Tightening operation process quality control method and system based on Internet of Things platform

Abstract

The invention discloses a tightening operation process quality control method based on an Internet of Things platform. The tightening operation process quality control method comprises the following steps that S100, an Internet of Things server collects data item data recorded by a system and equipment in a tightening operation process; s200, checking, detecting and processing the data item data by the Internet of Things server; step S300, the Internet of Things server transmits the processed data item data to an SPC system, and the SPC system displays the data item data and performs data analysis by using an SPC control chart; step S400, if the SPC system monitors that the data analysis is out of control and abnormal, accessing the knowledge base of the SPC system, retrieving whether the same data abnormal problem is stored or not, if so, acquiring and displaying a data abnormal problem processing scheme, and if not, giving an alarm to inform a technician and starting a disposal process; and step S500, receiving a data exception handling scheme, and storing the data exception handling scheme and the data exception problem in the SPC system knowledge base. The product quality in the manufacturing process can be improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing quality control, and in particular to a tightening operation process quality control method and system based on an Internet of Things platform. Background Art

[0002] In the field of industrial manufacturing quality management, most domestic factories are still focusing on quality management for manufacturing results. The disadvantage of this management method is that the quality process is obviously uncontrollable. Quality causes can only be traced back and improved after quality problems occur, resulting in frequent high levels of quality problems.

[0003] In order to be competitive in today's global economy, companies must seek new ways to reduce costs and improve product quality. Therefore, more and more managers hope to use SPC charts to achieve quality management of the manufacturing process by obtaining equipment measurement data (angle, accuracy, thickness, etc.) to improve corporate production efficiency. Therefore, SPC-related data collection and data processing technologies are particularly important. Summary of the invention

[0004] The main purpose of the present invention is to provide a tightening operation process quality control method and system based on an Internet of Things platform to address the shortcomings of the prior art that measurement data is imported by manual transcription, there is no mechanism to ensure the integrity of test data, the test data is not processed resulting in no obvious analysis effect, and previous abnormal problems cannot be responded to quickly.

[0005] To achieve the above object, the present invention provides a tightening operation process quality control method based on the Internet of Things platform, comprising the following steps:

[0006] Step S100: The IoT server collects data items recorded by the system and equipment during the tightening operation;

[0007] Step S200: The IoT server checks and processes the data item data;

[0008] Step S300: The IoT server transmits the processed data item data to the SPC system, and the SPC system displays the data item data and uses the SPC control chart to perform data analysis;

[0009] Step S400: If the SPC system detects that the data analysis is out of control, the SPC system knowledge base is accessed to search whether the same data abnormality problem is stored. If so, a solution to the data abnormality problem is obtained and displayed. If not, an alarm is issued to notify the technician and the disposal process is started;

[0010] Step S500: receiving a data anomaly handling plan and storing it together with the data anomaly problem in the SPC system knowledge base.

[0011] Preferably, step S100 includes: the system and equipment used in the tightening operation communicate with the Internet of Things server through an interface with a protocol driver, the system and equipment record data items of the tightening operation, and transmit them to the Internet of Things server through the interface for storage, and the data items include vehicle identification code, vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, current tightening duration, current tightening end time, tightening status, tightening part, n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, and n-axis tightening result.

[0012] Preferably, the step S200 includes: the Internet of Things server performs an abnormal check on the data item data according to the set data configuration rules to obtain the corrected data item data, and the Internet of Things server performs an integrity check on the corrected data item data according to the set configuration data verification rules, and if it is incomplete, an alarm prompts.

[0013] Preferably, step S300 includes: the Internet of Things server transmits the data item data to the SPC system through the configuration interface, the SPC system displays the data item data in blocks according to the data item, and filters the data item data according to the data item filtering conditions, and uses the mean range chart in the SPC control chart to display and analyze the filtered data item data, and the data item data filtering conditions are filtering by vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening part, and shaft number.

[0014] Preferably, step S400 includes: the SPC system monitors the data distribution status of the mean range chart, and if an abnormal out-of-control data group is found, reads the abnormal problem category of the current data anomaly in the mean range chart, further accesses the SPC system knowledge base, and searches whether the same data anomaly problem is stored in the SPC system knowledge base; if so, obtains the data anomaly processing plan and displays it visually in the SPC system; if not, issues an alarm to notify the technician and starts the disposal process.

[0015] In addition, the present invention also provides a tightening operation process quality control system based on the Internet of Things platform, including: a recording module, used to record data item data in the tightening operation process; a verification and inspection module, used to verify, detect and process the data item data; a transmission module, used to transmit the recorded data item data to the Internet of Things server, and used to transmit the processed data item data to the SPC system; a display module, used to visualize the data item data, and used to display the data abnormality problem processing solution; an analysis module, used to analyze the data item data using the SOC control chart; a monitoring module, used to monitor whether the data item data analysis results have an out-of-control abnormal condition; an access module, used to access the SPC system knowledge base; a retrieval module, used to retrieve whether the same data abnormality problem is stored in the SPC system knowledge base; an alarm module, used to alarm for abnormal situations; the recording module is located in the equipment system, the verification and inspection module is located in the Internet of Things server, the display module, the analysis module, the monitoring module, the access module, the retrieval module, and the alarm module are located in the SPC system, and the transmission module is located in the equipment, the Internet of Things server, and the SPC system.

[0016] Preferably, the data items recorded by the recording module include vehicle identification code, vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, current tightening duration, current tightening end time, tightening status, tightening position, n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, and n-axis tightening result.

[0017] Preferably, the checking module is used to perform abnormal checking on the data item data according to the set data configuration rules, obtain the corrected data item data, and perform integrity checking on the corrected data item data according to the set configuration data checking rules.

[0018] Preferably, the display module displays the data item data in blocks according to the data item, and the analysis module selects the mean range chart in the SPC control chart to analyze the data item data after filtering according to the data item filtering conditions, and the data item data filtering conditions are filtering by vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening location, and shaft number.

[0019] Preferably, the monitoring module monitors the data distribution of the mean range chart, and if an abnormal out-of-control data group is found, reads the abnormal problem category of the current data anomaly in the mean range chart.

[0020] The invention provides a tightening operation process quality control method based on the Internet of Things platform, which has the following beneficial effects: the Internet of Things server collects data item data recorded by the system and equipment during the tightening operation; by recording the test data in the tightening operation, the first-hand original data in the product manufacturing quality control process is obtained, which provides a basis for subsequent data analysis; the Internet of Things server verifies, detects and processes the data item data; by correcting the original data according to the verification and inspection rules, the effectiveness of subsequent analysis is improved; the Internet of Things server transmits the processed data item data to the SPC system, the SPC system displays the data item data and uses the SPC control chart to perform data analysis, so that the manufacturing quality can be more intuitively understood in the manufacturing process by displaying the data, and the manufacturing data can be analyzed in real time, so as to timely Discover quality anomalies in the manufacturing process; if the SPC system detects out-of-control anomalies in the data analysis, access the SPC system knowledge base to search whether the same data anomaly problem is stored. If so, obtain the data anomaly problem handling solution for display. If not, an alarm is triggered to notify the technical staff and start the disposal process; monitor the anomalies in real time, discover the anomalies as soon as possible, and provide solutions to repeated anomaly problems based on the knowledge base, which provides timeliness and pertinence for solving manufacturing quality problems. At the same time, for new anomalies, promptly notify the responsible personnel and start the processing process in time, which provides convenience for anomaly handling; receive the data anomaly handling solution and store it together with the data anomaly problem in the SPC system knowledge base; store the solution for each abnormal problem and provide a solution in time for the subsequent occurrence of the same abnormal problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the provided drawings without creative work:

[0022] Figure 1 A schematic flow chart of a tightening operation process quality control method based on an Internet of Things platform provided by an embodiment of the present invention;

[0023] Figure 2 A module schematic diagram of a tightening operation process quality control system based on an Internet of Things platform provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to facilitate understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0026] The general idea of ​​the present invention is to overcome the shortcomings of measuring data being imported by manual transcription, having no mechanism to ensure the integrity of test data, having no obvious effect in analysis due to unprocessed test data, and being unable to respond quickly to previous abnormal problems, and to provide a method and system for quality control of tightening operations based on an Internet of Things platform. The Internet of Things server in the present invention collects data item data recorded by the system and equipment during the tightening operation; by recording test data during the tightening operation, first-hand original data in the product manufacturing quality control process is obtained, providing a basis for subsequent data analysis; the Internet of Things server verifies, detects and processes the data item data; by correcting the original data according to the verification and inspection rules, the effectiveness of subsequent analysis is improved; the Internet of Things server transmits the processed data item data to the SPC system, and the SPC system displays the data item data and uses the SPC control chart for data analysis, so that the manufacturing quality can be more intuitively understood during the manufacturing process by displaying the data, and the manufacturing data can be analyzed in real time to promptly discover quality anomalies in the manufacturing process; such as SPC When the system detects out-of-control anomalies in data analysis, it accesses the SPC system knowledge base to check whether the same data anomaly problem is stored. If so, it obtains the data anomaly problem handling solution for display. If not, it notifies the technical staff with an alarm and starts the disposal process. The system monitors the anomalies in real time, discovers the anomalies at the first time, and provides solutions to repeated anomaly problems based on the knowledge base, which provides timeliness and pertinence for solving manufacturing quality problems. At the same time, for new anomaly problems, it promptly notifies the responsible personnel and promptly starts the processing process, which provides convenience for anomaly handling. The disposal solution for data anomalies is received and stored together with the data anomaly problem in the SPC system knowledge base. The solution for each abnormal problem is stored to provide a timely solution for the subsequent occurrence of the same abnormal problem.

[0027] In order to better understand the above-mentioned technical scheme, the above-mentioned technical scheme will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical scheme of the present application, rather than limitations on the technical scheme of the present application. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0028] Reference Figure 1 , Figure 1 The figure is a flow chart of a tightening operation process quality control method based on an Internet of Things platform provided by an embodiment of the present invention. In this embodiment, a tightening operation process quality control method based on an Internet of Things platform includes:

[0029] Step S100: The IoT server collects data items recorded by the system and equipment during the tightening operation.

[0030] By recording test data during tightening operations, first-hand original data in the product manufacturing quality control process is obtained, providing a basis for subsequent data analysis.

[0031] The present invention uses the Internet of Things platform technology. The entire system includes an Internet of Things platform layer and an SPC system application layer. In addition to having a rich set of protocol drivers, the platform layer also supports data compression storage, calculation, and flow configuration, and also includes network management functions. When network conditions permit, the system only needs to be configured to collect data from devices, products, and systems, and can be customized to process and manage the data, realizing a unified external transmission interface to support data sharing. The platform layer is arranged on the Internet of Things server.

[0032] Since the IoT server has data compression and storage capabilities, it can trace data for a longer period of time.

[0033] Specifically, step S100 includes: the system and equipment used in the tightening operation communicate with the Internet of Things server through an interface with a protocol driver, the system and equipment record the data items of the tightening operation, and transmit them to the Internet of Things server through the interface for storage, and the data items include vehicle identification code, vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, current tightening duration, current tightening end time, tightening status, tightening position, n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, and n-axis tightening result.

[0034] In the product manufacturing process, the tightening process needs to be completed using equipment. In the current intelligent manufacturing of vehicles, these devices all have stand-alone functions, can record and detect test data, and each process station has a stand-alone system, which can display the properties of the current product and the requirements of the process, and can also display the test parameters in the current equipment operation in real time. At the manufacturing site, the system and equipment directly record the relevant original data of the product and the tightening process, and transmit it to the Internet of Things server through the interface between the system and the Internet of Things server. The interface has a docking protocol driver, and the Internet of Things server completes the data collection. The intelligent manufacturing of the present invention is intelligent manufacturing of vehicles. For vehicle manufacturing, specifically, the data items recorded by the system and equipment for tightening operations include vehicle identification code, vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, this tightening duration, this tightening end time, tightening state, tightening position, n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, n-axis tightening result. The vehicle identification code is a unique identification code that distinguishes the vehicle, similar to a person's ID number, usually VIN code, chassis number, frame number, etc. The vehicle model is the model of the vehicle, such as YBS-500X, etc., to distinguish vehicles of the same brand and the same series. The torque setting value is the torque value that needs to be set for the current tightening operation process. The equipment number is the number of the current operating equipment. The tightening direction is forward or reverse. The tightening state is the judgment state of the equipment itself on the tightening result, generally OK or NG. The tightening part is the position of the tightening screw, which may be the front wheel, rear wheel, balance shaft, etc., n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, n-axis tightening result, according to the different number of axes of the tightening equipment, n is different, generally there are one-axis, two-axis, four-axis, five-axis tightening machines, and n represents the number of axes.

[0035] Step S200: The IoT server verifies, detects and processes the data item data.

[0036] By correcting the original data according to the verification and inspection rules, the effectiveness of subsequent analysis is improved.

[0037] Due to the influence of device manufacturer's programming on device system, the test data may be different from the actual data. At the same time, the test data may be incomplete due to temporary equipment failure, which will cause deviation in data analysis. At this time, the IoT platform needs to correct the original data. Usually, verification and inspection rules are set according to previous experience of data anomalies. The platform verifies the original data and outputs the corrected data, which effectively improves the accuracy and completeness of subsequent analysis data.

[0038] Specifically, the IoT server performs abnormal verification processing on the data item data according to the set data configuration rules, obtains the corrected data item data, and performs integrity check on the corrected data item data according to the set configuration data verification rules. If it is incomplete, an alarm prompts.

[0039] After the original data is collected on the IoT platform, it is necessary to process and transform the collected data in real time through the IoT platform. For example, the collected equipment process value is 300000, but the actual value should be 30 based on experience. The IoT platform can be used to perform actual conversion processing through data configuration rules to avoid getting an incorrect value that causes subsequent data to be unusable. After the original data is collected on the IoT platform, it is also necessary to check its integrity. Here, the set configuration data verification rules are used for integrity check. The configuration data verification rules are as follows: 1. Each tightening of each vehicle must have n data items 2. If it is planned to produce m equipment per day, n*m data items must be collected 3. Different equipment has different process types, such as tire tightening, balance shaft tightening, etc. The tightening times S are also different, and the operator must also collect S data when operating the tightening machine for vehicle operations. If any of the above three situations is not met, it is considered that the data is incomplete, and the platform will alarm.

[0040] Step S300: The IoT server transmits the processed data item data to the SPC system, and the SPC system displays the data item data and uses the SPC control chart to perform data analysis.

[0041] By displaying data, the manufacturing quality can be more intuitively understood during the manufacturing process, and the manufacturing data can be analyzed in real time to promptly identify quality anomalies in the manufacturing process;

[0042] Specifically, the IoT server transmits the data item data to the SPC system through the configuration interface. The SPC system displays the data item data in blocks according to the data item, and filters the data item data according to the data item filtering conditions. The mean and range chart in the SPC control chart is used to display and analyze the filtered data item data. The data item data filtering conditions are to filter by vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening part, and shaft number.

[0043] The data item data is shared with the application layer SPC system through the configuration interface of the IoT platform. The interface protocol is not limited to a certain one, as long as the SPC system supports it. The MQTT message queue protocol can be used. Users can trace the information of the measurement data through the SPC system. In addition, since the IoT platform generally has the ability to compress and store data, the longest traceable data of the SPC system is generally longer than that of the traditional system. After the SPC system receives the data item data, it will display the data in blocks in the display area according to the data item. At the same time, the SPC system uses SPC control charts to analyze the data item data. There are many types of SPC control charts. Generally, the mean range chart (Xbar-R) is selected. Other control charts can be freely selected according to the characteristics of the SPC control chart. The specific selection rules have industry standard guidelines, so I will not explain them here. The data item data mainly analyzes the measured data, specifically the data items of n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, and n-axis tightening result. These data item data and other data items such as vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening part, and shaft number are regarded as a complete set of data item data. When analyzing the measured data, it is necessary to filter the data. The filtering conditions here are to filter by vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening part, and shaft number. The filtered data are analyzed through the mean range chart in the SPC control chart.

[0044] Step S400: If the SPC system detects that the data analysis is out of control, the SPC system knowledge base is accessed to search whether the same data anomaly problem is stored. If so, the data anomaly problem processing solution is obtained and displayed. If not, an alarm is issued to notify the technician and the disposal process is started.

[0045] Real-time monitoring of anomalies is carried out to detect anomalies at the first time, and solutions to repeated abnormal problems are given based on the knowledge base, which provides timeliness and pertinence for solving manufacturing quality problems. At the same time, for new abnormal problems, the responsible personnel are notified in time and the processing flow is started in time, which provides convenience for exception handling.

[0046] Specifically, step S400 includes: the SPC system monitors the data distribution status of the mean range chart, and if an abnormal out-of-control data group is found, reads the abnormal problem category of the current data anomaly in the mean range chart, further accesses the SPC system knowledge base, and searches whether the same data anomaly problem is stored in the SPC system knowledge base; if so, obtains the data anomaly processing plan and displays it visually in the SPC system; if not, issues an alarm to notify the technician and starts the disposal process.

[0047] During the analysis process of the mean range chart by the SPC system, the SPC system monitors the data distribution of the mean range chart in real time and finds an abnormal out-of-control data group. For example, the data group has ten numbers, nine of which are between one and nine, and the remaining one is 100. Then the number 100 is judged to be out of control, and the data group is an abnormal out-of-control data group. By comparing the mean range chart of the data group with the abnormal problem diagram in the SPC system buffer, it is determined whether the diagram is consistent. If it is determined to be consistent, the abnormal problem category in the buffer is read to obtain the current Abnormal out-of-control data problem category. Access the knowledge base of the SPC system with the abnormal out-of-control problem category information. The SPC system knowledge base stores various previous data abnormality problem categories and corresponding processing solutions. Search the SPC system knowledge base to check whether the same data abnormality problem is stored. If so, retrieve the abnormal problem processing solution and transmit it to the SPC system display area for visual display. Relevant personnel can handle product quality according to the processing solution. If not, an alarm will be issued and the abnormal handling process associated with the SPC system will be actively triggered and pushed to the relevant personnel involved in the process.

[0048] Step S500: receiving a data anomaly handling plan and storing it together with the data anomaly problem in the SPC system knowledge base.

[0049] The solution for each abnormal problem is stored, so that a solution can be provided in time for the subsequent occurrence of the same abnormal problem.

[0050] After the relevant personnel give a solution to the abnormal problem, it is transmitted to the SPC system through the process associated with the SPC system. The SPC system receives the solution and stores it in the SPC knowledge base together with the read data abnormality problem category, so as to provide a solution in time for the subsequent abnormal data problems with the same abnormal data.

[0051] Based on the above methods, the Internet of Things server in the present invention collects data item data recorded by the system and equipment during the tightening operation; by recording test data in the tightening operation, the first-hand original data in the product manufacturing quality control process is obtained, which provides a basis for subsequent data analysis; the Internet of Things server verifies, detects and processes the data item data; by correcting the original data according to the verification and inspection rules, the effectiveness of subsequent analysis is improved; the Internet of Things server transmits the processed data item data to the SPC system, and the SPC system displays the data item data and uses the SPC control chart to perform data analysis, so as to more intuitively understand the manufacturing quality in the manufacturing process by displaying the data, and analyze the manufacturing data in real time to promptly discover quality anomalies in the manufacturing process; such as When the SPC system detects that the data analysis has an out-of-control anomaly, it accesses the SPC system knowledge base to check whether the same data anomaly problem is stored. If so, it obtains the data anomaly problem handling solution for display. If not, it notifies the technical staff with an alarm and starts the disposal process. It monitors the anomaly in real time, discovers the anomaly as soon as possible, and provides solutions to repeated anomaly problems based on the knowledge base, which provides timeliness and pertinence for solving manufacturing quality problems. At the same time, it notifies the responsible personnel in time for new anomaly problems and starts the processing process in time, which provides convenience for anomaly handling. It receives the data anomaly handling solution and stores it together with the data anomaly problem in the SPC system knowledge base. It stores the solution for each anomaly problem and provides a solution in time for the subsequent occurrence of the same anomaly problem.

[0052] Accordingly, the present invention also provides a tightening operation process quality control system based on the Internet of Things platform, referring to Figure 2 , Figure 2The figure shows a schematic diagram of the module structure of a tightening operation process quality control system based on an Internet of Things platform provided by an embodiment of the present invention. The system performs quality control on the tightening operation through the tightening operation process quality control method based on the Internet of Things platform described above. The system recording module is used to record data item data in the tightening operation process; the checking module is used to check, detect and process the data item data; the transmission module is used to transmit the recorded data item data to the Internet of Things server, and is used to transmit the processed data item data to the SPC system; the display module is used to visualize the data item data and to display the data abnormality problem processing solution; the analysis module is used to analyze the data item data and analyze the data item data. A module is used to analyze data item data using a SOC control chart; a monitoring module is used to monitor whether the data item data analysis results have any out-of-control abnormal conditions; an access module is used to access an SPC system knowledge base; a retrieval module is used to retrieve whether the SPC system knowledge base stores the same data abnormality problems; an alarm module is used to alarm for abnormal situations; the recording module is located in the equipment system, the checking module is located in the Internet of Things server, the display module, the analysis module, the monitoring module, the access module, the retrieval module, and the alarm module are located in the SPC system, and the transmission module is located in the equipment, the Internet of Things server, and the SPC system.

[0053] Preferably, the data items recorded by the recording module include vehicle identification code, vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, current tightening duration, current tightening end time, tightening status, tightening position, n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, and n-axis tightening result.

[0054] Preferably, the checking module is used to perform abnormal checking on the data item data according to the set data configuration rules, obtain the corrected data item data, and perform integrity checking on the corrected data item data according to the set configuration data checking rules.

[0055] Preferably, the display module displays the data item data in blocks according to the data item, and the analysis module selects the mean range chart in the SPC control chart to analyze the data item data after filtering according to the data item filtering conditions, and the data item data filtering conditions are filtering by vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening location, and shaft number.

[0056] Preferably, the monitoring module monitors the data distribution of the mean range chart, and if an abnormal out-of-control data group is found, reads the abnormal problem category of the current data anomaly in the mean range chart.

[0057] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0058] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the intention that the claimed invention requires more features than those explicitly recited in each claim. More specifically, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present invention.

[0059] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0060] In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present invention and form different embodiments. For example, in the claims below, any one of the claimed embodiments may be used in any combination.

[0061] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components in the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., computer program and computer program product) for executing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0062] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc., does not indicate any order. These words may be interpreted as names.

Claims

1. A tightening process quality control method based on the Internet of Things platform, characterized in that: The following steps are involved: Step S100: The IoT server collects data items recorded by the system and equipment during the tightening operation; Step S200: The IoT server checks and processes the data item data; Step S300: The IoT server transmits the processed data item data to the SPC system, and the SPC system displays the data item data and uses the SPC control chart to perform data analysis; Step S400: If the SPC system detects that the data analysis is out of control, the SPC system knowledge base is accessed to search whether the same data abnormality problem is stored. If so, a solution to the data abnormality problem is obtained and displayed. If not, an alarm is issued to notify the technician and the disposal process is started; Step S500: receiving a data anomaly handling plan and storing it together with the data anomaly problem in the SPC system knowledge base.

2. The method for quality control of tightening operation process based on the Internet of Things platform as claimed in claim 1, characterized in that: The step S100 includes: The system and equipment used in the tightening operation communicate with the Internet of Things server through a protocol-driven interface. The system and equipment record the data items of the tightening operation and transmit them to the Internet of Things server through the interface for storage. The data items include vehicle identification code, vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, duration of this tightening, end time of this tightening, tightening status, tightening part, n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, and n-axis tightening result.

3. The method for quality control of tightening operation process based on the Internet of Things platform as claimed in claim 2, characterized in that: The step S200 includes: The IoT server performs abnormal verification on the data item data according to the set data configuration rules, obtains the corrected data item data, and performs integrity check on the corrected data item data according to the set configuration data verification rules. If it is incomplete, an alarm prompts.

4. The method for quality control of tightening operation process based on the Internet of Things platform as claimed in claim 3, characterized in that: The step S300 includes: The IoT server transmits the data item data to the SPC system through the configuration interface. The SPC system displays the data item data in blocks according to the data item, and filters the data item data according to the data item filtering conditions. The mean range chart in the SPC control chart is used to display and analyze the filtered data item data. The data item data filtering conditions are to filter by vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening location, and shaft number.

5. The method for quality control of tightening operation process based on the Internet of Things platform as claimed in claim 4, characterized in that: The step S400 includes: The SPC system monitors the data distribution of the mean range chart. If an abnormal out-of-control data group is found, the abnormal problem category of the current data anomaly in the mean range chart is read, and the SPC system knowledge base is further accessed to check whether the same data anomaly problem is stored in the SPC system knowledge base; if so, the data anomaly processing plan is obtained and visualized in the SPC system. If not, an alarm is issued to notify the technical staff and the disposal process is initiated.

6. A tightening process quality control system based on the Internet of Things platform, characterized in that: include: A recording module, used to record data items during the tightening operation; A verification and inspection module is used to verify and process data items; A transmission module, used to transmit the recorded data item data to the IoT server, and used to transmit the processed data item data to the SPC system; The display module is used to visualize the data items and to display the solutions to data anomaly problems; An analysis module for analyzing data item data using a SOC control chart; Monitoring module, used to monitor whether the data item data analysis results have any out-of-control abnormal conditions; Access module, used to access the SPC system knowledge base; A retrieval module is used to retrieve whether the same data anomaly problem is stored in the SPC system knowledge base; An alarm module is used to alarm for abnormal situations; The recording module is located in the equipment system, the checking module is located in the Internet of Things server, the display module, the analysis module, the monitoring module, the access module, the retrieval module, and the alarm module are located in the SPC system, and the transmission module is located in the equipment, the Internet of Things server, and the SPC system.

7. The tightening process quality control system based on the Internet of Things platform as claimed in claim 6 is characterized in that: The data items recorded by the recording module include vehicle identification code, vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, duration of this tightening, end time of this tightening, tightening status, tightening position, n-axis torque, n-axis angle, n-axis final torque, n-axis torque upper limit, n-axis torque lower limit, n-axis final angle, n-axis angle upper limit, n-axis angle lower limit, and n-axis tightening result.

8. The tightening process quality control system based on the Internet of Things platform as claimed in claim 7 is characterized in that: The checking module is used to perform abnormal checking on the data item data according to the set data configuration rules, obtain the corrected data item data, and perform integrity checking on the corrected data item data according to the set configuration data checking rules.

9. The tightening process quality control system based on the Internet of Things platform as claimed in claim 8, characterized in that: The display module displays the data item data in blocks according to the data item, and the analysis module uses the mean range chart in the SPC control chart to analyze the data item data after filtering according to the data item filtering conditions, and the data item data filtering conditions are filtering according to vehicle model, torque setting value, equipment number, gear selection mode, tightening direction, tightening location, and shaft number.

10. The tightening process quality control system based on the Internet of Things platform according to claim 9, characterized in that: The monitoring module monitors the data distribution status of the mean range chart, and if an abnormal out-of-control data group is found, reads the abnormal problem category of the current data anomaly in the mean range chart.

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