CN116339260A - Production time adjustment analysis method and system for flexible manufacturing of black lamp factory - Google Patents
Production time adjustment analysis method and system for flexible manufacturing of black lamp factory Download PDFInfo
- Publication number
- CN116339260A CN116339260A CN202310324620.XA CN202310324620A CN116339260A CN 116339260 A CN116339260 A CN 116339260A CN 202310324620 A CN202310324620 A CN 202310324620A CN 116339260 A CN116339260 A CN 116339260A
- Authority
- CN
- China
- Prior art keywords
- production
- time
- process flow
- flexible
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 266
- 238000004458 analytical method Methods 0.000 title claims abstract description 30
- 238000000034 method Methods 0.000 claims abstract description 172
- 230000008569 process Effects 0.000 claims abstract description 126
- 230000006872 improvement Effects 0.000 claims abstract description 20
- 238000004364 calculation method Methods 0.000 claims description 10
- 230000007704 transition Effects 0.000 claims description 10
- 238000000342 Monte Carlo simulation Methods 0.000 claims description 4
- 239000011159 matrix material Substances 0.000 claims description 4
- 238000004590 computer program Methods 0.000 claims description 3
- 238000003860 storage Methods 0.000 claims description 2
- 238000004886 process control Methods 0.000 abstract description 2
- 238000012545 processing Methods 0.000 description 7
- 238000004891 communication Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- 238000011156 evaluation Methods 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000011990 functional testing Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 208000012826 adjustment disease Diseases 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 239000000872 buffer Substances 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000004836 empirical method Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000036632 reaction speed Effects 0.000 description 1
- 230000011664 signaling Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000000528 statistical test Methods 0.000 description 1
- 238000005309 stochastic process Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- General Factory Administration (AREA)
Abstract
The invention provides a production time adjustment analysis method and system for flexible manufacturing of a black lamp factory, and relates to the field of process control. Comprising the following steps: the method comprises the steps of obtaining the number of machines of the flexible production line and the circulation time of the machines, obtaining production indexes of preset products, each technological process and the production time of each technological process, obtaining the takt time of the products according to the production indexes and the circulation time of the machines, improving each technological process, and observing and recording the production time of each technological process after improvement. According to the invention, the process flow of the preset product is split and integrated, so that the production efficiency of the process flow of the preset product is improved, and meanwhile, the production efficiency of the corresponding preset product can be obtained more intuitively and accurately, so that the production time of the process flow on the flexible production line can be adjusted more accurately.
Description
Technical Field
The invention relates to the field of process control, in particular to a production time adjustment analysis method and system for flexible manufacturing of a black lamp factory.
Background
With the continuous development and progress of the manufacturing industry, it is an continuously improved process for the manufacturing industry to increase the balance rate of the production line. With the continuous change of market demands, the order structure of products is changed from few varieties to many varieties to small batches. Therefore, the line balance is an important index of a production line in a manufacturing industry, and the line balance means that the cycle time of each process is adjusted by various means and methods so that the cycle time of each process tends to be the same. Under the market demands described above, flexible manufacturing techniques have evolved.
The existing flexible manufacturing technology mainly adopts a stopwatch time measurement method to observe and record each process for 10 times, and adopts a 'three standard deviation elimination method', and then uses qualified data to average as observation time. According to the difficulty of assembly work, the operating proficiency of staff and a company management system, the evaluation coefficient is set to be 1, the rest wide release rate is set to be 10%, and the standard working time of each process is calculated. Because different processes are involved in the production process, the time difference of the different processes is larger, the longest production time used in each process flow is the bottleneck time, and the current flexible manufacturing technology does not have a method for adjusting the corresponding production time, if the corresponding process flow is directly adopted for production, the balance rate of the production line of the corresponding product is low, the line balance loss is large, and the production efficiency is lower.
In view of the above-mentioned technology, finding a production time adjustment and analysis method that can improve production efficiency in real time according to production status is a problem to be solved by those skilled in the art.
Disclosure of Invention
The invention aims to provide a production time adjustment analysis method and system for flexible manufacturing of a black lamp factory, which can solve the problems that the existing flexible manufacturing technology is not provided with a method for adjusting corresponding production time, and if the corresponding process flow is directly adopted for production, the balance rate of production lines of corresponding products is low, the line balance loss is large and the production efficiency is low.
The invention is realized in the following way:
in a first aspect, an embodiment of the present application provides a method for analyzing production time adjustment of flexible manufacturing of a black light factory, including the steps of: the method comprises the steps of obtaining the number of machines of a flexible production line and the circulation time of the machines, obtaining production indexes of preset products, each process flow and the production time of each process flow, obtaining the takt time of the products according to the production indexes and the circulation time of the machines, improving each process flow, splitting each process flow with the production time longer than the takt time, combining each process flow with the production time shorter than the takt time so that the production time of each split and combined process flow is the same as the takt time, observing and recording the production time of each improved process flow, and calculating the corresponding production efficiency through a Markov analysis method.
In some embodiments of the present invention, if the number of types of the preset products is 1, observing and recording the production time of each improved process flow, and calculating the corresponding production efficiency includes:
calculating the total number Wd of the system states through the following formula;
W d ＝Q∑j＝1W d ，j；
wherein j is the batch of the preset product, and Q is the number of the batches of the preset product;
calculating the non-zero transition probability X of the corresponding Markov chain according to the system state s ；
Xs(n+1)＝AsXs(n)；
wherein n is a time period, g is a period state, and As is a probability transition matrix;
Pcti，j(n)＝xs，W_，j(n)；
Pcti，j(n)＝P(cti，j＝n)；
its average value E (cti, j) and standard deviation delta (ct) i J) is represented as;
wherein cTi, j represents the instant when machine mi completes the process of product Bj in batch j; wherein i= … M, j=1q;
and calculating the average value and the standard deviation of the production time of each batch of the preset product according to the formula, wherein the average value and the standard deviation are used for representing the production efficiency of the preset product.
In some embodiments of the present invention, after the obtaining the production index of the preset product, each process flow, and the production time of each process flow, and obtaining the takt time of the product according to the production index and the cycle time of the machine, the method further includes:
calculating the balance loss L of the preset product on the flexible production line according to the following formula LB ；
L LB ＝(1-R LB )·n1·T max
Wherein R is LB For the balance rate of the production line, n 1 T is the number of machines of the flexible production line max T is the longest time in the production time used by each process flow i The production time used for each of the process flows;
the improvement of each process flow comprises the following steps:
according to the balance loss L LB And improving each process flow.
In some embodiments of the present invention, if the number of types of the preset products is greater than 2, observing and recording the production time of each improved process flow, and calculating the corresponding production efficiency includes:
observing and recording the production time of each improved process flow, and evaluating the machine performance in the flexible production line by using Monte Carlo simulation;
and calculating corresponding production efficiency according to the machine performance.
In some embodiments of the present invention, after the observing and recording the production time of each improved process flow and calculating the corresponding production efficiency by using a markov analysis method, the method further includes:
and obtaining the production expectation of the preset product, comparing according to the production expectation and the production efficiency, and drawing a chart so as to facilitate the subsequent production adjustment of the preset product by the flexible production line.
In some embodiments of the present invention, the obtaining the production expectations of the preset products and comparing according to the production expectations and the production efficiency further includes:
and if the comparison result exceeds the preset deviation, alarming so as to prompt a user to timely adjust the flexible production line.
In a second aspect, embodiments of the present application provide a production time adjustment analysis system for flexible manufacturing of black lamps, comprising:
an acquisition module for acquiring the number of machines of the flexible production line and the cycle time of the machines;
the product time module is used for acquiring production indexes of preset products, each process flow and the production time of each process flow, and acquiring beat time of the products according to the production indexes and the circulation time of the machine;
a process improvement module, configured to improve each of the process flows, where the improvement includes splitting each of the process flows with a production time longer than the takt time, and combining each of the process flows with a production time shorter than the takt time, so that the split and combined process flows have a production time identical to the takt time;
and the efficiency calculation module is used for observing and recording the production time of each improved process flow and calculating the corresponding production efficiency through a Markov analysis method.
In a third aspect, embodiments of the present application provide an electronic device comprising a memory for storing one or more programs; a processor; the method as described in any one of the first aspects is implemented when the one or more programs are executed by the processor.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method as described in any of the first aspects above.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects: the embodiment of the invention provides a production time adjustment analysis method for flexible manufacturing of a black lamp factory, which ensures that the bottleneck time is smaller than or equal to the production takt time by adjusting the production time of each different process flow in a flexible production line, and improves the efficiency of the production flow of a preset product by calculating the corresponding production takt time of the preset product and then splitting and integrating the process flow of the preset product. Meanwhile, the production efficiency of the corresponding preset product is calculated and analyzed, and compared with the mode that analysis is not adopted and simple calculation is adopted in the past, the production efficiency of the corresponding preset product can be obtained more intuitively and accurately, and therefore the production time of the process flow on the flexible production line can be adjusted more accurately.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an embodiment of a method for analyzing production time adjustment for flexible manufacturing of black lamps in accordance with the present invention;
FIG. 2 is a block diagram illustrating an embodiment of a system for manufacturing time adjustment analysis for flexible manufacturing of black lamps in accordance with the present invention;
fig. 3 is a block diagram of an electronic device according to an embodiment of the present invention.
Icon: 101. a memory; 102. a processor; 103. a communication interface.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The various embodiments and features of the embodiments described below may be combined with one another without conflict.
Examples
Fig. 1 is a flowchart of an embodiment of a method for adjusting and analyzing production time of flexible manufacturing of a black-light factory, referring to fig. 1, the method for adjusting and analyzing production time of flexible manufacturing of a black-light factory includes the following steps:
step S10: the number of machines of the flexible production line and the cycle time of the machines are obtained.
The flexible production line is a production line formed by connecting a plurality of adjustable machine tools (most of special machine tools) and matching with an automatic conveying device. The method relies on computer management and combines a plurality of production modes, thereby reducing the production cost and making the best use of things. It is to be understood that the number of machines in the flexible production line, the kind of machines, and the like are not limited in this embodiment. It is easy to understand that the flexible production line is adjustable relative to the rigid production line, and the specific production mode, working principle and the like of the flexible production line are not greatly related to the scheme, and are not described herein.
Step S11: obtaining production indexes of preset products, each technological process and production time of each technological process, and obtaining beat time of the products according to the production indexes and circulation time of the machine.
It should be noted that the line balancing is a continuous bottleneck improvement process. After one bottleneck process is eliminated, another bottleneck process occurs, requiring optimization until the bottleneck time is less than or equal to the standard operating time. The improved process comprises the following steps: antenna board assembly, cast board scanning, installation mainboard, fixed mainboard, lower cover processing, installation lower cover, set screw, functional test 1 and functional test 2. After improvement, each process was observed and recorded 10 times using the stopwatch time measurement method, anomaly values were eliminated using the three standard deviation method, and then the average value was obtained using the qualified data as the observation time. Similarly, the evaluation coefficient was set to 1, and the rest wide rate (allowances) was set to 10%. Then we can get the standard time after each process is improved. The specific improvement plan and the change conditions of the working time before and after improvement are shown in the table in step S12.
Step S12: and improving each process flow.
The improvement comprises splitting each process flow with production time longer than the beat time, and combining each process flow with production time shorter than the beat time so that the split and combined process flows have the same production time as the beat time;
the following table is a specific table for optimizing the product;
assume that the monthly market demand for products is about 5 tens of thousands. The daily requirement is 2000 calculated according to the working time of 25 days per month. The workshops are made of daily and night shifts, and the effective working time of each shift is 10 hours. Thereby calculating the effective working time and the takt time.
The calculation results are as follows:
effective time=2×10×3600=72000 s, takt time=72000++2000=36 s
The takt time is 36 seconds, that is, the production period of each product must be less than or equal to 36 seconds to meet the customer demand.
To analyze the product line flow of a company, each process was observed and recorded 10 times using the stopwatch time method, and using the "eliminate three standard deviation method (triple standard difference method)", and then averaged with the qualified data as the observation time. The evaluation coefficient was set to 1 and the rest wide rate (allowances) was set to 10% according to the difficulty of the assembly work, the skill of the staff operation and the company management system.
As can be seen from fig. 2, the ninth process takes the longest time, which is the bottleneck of the production line. Bottleneck time was 51 seconds, resulting in severe non-uniformity of the workload of each process. The calculation result of the line balance index is as follows, llb= 73351 ×20×100% = (1-71.86%) ×20×51= 287.03sSI =120 Σi=120 (Ti-32.65) 2=1.7.
According to the data, the line balance rate is low, the line balance loss is large, and the production efficiency of the existing product production line can be seen to be low, so that a great improvement space is provided. And the bottleneck time is far longer than the beat time. Therefore, the productivity of the product line cannot meet the market demand.
And S13, observing and recording the production time of each improved process flow, and calculating to obtain the corresponding production efficiency.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects: the embodiment of the invention provides a production time adjustment analysis method for flexible manufacturing of a black lamp factory, which ensures that the bottleneck time is smaller than or equal to the production takt time by adjusting the production time of each different process flow in a flexible production line, and improves the efficiency of the production flow of a preset product by calculating the corresponding production takt time of the preset product and then splitting and integrating the process flow of the preset product. Meanwhile, the production efficiency of the corresponding preset product is calculated and analyzed, and compared with the mode that analysis is not adopted and simple calculation is adopted in the past, the production efficiency of the corresponding preset product can be obtained more intuitively and accurately, and therefore the production time of the process flow on the flexible production line can be adjusted more accurately.
The method comprises the steps of obtaining the number of machines of a flexible production line and the circulation time of the machines, obtaining production indexes of preset products, each process flow and the production time of each process flow, obtaining the beat time of the products according to the production indexes and the circulation time of the machines, improving each process flow, splitting each process flow with the production time being greater than the beat time, combining each process flow with the production time being less than the beat time so that the split and combined production time of each process flow is the same as the beat time, observing and recording the production time of each improved process flow, and calculating to obtain the corresponding production efficiency.
In the above embodiments, the specific method for calculating the production efficiency is not limited, and in some embodiments of the present invention, if the number of types of preset products is 1, observing and recording the production time of each improved process flow, and calculating the corresponding production efficiency includes:
calculating the total number Wd of the system states through the following formula;
W d ＝Q∑j＝1W d ，j；
wherein j is the batch of the preset product, and Q is the number of the batches of the preset product;
calculating the non-zero transition probability X of the corresponding Markov chain according to the system state s ；
Xs(n+1)＝AsXs(n)；
wherein n is a time period, g is a period state, and As is a probability transition matrix;
Pcti，j(n)＝xs，W_，j(n)；
Pcti，j(n)＝P(cti，j＝n)；
its average value E (cti, j) and standard deviation delta (ct) i J) is represented as;
wherein cTi, j represents the instant when machine mi completes the process of product Bj in batch j; wherein i= … M, j= 1^Q;
and calculating the average value and the standard deviation of the production time of each batch of the preset product according to the formula, wherein the average value and the standard deviation are used for representing the production efficiency of the preset product.
The Markov Chain (MC) is a random process (stochastic process) having Markov properties (Markov property) in probability theory and statistics and existing in a discrete index set (index set) and state space (state space) [1-2]. Markov chains suitable for Continuous index sets are known as Markov processes (Markov processes), but are sometimes also regarded as a subset of Markov chains, i.e. Continuous-Time chains (CTMC), corresponding to Discrete-Time Markov chains (DTMC), and thus Markov chains are a broader concept.
It should be added that, according to the system model description, the non-zero transition probability of the markov chain is as follows:
P[q(n+1)＝j，s 1，q (n+1)＝0，f q (n+1)＝l，
u q (n+1)＝β(j)|q(n)＝j，s 1，q (n)＝0，
f q (n)＝l，u q (n)＝β(j)]＝1-R 1，j ，
j＝1，...，Q，l＝0，...，B j -1，
P[q(n+1)＝j，s 1，q (n+1)＝1，f q (n+1)＝l，
u q (n+1)＝β(j)|q(n)＝j，s 1，q (n)＝0，
f q (n)＝l，u q (n)＝β(j)]＝R 1，j ，
j＝1，...，Q，l＝0，...，B j -1，
P[q(n+1)＝j，s 1，q (n+1)＝0，f q (n+1)＝l+1，
u q (n+1)＝β(j)|q(n)＝j，s 1，q (n)＝1，
f q (n)＝l，u q (n)＝β(j)]＝P 1，j ，
j＝1，...，Q，l＝0，...，B j -2，
P[q(n+1)＝j，s 1，q (n+1)＝1，f q (n+1)＝l+1，
u q (n+1)＝β(j)|q(n)＝j，s 1，q (n)＝1，
f j (n) ∈ {0, … …, bj } represents the number of products of the j-th lot that the system completes at the beginning of time period n,
beta (j) represents the period of time that elapses in the set process state of lot j when the system starts in period of time n.
Q (n) ∈ {1, … …, j, … …, Q } represents the number of lots being processed during time period n
As represents the transition probability matrix of a Markov chain
h (n) represents the number of product buffers at the beginning of time period n
A total of Q lots of products, denoted lot j, j=1, 2, … …, Q,
each batch size Bj, si, j (n) ∈ { 0=down, 1=up } represents the state of the machine processing the product of the first batch j during the period n. Where i=1, …, M, i.e. the number of machines; j=1, … …, Q.
Furthermore, if it is assumed that the machine is started after setting the process state, an additional non-zero transition probability is given.
P[q(n+1)＝j，s 1，q (n+1)＝1，f q (n+1)＝0，
u q (n+1)＝t set，j |q(n)＝j，s 1，q (n)＝|0，
f q (n)＝0，u q (n)＝t set，j -1]＝1，j＝2，...，Q，
If it is assumed that the machine is shut down after setting the process state, an additional non-zero transition probability is given.
P[q(n+1)＝j，s 1，q (n+1)＝0，f q (n+1)＝0，
u q (n+1)＝t set，j |q(n)＝j，s 1，q (n)＝0，
f q (n)＝0，u q (n)＝t set，j -1]＝1，j＝2，...，Q.
In the embodiment, the Markov is integrated into the corresponding evaluation analysis of the production efficiency, so that a more accurate analysis result is obtained.
In some embodiments of the present invention, after obtaining the production index of the preset product, each process flow, and the production time of each process flow, and obtaining the takt time of the product according to the production index and the cycle time of the machine, the method further includes:
calculating the balance loss L of the preset product on the flexible production line according to the following formula LB ；
L LB ＝(1-R LB )·n1·T max ；
Wherein LBR is the balance rate of the production line, n is the number of machines of the flexible production line, and Tmax is the longest time in the production time used by each process flow;
the improvement of each process flow comprises:
according to balance loss L LB And improving each process flow.
The smoothness index of the production line is an index for measuring the deviation degree between the cycle time of each workstation and the average cycle time of each workstation. The smaller the degree of deviation, the more balanced the production line. The calculation formula is as follows:
SI＝1n∑i＝1n(Ti-T)2
SI is the smoothness index, n is the number of stations, ti is the standard on-time for each station, and T is the average standard on-time for each station.
In general, there are two main methods for improving a production line based on the above-mentioned low production balance rate: method learning (method) and work measurement (work measurement).
The method learning is to record, analyze and improve the existing working method by utilizing various analysis technologies, design the most economical, reasonable and effective working method and standardize the working method. The final purpose is to improve the production efficiency and reduce the production cost. Methods commonly used analytical methods in learning include 5W1H and ECRS improvement principles.
The working measurement is a method for determining standard working time, and comprises the following steps:
step 1: the observation time is calculated by measuring the operation time.
Step 2: and calculating the standard working time according to the evaluation coefficient and the benefits rate.
Step 3: the balance index of the production line is calculated according to the standard working time.
Step 4: according to the balance index of the production line, the current situation of the production line is analyzed, and an improvement scheme is provided.
In some embodiments of the present invention, if the number of types of the preset products is greater than 2, observing and recording the production time of each improved process flow, and calculating the corresponding production efficiency includes:
observing and recording the production time of each improved process flow, and evaluating the machine performance in the flexible production line by using Monte Carlo simulation;
and calculating according to the machine performance to obtain the corresponding production efficiency.
It should be noted that the system can theoretically be characterized by a markov chain for a serial flexible production line with a number of machines greater than 2. However, the number of states increases dramatically with system parameters, and it is impractical to analyze this situation with the method in the above-described embodiment. The Monte Carlo (Monte Carlo) method, also known as random sampling or statistical test method, belongs to a branch of computational mathematics, which was developed in mid forty of the last century to accommodate the development of atomic energy industry at that time. While the conventional empirical method cannot approach the actual physical process, it is difficult to obtain a satisfactory result, and the Monte Carlo method can truly simulate the actual physical process, so that the solution problem is very consistent with the actual process, and a very satisfactory result can be obtained. This is also a calculation method based on probabilistic and statistical theory methods, which is a method that uses random numbers (or more commonly pseudo-random numbers) to solve many calculation problems. The solved problem is associated with a certain probability model, and statistical simulation or sampling is realized by an electronic computer so as to obtain an approximate solution of the problem.
The present embodiment proposes a specific analysis method for the production efficiency of a flexible production line with a machine number greater than 2.
In some embodiments of the present invention, after observing and recording the production time of each improved process flow and calculating the corresponding production efficiency by using a markov analysis method, the method further includes:
and obtaining the production expectation of the preset product, comparing according to the production expectation and the production efficiency, and drawing a chart so as to facilitate the subsequent production adjustment of the preset product on the flexible production line.
In this embodiment, the specific drawing method and drawing flow of the icon are not limited, and it can be understood that, by drawing the chart, a user with weak expertise can more intuitively understand the current factory production state, so as to further improve the corresponding production adjustment reaction speed.
In some embodiments of the present invention, when obtaining the production expectations of the preset products and comparing according to the production expectations and the production efficiency, further includes:
if the comparison result exceeds the preset deviation, an alarm is given so as to prompt a user to timely adjust the flexible production line.
Based on the same inventive concept, referring to fig. 2, the invention further provides a production time adjustment analysis system for flexible manufacturing of a black light factory, which comprises:
an acquisition module 10 for acquiring the number of machines of the flexible production line and the cycle time of the machines;
the product time module 11 is configured to obtain a production index of a preset product, each process flow, and a production time of each process flow, and obtain a takt time of the product according to the production index and a cycle time of the machine;
a process improvement module 12 for improving each of the process flows, the improvement comprising splitting each of the process flows having a production time longer than the takt time, and combining each of the process flows having a production time shorter than the takt time so that the split and combined process flows have a production time identical to the takt time;
the efficiency calculation module 13 is configured to observe and record the production time of each improved process flow, and calculate the corresponding production efficiency through a markov analysis method.
The specific implementation process and the specific beneficial effects of the system refer to the production time adjustment analysis method for flexible manufacturing of the black light factory provided by the embodiment of the application, and are not described herein again.
Referring to fig. 3, fig. 3 is a block diagram of an electronic device according to an embodiment of the present invention. The electronic device comprises a memory 101, a processor 102 and a communication interface 103, wherein the memory 101, the processor 102 and the communication interface 103 are electrically connected with each other directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 101 may be used to store software programs and modules, such as program instructions/modules corresponding to a flexible manufacturing process time adjustment analysis system for a black-light fixture according to embodiments of the present application, and the processor 102 executes the software programs and modules stored in the memory 101, thereby performing various functional applications and data processing. The communication interface 103 may be used for communication of signaling or data with other node devices.
The Memory 101 may be, but is not limited to, a random access Memory (Random Access Memory, RAM), a Read Only Memory (ROM), a programmable Read Only Memory (Programmable Read-Only Memory, PROM), an erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), an electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.
The processor 102 may be an integrated circuit chip with signal processing capabilities. The processor 102 may be a general purpose processor including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processing, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative, and that the electronic device may also include more or fewer components than shown in fig. 3, or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
In summary, the embodiment of the electronic device and the corresponding beneficial effects are provided in the method section.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (9)
1. The production time adjustment analysis method for flexible manufacturing of the black lamp factory is characterized by being applied to a flexible manufacturing production line and comprising the following steps of:
acquiring the number of machines of the flexible production line and the cycle time of the machines;
acquiring production indexes of preset products, each technological process and the production time of each technological process, and acquiring beat time of the products according to the production indexes and the circulation time of the machine;
improving each process flow, wherein the improvement comprises splitting each process flow with the production time longer than the beat time, and combining each process flow with the production time shorter than the beat time so that the production time of the split and combined process flows is the same as the beat time;
and observing and recording the production time of each improved process flow, and calculating to obtain the corresponding production efficiency.
2. The method for adjusting and analyzing the production time of flexible manufacturing of a black-light factory according to claim 1, wherein if the number of types of the preset products is 1, the steps of observing and recording the production time of each improved process flow and calculating the corresponding production efficiency include:
calculating the total number Wd of the system states through the following formula;
W d ＝Q∑j＝1W d ，j；
wherein j is the batch of the preset product, and Q is the number of the batches of the preset product;
calculating the non-zero transition probability X of the corresponding Markov chain according to the system state s ；
X s ＝[x s，1 …x s，g …x s ，W s ] T ，x s，g (n) =p, where P is the probability that the system is in the g-phase in period n, and is calculated from the following formula;
Xs(n+1)＝AsXs(n)；
wherein n is a time period, g is a period state, and As is a probability transition matrix;
Pcti，j(n)＝xs，W _ ，j(n)；
Pcti，j(n)＝P(cti，j＝n)；
its average value E (cti, j) and standard deviation delta (ct) i J) is represented as;
wherein cTi, j represents the instant when machine mi completes the process of product Bj in batch j; wherein i= … M, j= 1^Q;
and calculating the average value and the standard deviation of the production time of each batch of the preset product according to the formula, wherein the average value and the standard deviation are used for representing the production efficiency of the preset product.
3. The method for adjusting and analyzing the production time of flexible manufacturing in a black-light factory according to claim 2, wherein after the obtaining the production index of the preset product, each process flow and the production time of each process flow, and obtaining the takt time of the product according to the production index and the cycle time of the machine, the method further comprises:
calculating the balance loss L of the preset product on the flexible production line according to the following formula LB ；
L LB ＝(1-R LB )·n1·T max ；
Wherein R is LB For the balance rate of the production line, n 1 T is the number of machines of the flexible production line max T is the longest time in the production time used by each process flow i For each of the processesProduction time used in the process;
the improvement of each process flow comprises the following steps:
according to the balance loss L LB And improving each process flow.
4. The method of claim 1, wherein if the number of types of the preset products is greater than 2, the observing and recording the production time of each improved process flow, and calculating the corresponding production efficiency includes:
observing and recording the production time of each improved process flow, and evaluating the machine performance in the flexible production line by using Monte Carlo simulation;
and calculating corresponding production efficiency according to the machine performance.
5. The method according to any one of claims 1 to 4, wherein after observing and recording the production time of each of the improved process flows and calculating the corresponding production efficiency by a markov analysis method, further comprising:
and obtaining the production expectation of the preset product, comparing according to the production expectation and the production efficiency, and drawing a chart so as to facilitate the subsequent production adjustment of the preset product by the flexible production line.
6. The method of claim 1, wherein the step of obtaining the production expectations of the preset products and comparing according to the production expectations and the production efficiency further comprises:
and if the comparison result exceeds the preset deviation, alarming so as to prompt a user to timely adjust the flexible production line.
7. A production time adjustment analysis system for flexible manufacturing of black lamps in a factory, comprising:
an acquisition module for acquiring the number of machines of the flexible production line and the cycle time of the machines;
the product time module is used for acquiring production indexes of preset products, each process flow and the production time of each process flow, and acquiring beat time of the products according to the production indexes and the circulation time of the machine;
a process improvement module, configured to improve each of the process flows, where the improvement includes splitting each of the process flows with a production time longer than the takt time, and combining each of the process flows with a production time shorter than the takt time, so that the split and combined process flows have a production time identical to the takt time;
and the efficiency calculation module is used for observing and recording the production time of each improved process flow and calculating to obtain the corresponding production efficiency.
8. An electronic device, comprising:
a memory for storing one or more programs;
a processor. The production time adjustment and analysis method according to any one of claims 1-6 is implemented when said one or more programs are executed by said processor.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the production time adjustment and analysis method according to any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310324620.XA CN116339260A (en) | 2023-03-28 | 2023-03-28 | Production time adjustment analysis method and system for flexible manufacturing of black lamp factory |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310324620.XA CN116339260A (en) | 2023-03-28 | 2023-03-28 | Production time adjustment analysis method and system for flexible manufacturing of black lamp factory |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116339260A true CN116339260A (en) | 2023-06-27 |
Family
ID=86892765
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310324620.XA Pending CN116339260A (en) | 2023-03-28 | 2023-03-28 | Production time adjustment analysis method and system for flexible manufacturing of black lamp factory |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116339260A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117075556A (en) * | 2023-08-25 | 2023-11-17 | 安徽鸿凌智能仪表科技有限公司 | Intelligent instrument assembly method and system based on Internet of things |
-
2023
- 2023-03-28 CN CN202310324620.XA patent/CN116339260A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117075556A (en) * | 2023-08-25 | 2023-11-17 | 安徽鸿凌智能仪表科技有限公司 | Intelligent instrument assembly method and system based on Internet of things |
| CN117075556B (en) * | 2023-08-25 | 2024-05-14 | 安徽鸿凌智能仪表科技有限公司 | Intelligent instrument assembly method and system based on Internet of things |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Agrawal et al. | Analysis of variation transmission in manufacturing processes—part II | |
| CN103187329B (en) | A kind of analytical method of wafer yield | |
| CN101996855B (en) | Wafer defect analysis method | |
| CN109409628A (en) | Acquisition terminal production firm evaluation method based on metering big data Clustering Model | |
| CN109389145A (en) | Electric energy meter production firm evaluation method based on metering big data Clustering Model | |
| CN107146035B (en) | Method for calculating batch coefficients in large-goods production of knitted clothes | |
| CN110333962B (en) | Electronic component fault diagnosis model based on data analysis and prediction | |
| CN113614758A (en) | Equipment index goodness grade prediction model training method, monitoring system and method | |
| CN104700200A (en) | Multivariate product quality monitoring method oriented to digital workshop | |
| CN116339260A (en) | Production time adjustment analysis method and system for flexible manufacturing of black lamp factory | |
| CN118191473B (en) | Photovoltaic inverter production aging test data analysis system | |
| CN109389282A (en) | A kind of electric energy meter production firm evaluation method based on gauss hybrid models | |
| CN111737249A (en) | Abnormal data detection method and device based on Lasso algorithm | |
| US11599889B2 (en) | Qualification of second-source raw materials in the presence of multiple batch effects | |
| CN116051037A (en) | Project progress supervision system based on data analysis | |
| CN117633571A (en) | Abnormal user early warning method and device based on multiple clusters | |
| CN109409629B (en) | Acquisition terminal manufacturer evaluation method based on multi-attribute decision model | |
| CN114926051A (en) | Analysis system for evaluating manufacturing capacity of semiconductor equipment | |
| CN113673842A (en) | Production efficiency diagnosis method, device, equipment and storage medium based on big data | |
| CN117114418A (en) | E-commerce purchasing risk control system | |
| WO2024000356A1 (en) | Data processing method and apparatus, data display method and apparatus, and device and medium | |
| WO2022227094A1 (en) | Data processing method and apparatus, and device and storage medium | |
| CN109389281A (en) | A kind of acquisition terminal production firm evaluation method based on gauss hybrid models | |
| CN116150989A (en) | Photovoltaic module manufacturing method and photovoltaic module | |
| CN115344495A (en) | Data analysis method and device for batch task test, computer equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |