A method for adjusting the buffer capacity of a detection line of an air conditioner outdoor unit

Abstract

The present invention relates to the technical field of air-conditioning outdoor unit detection process, and specifically to a method for adjusting the buffer capacity of an air-conditioning outdoor unit detection line. This method changes the mode in which materials are only stored in a fixed order in the traditional cache strategy by dynamically calculating the cache probability and combining it with a retry allocation mechanism. When the host passes through each cache area, the system will determine the allocation destination based on the real-time cache status. If the allocation is unsuccessful, the process can be re-entered and retried. This flexible closed-loop design can effectively cope with fluctuations in production rhythm, avoid backlogs in the front-end cache area and idleness in the back-end, and make the workload of each link in the detection line more balanced.

Description

Technical Field

[0001] The present invention relates to the technical field of air-conditioning outdoor unit detection process, and in particular to an air-conditioning outdoor unit detection line buffer amount adjustment method. Background Art

[0002] Factory production of air conditioner outdoor units typically utilizes an assembly line-style process. This involves using multiple four-way transfer machines to form multiple conveyor lines, one of which serves as the main conveyor line, with two secondary conveyor lines located on either side. These secondary conveyor lines serve as buffers and also transport outdoor units to various inspection stations.

[0003] In the inspection process of air-conditioning outdoor units, in order to further improve the inspection efficiency, the production system adopts a zoned collaborative operation mode: according to the inspection station conditions on site, multiple inspection stations are scientifically divided into several inspection areas; at the same time, corresponding buffer areas are provided at the front end of each inspection area. These buffer areas serve as "material transfer stations", which can not only buffer the production capacity fluctuations caused by differences in process rhythm, but also dynamically adjust the flow order of outdoor units through the intelligent scheduling system, realize the efficient use of inspection resources, greatly shorten the inspection cycle of a single product, and ensure the continuity and smoothness of the entire inspection process.

[0004] In actual applications, the principle of caching in the nearest buffer operates in the direction of material delivery. Materials are only stored in the next buffer area when the immediately preceding buffer area is completely full. However, this strategy has significant drawbacks. It is difficult to respond to dynamic changes in the production rhythm in real time and can easily lead to imbalanced allocation of buffer area resources. Specifically, the front buffer area frequently overflows due to fluctuations in upstream process efficiency or short-term production capacity surges, causing the corresponding inspection area to operate overloaded for a long time. At the same time, the back buffer area remains vacant for a long time due to downstream process failures, process adjustments, and other reasons. This causes serious uneven workload in the inspection area and significant differences in the working conditions of various links on the same inspection line, which in turn affects overall production efficiency and equipment life.

[0005] It can be seen that the current detection method of the proximity cache principle has great deficiencies and needs to be further improved to solve the above problems. Summary of the Invention

[0006] To avoid and overcome the technical problems existing in the prior art, the present invention provides a method for adjusting the buffer capacity of an air conditioner outdoor unit detection line. The method determines whether a host is allocated to a corresponding buffer area based on the real-time buffer capacity of the buffer area, thereby ensuring uniformity in the allocation of each buffer area and optimizing the utilization of detection resources.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for adjusting the buffer capacity of a detection line of an air conditioner outdoor unit includes the following adjustment steps:

[0009] S1. Transport each host to be tested on the main conveyor line;

[0010] S2. When a host passes through a buffer zone, its probability of being stored in that buffer zone is calculated based on the real-time buffer capacity of that buffer zone. If the probability is greater than the set probability threshold for that buffer zone, the host is assigned to that buffer zone. Otherwise, the host continues to the next buffer zone.

[0011] S3. Convey each host in sequence according to step S2. If the host has traversed all the buffer areas and has not been allocated to any buffer area, put the host back on the main conveyor line and continue the allocation work according to step S2.

[0012] As a further solution of the present invention: the calculation formula of the cache probability is as follows:

[0013] (1);

[0014] Where, Indicates that the current host is The cache probability allocated to the current cache area at any moment; Indicates the volume dynamic parameters of the current host; Indicates the Cache area in The real-time buffer capacity at the moment, that is, the real-time buffer capacity of the buffer area at the current delivery position of the host; Indicates the Cache area in The real-time maximum cache capacity at the moment; represents a natural constant; represents the time attenuation coefficient; Indicates the time from the last host assignment to the The time interval between buffers; Indicates the Cache area in Real-time cache weight at the moment; Indicates the total number of cache areas.

[0015] As a further solution of the present invention: the calculation formula of the real-time maximum cache capacity of the cache area is as follows:

[0016] (2);

[0017] (3);

[0018] Where, Indicates the The standard cache capacity of each cache area; Indicates the The minimum cache capacity of a cache area; Indicates the Cache area in Time fluctuation coefficient of the moment; Indicates the Cache area in The partition attenuation coefficient at the moment; Indicates rounding operation; Indicates the maximum value operation.

[0019] As a further solution of the present invention: the calculation formula of the time fluctuation coefficient is as follows:

[0020] (4);

[0021] Where, Indicates the The detection area corresponding to the cache area is Real-time detection cycle at all times; Indicates the The detection area corresponding to the buffer area is detected from the beginning The average detection period at time.

[0022] As a further solution of the present invention: the calculation formula of the partition attenuation coefficient is as follows:

[0023] (5);

[0024] Where, Indicates the In the cache The number of conflicts per unit time at a given moment.

[0025] As a further solution of the present invention: the calculation formula of the detection period is as follows:

[0026] (6);

[0027] Where, Indicates the The standard detection cycle of the detection area corresponding to each buffer area; Indicates the The detection area corresponding to the cache area is The time taken for a single rotation during moment detection; Indicates the The detection area corresponding to the cache area is Detection cycle parameters at the moment; Indicates the standard volume of the host; Indicates the actual volume of the current host; Indicates the maximum volume of the host; Represents the volume balance coefficient.

[0028] As a further solution of the present invention: the calculation formula of the detection period parameter is as follows:

[0029] (7);

[0030] Where, Indicates the The detection area corresponding to the cache area is The number of hosts being tested at the moment; Indicates the The maximum host capacity of the detection area corresponding to each cache area.

[0031] As a further solution of the present invention, the cache weight of the cache area is updated in real time during the host transmission process, and the update formula is as follows:

[0032] (8);

[0033] Where, Indicates the Cache area in Real-time cache weight at the moment; Indicates the Cache area in The real-time cache amount at the moment; Indicates the Cache area in The real-time maximum cache capacity at the moment, ; Indicates the time compensation coefficient; Indicates the total running time of the main conveyor line from the beginning to the current moment.

[0034] As a further solution of the present invention: the calculation formula of the volume dynamic parameter of the host is as follows:

[0035] (9);

[0036] Where, Indicates the set host standard volume; Indicates the actual volume of the host; Indicates the maximum volume of the host; represents the excess volume compensation coefficient.

[0037] As a further solution of the present invention: the calculation formula of the volume balance coefficient is as follows: (10);

[0038] Where, represents the scale factor, .

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] 1. This method changes the traditional caching strategy of storing materials in a fixed order by dynamically calculating caching probabilities and combining them with a retry allocation mechanism. As the host passes through each cache, the system determines the allocation destination based on the real-time cache status. If the allocation is unsuccessful, the process can be re-entered and retried. This flexible closed-loop design effectively copes with fluctuations in production rhythm, avoids backlogs in the front-end cache and idleness in the back-end, and ensures a more balanced workload across the inspection line.

[0041] 2. The calculation of cache probability incorporates multiple dynamic factors: host size influences its allocation priority, the remaining cache space percentage determines current availability, the time interval since the last allocation reflects the cache's idle state, and the cache weight reflects the importance of each area. This multi-dimensional calculation logic gives the system an "intelligent scheduling brain," dynamically adjusting allocation strategies based on real-time production data, prioritizing large hosts in appropriate areas and fully utilizing cache areas that have been unused for a long time, thereby optimizing resource allocation.

[0042] 3. The real-time maximum cache capacity is not a fixed value but is dynamically adjusted based on the partition attenuation coefficient and the time fluctuation coefficient. When the operating status of a detection zone becomes unstable or cache conflicts increase, the system automatically reduces the maximum capacity of that zone while maintaining basic cache capacity through a minimum capacity setting. This "elastic capacity" design acts like an "adaptive valve" for the cache, reducing the risk of material backlogs during production fluctuations while avoiding excessive waste of cache space.

[0043] 4. The core of the time fluctuation coefficient is to reflect the production stability of each testing area through fluctuations in the testing cycle. When the cycle fluctuations in a particular testing area are large, the corresponding time fluctuation coefficient will increase, which in turn affects the adjustment of the buffer area capacity and encourages material flow to more stable testing areas. This mechanism acts as a "dynamic balancer" for the testing line, automatically guiding material flow to more stable links and reducing overall efficiency losses caused by local fluctuations.

[0044] 5. The partition decay coefficient is directly related to the number of conflicts per unit time in a buffer zone. When a buffer zone experiences frequent material congestion, the coefficient automatically increases, accelerating the decay of the corresponding buffer zone's maximum capacity and reducing its allocation probability. This "conflict-sensitive" adjustment method acts like a "flow limiter" for congested areas, quickly alleviating local bottlenecks and reducing pauses in the inspection process.

[0045] 6. The inspection cycle calculation intelligently differentiates strategies based on host size: hosts within the standard size use a basic inspection cycle, while hosts exceeding the standard size have the inspection time dynamically extended based on the size difference. This tailored design ensures inspection accuracy for hosts of varying sizes while avoiding wasted inspection time or inaccurate inspections caused by standardized standards, making the inspection process more tailored to actual production needs.

[0046] 7. The detection cycle parameter takes into account the host size ratio and the current load of the detection area: the larger the host or the busier the detection area, the higher the parameter will be, thus extending the detection time. This mechanism is like adding an "intelligent speed regulator" to the detection equipment, which can not only meet the detection needs of large hosts, but also adjust the rhythm according to the real-time load, reducing the risk of equipment failure due to overload.

[0047] 8. Cache weights are updated in real time based on the time integral of historical cached volumes. Caches that experience prolonged high loads will see their weights gradually decay, reducing their allocation probability. This "load feedback" mechanism acts like a "flow regulation channel" between caches, automatically directing material flow to idle areas, preventing individual caches from being chronically overloaded and achieving balanced overall load distribution.

[0048] 9. Dynamic volume parameters employ a compensation mechanism for oversized hosts. When a host exceeds the specified size, its allocation probability is reduced accordingly, preventing congestion in small caches due to excessive size. This "volume adaptation" strategy establishes a "size matching rule" between the cache and hosts, effectively reducing material jams caused by space mismatches and improving cache space utilization.

[0049] 10. The volume balance coefficient and the over-volume compensation coefficient are linearly linked via a proportional factor, allowing for flexible adjustment of the volume's impact on the inspection cycle based on production needs. This "flexible linkage" design acts like a "tune knob" for the system, ensuring inspection quality for over-volume hosts when needed while avoiding excessively extending the inspection cycle and impacting overall efficiency, ultimately achieving the optimal balance between accuracy and production capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 Flowchart of the present invention. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] See also Figure 1 In the embodiment of the present invention, the following contents are mainly included:

[0053] 1. Main parameter settings

[0054] A certain air conditioner outdoor unit inspection line utilizes a modular layout, consisting of a main conveyor line with a rated speed of 1.5 m / s. Along one side of this line, three buffer zones—A, B, and C—are arranged in series along the material flow. Each buffer zone is equipped with independent inspection stations. Buffer zone A, corresponding to the appearance inspection area, is equipped with industrial vision cameras and laser ranging sensors to automatically inspect various appearance indicators, such as the unit housing flatness and coating defects. After inspection, an inkjet printer annotates the results (pass / fail) in real time at a designated location on the unit, and the data is simultaneously uploaded to the MES system. Each buffer zone is connected by a variable-frequency conveyor chain, whose speed is dynamically synchronized with the main conveyor line by ±0.2 m / s, ensuring a smooth transition of the unit to the next inspection step. Buffer zones B and C, corresponding to the performance testing area and the packaging process, respectively, form a fully automated inspection closed loop. A photoelectric sensor array is installed between the main conveyor line and each buffer zone to monitor the unit position and buffer capacity in real time, providing data support for subsequent dynamic adjustment of the buffer level. The corresponding parameter values ​​are shown in Table 1.

[0055] Table 1 Parameter values

[0056] .

[0057] 2. Host transportation

[0058] The host P001 to be tested enters the main conveyor line and is about to pass through buffer area A. t 1000s, the total running time of the main conveyor line from the beginning to the current moment T is 1000s.

[0059] 3. Calculating Cache Probability

[0060] 1. Testing cycle

[0061] The system detects the actual volume of the host P001 to be detected through common volume detection equipment , which is larger than the standard volume. The number of hosts being tested in detection area A at 1000s tower.

[0062] Substituting the above data into formula (7), we can get the detection period parameter of detection zone A at 1000s: , substituted into formula (6), we can get the standard detection period of detection area A at 1000s .

[0063] 2. Time Fluctuation Coefficient

[0064] Statistics show the average detection cycle of cache area A in 1000s , substituted into formula (4), we can get the time fluctuation coefficient of buffer area A at 1000s .

[0065] 3. Partition attenuation coefficient

[0066] Obtain statistics on the number of conflicts per unit time in cache area A at 1000s times / hour, and substitute into formula (5) to obtain the partition attenuation coefficient of cache area A at 1000s: .

[0067] 4. Real-time maximum cache capacity

[0068] The minimum cache capacity of cache area A is calculated according to formula (3): , substituting into formula (2), we can get the real-time maximum cache capacity of cache area A at 1000s tower.

[0069] 5. Volume dynamic parameters

[0070] Substituting the corresponding data into formula (9), we can get the volume dynamic parameters of the host P001 to be tested: .

[0071] 6. Real-time cache capacity

[0072] Real-time cache capacity of cache area A at 1000s tower.

[0073] 7. Time interval

[0074] The time interval since the last host was assigned to cache A .

[0075] 8. Real-time caching weights

[0076] Real-time cache weight of cache area A at 1000s .

[0077] 9. Data in cache area B

[0078] Similarly, the data of cache area B required by the above analysis steps are: the real-time cache capacity of cache area B The real-time maximum cache capacity of cache area B in 1000s The real-time cache weight of cache area B at 1000s , the time interval since the last host was assigned to cache area B .

[0079] 10. Data in cache C

[0080] Similarly, the data of the buffer area C required by the above analysis steps are: the real-time buffer capacity of the buffer area C The real-time maximum cache capacity of cache area C in 1000s The real-time cache weight of cache area B at 1000s , the time interval since the last allocation of the host to cache area C .

[0081] 11. Cache probability of cache area A

[0082] Substituting the above data into formula (1) we can calculate the cache probability of the host P001 to be detected being assigned to cache area A: , which is less than the set threshold of 0.5, it will not be stored in cache area A but will be sent to cache area B.

[0083] 12. Cache probability of cache area B

[0084] Similarly, by substituting the above data into formula (1), we can calculate the cache probability of the host P001 to be detected being assigned to cache area B: , which is less than the set threshold of 0.5, it will not be stored in buffer area B but will be sent to buffer area C.

[0085] 12. Cache probability of cache area C

[0086] Similarly, by substituting the above data into formula (1), we can calculate the cache probability of the host P001 to be detected being assigned to the cache area C: , which is less than the set threshold of 0.5, it is not stored in the cache area C. The host P001 to be detected traverses all the cache areas and is not allocated.

[0087] The host P001 to be tested is placed back on the main conveyor line, and the retry counter is incremented by 1 (currently 1). The system sets a maximum retry count of 3. If no allocation is made after 3 retries, the device is directed to a temporary buffer and an alarm is triggered.

[0088] 4. Real-time update of cache weight

[0089] Taking cache area A as an example, t+1=1001s.

[0090] Total running time of main conveyor line T is 1000s, is the cache volume integral of cache area A in the first 1000 seconds. Assuming that tower, The above data is substituted into formula (8) to update the weight. The updated real-time cache weight is: .

[0091] 5. Compared with the principle of proximity allocation

[0092] The distribution at 1000s is used to compare the difference between this method and the proximity principle. The comparison results are briefly summarized in Table 2.

[0093] Table 2 Comparison results

[0094] ;

[0095] From the data in Table 2, we can see that this method optimizes the traditional nearest cache principle and effectively solves the cache imbalance problem of the detection line.

[0096] 6. Multi-host allocation scenario application simulation

[0097] The process of establishing the transmission cache of multiple hosts is shown in Table 3.

[0098] Table 3 Multi-host cache situation

[0099] ;

[0100] 6. Handling Abnormal Situations

[0101] When the utilization of cache area A is > 90% for 5 consecutive minutes (e.g. For example, if there are 2 hosts with a utilization rate of 90%, the system automatically increases the cache weight of cache area B by 20% (from 0.3 to 0.36) and lowers the allocation threshold of A to 0.4, guiding subsequent hosts to prioritize storing data in B.

[0102] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for adjusting the buffer capacity of an air conditioner outdoor unit detection line, characterized in that: The adjustment steps include the following: S1. Transport each host to be tested on the main conveyor line; S2. When a host passes through a cache area, it calculates the cache probability of the host being stored in the cache area based on the real-time cache capacity of the cache area. If the cache probability is greater than the set cache probability threshold of the cache area, the host is assigned to the cache area; otherwise, the host continues to be transferred to the next cache area; S3. Each host is transported in sequence according to step S2. If a host has traversed all buffer zones and is not allocated to any buffer zone, the host is put back on the main conveyor line and the allocation work is continued according to step S2. The calculation formula for cache probability is as follows: ； Where, Indicates that the current host is The cache probability allocated to the current cache area at any moment; Indicates the volume dynamic parameters of the current host; Indicates the Cache area in The real-time buffer capacity at the moment, that is, the real-time buffer capacity of the buffer area at the current delivery position of the host; Indicates the Cache area in The real-time maximum cache capacity at the moment; represents a natural constant; represents the time attenuation coefficient, with a value of 0.03; Indicates the time from the last host assignment to the The time interval between buffers; Indicates the Cache area in Real-time cache weight at the moment; Indicates the total number of cache areas; The calculation formula for the real-time maximum cache capacity of the cache area is as follows: ； ； Where, Indicates the The standard cache capacity of each cache area; Indicates the The minimum cache capacity of a cache area; Indicates the Cache area in Time fluctuation coefficient of the moment; Indicates the Cache area in The partition attenuation coefficient at the moment; Indicates rounding operation; Indicates the maximum value operation; the calculation formula of the time fluctuation coefficient is as follows: ； Where, Indicates the The detection area corresponding to the cache area is Real-time detection cycle at all times; Indicates the The detection area corresponding to the buffer area is detected from the beginning The average detection cycle at time t; the calculation formula of the partition attenuation coefficient is as follows: ； Where, Indicates the In the cache The number of conflicts per unit time at a given moment; The calculation formula for the detection period is as follows: ； Where, Indicates the The standard detection cycle of the detection area corresponding to each buffer area; Indicates the The detection area corresponding to the cache area is The time taken for a single rotation during moment detection; Indicates the The detection area corresponding to the cache area is Detection cycle parameters at the moment; Indicates the standard volume of the host; Indicates the actual volume of the current host; Indicates the maximum volume of the host; represents the volume balance coefficient; The calculation formula for the detection cycle parameters is as follows: ； Where, Indicates the The detection area corresponding to the cache area is The number of hosts being tested at the moment; Indicates the The maximum host load capacity of the detection area corresponding to each cache area; The cache weight of the cache area will be updated in real time during the host transmission process. The update formula is as follows: ； Where, Indicates the Cache area in Real-time cache weight at the moment; Indicates the Cache area in The real-time cache volume at the moment; Indicates the Cache area in The maximum real-time cache capacity at the moment, ; Indicates the time compensation coefficient, the value is 0.01; Indicates the total running time of the main conveyor line from the beginning to the current moment; The calculation formula of the host's volume dynamic parameters is as follows: ； Where, Indicates the set standard volume of the host; Indicates the actual volume of the host; Indicates the maximum volume of the host set; represents the excess volume compensation coefficient, which is set to 0.6; The calculation formula of volume balance coefficient is as follows: ； Where, represents the scale factor, .

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