CN117754834A - Injection molding machine one-stop service platform based on intelligent factory - Google Patents
Injection molding machine one-stop service platform based on intelligent factory Download PDFInfo
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- 238000001746 injection moulding Methods 0.000 title claims abstract description 116
- 238000004519 manufacturing process Methods 0.000 claims abstract description 105
- 238000012544 monitoring process Methods 0.000 claims abstract description 73
- 238000007726 management method Methods 0.000 claims abstract description 48
- 238000004458 analytical method Methods 0.000 claims abstract description 21
- 238000003908 quality control method Methods 0.000 claims abstract description 15
- 238000007405 data analysis Methods 0.000 claims abstract description 13
- 238000002347 injection Methods 0.000 claims description 34
- 239000007924 injection Substances 0.000 claims description 34
- 238000007689 inspection Methods 0.000 claims description 27
- 238000012423 maintenance Methods 0.000 claims description 16
- 238000001514 detection method Methods 0.000 claims description 13
- 230000002159 abnormal effect Effects 0.000 claims description 10
- 230000000007 visual effect Effects 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 5
- 239000000853 adhesive Substances 0.000 claims description 3
- 230000001070 adhesive effect Effects 0.000 claims description 3
- 239000000155 melt Substances 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- 238000012384 transportation and delivery Methods 0.000 claims description 2
- 239000000047 product Substances 0.000 description 43
- 238000005265 energy consumption Methods 0.000 description 17
- 239000000203 mixture Substances 0.000 description 9
- 230000005856 abnormality Effects 0.000 description 7
- 239000011159 matrix material Substances 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 238000007781 pre-processing Methods 0.000 description 3
- 239000002994 raw material Substances 0.000 description 3
- 238000013135 deep learning Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003139 buffering effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
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Abstract
The invention discloses an injection molding machine one-stop service platform based on an intelligent factory, which comprises an injection molding machine monitoring module, a production plan management module, a production data analysis module and a quality control module; the injection molding machine monitoring module is used for acquiring monitoring index information of the injection molding machine and monitoring the injection molding machine according to the monitoring index information; the production data analysis module is used for acquiring production data, analyzing the production data and outputting an analysis result; the quality control module is used for monitoring the quality of the product in the production process; the production plan management module is used for managing the production plan, and the management comprises the steps of making the production plan, displaying production orders, distributing and tracking production tasks. The invention improves the production efficiency of the injection molding machine.
Description
Technical Field
The invention relates to the technical field of injection molding machine service platforms, in particular to an intelligent factory-based one-stop service platform of an injection molding machine.
Background
An injection molding machine is a machine apparatus for manufacturing plastic products, which is mainly formed by injecting molten plastic material into a mold and by rapid cooling. With the continuous expansion of the market for plastic products and the continuous progress of technology, injection molding machines have become one of the indispensable devices in the modern industry.
At present, the injection molding machine is continuously developed towards digital and intelligent, however, the prior art lacks intelligent digital service for the omnibearing production links of the injection molding machine, which results in unsmooth production control and low production efficiency, so that a comprehensive service system integrating a plurality of production links is needed.
Disclosure of Invention
The invention provides a one-stop service platform of an injection molding machine based on an intelligent factory, which solves the problem of unsmooth production control and improves the production efficiency of the injection molding machine.
In order to solve the technical problems, the embodiment of the invention provides a one-stop type service platform of an injection molding machine based on an intelligent factory, which is characterized by comprising an injection molding machine monitoring module, a production plan management module, a production data analysis module and a quality control module;
the injection molding machine monitoring module is used for acquiring monitoring index information of the injection molding machine and monitoring the injection molding machine according to the monitoring index information;
the production data analysis module is used for acquiring production data, analyzing the production data and outputting an analysis result;
the quality control module is used for monitoring the quality of the product in the production process;
the production plan management module is used for managing the production plan, and the management comprises the steps of making the production plan, displaying production orders, distributing and tracking production tasks.
As one preferable scheme, the system also comprises an equipment maintenance management module, a logistics management module and a personnel management module, wherein the equipment maintenance management module is used for managing equipment maintenance;
the logistics management module is used for managing purchasing, warehousing, sales orders and delivery of products;
the personnel management module is used for managing personnel files, attendance, salary, performance and training.
As one preferable scheme, a PLC controller is arranged in the injection molding machine, and is connected with a plurality of sensors, acquires monitoring index information through the plurality of sensors and uploads the monitoring index information to a 5G server;
the injection molding machine monitoring module acquires monitoring index information of the injection molding machine from the monitoring module, judges whether each index value in the monitoring index information is in a preset normal interval, and alarms for abnormal index information which is not in the normal interval; the preset normal interval refers to a preset interval range or a preset interval calculation formula.
As one preferable scheme, a dryer, a mould temperature box and a temperature control box are arranged on the periphery of the injection molding machine, a plurality of groups of first temperature sensors are arranged on the dryer, a plurality of groups of second temperature sensors are arranged on the mould temperature box, and a plurality of groups of third temperature sensors are arranged on the temperature control box;
the PLC is connected with the first temperature sensor, the second temperature sensor and the third temperature sensor, and is used for acquiring monitoring index information of the dryer, the mold temperature box and the temperature control box in real time and uploading the monitoring index information to the 5G server.
As one preferable scheme, the injection molding machine monitoring module is configured to obtain monitoring index information of an injection molding machine, and monitor the injection molding machine according to the monitoring index information, and specifically includes:
acquiring monitoring index information of the injection molding machine from the 5G server;
judging whether each index value of the monitoring index information is in a preset normal interval, wherein the preset normal interval refers to a preset interval range or a preset interval calculation formula, and setting a monitoring index corresponding to the index value which is not in the normal interval as an alarm index;
and displaying the monitored key index information and the monitored alarm index information through a screen.
As one preferable scheme, the quality control module is used for monitoring the product quality in the production process, and specifically comprises the following steps:
collecting first image information of an injection product of the injection molding machine, and comparing the first image information with preset image information to judge whether the injection product is qualified or not;
and when the injection molding product is judged to be qualified, judging whether the injection molding product is qualified or not according to the detection standard issued by the 5G server.
As one preferable scheme, the first image information comprises structural image information, color image information and flatness image information, and the quality control module comprises a first quality inspection unit, a second quality inspection unit and a third quality inspection unit;
the first quality inspection unit is used for comparing the structural image information with preset image information;
the second quality inspection unit is used for comparing the color image information with preset image information;
and the third quality inspection unit is used for comparing the structural flatness image information with preset image information.
As one preferable solution, the collecting the first image information of the injection product of the injection molding machine, comparing the first image information with preset image information to determine whether the injection product is qualified, specifically includes:
the first quality inspection unit acquires structural image information of an injection product of the injection molding machine and compares the structural image information with preset image information to judge whether the injection product is qualified or not;
the second quality inspection unit acquires color image information of an injection product of the injection molding machine and compares the structural image information with preset image information to judge whether the injection product is qualified or not;
and the third quality inspection unit acquires flatness image information of an injection product of the injection molding machine and compares the structural image information with preset image information so as to judge whether the injection product is qualified or not.
As one preferable mode, the production data analysis module is configured to acquire production data of an injection molding machine and analyze the production data, and specifically includes:
acquiring production data of the injection molding machine according to preset conditions, and calling a corresponding analysis algorithm according to a preselected analysis type to analyze the production data;
and outputting an analysis result and performing visual display.
As one preferable scheme, the curve information comprises name information and data address information of a curve hopper temperature curve, an injection speed curve, a template speed curve, a melt adhesive speed curve, a storage pressure curve and an injection screw position curve.
Compared with the prior art, the embodiment of the invention has the beneficial effects that at least one of the following points is adopted:
the one-stop service system of the injection molding machine is designed with an injection molding machine monitoring module, a production plan management module, a production data analysis module and a quality control module, and the four modules realize the digital and intelligent management of the whole production process of the injection molding machine, thereby improving the production efficiency and the product quality. The invention provides a comprehensive service system integrating a plurality of production links, solves the problem of unsmooth production control, and realizes the intelligent and digital service of the omnibearing production links of an injection molding machine.
Drawings
FIG. 1 is a schematic diagram of a smart factory-based one-stop service system of an injection molding machine according to one embodiment of the present invention;
FIG. 2 is a schematic diagram of a smart factory-based one-stop service system of an injection molding machine according to an embodiment of the present invention.
Description of the embodiments
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention, and the purpose of these embodiments is to provide a more thorough and complete disclosure of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
An embodiment of the invention provides a one-stop service platform of an injection molding machine based on an intelligent factory, please refer to fig. 1, fig. 1 shows a schematic structure diagram of the one-stop service system of the injection molding machine based on the intelligent factory in one embodiment of the invention, which includes.
The intelligent factory-based one-stop service system of the injection molding machine comprises an injection molding machine monitoring module 101, a production plan management module 102, a production data analysis module 103 and a quality control module 104;
the injection molding machine monitoring module 101 is used for acquiring monitoring index information of an injection molding machine and monitoring the injection molding machine according to the monitoring index information;
the production plan management module 102 is configured to manage a production plan, where the management includes making the production plan, displaying production orders, allocating and tracking production tasks;
the production data analysis module 103 is used for acquiring production data and analyzing the production data to output an analysis result;
the quality control module 104 is used to monitor the quality of the product during the production process.
As an embodiment, referring to fig. 2, the one-station service system of the injection molding machine further includes an equipment maintenance management module 105, a logistics management module 106, and a personnel management module 107, where the equipment maintenance management module 105 is configured to manage equipment maintenance;
the logistics management module 106 is used for managing purchasing, warehousing, sales order and shipping of the products;
the personnel management module 107 is configured to manage personnel files, attendance, salary, performance and training.
As one embodiment, a PLC controller is disposed in the injection molding machine, and the PLC controller is connected to a plurality of sensors, obtains monitoring index information through the plurality of sensors, and uploads the monitoring index information to a 5G server.
The periphery of the injection molding machine is provided with a dryer, a mold temperature box and a temperature control box, wherein a plurality of groups of first temperature sensors are arranged on the dryer, a plurality of groups of second temperature sensors are arranged on the mold temperature box, and a plurality of groups of third temperature sensors are arranged on the temperature control box; and the injection molding machine is in communication connection with the 5G server through an Ethernet switch.
The PLC is connected with the first temperature sensor, the second temperature sensor and the third temperature sensor, and monitors index information of the dryer, the mold temperature box and the temperature control box, which are acquired in real time through the first temperature sensor, the second temperature sensor and the third temperature sensor, wherein the monitor index information comprises temperature values and temperature alarm information;
and uploading the monitoring index information of the dryer, the mold temperature box and the temperature control box to a 5G server.
As one embodiment, the injection molding machine monitoring module 101 is configured to obtain monitoring index information of an injection molding machine, and monitor the injection molding machine according to the monitoring index information, specifically:
the injection molding machine monitoring module 101 acquires monitoring index information of the injection molding machine from the 5G server; the monitoring index information comprises, but is not limited to, the number information of the injection molding machine, the total yield, the ID of an operator, production injection molding, qualified product injection molding, unqualified product injection molding, monitoring injection molding, production time, circulation time, filling time, metering time, take-out time, pressure maintaining switching mark position, injection molding start mark position, minimum buffering mark position, injection molding pressure, pressure maintaining switching pressure, injection molding pressure, mold opening time, mold locking time, ejection time, safety door opening time, qualified product number in a product container, product container replacement frequency, charging barrel temperature, mold temperature, upper and lower limit alarm of charging barrel, heater wire breakage, mold locking force compensation quantity and metering start mark position; the number information comprises a machine number, a product number, a die number, a raw material number and an operation file source number.
Judging whether each index value of the monitoring index information is in a preset normal interval or not, and alarming for abnormal index information which is not in the normal interval, wherein the preset normal interval refers to a preset interval range or a preset interval calculation formula.
As one embodiment, the injection molding machine monitoring module 101 is provided with a display unit, where the display unit is configured to display monitored key index information and alarm index information, and the alarm index is monitoring index information that the index value is not in a preset normal interval; the key index information refers to monitoring index information of important attention of configuration.
As one embodiment, the injection molding machine monitoring module 101 is provided with an energy consumption monitoring unit, and the energy consumption monitoring unit monitors abnormal energy consumption by adopting an energy consumption abnormality detection model and performs abnormality warning according to a monitoring result. The method specifically comprises the following steps:
collecting first energy consumption data of the injection molding machine in real time, preprocessing the first energy consumption data, and inputting the preprocessed first energy consumption data into a Gaussian mixture model for cluster feature learning to obtain a first cluster data set; specifically, the gaussian mixture model is as follows:(1)
wherein,for the number of Gaussian models, +.>Is->Weights of the individual Gaussian models, +.>And->Are respectively->Mean and variance of the individual gaussian models. The gaussian mixture model parameters may be solved iteratively by a maximum expectation algorithm (EM). In the Gaussian mixture model, < >>（/>) Probability of->Use->A weighted model representation of gaussian random variables, and thus, each gaussian model represents a cluster. Inputting the data set between the Gaussian mixture models as D=>，D-dimensional vector after preprocessing for data, +.>. Clustering by the Gaussian mixture model to obtain +.>Mean vector of class samples->（/>) And covariance matrix->（/>）。In the plane of the m-dimensional super, the corresponding basis vector is (>) The basis vector matrix is WR->。
And inputting the first clustering data set into an energy consumption abnormality detection model, and outputting an abnormality monitoring classification result.
As one embodiment, when the first energy consumption data of the injection molding machine is collected in real time, the offset calculation is performed on the accumulated data such as the electric quantity, so as to obtain an electric quantity offset set with the same time interval, and the rest data are sampled equidistantly according to the time interval.
As one embodiment, preprocessing the first energy consumption data, and inputting the preprocessed first energy consumption data into a gaussian mixture model to obtain a first cluster data set, which includes the following steps:
classifying normal energy consumption data and abnormal energy consumption data of the energy consumption data to obtain a normal database and an abnormal database, and inputting the normal database and the abnormal database into the Gaussian mixture model to perform clustering operation to obtain a first clustering result;
generating a first clustering data set according to the first clustering result; the method specifically comprises the following steps:
evaluating the first clustering result by adopting an LDA algorithm to obtain a first evaluation index, judging whether the first evaluation index is in a preset evaluation condition, and if so, obtaining a corresponding output instruction;
and obtaining an optimal clustering feature according to the output instruction, and taking a data set corresponding to the optimal clustering feature as a first clustering data set. -deriving the first cluster dataset according to the following objective function (2):
(2)
wherein,the minimum value of (2) is the matrix +.>Maximum characteristic value of>The maximum value is the matrix>Is a minimum of (2). Cluster number->By objective function->And (5) determining. For the number of clusters in each iteration +.>When->Along with->When the value changes to the minimum value, the cluster number is the optimal cluster number. Matrix->For the basis vector matrix of the objective function (2), ->Is a basis vector. Meanwhile, the latest normal mode library and the latest abnormal mode library are dynamically generated by using the update modes, the minimum value of the current objective function is evaluated, and the optimal data set, namely the output matrix>A corresponding optimal data set.
Because normal or abnormal samples are clustered when the Gaussian mixture model is adopted for clustering, categories can be marked according to the first clustering data set, and the latest normal mode library and the latest abnormal mode library are dynamically generated by updating modes so as to improve the self-adaption capability of the database.
And inputting the first clustering data set into an energy consumption abnormality detection model, and outputting an abnormality monitoring classification result. The energy consumption abnormality detection model is an SVM model. And when the SVM model is trained, optimizing the SVM model by adopting a PSO algorithm to obtain an optimal SVM model, and thus the energy consumption anomaly detection model is obtained.
As one embodiment, the quality control module 104 is configured to monitor quality in a production process, and specifically includes:
collecting first image information of an injection product of the injection molding machine, and comparing the first image information with preset image information to judge whether the injection product is qualified or not;
and when the injection molding product is judged to be qualified, judging whether the injection molding product is qualified or not according to the detection standard issued by the 5G server. The detection standard is a detection rule which is pre-configured and used for judging whether the product is qualified or not, and the detection rule is used as a supplement of the image information comparison method, so that the quality detection precision of the injection molding product is further improved, such as the detection of the size of each part of the injection molding product.
As one embodiment, the first image information includes structural image information, color image information, and flatness image information, and the quality control module 104 includes a first quality inspection unit, a second quality inspection unit, and a third quality inspection unit;
the first quality inspection unit is used for comparing the structural image information with preset image information;
the second quality inspection unit is used for comparing the color image information with preset image information;
and the third quality inspection unit is used for comparing the structural flatness image information with preset image information.
As one embodiment, the collecting the first image information of the injection product of the injection molding machine, comparing the first image information with preset image information to determine whether the injection product is qualified, specifically includes:
the first quality inspection unit acquires structural image information of an injection product of the injection molding machine and compares the structural image information with preset image information to judge whether the injection product is qualified or not;
the second quality inspection unit acquires color image information of an injection product of the injection molding machine and compares the structural image information with preset image information to judge whether the injection product is qualified or not;
and the third quality inspection unit acquires flatness image information of an injection product of the injection molding machine and compares the structural image information with preset image information so as to judge whether the injection product is qualified or not.
As one embodiment, the production data analysis module 103 is configured to obtain production data of an injection molding machine from the 5G server according to a preset condition, analyze the production data, and output an analysis result, and specifically includes:
obtaining first production data and second production data of the injection molding machine according to preset conditions, wherein the first production data comprise, but are not limited to, temperature, pressure, current, voltage and equipment alarm signals, the second production data comprise, but are not limited to, real-time yield, mold parameters, rejection rate statistics and operators, the preset conditions comprise numbering information, analysis time periods, operators and analysis types, and the numbering information comprises machine numbers, product numbers, mold numbers, raw material codes and operation file source numbers.
And selecting a corresponding analysis algorithm according to the analysis type to analyze the first production data and the second production data, outputting an analysis result and performing visual display. Specifically, different analysis types are selected according to different analysis scenes and analysis requirements, and the analysis algorithm specifically adopts deep learning, a neural network, a model algorithm and the like to analyze modes and rules in production data, including descriptive statistics algorithm, predictive statistics algorithm, machine learning algorithm, deep learning algorithm and graph theory algorithm, for example, is used for predicting and analyzing future production conditions (prediction of indexes such as consumption, cost, inventory and the like).
And the visual display is specifically to acquire curve information corresponding to the analysis type, draw a corresponding curve according to the curve information and the production data and perform visual display.
As one embodiment, the visual display specifically includes:
and acquiring pre-configured curve information and time information from the production data analysis module 103, acquiring corresponding third production data from the 5G server according to the curve information, drawing a corresponding curve according to the third production data and the time information, and performing visual display.
The curve information comprises curve name information and data address information, wherein the curve name information comprises a curve hopper temperature curve, an injection speed curve, a template speed curve, a melt adhesive speed curve, a storage pressure curve and an injection screw position curve.
As one example, the production plan management module 102 is configured to intelligently manage production plans, including making production plans, displaying production orders, distributing and tracking production tasks. The production plan management module 102 further analyzes the execution of the production plan, specifically, analyzes the production progress and the productivity, helps the enterprise to know the execution of the production plan, and provides data support for business decision. The production plan management module 102 is connected with a collaborative cooperation system to realize collaboration of data and business processes. Other important connection functions include ERP, MES, PLM, etc. to realize seamless connection of production service. The production plan management module 102 may help the enterprise to make production plan management and improve production quality and efficiency.
The device maintenance management module 105 is configured to intelligently manage device maintenance, specifically: and managing the equipment files, planning the maintenance, dispatching and executing the maintenance tasks, notifying and analyzing faults and the like so as to realize comprehensive supervision and maintenance of the equipment. The device maintenance management module 105 can help enterprises to realize comprehensive supervision and maintenance of devices, and improve the reliability and production efficiency of the devices.
The logistics management module 106 is configured to manage purchasing, warehousing, sales order and shipping of raw materials and finished products, specifically:
the logistics management module 106 includes a procurement management subunit, a warehousing management subunit, a sales order processing subunit, and a shipping management subunit. The purchase management subunit is used for making a purchase plan, providing a supply schedule and applying for payment. The purchase management subunit can help the enterprise to improve purchase efficiency. The warehouse management subunit is used for managing inventory information, warehouse inventory, warehouse maps and article groups. The sales order processing subunit is used for managing the processing flow of sales orders, including order inquiry, order tracking and order processing. The sales order processing subunit can conveniently manage sales orders, and improves sales efficiency. The logistics management module 106 can help enterprises to realize comprehensive supervision of logistics, and improves logistics efficiency and production efficiency.
Claims (10)
1. The intelligent factory-based one-stop service platform of the injection molding machine is characterized by comprising an injection molding machine monitoring module, a production plan management module, a production data analysis module and a quality control module;
the injection molding machine monitoring module is used for acquiring monitoring index information of the injection molding machine and monitoring the injection molding machine according to the monitoring index information;
the production data analysis module is used for acquiring production data, analyzing the production data and outputting an analysis result;
the quality control module is used for monitoring the quality of the product in the production process;
the production plan management module is used for managing the production plan, and the management comprises the steps of making the production plan, displaying production orders, distributing and tracking production tasks.
2. The intelligent factory-based one-stop service system of the injection molding machine of claim 1, further comprising an equipment maintenance management module, a logistics management module and a personnel management module, wherein the equipment maintenance management module is used for managing equipment maintenance;
the logistics management module is used for managing purchasing, warehousing, sales orders and delivery of products;
the personnel management module is used for managing personnel files, attendance, salary, performance and training.
3. The intelligent factory-based one-stop service system of the injection molding machine according to claim 2, wherein a PLC (programmable logic controller) is arranged in the injection molding machine, the PLC is connected with a plurality of sensors, and acquires monitoring index information through the plurality of sensors and uploads the monitoring index information to a 5G server;
the injection molding machine monitoring module acquires monitoring index information of the injection molding machine from the monitoring module, judges whether each index value in the monitoring index information is in a preset normal interval, and alarms for abnormal index information which is not in the normal interval; the preset normal interval refers to a preset interval range or a preset interval calculation formula.
4. The intelligent factory-based one-stop service system of an injection molding machine, as claimed in claim 3, wherein a dryer, a mold temperature box and a temperature control box are arranged on the periphery of the injection molding machine, a plurality of groups of first temperature sensors are arranged on the dryer, a plurality of groups of second temperature sensors are arranged on the mold temperature box, and a plurality of groups of third temperature sensors are arranged on the temperature control box;
the PLC is connected with the first temperature sensor, the second temperature sensor and the third temperature sensor, and is used for acquiring monitoring index information of the dryer, the mold temperature box and the temperature control box in real time and uploading the monitoring index information to the 5G server.
5. The intelligent factory-based one-stop service system of an injection molding machine according to claim 4, wherein the injection molding machine monitoring module is configured to obtain monitoring index information of the injection molding machine, and monitor the injection molding machine according to the monitoring index information, specifically:
acquiring monitoring index information of the injection molding machine from the 5G server;
judging whether each index value of the monitoring index information is in a preset normal interval, wherein the preset normal interval refers to a preset interval range or a preset interval calculation formula, and setting a monitoring index corresponding to the index value which is not in the normal interval as an alarm index;
and displaying the monitored key index information and the monitored alarm index information through a screen.
6. The intelligent factory-based one-stop service system of an injection molding machine of claim 5, wherein the quality control module is configured to monitor product quality during production, and specifically comprises:
collecting first image information of an injection product of the injection molding machine, and comparing the first image information with preset image information to judge whether the injection product is qualified or not;
and when the injection molding product is judged to be qualified, judging whether the injection molding product is qualified or not according to the detection standard issued by the 5G server.
7. The intelligent factory-based one-stop service system of an injection molding machine of claim 6, wherein the first image information comprises structural image information, color image information and flatness image information, and the quality control module comprises a first quality inspection unit, a second quality inspection unit and a third quality inspection unit;
the first quality inspection unit is used for comparing the structural image information with preset image information;
the second quality inspection unit is used for comparing the color image information with preset image information;
and the third quality inspection unit is used for comparing the structural flatness image information with preset image information.
8. The intelligent factory-based one-stop service system of an injection molding machine of claim 7, wherein,
the method for acquiring the first image information of the injection molding product of the injection molding machine comprises the steps of comparing the first image information with preset image information to judge whether the injection molding product is qualified or not, and specifically comprises the following steps:
the first quality inspection unit acquires structural image information of an injection product of the injection molding machine and compares the structural image information with preset image information to judge whether the injection product is qualified or not;
the second quality inspection unit acquires color image information of an injection product of the injection molding machine and compares the structural image information with preset image information to judge whether the injection product is qualified or not;
and the third quality inspection unit acquires flatness image information of an injection product of the injection molding machine and compares the structural image information with preset image information so as to judge whether the injection product is qualified or not.
9. The intelligent factory-based one-stop service system of an injection molding machine of claim 8, wherein the production data analysis module is configured to obtain production data of the injection molding machine and analyze the production data, and specifically comprises:
acquiring production data of the injection molding machine according to preset conditions, and calling a corresponding analysis algorithm according to a preselected analysis type to analyze the production data;
and outputting an analysis result and performing visual display.
10. The intelligent factory-based one-stop service system of an injection molding machine of any one of claims 1 to 9, wherein the profile information includes name information and data address information of a profile hopper temperature profile, an injection speed profile, a mold plate speed profile, a melt adhesive speed profile, a stock pressure profile, and an injection screw position profile.
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