CN116502834A - Workshop intelligent management method and system based on digitization - Google Patents
Workshop intelligent management method and system based on digitization Download PDFInfo
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Abstract
The invention relates to the technical field of workshop efficiency management, and discloses a digital workshop intelligent management system based on people and divided from work to work, which comprises the following steps: the method comprises the steps of calculating the processing residual time and the workload of responsible persons of each working procedure according to the processing speed and the residual processing quantity of a die, intelligently calculating the completion time of the die, sequencing processing teams, transferring processed products to a lower-level processing working section according to the sequence by the processing teams, and automatically and intelligently alarming or delaying each processing working procedure to remind follow-up. The invention can solve the problem of low die processing connection efficiency and intelligently count the efficiency of each processing link, and reduce delay guidance and improve the realization efficiency.
Description
Technical Field
The invention relates to the technical field of workshop efficiency management, in particular to a workshop intelligent management method and system based on digitalization.
Background
Along with the development of economy, industrial production lines start to develop vigorously in various areas, and the increase of the number of factories solves a large number of employment problems and provides huge productivity for society.
The current factory workshop mainly utilizes a pipelining processing assembly mode to assemble products, the same workshop can be divided into different working sections, the different working sections are divided into different groups, each working section corresponds to an assembly process of a product, and the groups under the same working section execute the same assembly process. When the products are transported in the current working sections, the processed semi-finished products are sequentially transported to each group of the lower working section by the upper working section, and at the moment, the assembly speed of each group is not considered, so that semi-finished products are backlogged in some groups, and the situation that the semi-finished products are not assembled in some groups exists, and the assembly and transportation mode has the problem of low assembly efficiency.
Disclosure of Invention
The invention provides a workshop intelligent management method and system based on digitization, and mainly aims to solve the problem that an assembly transfer mode is low in assembly efficiency.
In order to achieve the above purpose, the invention provides a workshop intelligent management method based on digitization, which comprises the following steps:
extracting a current assembly working section from a pre-constructed digital working section model, and identifying a lower assembly working section of the current assembly working section;
sequentially calculating the product assembly speed and the residual product quantity to be assembled of each assembly team in the lower assembly working section;
Calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled;
obtaining the product transfer time length of the assembly team, and calculating the assembly net time length of the assembly team according to the assembly residual time length and the product transfer time length by utilizing a pre-constructed assembly net time length formula, wherein the assembly net time length formula is as follows:
t ij ＝t is -t iz
wherein; t is t ij Representation ofThe net assembly time length, t, of the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Representing a product transfer duration of an i-th assembly team;
sequencing the transfer priorities of the assembly teams according to the assembly net residual time of each assembly teams to obtain a transfer teams sequence;
and transferring the assembled product of the current assembly working section to the lower assembly working section according to the transferring team sequence, so as to complete the intelligent workshop management based on digitalization.
Optionally, the calculating, in turn, the product assembling speed and the remaining product to be assembled of each assembling team in the lower-level assembling section includes:
acquiring the real-time assembly speed of each assembly team in the lower assembly working section, and drawing an assembly speed-time graph according to the real-time assembly speed;
Acquiring current assembly time, and extracting the product assembly speed from the assembly speed-time curve graph according to the current assembly time;
and obtaining the original product quantity to be assembled of the assembly team, and calculating the residual product quantity to be assembled of the assembly team according to the original product quantity to be assembled and the assembly speed-time curve chart.
Optionally, the calculating the remaining amount of the products to be assembled of the assembly team according to the original amount of the products to be assembled and the assembly speed-time graph includes:
acquiring original assembly time, and intercepting a current assembly period in the assembly speed-time curve chart according to the original assembly time and the current assembly time;
extracting an assembly speed curve corresponding to the current assembly period from the assembly speed-time curve;
calculating the current accumulated assembly quantity by utilizing a pre-constructed current assembly integral formula according to the current assembly period and the assembly speed curve;
and calculating the quantity of the remaining products to be assembled according to the original quantity of the products to be assembled and the current accumulated assembled quantity.
Optionally, the current assembly integration formula is as follows:
wherein,,representing the current accumulated fit-up amount of the ith fit-up team during the original fit-up time and the current fit-up time, t iy Representing the original assembly time, t, of the ith assembly team id Representing the current assembly time, v, of the ith assembly team i And the assembly speed curve value of the ith assembly team between the original assembly time and the current assembly time is represented.
Optionally, the calculating the assembly remaining time of the assembly team according to the product assembly speed and the remaining product to be assembled includes:
extracting a current assembly speed corresponding to the current assembly time from the assembly speed-time graph;
extracting a current curve slope of the assembly speed-time curve graph at a current assembly time point;
judging whether the slope of the current curve is greater than zero;
if the current curve slope is greater than zero, extending an assembly speed-time curve in the assembly speed-time curve graph according to the curve slope to obtain an assembly increment-time curve segment;
calculating the predicted time length of the accumulated assembling quantity corresponding to the assembling acceleration-time curve section, which is equal to the quantity of the residual product to be assembled, and taking the predicted time length as the assembling residual time length;
if the slope of the current curve is not greater than zero, extending an assembly speed-time curve in the assembly speed-time curve graph according to the current assembly speed to obtain an assembly constant speed-time curve segment;
Calculating the predicted time length of the accumulated assembling quantity corresponding to the assembling constant speed-time curve section, which is equal to the quantity of the residual product to be assembled, and taking the predicted time length as the assembling residual time length.
Optionally, the calculating the cumulative assembling amount corresponding to the assembling acceleration-time curve segment is equal to the predicted duration of the remaining product to be assembled, including:
calculating a fitting amount-time function according to the slope of the current curve by using a pre-constructed fitting amount prediction formula;
extracting the speed-increasing prediction time of which the function quantity of the assembly quantity-time function is equal to the quantity of the residual product to be assembled;
and calculating the predicted time length according to the current assembly time and the speed-increasing predicted time.
Optionally, the assembly quantity prediction formula is as follows:
wherein s is zy Function value representing the function of the amount of the fitting-time, t if Represents the speed-up prediction time, V id Representing the current assembly speed, k representing the current curve slope, and t representing time.
Optionally, the obtaining the product transferring duration of the assembly team includes:
acquiring a transfer starting position of the assembled product and a transfer receiving position of the assembly team;
calculating the transfer distance of the assembly team according to the transfer starting position and the transfer receiving position;
And acquiring the transfer speed of the current assembly working section, and calculating the product transfer duration according to the transfer speed and the transfer distance.
Optionally, the sorting the assembly teams according to the assembly net remaining time of each assembly teams to obtain a transfer teams sequence includes:
sequencing the assembly net surplus time length of each assembly team according to the sequence from small to large to obtain a net surplus time length sequence;
and sequencing the assembly groups according to the positions of each assembly group in the lower assembly working section in the net surplus time duration sequence to obtain the transfer group sequence.
In order to solve the above problems, the present invention further provides a workshop intelligent management system based on digitization, the system comprising:
the assembly residual time length calculation module is used for extracting a current assembly working section from a pre-constructed digital working section model and identifying a lower assembly working section of the current assembly working section; sequentially calculating the product assembly speed and the residual product quantity to be assembled of each assembly team in the lower assembly working section; calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled;
The assembly net surplus time length calculation module is used for obtaining the product transfer time length of the assembly team, and calculating the assembly net surplus time length of the assembly team according to the assembly residual time length and the product transfer time length by utilizing a pre-constructed assembly net surplus time length formula, wherein the assembly net surplus time length formula is as follows:
t ij ＝t is -t iz
wherein; t is t ij Indicating the net remaining length of assembly, t, for the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Representing a product transfer duration of an i-th assembly team;
the assembly team ordering module is used for ordering the transfer priorities of the assembly teams according to the assembly net residual time of each assembly team to obtain a transfer team sequence;
and the assembled product transferring module is used for transferring the assembled product of the current assembly working section to the lower assembly working section according to the transferring team sequence.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to implement the digital-based plant intelligent management method described above.
In order to solve the above-mentioned problems, the present invention also provides a computer-readable storage medium having at least one instruction stored therein, the at least one instruction being executed by a processor in an electronic device to implement the above-mentioned digital-based workshop intelligent management method.
Compared with the background art, the method comprises the following steps: the method comprises the steps of extracting a current assembly working section from a pre-constructed digital working section model to obtain an initial working section for starting assembly transfer, analyzing the assembly condition of each assembly working section in a lower assembly working section to determine the transfer mode, firstly obtaining the product assembly speed and the residual product quantity to be assembled of each assembly working section in the process of analyzing the assembly condition, calculating the assembly residual time of the assembly working section according to the product assembly speed and the residual product quantity to be assembled, calculating the assembly residual time of the assembly working section according to the pre-constructed assembly residual time formula due to the fact that the transfer time exists in the transfer process, and calculating the assembly residual time of the assembly working section according to the assembly residual time and the product transfer time, wherein the transfer priority ordering of the assembly working section can be carried out according to the assembly residual time of each assembly working section to obtain a transfer working section sequence, and finally transferring the assembled product of the current assembly working section to the lower assembly working section according to the transfer working section sequence. Therefore, the workshop intelligent management method, the system, the electronic equipment and the computer readable storage medium based on the digitization can solve the problem of low assembly efficiency in an assembly transfer mode.
Drawings
FIG. 1 is a flowchart of a workshop intelligent management method based on digitization according to an embodiment of the invention;
FIG. 2 is a functional block diagram of a workshop intelligent management system based on digitization according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the workshop intelligent management method based on digitization according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a workshop intelligent management method based on digitization. The execution subject of the digitalized workshop intelligent management method includes, but is not limited to, at least one of a server, a terminal and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the digital-based workshop intelligent management method may be performed by software or hardware installed in a terminal device or a server device. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Example 1:
referring to fig. 1, a flowchart of a workshop intelligent management method based on digitization according to an embodiment of the invention is shown. In this embodiment, the workshop intelligent management method based on digitization includes:
s1, extracting a current assembly working section from a pre-constructed digital working section model, and identifying a lower assembly working section of the current assembly working section.
The digital section model is a digital model for displaying the positions of each section and each team position in the section on the workshop production line. The current assembly section is one section in a factory workshop production line, for example: the sections in the air conditioner production plant can be divided into a part installation section, a product welding section, a line connection section, a product assembling section, a product packaging section and the like. The assembled product is a semi-finished product which is already finished in the current assembly section, for example: when the front assembly working section is a product welding working section, the assembled product refers to the welded product, and the product is waited to be transported to the next working section of the product welding working section for further assembly processing.
It will be appreciated that when the product order delivery time is received, a large schedule time and a small schedule time need to be set according to the time characteristics of each section, for example: when the product order is mold processing, the large schedule time may be a cut-off time of mold design, a cut-off time of inner film material purchase, a cut-off time of mold frame material purchase, a cut-off time of component processing, a mold frame processing cut-off time, a mold loading cut-off time, a mold testing cut-off time, etc., and when the large schedule time is a mold frame processing cut-off time, the small schedule time may be: the die carrier rough machining cut-off time, the die carrier finish machining cut-off time and the like. And determining the duration of each processing section through the size schedule time.
Further, the lower assembly section refers to a next stage section of the current assembly section, for example: the current assembly working section is a product welding working section, wiring is needed after welding is finished, and the lower assembly working section of the product welding working section is a line connection working section.
S2, sequentially calculating the product assembly speed of each assembly team in the lower assembly working section and the quantity of the remaining products to be assembled.
As will be appreciated, the assembly team refers to the individual assembly team in the subordinate assembly station, such as: in order to improve the production efficiency, the product welding sections can be further divided into a first welding group, a second welding group and a third welding group. The product assembly speed refers to the amount of product assembly completed per unit time per assembly team, for example: the first welding team can weld 5 air conditioners in 1 minute, and the product assembly speed of the first welding team is 5 per minute.
It should be appreciated that the remaining amount of product to be assembled refers to the amount of product that arrives at the assembly team and has not yet been assembled.
In the embodiment of the present invention, the calculating, in order, the product assembly speed and the remaining product to be assembled of each assembly team in the lower assembly working section includes:
Acquiring the real-time assembly speed of each assembly team in the lower assembly working section, and drawing an assembly speed-time graph according to the real-time assembly speed;
acquiring current assembly time, and extracting the product assembly speed from the assembly speed-time curve graph according to the current assembly time;
and obtaining the original product quantity to be assembled of the assembly team, and calculating the residual product quantity to be assembled of the assembly team according to the original product quantity to be assembled and the assembly speed-time curve chart.
It is understood that the assembly speed-time graph refers to constructing a two-dimensional coordinate system with time as the abscissa scale value and assembly speed as the ordinate scale value. The original amount of the product to be assembled refers to the amount of the semi-finished products that need to be assembled after the assembly team performs product transfer last time, for example: the number of semi-finished products waiting for welding, which are transferred last time by the first welding team, is 100, and 10 products remain at the moment, and the number of the original products to be assembled is 110. The remaining amount of product to be assembled refers to the number of semi-finished products that the assembly team needs to assemble at the current assembly time, for example: the original amount of the product to be assembled is 110, the real-time assembling speed is consistent and maintained at 10 pieces/min, and after 5 minutes, the amount of the remaining product to be assembled is 60 pieces.
In the embodiment of the present invention, the calculating the remaining product to be assembled of the assembly team according to the original product to be assembled and the assembly speed-time graph includes:
acquiring original assembly time, and intercepting a current assembly period in the assembly speed-time curve chart according to the original assembly time and the current assembly time;
extracting an assembly speed curve corresponding to the current assembly period from the assembly speed-time curve;
calculating the current accumulated assembly quantity by utilizing a pre-constructed current assembly integral formula according to the current assembly period and the assembly speed curve;
and calculating the quantity of the remaining products to be assembled according to the original quantity of the products to be assembled and the current accumulated assembled quantity.
It is understood that the initial assembly time is the time for counting the amount of the product to be assembled, and the current assembly time is a time period between the initial assembly time and the current assembly time.
In the embodiment of the present invention, the current assembly integral formula is as follows:
wherein,,representing the current accumulated fit-up amount of the ith fit-up team during the original fit-up time and the current fit-up time, t iy Representing the original assembly time, t, of the ith assembly team id Representing the current assembly time, v, of the ith assembly team i And the assembly speed curve value of the ith assembly team between the original assembly time and the current assembly time is represented.
It can be explained that when the assembly speed curve represents the assembly speed and the abscissa represents time, the projected area (integral) of the curve on the abscissa is the current accumulated assembly amount.
S3, calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled.
It is understood that the assembly remaining time period refers to a time period during which the assembly team completes the assembly of the remaining amount of product to be assembled.
In the embodiment of the present invention, the calculating the assembly remaining time of the assembly team according to the product assembly speed and the remaining product to be assembled includes:
extracting a current assembly speed corresponding to the current assembly time from the assembly speed-time graph;
extracting a current curve slope of the assembly speed-time curve graph at a current assembly time point;
judging whether the slope of the current curve is greater than zero;
if the current curve slope is greater than zero, extending an assembly speed-time curve in the assembly speed-time curve graph according to the curve slope to obtain an assembly increment-time curve segment;
Calculating the predicted time length of the accumulated assembling quantity corresponding to the assembling acceleration-time curve section, which is equal to the quantity of the residual product to be assembled, and taking the predicted time length as the assembling residual time length;
if the slope of the current curve is not greater than zero, extending an assembly speed-time curve in the assembly speed-time curve graph according to the current assembly speed to obtain an assembly constant speed-time curve segment;
calculating the predicted time length of the accumulated assembling quantity corresponding to the assembling constant speed-time curve section, which is equal to the quantity of the residual product to be assembled, and taking the predicted time length as the assembling residual time length.
It should be appreciated that when the current curve slope is greater than zero, indicating that the current assembly speed of the assembly team is the up-phase, the assembly speed of the assembly team in the future may be predicted to be an increment that keeps the slope unchanged, i.e., the assembly speed curve is a ray having a slope that is the current curve slope in the future. And when the slope of the current curve is equal to zero, representing that the current assembly speed of the assembly team is in a constant stage, and when the slope of the current curve is smaller than zero, representing that the current assembly speed of the assembly team is in a descending stage, wherein in order to ensure that the assembly team does not have the condition of no semi-product assembly in the future, the current assembly speed is taken as the future assembly speed.
It can be appreciated that when the assembly team is a mold finishing team, the mold finishing completion time can be intelligently calculated according to the mold processing speed of the mold finishing team and the remaining time length of the remaining waiting processing amount for the mold finishing process.
Further, for example: the slope of the current curve is 2, and the current assembly speed is 10 pieces/min, so that the assembly speed after one minute is 12 pieces/min, and the assembly speed after two minutes is 14 pieces/min; the slope of the current curve is 0, and the current assembly speed is 10 pieces/min, so that the assembly speed after one minute is 10 pieces/min, and the assembly speed after two minutes is still 10 pieces/min; the current slope of the curve is-1, and the current assembly speed is 10 pieces/min, the assembly speed after one minute is 9 pieces/min, the assembly speed after two minutes is 8 pieces/min, and so on.
In the embodiment of the present invention, the calculating the predicted time length for the accumulated assembling quantity corresponding to the assembling acceleration-time curve segment to be equal to the remaining product quantity to be assembled includes:
calculating a fitting amount-time function according to the slope of the current curve by using a pre-constructed fitting amount prediction formula;
Extracting the speed-increasing prediction time of which the function quantity of the assembly quantity-time function is equal to the quantity of the residual product to be assembled;
it will be appreciated that the fit-time function represents a value of the change in fit of the fit team over time. The speed-up prediction time refers to a time point at which the function quantity of the assembly quantity-time function is equal to the quantity of the remaining product to be assembled.
And calculating the predicted time length according to the current assembly time and the speed-increasing predicted time.
Further, the predicted time period indicates a time period during which the remaining amount of the product to be assembled is completely assembled at the predicted assembly speed. And subtracting the current assembly time and the speed-increasing prediction time when the current assembly time and the speed-increasing prediction time are obtained, so as to obtain the prediction duration.
In the embodiment of the invention, the assembly quantity prediction formula is as follows:
wherein s is zy Representing the fit-time functionFunction value t of (2) if Represents the speed-up prediction time, V id Representing the current assembly speed, k representing the current curve slope, and t representing time.
Further, the same principle as the calculation of the current accumulated assembly amount, the current assembly speed plus the product of the slope of the current curve and time may represent the value of the assembly speed at the time t. And integrating to obtain the assembly quantity, and obtaining the predicted time length when the assembly quantity calculated by accumulated prediction is equal to the quantity of the remaining products to be assembled.
S4, acquiring the product transfer time length of the assembly team, and calculating the assembly net time length of the assembly team according to the assembly residual time length and the product transfer time length by utilizing a pre-constructed assembly net time length formula.
Further, since the distances of different assembly teams from the current assembly station are different, for example: in carrying out the transportation on the line, the distances between different assembly teams and the transport starting position of the current assembly working section are different, and the general transport speed is constant, so that the transport time length needs to be subtracted.
In detail, the assembly net remaining time formula is as follows:
t ij ＝t is -t iz
wherein; t is t ij Indicating the net remaining length of assembly, t, for the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Indicating the product transfer duration of the ith assembly team.
In the embodiment of the present invention, the obtaining the product transferring duration of the assembly team includes:
acquiring a transfer starting position of the assembled product and a transfer receiving position of the assembly team;
calculating the transfer distance of the assembly team according to the transfer starting position and the transfer receiving position;
and acquiring the transfer speed of the current assembly working section, and calculating the product transfer duration according to the transfer speed and the transfer distance.
S5, sorting the transfer priorities of the assembly groups according to the assembly net residual time of each assembly group to obtain a transfer group sequence.
The order of the transfer team may be interpreted to indicate a priority order of the assembly transfer required, the earlier the ordering, the higher the priority of the diversion.
In the embodiment of the present invention, the sorting the transfer priorities of the assembly teams according to the assembly net remaining time of each assembly teams to obtain a transfer teams sequence includes:
sequencing the assembly net surplus time length of each assembly team according to the sequence from small to large to obtain a net surplus time length sequence;
and sequencing the assembly groups according to the positions of each assembly group in the lower assembly working section in the net surplus time duration sequence to obtain the transfer group sequence.
It can be appreciated that during the process of transferring the semi-finished product to the next assembly section, each assembly team of the next assembly section can be ordered in processing capacity, and the semi-finished product is preferentially transported to the assembly team with larger residual assembly capacity (i.e. the assembly team has smaller assembly net residual time), and when the adjacent materials in each assembly team are completely assembled, automatic intelligent alarm is carried out to remind of timely transfer.
S6, transferring the assembled product of the current assembly working section to the lower assembly working section according to the transferring team sequence, and completing workshop intelligent management based on digitalization.
Further, the assembled product of the current assembly station may be transported to the subordinate assembly station in units of transport capacity, for example: the unit transfer amount is 100 pieces per car, and 100 pieces can be transferred to the team with the highest priority in the lower-level assembly working section at one time.
It will be appreciated that the required components can be transported synchronously during the transport of the assembled product.
Compared with the background art, the method comprises the following steps: the method comprises the steps of extracting a current assembly working section from a pre-constructed digital working section model to obtain an initial working section for starting assembly transfer, analyzing the assembly condition of each assembly working section in a lower assembly working section to determine the transfer mode, firstly obtaining the product assembly speed and the residual product quantity to be assembled of each assembly working section in the process of analyzing the assembly condition, calculating the assembly residual time of the assembly working section according to the product assembly speed and the residual product quantity to be assembled, calculating the assembly residual time of the assembly working section according to the pre-constructed assembly residual time formula due to the fact that the transfer time exists in the transfer process, and calculating the assembly residual time of the assembly working section according to the assembly residual time and the product transfer time, wherein the transfer priority ordering of the assembly working section can be carried out according to the assembly residual time of each assembly working section to obtain a transfer working section sequence, and finally transferring the assembled product of the current assembly working section to the lower assembly working section according to the transfer working section sequence. Therefore, the workshop intelligent management method, the system, the electronic equipment and the computer readable storage medium based on the digitization can solve the problem of low assembly efficiency in an assembly transfer mode.
Example 2:
FIG. 2 is a functional block diagram of a system for intelligent workshop management based on digitization according to an embodiment of the present invention.
The digital-based workshop intelligent management system 100 of the invention can be installed in electronic equipment. Depending on the functions implemented, the digital-based workshop intelligent management system 100 may include an assembly remaining length calculation module 101, an assembly net remaining length calculation module 102, an assembly team ordering module 103, and an assembly product diversion module 104. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
The assembly remaining time calculation module 101 is configured to extract a current assembly working section from a pre-constructed digital working section model, and identify a next assembly working section of the current assembly working section; sequentially calculating the product assembly speed and the residual product quantity to be assembled of each assembly team in the lower assembly working section; calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled;
The assembly net remaining time calculation module 102 is configured to obtain a product transfer time of the assembly team, and calculate an assembly net remaining time of the assembly team according to the assembly remaining time and the product transfer time by using a pre-constructed assembly net remaining time formula, where the assembly net remaining time formula is as follows:
t ij ＝t is -t iz
wherein; t is t ij Indicating the net remaining length of assembly, t, for the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Representing a product transfer duration of an i-th assembly team;
the assembly team ordering module 103 is configured to order the transfer priorities of the assembly teams according to the assembly net remaining time of each assembly team, so as to obtain a transfer team sequence;
the assembled product transfer module 104 is configured to transfer the assembled product of the current assembly station to the subordinate assembly station according to the transfer team sequence.
In detail, the modules in the digitalized-based workshop intelligent management system 100 in the embodiment of the present invention use the same technical means as the digitalized-based workshop intelligent management method described in fig. 1, and can produce the same technical effects, which are not described herein.
Example 3:
fig. 3 is a schematic structural diagram of an electronic device for implementing a workshop intelligent management method based on digitization according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as a digitally based smart workshop management program.
The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only for storing application software installed in the electronic device 1 and various types of data, such as codes based on a digitized shop intelligent management program, but also for temporarily storing data that has been output or is to be output.
The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects the respective components of the entire electronic device using various interfaces and lines, executes programs or modules stored in the memory 11 (for example, a shop intelligent management program based on digitization, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device 1 and process the data.
The bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
Fig. 3 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 10 through a power management system, so as to perform functions of charge management, discharge management, and power consumption management through the power management system. The power supply may also include one or more of any of a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
Further, the electronic device 1 may also comprise a network interface, optionally the network interface may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used for establishing a communication connection between the electronic device 1 and other electronic devices.
The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The digitised workshop wisdom management program stored in the memory 11 of the electronic device 1 is a combination of instructions which, when executed in the processor 10, enable:
extracting a current assembly working section from a pre-constructed digital working section model, and identifying a lower assembly working section of the current assembly working section;
sequentially calculating the product assembly speed and the residual product quantity to be assembled of each assembly team in the lower assembly working section;
Calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled;
obtaining the product transfer time length of the assembly team, and calculating the assembly net time length of the assembly team according to the assembly residual time length and the product transfer time length by utilizing a pre-constructed assembly net time length formula, wherein the assembly net time length formula is as follows:
t ij ＝t is -t iz
wherein; t is t ij Indicating the net remaining length of assembly, t, for the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Representing a product transfer duration of an i-th assembly team;
sequencing the transfer priorities of the assembly teams according to the assembly net residual time of each assembly teams to obtain a transfer teams sequence;
and transferring the assembled product of the current assembly working section to the lower assembly working section according to the transferring team sequence, so as to complete the intelligent workshop management based on digitalization. Specifically, the specific implementation method of the above instruction by the processor 10 may refer to descriptions of related steps in the corresponding embodiments of fig. 1 to 2, which are not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a Read-only memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
extracting a current assembly working section from a pre-constructed digital working section model, and identifying a lower assembly working section of the current assembly working section;
sequentially calculating the product assembly speed and the residual product quantity to be assembled of each assembly team in the lower assembly working section;
calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled;
obtaining the product transfer time length of the assembly team, and calculating the assembly net time length of the assembly team according to the assembly residual time length and the product transfer time length by utilizing a pre-constructed assembly net time length formula, wherein the assembly net time length formula is as follows:
t ij ＝t is -t iz
wherein; t is t ij Indicating the net remaining length of assembly, t, for the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Representing a product transfer duration of an i-th assembly team;
sequencing the transfer priorities of the assembly teams according to the assembly net residual time of each assembly teams to obtain a transfer teams sequence;
And transferring the assembled product of the current assembly working section to the lower assembly working section according to the transferring team sequence, so as to complete the intelligent workshop management based on digitalization.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, system and method may be implemented in other manners. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. The workshop intelligent management method based on the digitization is characterized by comprising the following steps of:
extracting a current assembly working section from a pre-constructed digital working section model, and identifying a lower assembly working section of the current assembly working section;
sequentially calculating the product assembly speed and the residual product quantity to be assembled of each assembly team in the lower assembly working section;
calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled;
obtaining the product transfer time length of the assembly team, and calculating the assembly net time length of the assembly team according to the assembly residual time length and the product transfer time length by utilizing a pre-constructed assembly net time length formula, wherein the assembly net time length formula is as follows:
t ij ＝t is -t iz
Wherein; t is t ij Indicating the net remaining length of assembly, t, for the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Representing a product transfer duration of an i-th assembly team;
sequencing the transfer priorities of the assembly teams according to the assembly net residual time of each assembly teams to obtain a transfer teams sequence;
and transferring the assembled product of the current assembly working section to the lower assembly working section according to the transferring team sequence, so as to complete the intelligent workshop management based on digitalization.
2. The digital-based workshop intelligent management method of claim 1, wherein the sequentially calculating the product assembly speed and the remaining amount of product to be assembled for each assembly team in the subordinate assembly section comprises:
acquiring the real-time assembly speed of each assembly team in the lower assembly working section, and drawing an assembly speed-time graph according to the real-time assembly speed;
acquiring current assembly time, and extracting the product assembly speed from the assembly speed-time curve graph according to the current assembly time;
and obtaining the original product quantity to be assembled of the assembly team, and calculating the residual product quantity to be assembled of the assembly team according to the original product quantity to be assembled and the assembly speed-time curve chart.
3. The digital based workshop intelligent management method of claim 2, wherein the calculating the remaining amount of product to be assembled of the assembly team from the original amount of product to be assembled and the assembly speed-time graph comprises:
acquiring original assembly time, and intercepting a current assembly period in the assembly speed-time curve chart according to the original assembly time and the current assembly time;
extracting an assembly speed curve corresponding to the current assembly period from the assembly speed-time curve;
calculating the current accumulated assembly quantity by utilizing a pre-constructed current assembly integral formula according to the current assembly period and the assembly speed curve;
and calculating the quantity of the remaining products to be assembled according to the original quantity of the products to be assembled and the current accumulated assembled quantity.
4. The digital based plant intelligent management method according to claim 3, wherein the current assembly point formula is as follows:
wherein,,representing the current accumulated fit-up amount of the ith fit-up team during the original fit-up time and the current fit-up time, t iy Representing the original assembly time, t, of the ith assembly team id Representing the current assembly time, v, of the ith assembly team i And the assembly speed curve value of the ith assembly team between the original assembly time and the current assembly time is represented.
5. The digital workshop intelligent management method according to claim 2, wherein calculating the assembly remaining time of the assembly team according to the product assembly speed and the remaining product to be assembled comprises:
extracting a current assembly speed corresponding to the current assembly time from the assembly speed-time graph;
extracting a current curve slope of the assembly speed-time curve graph at a current assembly time point;
judging whether the slope of the current curve is greater than zero;
if the current curve slope is greater than zero, extending an assembly speed-time curve in the assembly speed-time curve graph according to the curve slope to obtain an assembly increment-time curve segment;
calculating the predicted time length of the accumulated assembling quantity corresponding to the assembling acceleration-time curve section, which is equal to the quantity of the residual product to be assembled, and taking the predicted time length as the assembling residual time length;
if the slope of the current curve is not greater than zero, extending an assembly speed-time curve in the assembly speed-time curve graph according to the current assembly speed to obtain an assembly constant speed-time curve segment;
Calculating the predicted time length of the accumulated assembling quantity corresponding to the assembling constant speed-time curve section, which is equal to the quantity of the residual product to be assembled, and taking the predicted time length as the assembling residual time length.
6. The method of claim 5, wherein calculating a cumulative fit amount corresponding to the fit acceleration-time curve segment is equal to a predicted time period for the remaining amount of product to be fitted comprises:
calculating a fitting amount-time function according to the slope of the current curve by using a pre-constructed fitting amount prediction formula;
extracting the speed-increasing prediction time of which the function quantity of the assembly quantity-time function is equal to the quantity of the residual product to be assembled;
and calculating the predicted time length according to the current assembly time and the speed-increasing predicted time.
7. The digital based intelligent workshop management method of claim 6, wherein the assembly quantity prediction formula is as follows:
wherein s is zy Function value representing the function of the amount of the fitting-time, t if Represents the speed-up prediction time, V id Indicating the current assembly speed ， k represents the current curve slope and t represents time.
8. The method for digitally based intelligent management of a plant of claim 2, wherein said obtaining a product diversion duration of said assembly team comprises:
Acquiring a transfer starting position of the assembled product and a transfer receiving position of the assembly team;
calculating the transfer distance of the assembly team according to the transfer starting position and the transfer receiving position;
and acquiring the transfer speed of the current assembly working section, and calculating the product transfer duration according to the transfer speed and the transfer distance.
9. The method of claim 2, wherein said sequencing the assembly teams to obtain a sequence of diversion teams based on the assembly net time remaining for each of the assembly teams comprises:
sequencing the assembly net surplus time length of each assembly team according to the sequence from small to large to obtain a net surplus time length sequence;
and sequencing the assembly groups according to the positions of each assembly group in the lower assembly working section in the net surplus time duration sequence to obtain the transfer group sequence.
10. A digital-based workshop intelligent management system, the system comprising:
the assembly residual time length calculation module is used for extracting a current assembly working section from a pre-constructed digital working section model and identifying a lower assembly working section of the current assembly working section; sequentially calculating the product assembly speed and the residual product quantity to be assembled of each assembly team in the lower assembly working section; calculating the assembly residual time length of the assembly team according to the product assembly speed and the residual product quantity to be assembled;
The assembly net surplus time length calculation module is used for obtaining the product transfer time length of the assembly team, and calculating the assembly net surplus time length of the assembly team according to the assembly residual time length and the product transfer time length by utilizing a pre-constructed assembly net surplus time length formula, wherein the assembly net surplus time length formula is as follows:
t ij ＝t is -t iz
wherein; t is t ij Indicating the net remaining length of assembly, t, for the ith assembly team is Indicating the remaining assembly time period, t, of the ith assembly team iz Representing a product transfer duration of an i-th assembly team;
the assembly team ordering module is used for ordering the transfer priorities of the assembly teams according to the assembly net residual time of each assembly team to obtain a transfer team sequence;
and the assembled product transferring module is used for transferring the assembled product of the current assembly working section to the lower assembly working section according to the transferring team sequence.
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Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06126333A (en) * | 1992-10-22 | 1994-05-10 | Mitsubishi Heavy Ind Ltd | Method for controlling speed of continuous steel plate processing line |
| CN104657826A (en) * | 2015-02-15 | 2015-05-27 | 百度在线网络技术（北京）有限公司 | Resource allocating method and device |
| JP2018032365A (en) * | 2016-08-25 | 2018-03-01 | ナカシャ クリエイテブ株式会社 | Real time computer integrated production system |
| CN109782699A (en) * | 2017-11-14 | 2019-05-21 | 迅得机械股份有限公司 | Production scheduling monitoring method |
| CN111241620A (en) * | 2020-01-09 | 2020-06-05 | 中交二公局东萌工程有限公司 | Construction period prediction method and construction method based on tunnel engineering progress slope diagram |
| CN111381950A (en) * | 2020-03-05 | 2020-07-07 | 南京大学 | Task scheduling method and system based on multiple copies for edge computing environment |
| CN111880502A (en) * | 2020-07-30 | 2020-11-03 | 上海数策软件股份有限公司 | Factory equipment preventive maintenance scheduling system and method based on delivery satisfaction |
| CN111882144A (en) * | 2020-06-10 | 2020-11-03 | 中国人民解放军海军航空大学 | Airplane guarantee procedure parallel scheduling method considering resource transfer |
| CN112650187A (en) * | 2021-01-22 | 2021-04-13 | 北京理工大学 | Workshop scheduling method, device and system |
| CN114249057A (en) * | 2021-11-25 | 2022-03-29 | 苏州易泰勒电子科技有限公司 | Electronic tag picking management method for man-machine cooperation |
| CN114399256A (en) * | 2022-01-14 | 2022-04-26 | 昊链(中山)科技有限责任公司 | Material calling method, device, equipment and storage medium based on assembly line |
| CN115115255A (en) * | 2022-07-13 | 2022-09-27 | 国网浙江省电力有限公司台州供电公司 | Battery replacement station scheduling control method participating in collaborative multi-scene application |
| CN115186945A (en) * | 2021-04-02 | 2022-10-14 | 天津市环智新能源技术有限公司 | Thread cutting dispatching method, thread cutting dispatching system, computer equipment and storage medium |
| CN115860426A (en) * | 2022-12-28 | 2023-03-28 | 龙岩烟草工业有限责任公司 | Task scheduling method and device, material conveying system and storage medium |
-
2023
- 2023-04-10 CN CN202310401681.1A patent/CN116502834B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06126333A (en) * | 1992-10-22 | 1994-05-10 | Mitsubishi Heavy Ind Ltd | Method for controlling speed of continuous steel plate processing line |
| CN104657826A (en) * | 2015-02-15 | 2015-05-27 | 百度在线网络技术（北京）有限公司 | Resource allocating method and device |
| JP2018032365A (en) * | 2016-08-25 | 2018-03-01 | ナカシャ クリエイテブ株式会社 | Real time computer integrated production system |
| CN109782699A (en) * | 2017-11-14 | 2019-05-21 | 迅得机械股份有限公司 | Production scheduling monitoring method |
| CN111241620A (en) * | 2020-01-09 | 2020-06-05 | 中交二公局东萌工程有限公司 | Construction period prediction method and construction method based on tunnel engineering progress slope diagram |
| CN111381950A (en) * | 2020-03-05 | 2020-07-07 | 南京大学 | Task scheduling method and system based on multiple copies for edge computing environment |
| CN111882144A (en) * | 2020-06-10 | 2020-11-03 | 中国人民解放军海军航空大学 | Airplane guarantee procedure parallel scheduling method considering resource transfer |
| CN111880502A (en) * | 2020-07-30 | 2020-11-03 | 上海数策软件股份有限公司 | Factory equipment preventive maintenance scheduling system and method based on delivery satisfaction |
| CN112650187A (en) * | 2021-01-22 | 2021-04-13 | 北京理工大学 | Workshop scheduling method, device and system |
| CN115186945A (en) * | 2021-04-02 | 2022-10-14 | 天津市环智新能源技术有限公司 | Thread cutting dispatching method, thread cutting dispatching system, computer equipment and storage medium |
| CN114249057A (en) * | 2021-11-25 | 2022-03-29 | 苏州易泰勒电子科技有限公司 | Electronic tag picking management method for man-machine cooperation |
| CN114399256A (en) * | 2022-01-14 | 2022-04-26 | 昊链(中山)科技有限责任公司 | Material calling method, device, equipment and storage medium based on assembly line |
| CN115115255A (en) * | 2022-07-13 | 2022-09-27 | 国网浙江省电力有限公司台州供电公司 | Battery replacement station scheduling control method participating in collaborative multi-scene application |
| CN115860426A (en) * | 2022-12-28 | 2023-03-28 | 龙岩烟草工业有限责任公司 | Task scheduling method and device, material conveying system and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| ADZAKPA, KP 等: ""On-line maintenance job scheduling and assignment to resources in distributed systems by heuristic-based optimization"", 《JOURNAL OF INTELLIGENT MANUFACTURING》, vol. 15, no. 2, pages 131 - 140 * |
| 严泽强 等: "一种基于加工匹配度的车间作业调度方法研究", 《世界科技研究与发展》, vol. 2008, no. 03, pages 270 - 274 * |
| 周琪森等: "考虑班组负荷均衡的智能制造车间工序级作业任务排程模型研究", 《制造业自动化》, vol. 40, no. 03, pages 101 - 105 * |
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