blades are not assembled integrally, and there will be no interference between adjacent blades, so there is no need for slow assembly (Score: 0)

[0230] C. Don't know (Score: 0)

[0231] 11. Do you know how to assemble the snap ring assembly into the second-stage disk groove after all the second-stage disk blades have entered the disk groove?

[0232] A. After ensuring that the snap ring is free of defects, insert all the snap rings into the groove in sequence, and tap the boss of the snap ring with a nylon hammer to assemble it into the groove at the front end of the second-stage disk rim (Score: 0)

[0233] B. After ensuring that the snap ring is free of defects, first place the boss at one end of the snap ring against the stop surface of the groove, insert all of them into the groove in sequence, place an aluminum rod on the boss at one end of the snap ring, and tap the aluminum rod with a nylon hammer to assemble it into the groove at the front end of the second-stage disk rim (Score: 10)

[0234] C. Neither of the above is correct (Score: 0)

[0235] D. Don't know (Score: 0)

[0236] 12. Do you think that when all the blades have entered the disk groove and the snap ring assembly is assembled into the groove at the front end of the second-stage disk rim, it can be sent to the balancing team for dynamic balancing detection

[0237] A. Correct (Score: 0)

[0238] B. Incorrect (Score: 5)

[0239] C. Don't know (Score: 0)

[0240] 13. For blade assembly, approximately how much time do you need for the assembly work?

[0241] A. Less than 30 minutes (Score: 30)

[0242] B. 30 - 60 minutes (Score: 40)

[0243] C. More than 60 minutes (Score: 50)

[0244] 14. If you are asked to complete the assembly of single-stage blades now, you need:

[0245] A. Need detailed auxiliary guidance materials for prompt (Score: 30)

[0246] B. Only need a small amount of auxiliary guidance materials for prompt (Score: 40)

[0247] C. Don't need learning or prompt materials and can complete it quickly and independently (Score: 50)

Claims

1. An assembly process physical design method based on user cognition, characterized in that: Adopt the following steps: Step 1: Design the user assembly guidance interaction experiment; by means of the user interaction experiment method, compare the cognitive differences in the assembly process among individual users, understand their expression needs for the assembly process, and conduct an experimental design with the user experience level and the assembly process expression method as the predictive factors for user process cognitive differences, which is divided into 5 sub-steps: Step 1.1: Divide the user experience level into 2 types: novice users and experienced users, and divide the assembly process expression methods into 4 types: text, pictures, animations, and videos; Step 1.2: Select the experimental assembly task and determine the assembly key points as the basis for judging the assembly correctness. At the same time, express the assembly process of the assembly task in the above 4 ways to guide the users in assembly; Step 1.3: Use the multi-factor repeated measurement experiment as the experimental model to conduct the experimental group design; the influence of the user experience level is studied through the between-group design, and the influence of the assembly process instruction expression method is studied through the within-group design method; Step 1.4: Design the methods for observing and recording user behavior during the experiment, the NASA-TLX questionnaire, the interest tendency questionnaire, and the in-depth interview content; Step 1.5: Design the implementation process of the user assembly guidance interaction experiment, and its process is as follows: 1) Conduct a pre-test of the user experience experiment; 2) Recruit, group, and train the participants; 3) The assembly process of the user experience experiment and record; 4) Fill in the questionnaire of the user experience experiment; 5) Conduct in-depth interviews of the user experience experiment; 6) Sort out and summarize the data; Step 2: Implement the user assembly guidance interaction experiment; according to the experimental process in Step 1.5, enable users with different experience levels to conduct the assembly interaction experience experiment, and obtain the experimental task data completed by the users from 5 aspects: the assembly time, assembly correct rate, assembly load interest tendency, and subjective feelings of the users when completing the assembly experiment task; during the experimental implementation process, through the observation and recording of user behavior, obtain the objective performance of the assembly users in terms of assembly time, assembly correct rate, and operation behavior during the assembly process; quantitatively evaluate the assembly load of the assembly users during the assembly process through the NASA-TLX questionnaire; obtain the preferences of the assembly users for the process expression method and their experience feelings of the assembly process instruction expression through the interest tendency questionnaire and in-depth interviews; Step 3: Analyze the data of the user assembly guidance interaction experiment; use the repeated trial analysis model to analyze the cognitive differences of users with different experience levels in the guidance process instructions. By analyzing the performance of 2 types of users with different experience levels under 4 types of process instruction expression conditions, that is, the subjective and objective data analysis of the assembly time, assembly correct rate, assembly load, interest tendency, and experience feelings of the assembly users when completing the experimental tasks; it is mainly divided into 3 sub-steps: Step 3.1: Based on the experimental data obtained in Step 2, use SPSS to analyze whether there are significant differences in the assembly time, assembly correct rate, assembly load, and interest tendency of users with different experience levels using different assembly guidance expression methods by using the general linear repeated measurement data analysis model; Step 3.2: Compare the average error values of the assembly time, assembly accuracy rate, and subjective and objective data of assembly load obtained in the above Step 2 through two comparison methods, that is, compare the performance of two users with different experience levels under the guidance of four expression methods of assembly process instructions and compare the performance of two users with different experience levels in completing the assembly tasks under the guidance of the same expression method of assembly process instructions; at the same time, in terms of interest tendency selection, compare the number of times of tendency selection of the expression method by two users with different experience levels; Step 3.3: Based on the analysis and comparison results of the above Steps 3.1 and 3.2, obtain the ranking of the assembly effects of the four expression methods guided by novice users and experienced users in terms of assembly time, assembly accuracy rate, assembly load, and interest tendency respectively; In terms of assembly time, the expression method with a shorter guiding assembly time ranks higher; in terms of assembly accuracy rate, the expression method with a higher guiding assembly accuracy rate ranks higher; in terms of assembly load, the expression method with a smaller guiding assembly load ranks higher; in terms of interest tendency, the expression method with a larger number of times of tendency selection ranks higher; in the above four aspects, when there are significant differences in the use of different assembly guiding expression methods by users with different experience levels, the ranking of the assembly effects of the four expression methods guided by novice users and experienced users is different, otherwise, they are the same; Step 4: Analysis of the requirements for the user assembly guiding process instructions; based on the results obtained in Step 3.3 and combined with the user experience, analyze the requirements of novice users and experienced users for the information content and intuitive vividness of the process instructions expression, which is divided into the following 3 sub-steps: Step 4.1: Assembly accuracy rate and assembly time are important factors affecting assembly efficiency. According to the characteristics of the user experience level, novice users should first refer to the performance results in terms of assembly accuracy rate, while experienced users should first refer to the performance results in terms of assembly time; Step 4.2: Let the participating users rate the information content and intuitive vividness of the four expression methods, and it is obtained that in terms of information content, the size of the four expression methods can be controlled, and in terms of intuitive vividness, the video and animation are the most intuitive and vivid; the pictures are the second, and the text is the weakest; Step 4.3: Combined with the user experience, analyze the requirements of two users with different experience levels for the information content and intuitive vividness of the process instructions expression, and it is obtained that novice users have a greater demand for the information content of the process instructions expression, and also have a relatively strong demand for the intuitiveness and vividness of the content; during the assembly process, the information content and intuitiveness of the guiding process instructions required by experienced users will relatively decrease, which is related to the user's familiarity with the assembly operation and user preferences, and it is not the demand rule that the less information content, the better; Step 5: Based on the assembly process requirements laws of users with different experience levels, construct an assembly user portrait; divide this user group into low, medium, and high levels according to the familiarity of assembly operators with assembly operations, and further divide the assembly user group into three assembly user levels: beginner, intermediate, and advanced; comprehensively describe them according to the user interest tendency, complete the construction of the assembly process user portrait, and determine the demand characteristics of different-level users for the expression of assembly process instructions from three aspects: the amount of information, the intuitive vividness of content expression, and the selection of interest tendency; Step 6: Physical design of assembly process instructions; based on the demand characteristics of each level of assembly users for the expression of process instructions in Step 5, combined with the evaluation of assembly process expression methods in Step 4.2, obtain assembly knowledge and carry out the physical design of assembly processes, which is divided into 2 sub-steps: Step 6.1: Obtain assembly knowledge through assembly process manuals or on-site assembly teaching methods as the object-oriented of the physical design of assembly processes; Step 6.2: Based on the principles of visual language sensory, functional, and relevance, for the demand characteristics of different-level users for the expression of assembly process instructions in Step 5, combined with the evaluation results of assembly process expression methods in Step 4.2, design corresponding physical assembly process instructions and construct a physical assembly process instruction library; Step 7: Construct the association relationship between the user individual and the physical process; Design a user level test, divide users into beginner, intermediate, and advanced through an assembly knowledge test, match the user process demand characteristics corresponding to the user individual, and thus associate with the physical assembly process instructions in Step 6.2; Step 8: Establish a prototype system for pushing physical process instructions; Based on the system development framework and the theoretical guidance of the association relationship between the user individual and the physical process, build a physical process instruction push system platform from both virtual and physical environments, and complete the verification of the usability and applicability of the physical design method of assembly processes based on user cognition.

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