A workshop production process control system and method

Abstract

The present invention provides a workshop production process control system and method, which obtains product processing attribute information of each of the key production intervals on the assembly line within the workshop based on the production data of each of the key production intervals, thereby identifying abnormal key production intervals with inconsistent processing progress, and quickly and accurately identifying key production intervals with delayed processing progress; then obtains actual processing data from visual inspection of the abnormal key production intervals, thereby obtaining product processing status information and machine action status information, distinguishing and identifying abnormal product transportation events and abnormal machine action events occurring in the abnormal key production intervals, facilitating subsequent targeted transportation position adjustment operations for the products and / or action parameter adjustment operations for the processing machines, ensuring that the key production intervals can operate the products in a timely and stable manner, ensuring continuous transportation of products to other key production intervals downstream, and improving the production continuity and stability of the entire assembly line.

Description

Technical Field

[0001] The present invention relates to the field of workshop production control, and particularly to a workshop production process control system and method. Background Art

[0002] The assembly line inside the workshop can perform processing operations on products in different processes to obtain the final products. The assembly line includes a conveyor belt and a number of key production intervals arranged at different positions in sequence along the conveying direction of the conveyor belt. Each key production interval is used to perform specific product production operations. When the product completes the corresponding production operation in the currently located key production interval, it will be transported by the conveyor belt to the next key production interval for the next production operation. If the production operation progress of a certain key production interval slows down, it will not be able to provide products to the next key production interval in time, affecting the product production progress of the entire assembly line, resulting in product accumulation in some key production intervals and idling in some other key production intervals, reducing the production continuity and stability of the entire assembly line. Summary of the Invention

[0003] The purpose of the present invention is to provide a workshop production process control system and method, which, based on the production data of all key production intervals on the assembly line inside the workshop, obtains the product processing attribute information of all key production intervals, thereby identifying abnormal key production intervals with inconsistent processing progress and quickly and accurately identifying key production intervals with delayed processing progress; then visually detecting the processing live data from the abnormal key production intervals to obtain the product processing status information and machine action status information, distinguishing and identifying product transportation abnormal events and machine action abnormal events occurring in the abnormal key production intervals, facilitating subsequent targeted operations for adjusting the product transportation position and / or adjusting the action parameters of the processing machine, ensuring that the key production intervals can operate on the products in a timely and stable manner, ensuring continuous transportation of products to other key production intervals downstream, globally controlling the workshop production process, and improving the production continuity and stability of the entire assembly line.

[0004] The present invention is realized through the following technical solutions:

[0005] A workshop production process control system, comprising:

[0006] A production interval working recognition module, configured to obtain the production data of all key production intervals on the assembly line inside the workshop, analyze the production data, and obtain the product processing attribute information of all key production intervals;

[0007] An abnormal key production interval recognition module, configured to perform correlation processing on the product processing attribute information of all key production intervals to identify abnormal key production intervals with inconsistent processing progress;

[0008] A visual inspection module, configured to visually monitor the abnormal critical production interval and obtain actual processing data of the abnormal critical production interval;

[0009] an abnormal event identification module, which analyzes the actual processing data to obtain product processing status information and machine operation status information of the abnormal critical production interval, thereby identifying whether an abnormal product transportation event or an abnormal machine operation event occurs in the abnormal critical production interval;

[0010] A product transportation adjustment module, configured to adjust the transportation position of the product based on the transportation obstacle information of the product in the abnormal critical production section when an abnormal product transportation event occurs in the abnormal critical production section;

[0011] The machine motion adjustment module is used to adjust the motion parameters of the processing machine based on the motion trajectory information of the processing machine in the abnormal critical production interval when an abnormal machine motion event occurs in the abnormal critical production interval.

[0012] Optionally, the production interval work identification module is used to obtain production data of all key production intervals on the assembly line within the workshop, analyze the production data, and obtain product processing attribute information of all key production intervals, including:

[0013] Based on the location information of all key production areas on the assembly line within the workshop, production data for each key production area is obtained from the workshop cloud. This production data includes the variation in processing time of the product in each key production area. This production data is compared with the benchmark processing time of a single product corresponding to each key production area to obtain the processing progress attribute information of the product in each key production area.

[0014] The abnormal critical production interval identification module is used to associate product processing attribute information of all key production intervals and identify abnormal critical production intervals where processing progress is inconsistent, including:

[0015] Based on the processing sequence of products in all key production intervals, the processing progress attribute information of products in all key production intervals is time-correlated and abnormal key production intervals with inconsistent processing progress are identified; where inconsistent processing progress occurs, it means that the product processing progress lags behind and the product cannot be delivered to the next adjacent key production interval within the preset time range.

[0016] Optionally, the visual inspection module is used to perform visual monitoring on the abnormal critical production interval to obtain actual processing data of the abnormal critical production interval, including:

[0017] Perform binocular vision shooting on the abnormal key production interval to obtain binocular dynamic images; based on the binocular parallax of the binocular dynamic images, obtain the three-dimensional dynamic images of the abnormal key production interval; perform recognition on the three-dimensional dynamic images to obtain the product contour live data and machine contour live data of the abnormal key production interval;

[0018] The abnormal event recognition module analyzes the processing live data to obtain the product processing status information and machine action status information of the abnormal key production interval, and thereby identifies whether a product transportation abnormal event or a machine action abnormal event occurs in the abnormal key production interval, including:

[0019] Analyze the product contour live data and the machine contour live data to obtain the product processed area position information and machine action orientation and amplitude information of the abnormal key production interval; based on the product processed area position information, judge whether the product is processed in its own preset area, if not, then judge that a product transportation abnormal event occurs in the abnormal key production interval, if so, judge that the abnormal key production interval is a product transportation abnormal event; based on the machine action orientation and amplitude information, judge whether the machine performs a processing action with a preset orientation and amplitude on the product, if not, then judge that a machine action abnormal event occurs in the abnormal key production interval, if so, then judge that no machine action abnormal event occurs in the abnormal key production interval.

[0020] Optionally, the product transportation adjustment module is used to, when a product transportation abnormal event occurs in the abnormal key production interval, perform a transportation position adjustment operation on the product based on the transportation obstacle information of the product in the abnormal key production interval, including:

[0021] When a product transportation abnormal event occurs in the abnormal key production interval, perform a transportation position adjustment operation with corresponding orientation and displacement on the product based on the line deviation between the actual transportation line of the product in the abnormal key production interval and the preset reference transportation line;

[0022] The machine action adjustment module is used to, when a machine action abnormal event occurs in the abnormal key production interval, perform an action parameter adjustment operation on the processing machine based on the action trajectory information of the processing machine in the abnormal key production interval, including:

[0023] When a machine action abnormal event occurs in the abnormal key production interval, perform an action parameter adjustment operation with corresponding direction and amplitude on the processing machine based on the trajectory deviation between the actual action trajectory of the processing machine in the abnormal key production interval and the preset standard action trajectory.

[0024] A workshop production process control method, including:

[0025] Obtain production data from all key production areas on the assembly line within the workshop, analyze the production data, and obtain product processing attribute information for each key production area; correlate the product processing attribute information of all key production areas to identify abnormal key production areas with inconsistent processing schedules;

[0026] Visually monitor the abnormally critical production section to obtain actual processing data of the abnormally critical production section; analyze the actual processing data to obtain product processing status information and machine operation status information of the abnormally critical production section, thereby identifying whether an abnormal product transportation event or an abnormal machine operation event has occurred in the abnormally critical production section;

[0027] When an abnormal product transportation event occurs in the abnormal critical production interval, the transportation position of the product is adjusted based on the transportation obstacle information of the product in the abnormal critical production interval; when an abnormal machine action event occurs in the abnormal critical production interval, the action parameters of the processing machine are adjusted based on the action trajectory information of the processing machine in the abnormal critical production interval.

[0028] Optionally, production data of all key production sections on the assembly line within the workshop is obtained, and the production data is analyzed to obtain product processing attribute information of all key production sections; the product processing attribute information of all key production sections is correlated to identify abnormal key production sections with inconsistent processing schedules, including:

[0029] Based on the location information of all key production areas on the assembly line within the workshop, production data for each key production area is obtained from the workshop cloud. This production data includes the variation in processing time of the product in each key production area. This production data is compared with the benchmark processing time of a single product corresponding to each key production area to obtain the processing progress attribute information of the product in each key production area.

[0030] Based on the processing sequence of products in all key production intervals, the processing progress attribute information of products in all key production intervals is time-correlated and abnormal key production intervals with inconsistent processing progress are identified; where inconsistent processing progress occurs, it means that the product processing progress lags behind and the product cannot be delivered to the next adjacent key production interval within the preset time range.

[0031] Optionally, the production data is compared with a benchmark processing time of a single product corresponding to the key production interval to obtain processing progress attribute information of the key production interval for the product, including:

[0032] Step S1. Assume there are n pieces of actual production data corresponding to the critical production interval, and the actual production time of the i-th piece is T i , where i is an integer greater than or equal to 1 and less than or equal to n. Then the actual average production time of the critical production interval is:

[0033]

[0034] In the above formula (1), is the actual average production time of the critical production interval;

[0035] Step S2. Assume that among the n pieces of actual production data, A pieces of data belong to spring, B pieces of data belong to summer, C pieces of data belong to autumn, and D pieces of data belong to winter. Then the actual production time of the critical production interval is:

[0036]

[0037] In the above formula (2), T is the actual production time of the critical production interval, α and β are preset adjustment coefficients, and their values are both greater than 0 and less than 1, and the sum of α and β is 1. a, b, c, and d are the numbers of the data corresponding to spring, summer, autumn, and winter respectively, and their values are all integers greater than or equal to 1 and less than or equal to the total amount of seasonal data. T a is the actual production time of the a-th piece of data corresponding to spring, T b is the actual production time of the b-th piece of data corresponding to summer, T c is the actual production time of the c-th piece of data corresponding to autumn, T d is the actual production time of the d-th piece of data corresponding to winter;

[0038] Step S3. Assume that the processing reference time of a single product m is t m , then the processing progress attribute information of the corresponding product is:

[0039]

[0040] In the above formula (3), K m is the processing progress attribute information of the corresponding product, M is the total number of types of single products produced in the critical production interval, and m is an integer greater than or equal to 1 and less than or equal to M.

[0041] Optionally, visually monitor the abnormal critical production interval to obtain the processing live data of the abnormal critical production interval; analyze the processing live data to obtain the product processing status information and machine action status information of the abnormal critical production interval, so as to identify whether a product transportation abnormal event or a machine action abnormal event occurs in the abnormal critical production interval, including:

[0042] Perform binocular vision shooting on the abnormal critical production interval to obtain binocular dynamic images; based on the binocular parallax of the binocular dynamic images, obtain three-dimensional dynamic images of the abnormal critical production interval; identify the three-dimensional dynamic images to obtain the actual product contour data and actual machine contour data of the abnormal critical production interval;

[0043] Analyze the actual product contour data and the actual machine contour data to obtain the position information of the processed area of the product and the machine action orientation and amplitude information in the abnormal critical production interval; based on the position information of the processed area of the product, determine whether the product is processed in its own preset area. If not, it is determined that a product transportation abnormal event occurs in the abnormal critical production interval. If so, it is determined that the abnormal critical production interval is a product transportation abnormal event; based on the machine action orientation and amplitude information, determine whether the machine performs a processing action with a preset orientation and amplitude on the product. If not, it is determined that a machine action abnormal event occurs in the abnormal critical production interval. If so, it is determined that no machine action abnormal event occurs in the abnormal critical production interval.

[0044] Optionally, when a product transportation abnormal event occurs in the abnormal critical production interval, perform a transportation position adjustment operation on the product based on the transportation obstacle information of the product in the abnormal critical production interval; when a machine action abnormal event occurs in the abnormal critical production interval, perform an action parameter adjustment operation on the processing machine based on the action trajectory information of the processing machine in the abnormal critical production interval, including:

[0045] When a product transportation abnormal event occurs in the abnormal critical production interval, perform a transportation position adjustment operation with corresponding orientation and displacement on the product based on the line deviation between the actual transportation line of the product in the abnormal critical production interval and the preset reference transportation line;

[0046] When a machine action abnormal event occurs in the abnormal critical production interval, perform an action parameter adjustment operation with corresponding direction and amplitude on the processing machine based on the trajectory deviation between the actual action trajectory of the processing machine in the abnormal critical production interval and the preset standard action trajectory.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The workshop production process control system and method provided by this application are based on the production data of all key production intervals on the assembly line inside the workshop, obtain the product processing attribute information of all key production intervals respectively, thereby identify the abnormal key production intervals with inconsistent processing progress, and quickly and accurately identify the key production intervals with delayed processing progress; then obtain the processing actual situation data from the visual inspection of the abnormal key production intervals, thereby obtain the product processing status information and the machine action status information, distinguish and identify the product transportation abnormal events and machine action abnormal events occurring in the abnormal key production intervals, which is convenient for subsequent targeted operations of adjusting the transportation position of the product and / or adjusting the action parameters of the processing machine, ensure that the key production intervals can operate on the product in a timely and stable manner, ensure the continuous transportation of products to other key production intervals downstream, and conduct global control over the workshop production process and improve the production continuity and stability of the entire assembly line. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. Among them:

[0050] Figure 1 It is a schematic structural diagram of a workshop production process control system provided by the present invention.

[0051] Figure 2 It is a schematic flow diagram of a workshop production process control method provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] In order to make the above-mentioned objects, features, and advantages of this application more obvious and understandable, the following will make a detailed description of the specific implementation manners of this application in conjunction with the drawings. It can be understood that the specific embodiments described herein are only used to explain this application, rather than limiting this application. Additionally, it should be noted that for the sake of description, only the parts related to this application rather than all the structures are shown in the drawings. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application.

[0053] The terms "including" and "having" and any variations thereof in this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0054] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0055] See also Figure 1 As shown, an embodiment of the present application provides a workshop production process control system. The workshop production process control system includes:

[0056] The production interval work identification module is used to obtain the production data of all key production intervals on the assembly line within the workshop, analyze the production data, and obtain the product processing attribute information of each key production interval;

[0057] The abnormal critical production interval identification module is used to associate the product processing attribute information of all key production intervals and identify abnormal critical production intervals where processing progress is inconsistent;

[0058] A visual inspection module is used to visually monitor the abnormal critical production interval and obtain the actual processing data of the abnormal critical production interval;

[0059] The abnormal event identification module analyzes the actual processing data to obtain the product processing status information and machine operation status information of the abnormal critical production interval, so as to identify whether the abnormal product transportation event or the abnormal machine operation event occurred in the abnormal critical production interval;

[0060] A product transportation adjustment module is used to adjust the transportation position of the product based on the transportation obstacle information of the product in the abnormal critical production section when a product transportation abnormality event occurs in the abnormal critical production section;

[0061] The machine motion adjustment module is used to adjust the motion parameters of the processing machine based on the motion trajectory information of the processing machine in the abnormal critical production interval when an abnormal machine motion event occurs in the abnormal critical production interval.

[0062] Beneficial effects of the above embodiments. The workshop production process control system obtains the product processing attribute information of each key production area based on the production data of each key production area on the production line inside the workshop, so as to identify the abnormal key production areas with inconsistent processing progress and quickly and accurately identify the key production areas with delayed processing progress. Then, the processing actual situation data is obtained through visual inspection of the abnormal key production areas, so as to obtain the product processing status information and the machine action status information, and distinguish and identify the product transportation abnormal events and machine action abnormal events occurring in the abnormal key production areas, which is convenient for subsequent targeted operations to adjust the transportation position of the product and / or adjust the action parameters of the processing machine, ensuring that the key production areas can operate on the product in a timely and stable manner, ensuring the continuous transportation of products to other key production areas downstream, and globally controlling the workshop production process and improving the production continuity and stability of the entire production line.

[0063] In another embodiment, the production area working identification module is used to obtain the production data of each key production area on the production line inside the workshop, analyze the production data, and obtain the product processing attribute information of each key production area, including:

[0064] Based on the location information of each key production area on the production line inside the workshop, obtain the production data of each key production area from the workshop cloud; wherein, the production data includes the processing time change data of the product in the key production area; compare the production data with the single product processing reference time corresponding to the key production area to obtain the processing progress attribute information of the product in the key production area.

[0065] The abnormal key production area identification module is used to perform correlation processing on the product processing attribute information of all key production areas to identify the abnormal key production areas with inconsistent processing progress, including:

[0066] Based on the processing sequence of the product in all key production areas, perform time correlation processing on the processing progress attribute information of the product in all key production areas to identify the abnormal key production areas with inconsistent processing progress; wherein, the inconsistent processing progress means that the processing progress of the product lags behind and the product cannot be transported to the adjacent next key production area within the preset time range.

[0067] Beneficial effects of the above embodiments: In the assembly line inside the workshop, a plurality of key production intervals are sequentially arranged along the product transportation direction of the assembly line itself. Different key production intervals are used to perform different types of production and processing operations on the product. These production and processing operations are sequentially continuous. Moreover, each key production interval has a corresponding time limit for performing the production and processing operations. If a certain key production interval cannot complete the corresponding production and processing operations within the preset time range, it will lead to the accumulation of products inside the key production interval and the inability of subsequent other key production intervals to be timely transported with products for processing operations. Therefore, based on the position information of all key production intervals on the assembly line, the processing time change data of all key production intervals for the product are obtained from the workshop cloud server. The processing time change data refers to the processing time change data of all products during the processing of several continuously transported products by the key production interval. Then, the processing time change data is compared with the single product processing reference time corresponding to the key production interval to obtain the processing progress attribute information of the key production interval for the product. Among them, the single product processing reference time refers to the reference time range for the key production interval to complete the corresponding processing operations for a single product. If the actual processing time of a certain product in the processing time change data is less than or equal to the single product processing reference time, it is determined that the processing progress of the key production interval for the product is normal; otherwise, it is determined that the processing progress of the key production interval for the product is delayed, and the corresponding processing progress delay duration corresponds to the difference between the actual processing time of the product and the single product processing reference time. Then, based on the processing order of all key production intervals for the product, time correlation processing is performed on the processing progress attribute information of all key production intervals for the product, that is, time correlation processing is performed on the processing progress delay durations of all key production intervals for the product, and the abnormal key production intervals that are behind in the processing progress of the product and cannot transport the product to the adjacent next key production interval within the preset time range are identified. In this way, all abnormal key production intervals with delayed and backward processing progress on the overall assembly line can be accurately identified, providing an accurate positioning for subsequent adjustment of the working state of the abnormal key production intervals.

[0068] In another embodiment, the vision detection module is used to visually monitor the abnormal key production interval to obtain the processing live data of the abnormal key production interval, including:

[0069] Perform binocular vision shooting on the abnormal key production interval to obtain binocular dynamic images; based on the binocular disparity of the binocular dynamic images, obtain the three-dimensional dynamic images of the abnormal key production interval; perform recognition on the three-dimensional dynamic images to obtain the product contour live data and machine contour live data of the abnormal key production interval;

[0070] The abnormal event recognition module analyzes the processing live data to obtain the product processing status information and machine operation status information in the abnormal key production interval, and uses this to identify whether a product transportation abnormal event or a machine operation abnormal event occurs in the abnormal key production interval, including:

[0071] Analyze the product contour live data and the machine contour live data to obtain the product processed area position information and machine operation orientation and amplitude information in the abnormal key production interval; based on the product processed area position information, determine whether the product is processed in its own preset area. If not, it is determined that a product transportation abnormal event occurs in the abnormal key production interval. If so, it is determined that the abnormal key production interval is a product transportation abnormal event; based on the machine operation orientation and amplitude information, determine whether the machine performs a processing action with a preset orientation and amplitude on the product. If not, it is determined that a machine operation abnormal event occurs in the abnormal key production interval. If so, it is determined that no machine operation abnormal event occurs in the abnormal key production interval.

[0072] The beneficial effects of the above embodiments are that the delay in the product processing progress in the abnormal key production interval is mainly caused by obstacles in the product transportation within the abnormal key production interval or the untimely processing of the product by the processing machine within the abnormal key production interval. Therefore, binocular vision shooting and analysis are performed on the abnormal key production interval to obtain the product contour live data and machine contour live data of the abnormal key production interval, so as to perform targeted analysis on the operation status of the abnormal key production interval from the product and the machine itself. Analyze the product contour live data and the machine contour live data respectively to obtain the product processed area position information and machine operation orientation and amplitude information in the abnormal key production interval. The product processed area position information can be, but is not limited to, the position information of the corresponding processing contact area during the processing of the product by the processing machine within the abnormal key production interval. The machine operation orientation and amplitude information can be, but is not limited to, the orientation and amplitude information of the processing action performed by the processing machine within the abnormal key production interval during the processing of the product. Then compare the product processed area position information with the expected product processed area position information. If the two are consistent, it is determined that the product is processed in its own preset area; otherwise, it is determined that the product is not processed in its own preset area, so as to accurately determine whether a product transportation abnormal event occurs in the abnormal key production interval. Also, compare the machine operation orientation and amplitude information with the orientation and amplitude information of the expected processing action applied by the machine. If the two are consistent, it is determined that the machine performs a processing action with a preset orientation and amplitude on the product; otherwise, it is determined that the machine does not perform a processing action with a preset orientation and amplitude on the product, so as to accurately determine whether a machine operation abnormal event occurs in the abnormal key production interval.

[0073] In another embodiment, the product transportation adjustment module is used to, when a product transportation anomaly event occurs in the abnormal critical production interval, perform a transportation position adjustment operation on the product based on the transportation obstacle information of the product in the abnormal critical production interval, including:

[0074] When a product transportation anomaly event occurs in the abnormal critical production interval, perform a transportation position adjustment operation on the product with corresponding orientation and displacement based on the line deviation between the actual transportation line of the product in the abnormal critical production interval and the preset reference transportation line;

[0075] The machine motion adjustment module is used to, when a machine motion anomaly event occurs in the abnormal critical production interval, perform a motion parameter adjustment operation on the processing machine based on the motion trajectory information of the processing machine in the abnormal critical production interval, including:

[0076] When a machine motion anomaly event occurs in the abnormal critical production interval, perform a motion parameter adjustment operation on the processing machine with corresponding direction and amplitude based on the trajectory deviation between the actual motion trajectory of the processing machine in the abnormal critical production interval and the preset standard motion trajectory.

[0077] The beneficial effects of the above embodiments are as follows. When a product transportation anomaly event occurs in the abnormal critical production interval, based on the line deviation between the actual transportation line of the product in the abnormal critical production interval and the preset reference transportation line, the line deviation can be, but is not limited to, the difference in line direction and / or line offset distance, and accordingly perform a transportation position adjustment operation on the product with corresponding orientation and displacement, so as to ensure that the product can be moved to the correct and appropriate position of the internal conveyor belt in the abnormal critical production interval for transportation movement. The transportation position adjustment operation on the product can be realized by a manipulator, which will not be described in detail here. When a machine motion anomaly event occurs in the abnormal critical production interval, based on the trajectory deviation between the actual motion trajectory of the processing machine in the abnormal critical production interval and the preset standard motion trajectory, the trajectory deviation can be, but is not limited to, the difference in the motion trajectory direction and / or displacement of the processing machine, and accordingly perform a motion parameter adjustment operation on the processing machine with corresponding direction and amplitude, so as to ensure that the processing machine can process the product with the correct motion direction and amplitude, and improve the processing accuracy of the product.

[0078] Please refer to Figure 2 As shown, a workshop production process control method provided by an embodiment of the present application. The workshop production process control method includes:

[0079] Obtain the production data of each key production area on the production line inside the workshop, analyze the production data, and obtain the product processing attribute information of each key production area; perform correlation processing on the product processing attribute information of all key production areas to identify abnormal key production areas where the processing progress is inconsistent;

[0080] Perform visual monitoring on the abnormal key production area to obtain the processing actual situation data of the abnormal key production area; analyze the processing actual situation data to obtain the product processing status information and machine action status information of the abnormal key production area, so as to identify whether a product transportation abnormal event or a machine action abnormal event occurs in the abnormal key production area;

[0081] When a product transportation abnormal event occurs in the abnormal key production area, perform an operation to adjust the transportation position of the product based on the transportation obstacle information of the product in the abnormal key production area; when a machine action abnormal event occurs in the abnormal key production area, perform an operation to adjust the action parameters of the processing machine based on the action trajectory information of the processing machine in the abnormal key production area.

[0082] The beneficial effects of the above embodiments are that the workshop production process control method is based on the production data of each key production area on the production line inside the workshop, obtains the product processing attribute information of each key production area, and thus identifies abnormal key production areas where the processing progress is inconsistent, quickly and accurately identifying key production areas with delayed processing progress; then visually detecting the processing actual situation data from the abnormal key production area, and thus obtaining the product processing status information and machine action status information, distinguishing and identifying the product transportation abnormal event and the machine action abnormal event occurring in the abnormal key production area, facilitating subsequent targeted operations to adjust the transportation position of the product and / or adjust the action parameters of the processing machine, ensuring that the key production area can operate on the product in a timely and stable manner, ensuring continuous transportation of products to other key production areas downstream, globally controlling the workshop production process and improving the production continuity and stability of the entire production line.

[0083] In another embodiment, obtain the production data of each key production area on the production line inside the workshop, analyze the production data, and obtain the product processing attribute information of each key production area; perform correlation processing on the product processing attribute information of all key production areas to identify abnormal key production areas where the processing progress is inconsistent, including:

[0084] Based on the location information of all key production areas on the assembly line within the workshop, production data for each key production area is obtained from the workshop cloud. This production data includes the variation in processing time of the product in each key production area. This production data is compared with the benchmark processing time of a single product corresponding to the key production area to obtain the processing progress attribute information of the product in each key production area.

[0085] Based on the processing sequence of products in all key production intervals, the processing progress attribute information of products in all key production intervals is time-correlated and abnormal key production intervals with inconsistent processing progress are identified; where inconsistent processing progress occurs, it means that the product processing progress lags behind and the product cannot be delivered to the next adjacent key production interval within the preset time range.

[0086] The beneficial effects of the above embodiments are as follows. Along the transportation direction of the products by itself, a plurality of key production intervals are sequentially arranged inside the workshop. Different key production intervals are used to perform different types of production and processing procedures on the products. These production and processing procedures are sequentially continuous. Moreover, each key production interval has a corresponding time limit for performing the production and processing procedures. If a certain key production interval cannot complete the corresponding production and processing procedures within the preset time range, it will lead to the accumulation of products inside this key production interval and the subsequent inability of other key production intervals to be timely transported with products for processing operations. For this reason, based on the position information of all key production intervals on the production line respectively, the processing time change data of all key production intervals for the products are obtained from the workshop cloud server. This processing time change data refers to the processing time change data of all products during the processing of several continuously transported products by the key production interval. Then, this processing time change data is compared with the single-product processing benchmark time corresponding to this key production interval to obtain the processing progress attribute information of this key production interval for the products. Among them, the single-product processing benchmark time refers to the benchmark time range for this key production interval to complete the corresponding processing procedures for a single product. If the actual processing time of a certain product in this processing time change data is less than or equal to this single-product processing benchmark time, it is determined that the processing progress of this key production interval for the products is normal; otherwise, it is determined that the processing progress of this key production interval for the products is delayed, and the corresponding processing progress delay duration corresponds to the difference between the actual processing time of the product and this single-product processing benchmark time. Then, based on the processing order of all key production intervals for the products, time correlation processing is performed on the processing progress attribute information of all key production intervals for the products, that is, time correlation processing is performed on the processing progress delay durations of all key production intervals for the products, and abnormal key production intervals that are behind in the processing progress of the products and cannot transport products to the adjacent next key production interval within the preset time range are identified. In this way, all abnormal key production intervals with delayed and backward processing progress of products on the overall production line can be accurately identified, providing an accurate positioning for subsequent adjustment of the working state of the abnormal key production intervals.

[0087] In another embodiment, the production data is compared with the single-product processing benchmark time corresponding to the key production interval to obtain the processing progress attribute information of the key production interval for the products, including:

[0088] Step S1, assume that there are n pieces of actual production data corresponding to the key production interval, and the actual production time of the i-th piece is T i , where i is an integer greater than or equal to 1 and less than or equal to n. Then the actual average production time of this key production interval is:

[0089]

[0090] In the above formula (1), is the actual average production time-consuming of this key production interval;

[0091] Step S2, assume that among the n actual production data, A data belong to spring, B data belong to summer, C data belong to autumn, and D data belong to winter. Then the actual production time-consuming of this key production interval is:

[0092]

[0093] In the above formula (2), T is the actual production time-consuming of this key production interval, α and β are preset adjustment coefficients, and their values are both greater than 0 and less than 1, and the sum of α and β is 1. a, b, c, and d are the numbers of the data corresponding to spring, summer, autumn, and winter respectively, and their values are all integers greater than or equal to 1 and less than or equal to the total amount of the corresponding seasonal data, T a is the actual production time-consuming of the a-th data corresponding to spring, T b is the actual production time-consuming of the b-th corresponding summer data, T c is the actual production time-consuming of the c-th data corresponding to autumn, T d is the actual production time-consuming of the d-th data corresponding to winter;

[0094] Step S3, assume that the processing reference time-consuming of a single product m is t m , then the processing progress attribute information of the corresponding product is:

[0095]

[0096] In the above formula (3), K m is the processing progress attribute information of the corresponding product, M is the total type of a single product produced in this key production interval, and m is an integer greater than or equal to 1 and less than or equal to M.

[0097] The beneficial effect of the above embodiment is that in the actual processing process, due to defects in the structure of a certain product itself or certain products are stuck in the mechanical structure inside the key production interval, or seasonal changes cause changes in production, these accidents will reduce the original processing speed of the key production interval. Therefore, for the determination of the processing progress attribute information of the product in the key production interval, it is necessary to consider the above-mentioned various factors that may cause changes in processing speed, so as to avoid the occurrence of production capacity bottlenecks or production stagnation due to special circumstances or abnormal circumstances. Based on the actual production time and the processing benchmark time of a single product, taking into account abnormal circumstances and seasonal changes, accurate product processing progress attribute information is calculated to avoid the occurrence of production capacity bottlenecks or production stagnation due to special circumstances or abnormal circumstances.

[0098] In another embodiment, visual monitoring is performed on the abnormally critical production section to obtain actual processing data of the abnormally critical production section; the actual processing data is analyzed to obtain product processing status information and machine operation status information of the abnormally critical production section, thereby identifying whether an abnormal product transportation event or an abnormal machine operation event has occurred in the abnormally critical production section, including:

[0099] Perform binocular vision shooting of the abnormal critical production area to obtain a binocular dynamic image; obtain a three-dimensional dynamic image of the abnormal critical production area based on the binocular parallax of the binocular dynamic image; and perform recognition on the three-dimensional dynamic image to obtain actual product profile data and machine profile data of the abnormal critical production area;

[0100] The actual data of the product profile and the actual data of the machine profile are analyzed to obtain the product processing area position information and the machine movement direction and amplitude information of the abnormal critical production interval; based on the product processing area position information, determine whether the product is processed in its own preset area; if not, determine that an abnormal product transportation event has occurred in the abnormal critical production interval; if so, determine that an abnormal product transportation event has occurred in the abnormal critical production interval; based on the machine movement direction and amplitude information, determine whether the machine performs a processing action of the preset direction and amplitude on the product; if not, determine that an abnormal machine movement event has occurred in the abnormal critical production interval; if so, determine that no abnormal machine movement event has occurred in the abnormal critical production interval.

[0101] The beneficial effects of the above embodiments are as follows. The delay in the processing progress of products in the abnormal critical production interval is mainly caused by obstacles in the internal transportation of products in the abnormal critical production interval or the untimely processing of products by the processing machines in the abnormal critical production interval. Therefore, binocular vision shooting and analysis are carried out on this abnormal critical production interval to obtain the actual product contour data and the actual machine contour data of this abnormal critical production interval, so as to conduct targeted analysis on the operation status of this abnormal critical production interval from the aspects of products and machines themselves. Analyze the actual product contour data and the actual machine contour data respectively to obtain the position information of the processed area of the product in this abnormal critical production interval and the information of the machine action orientation and amplitude. The position information of the processed area of the product can be, but is not limited to, the position information of the corresponding processing contact area during the processing of the product by the processing machine in the abnormal critical production interval. The information of the machine action orientation and amplitude can be, but is not limited to, the orientation and amplitude information of the processing action implemented by the processing machine in the abnormal critical production interval during the processing of the product. Then compare the position information of the processed area of the product with the expected processed area position information of the product. If the two are consistent, it is determined that the product is processed in its own preset area; otherwise, it is determined that the product is not processed in its own preset area, so as to accurately judge whether a product transportation abnormal event occurs in this abnormal critical production interval. Also, compare the information of the machine action orientation and amplitude with the orientation and amplitude information of the expected processing action to be applied by the machine. If the two are consistent, it is determined that the machine implements the processing action with the preset orientation and amplitude on the product; otherwise, it is determined that the machine does not implement the processing action with the preset orientation and amplitude on the product, so as to accurately judge whether a machine action abnormal event occurs in this abnormal critical production interval.

[0102] In another embodiment, when a product transportation abnormal event occurs in this abnormal critical production interval, a transportation position adjustment operation is performed on the product based on the transportation obstacle information of the product in this abnormal critical production interval; when a machine action abnormal event occurs in this abnormal critical production interval, an action parameter adjustment operation is performed on the processing machine based on the action trajectory information of the processing machine in this abnormal critical production interval, including:

[0103] When a product transportation abnormal event occurs in this abnormal critical production interval, a transportation position adjustment operation with corresponding orientation and displacement is performed on the product based on the line deviation between the actual transportation line of the product in this abnormal critical production interval and the preset reference transportation line;

[0104] When a machine action abnormal event occurs in this abnormal critical production interval, an action parameter adjustment operation with corresponding direction and amplitude is performed on the processing machine based on the trajectory deviation between the actual action trajectory of the processing machine in this abnormal critical production interval and the preset standard action trajectory.

[0105] Beneficial effects of the above embodiments: When a product transportation anomaly occurs in the abnormal critical production interval, based on the route deviation between the actual transportation route of the product in the abnormal critical production interval and the preset reference transportation route, the route deviation can be, but is not limited to, the difference in route direction and / or route offset distance. Accordingly, a transportation position adjustment operation for the product in the corresponding direction and displacement is performed, so as to ensure that the product can be moved to the correct and appropriate position on the internal conveyor belt of the abnormal critical production interval for transportation movement. The transportation position adjustment operation for the product can be implemented by a manipulator, which will not be described in detail here. When a machine action anomaly occurs in the abnormal critical production interval, based on the trajectory deviation between the actual action trajectory of the processing machine in the abnormal critical production interval and the preset standard action trajectory, the trajectory deviation can be, but is not limited to, the difference in the action trajectory direction and / or displacement of the processing machine. Accordingly, an action parameter adjustment operation for the processing machine in the corresponding direction and amplitude is performed, so as to ensure that the processing machine can process the product in the correct action direction and amplitude, and improve the processing accuracy of the product.

[0106] Generally speaking, the workshop production process control system and method obtain the product processing attribute information of each key production interval based on the production data of all key production intervals on the assembly line inside the workshop, so as to identify the abnormal critical production intervals with uncoordinated processing progress and quickly and accurately identify the critical production intervals with delayed processing progress; then, the processing live data is obtained through visual inspection of the abnormal critical production intervals, so as to obtain the product processing status information and the machine action status information, distinguish and identify the product transportation anomaly events and machine action anomaly events occurring in the abnormal critical production intervals, which is convenient for subsequent targeted transportation position adjustment operations for the product and / or action parameter adjustment operations for the processing machine, ensure that the key production intervals can operate on the product in a timely and stable manner, ensure continuous transportation of the product to other key production intervals downstream, and globally control the workshop production process and improve the production continuity and stability of the entire assembly line.

[0107] The above is only a specific embodiment of the present invention, and any improvement made on the premise of the present invention concept is regarded as the protection scope of the present invention.

Claims

1. A workshop production process control system, characterized in that, include: The production interval work identification module is used to obtain the production data of all key production intervals on the assembly line within the workshop, analyze the production data, and obtain the product processing attribute information of each key production interval; An abnormal critical production interval identification module is used to associate the product processing attribute information of all key production intervals and identify abnormal critical production intervals where processing progress is inconsistent; a visual inspection module is used to visually monitor the abnormal critical production intervals and obtain the actual processing data of the abnormal critical production intervals; an abnormal event identification module, which analyzes the actual processing data to obtain product processing status information and machine operation status information of the abnormal critical production interval, thereby identifying whether an abnormal product transportation event or an abnormal machine operation event occurs in the abnormal critical production interval; A product transportation adjustment module, configured to adjust the transportation position of the product based on the transportation obstacle information of the product in the abnormal critical production section when an abnormal product transportation event occurs in the abnormal critical production section; a machine motion adjustment module, configured to adjust motion parameters of the processing machine based on motion trajectory information of the processing machine in the abnormally critical production interval when an abnormal machine motion event occurs in the abnormally critical production interval; The visual inspection module is used to perform visual monitoring on the abnormal critical production interval to obtain actual processing data of the abnormal critical production interval, including: Perform binocular vision shooting of the abnormal critical production area to obtain a binocular dynamic image; obtain a three-dimensional dynamic image of the abnormal critical production area based on the binocular parallax of the binocular dynamic image; and perform recognition on the three-dimensional dynamic image to obtain product profile real-time data and machine profile real-time data of the abnormal critical production area; The abnormal event identification module analyzes the actual processing data to obtain product processing status information and machine operation status information of the abnormal critical production interval, thereby identifying whether a product transportation abnormal event or a machine operation abnormal event occurs in the abnormal critical production interval, including: The product profile actual data and the machine profile actual data are analyzed to obtain the product processing area position information and the machine movement direction and amplitude information of the abnormal critical production interval; based on the product processing area position information, determine whether the product is processed in its own preset area; if not, determine that an abnormal product transportation event has occurred in the abnormal critical production interval; if so, determine that an abnormal product transportation event has occurred in the abnormal critical production interval; based on the machine movement direction and amplitude information, determine whether the machine performs a processing action of the preset direction and amplitude on the product; if not, determine that an abnormal machine movement event has occurred in the abnormal critical production interval; if so, determine that no abnormal machine movement event has occurred in the abnormal critical production interval.

2. The workshop production process control system according to claim 1, characterized in that: The production area working identification module is used to obtain the production data of each key production area on the production line inside the workshop, analyze the production data, and obtain the product processing attribute information of each key production area, including: Based on the location information of each key production area on the production line inside the workshop, obtain the production data of each key production area from the workshop cloud; wherein, the production data includes the processing time change data of the product in the key production area; compare the production data with the single product processing reference time corresponding to the key production area to obtain the processing progress attribute information of the key production area for the product; The abnormal key production area identification module is used to perform correlation processing on the product processing attribute information of all key production areas to identify abnormal key production areas with inconsistent processing progress, including: Based on the processing sequence of the product in all key production areas, perform time correlation processing on the processing progress attribute information of the product in all key production areas to identify abnormal key production areas with inconsistent processing progress; where inconsistent processing progress means that the product processing progress lags behind and the product cannot be transported to the adjacent next key production area within the preset time range.

3. The workshop production process control system according to claim 1, wherein: The product transportation adjustment module is used to, when a product transportation abnormal event occurs in the abnormal key production area, perform a product transportation position adjustment operation based on the transportation obstacle information of the product in the abnormal key production area, including: When a product transportation abnormal event occurs in the abnormal key production area, perform a product transportation position adjustment operation with corresponding orientation and displacement based on the line deviation between the actual transportation line of the product in the abnormal key production area and the preset reference transportation line; The machine action adjustment module is used to, when a machine action abnormal event occurs in the abnormal key production area, perform a machine action parameter adjustment operation based on the action trajectory information of the processing machine in the abnormal key production area, including: When a machine action abnormal event occurs in the abnormal key production area, perform a machine action parameter adjustment operation with corresponding direction and amplitude based on the trajectory deviation between the actual action trajectory of the processing machine in the abnormal key production area and the preset standard action trajectory.

4. A workshop production process control method, characterized in that, Including: Obtain the production data of each key production area on the production line inside the workshop, analyze the production data, and obtain the product processing attribute information of each key production area; perform correlation processing on the product processing attribute information of all key production areas to identify abnormal key production areas with inconsistent processing progress; Perform visual monitoring on the abnormal key production area to obtain the processing live data of the abnormal key production area; analyze the processing live data to obtain the product processing status information and machine action status information of the abnormal key production area, so as to identify whether a product transportation abnormal event or a machine action abnormal event occurs in the abnormal key production area; When a product transportation anomaly event occurs in the abnormal critical production interval, based on the transportation obstacle information of the product in the abnormal critical production interval, a transportation position adjustment operation is performed on the product; when a machine action anomaly event occurs in the abnormal critical production interval, based on the action trajectory information of the processing machine in the abnormal critical production interval, an action parameter adjustment operation is performed on the processing machine; wherein, visual monitoring is performed on the abnormal critical production interval to obtain the processing live data of the abnormal critical production interval; the processing live data is analyzed to obtain the product processing status information and the machine action status information of the abnormal critical production interval, so as to identify whether a product transportation anomaly event or a machine action anomaly event occurs in the abnormal critical production interval, including: Perform binocular vision shooting on the abnormal critical production interval to obtain a binocular dynamic image; based on the binocular disparity of the binocular dynamic image, obtain the three-dimensional dynamic image of the abnormal critical production interval; identify the product contour live data and the machine contour live data of the abnormal critical production interval from the three-dimensional dynamic image; Analyze the product contour live data and the machine contour live data to obtain the processed area position information of the product and the machine action orientation and amplitude information in the abnormal critical production interval; based on the processed area position information of the product, judge whether the product is processed in its own preset area, if not, then judge that a product transportation anomaly event occurs in the abnormal critical production interval, if so, judge that the abnormal critical production interval does not have a product transportation anomaly event; based on the machine action orientation and amplitude information, judge whether the machine performs a processing action with a preset orientation and amplitude on the product, if not, then judge that a machine action anomaly event occurs in the abnormal critical production interval, if so, judge that no machine action anomaly event occurs in the abnormal critical production interval.

5. The workshop production process control method according to claim 4, wherein: Obtain the production data of each key production interval on the production line inside the workshop, analyze the production data to obtain the product processing attribute information of each key production interval; perform an association process on the product processing attribute information of all key production intervals to identify an abnormal critical production interval with inconsistent processing progress, including: Based on the position information of each key production interval on the production line inside the workshop, obtain the production data of each key production interval from the workshop cloud; wherein, the production data includes the processing time change data of the key production interval for the product; compare the production data with the single product processing reference time corresponding to the key production interval to obtain the processing progress attribute information of the key production interval for the product; Based on the processing sequence of products in all key production intervals, the processing progress attribute information of products in all key production intervals is time-correlated and abnormal key production intervals with inconsistent processing progress are identified; where inconsistent processing progress occurs, it means that the product processing progress lags behind and the product cannot be delivered to the next adjacent key production interval within the preset time range.

6. The workshop production process control method according to claim 5, characterized in that: Compare the production data with the benchmark processing time of a single product corresponding to the key production interval to obtain the processing progress attribute information of the key production interval for the product, including: Step S1, assume there are n pieces of actual production data corresponding to the critical production interval, and the actual production time of the i-th piece is T i , where i is an integer greater than or equal to 1 and less than or equal to n. Then the actual average production time of the critical production interval is: In the above formula (1), is the actual average production time-consuming of the key production interval; In step S2, assuming that among the n pieces of actual production data, piece A belongs to the spring season, piece B belongs to the summer season, piece C belongs to the autumn season, and piece D belongs to the winter season, then the actual production time of the key production interval is: In the above formula (2), T is the actual production time of the key production interval, α and β are preset adjustment coefficients, and their values are both greater than 0 and less than 1, and the sum of α and β is 1. a, b, c, and d are the numbers of the data corresponding to spring, summer, autumn, and winter respectively, and their values are all integers greater than or equal to 1 and less than or equal to the total amount of seasonal data corresponding to each season, T a is the actual production time of the data corresponding to the a-th spring, T b is the actual production time of the data corresponding to the b-th summer, T c is the actual production time of the data corresponding to the c-th autumn, T d is the actual production time of the data corresponding to the d-th winter; Step S3: Assume that the processing reference time for a single product m is t m , then the processing progress attribute information of the corresponding product is as follows: In the above formula (3), K m is the processing progress attribute information of the corresponding product, M is the total type of a single product produced in the key production interval, and m is an integer greater than or equal to 1 and less than or equal to M.

7. The workshop production process control method according to claim 4, characterized in that: When a product transportation abnormality event occurs in the abnormal critical production interval, the product transportation position is adjusted based on the transportation obstacle information of the product in the abnormal critical production interval; when a machine motion abnormality event occurs in the abnormal critical production interval, the motion parameter adjustment operation of the processing machine is performed based on the motion trajectory information of the processing machine in the abnormal critical production interval, including: When a product transportation abnormality event occurs in the abnormal critical production section, the product is adjusted in transportation position with corresponding orientation and displacement based on the deviation between the actual transportation route of the product in the abnormal critical production section and the preset reference transportation route; When an abnormal machine motion event occurs in the abnormal critical production interval, the motion parameters of the processing machine are adjusted in corresponding directions and amplitudes based on the trajectory deviation between the actual motion trajectory of the processing machine in the abnormal critical production interval and the preset standard motion trajectory.

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