A device maintenance optimization method

Abstract

The application discloses a device maintenance optimization method, comprising the following steps: classifying device faults into impact wear type faults and random type faults, and counting the occurrence intervals of various faults and the maintenance time after the faults occur; obtaining the average fault interval H0 of the impact wear type faults according to the statistics of the fault occurrence intervals; comparing the average fault interval H0 of the impact wear type faults with an order cycle h0; when H0>h0, it is not recommended to maintain within the order cycle; when H0 is less than h0, evaluating the inevitable loss Y caused by the impact wear type faults and the impact loss X; when XkY, it is not recommended to maintain within the order cycle; when X>kY, it is recommended to maintain before the end of the average fault interval; wherein, k is a preset parameter, and k is negatively correlated with X. Through the maintenance optimization method, it is determined whether and when the shutdown maintenance is needed, which has important guiding significance for production, especially in the case of tight order tasks.

Description

Technical Field

[0001] This application relates to the field of equipment, and more particularly to the field of equipment maintenance optimization. Background Technology

[0002] Equipment can experience various malfunctions during operation. When a malfunction occurs, maintenance can be delayed due to downtime, which can disrupt production schedules and even cause additional losses. Currently, most companies rely on experience to anticipate malfunctions and schedule maintenance shutdowns accordingly. However, anticipating a potential malfunction does not guarantee that it will actually occur. Especially when production tasks are urgent, many companies tend to ignore anticipated malfunctions and instead ramp up production in the hope of completing the task smoothly without the malfunction. However, this can sometimes lead to even greater losses. Therefore, determining whether and when to conduct maintenance shutdowns when a malfunction is anticipated has become a challenging issue in the industry.

[0003] Application content

[0004] To address the problems existing in the prior art, this application discloses an equipment maintenance optimization method, comprising the following steps;

[0005] Equipment failures are classified into impact and wear failures and random failures, and the occurrence intervals and repair times after each failure are statistically analyzed.

[0006] The average fault interval H0 of the impact and wear type faults is obtained based on the statistics of the fault occurrence intervals.

[0007] Compare the average failure interval H0 of the impact and wear type of failure with the order cycle h0;

[0008] When HO > h0, maintenance is not recommended within the order cycle;

[0009] When H0 is less than h0, evaluate the inevitable loss Y and impact loss X caused by the impact wear type of failure;

[0010] When X < kY, maintenance is not recommended within the order cycle;

[0011] When X > kY, it is recommended to perform maintenance before the mean time between failures ends.

[0012] Where k is a preset parameter, and k is negatively correlated with X.

[0013] The inevitable losses include: labor losses, replacement parts losses, and production stoppage losses during maintenance; the impact losses are mainly external losses, which refer to losses caused by sudden shutdowns due to malfunctions without prior notification to customers or suppliers.

[0014] The equipment maintenance optimization method also includes the following steps:

[0015] The probability of occurrence of the random type of fault over time is obtained by statistically analyzing the fault occurrence intervals.

[0016] Find the maximum probability S of the random type of fault occurring within the order cycle h0;

[0017] Evaluate the inevitable loss Y and the impact loss X caused by the random type of failure;

[0018] When S·X < kY, maintenance within the order cycle is not recommended;

[0019] When S·X>kY, S0 is calculated according to S0·X=kY. Based on the statistics of fault occurrence intervals, the fault interval corresponding to S0 is obtained. It is recommended to perform maintenance as soon as possible before the fault interval corresponding to S0 ends.

[0020] The inevitable losses include: the labor losses, the parts replacement losses, and the production downtime losses during maintenance, all of which are converted into days to comprehensively calculate the inevitable losses.

[0021] The external losses are converted into days to calculate the impact losses.

[0022] Faults that can be repaired without shutting down the machine are not included in the fault occurrence interval statistics.

[0023] The faults that can be repaired without shutting down include those caused by insufficient lubricating oil.

[0024] The order cycle refers to the period from the start of production based on a customer order to the completion of production corresponding to the order; the fault interval refers to the time between two faults when no maintenance is performed at the fault location.

[0025] The value of k ranges from 0.1 to 1.

[0026] The method for calculating the probability of random failures includes the following steps: Take a total of n equipment samples, operate the equipment and start timing. As time increases, equipment samples continuously fail. Record the number of samples that fail in different time periods. The probability of failure is then the number of samples that fail in the corresponding time period divided by the total number of samples n.

[0027] This application uses a maintenance optimization method to clearly determine whether and when maintenance downtime is needed, which has important guiding significance for production manufacturing, especially when order tasks are tight. Attached image description:

[0028] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0029] Figure 1This is a schematic diagram of the wear-related fault handling method of this application.

[0030] Figure 2 This is a schematic diagram of the random fault handling method in this application. Detailed Implementation

[0031] The technical solutions of this application will be clearly and completely described below in conjunction with the embodiments of this application;

[0032] To address the problems existing in the current technology, such as Figure 1-2 As shown: In order to solve the problems existing in the prior art, this application discloses an equipment maintenance optimization method, which includes the following steps;

[0033] Equipment failures are classified into impact and wear failures and random failures, and the occurrence intervals and repair times after each failure are statistically analyzed.

[0034] The average fault interval H0 of the impact and wear type faults is obtained based on the statistics of the fault occurrence intervals.

[0035] Compare the average failure interval H0 of the impact and wear type of failure with the order cycle h0;

[0036] When HO > h0, maintenance is not recommended within the order cycle;

[0037] When H0 is less than h0, evaluate the inevitable loss Y and impact loss X caused by the impact wear type of failure;

[0038] When X < kY, maintenance is not recommended within the order cycle;

[0039] When X > kY, it is recommended to perform maintenance before the mean time between failures ends.

[0040] Where k is a preset parameter, and k is negatively correlated with X.

[0041] The inevitable losses include: labor losses, replacement parts losses, and production stoppage losses during maintenance; the impact losses are mainly external losses, which refer to losses caused by sudden shutdowns due to malfunctions without prior notification to customers or suppliers.

[0042] The equipment maintenance optimization method also includes the following steps:

[0043] The probability of occurrence of the random type of fault over time is obtained by statistically analyzing the fault occurrence intervals.

[0044] Find the maximum probability S of the random type of fault occurring within the order cycle h0;

[0045] Evaluate the inevitable loss Y and the impact loss X caused by the random type of failure;

[0046] When S·X < kY, maintenance within the order cycle is not recommended;

[0047] When S·X>kY, S0 is calculated according to S0·X=kY. Based on the statistics of fault occurrence intervals, the fault interval corresponding to S0 is obtained. It is recommended to perform maintenance as soon as possible before the fault interval corresponding to S0 ends.

[0048] The inevitable losses include: the labor losses, the parts replacement losses, and the production downtime losses during maintenance, all of which are converted into days to comprehensively calculate the inevitable losses.

[0049] The external losses are converted into days to calculate the impact losses.

[0050] Faults that can be repaired without shutting down the machine are not included in the fault occurrence interval statistics.

[0051] The faults that can be repaired without shutting down include those caused by insufficient lubricating oil.

[0052] The order cycle refers to the period from the start of production based on a customer order to the completion of production corresponding to the order; the fault interval refers to the time between two faults when no maintenance is performed at the fault location.

[0053] The value of k ranges from 0.1 to 1.

[0054] The method for calculating the probability of random failure includes the following steps: Take a total of n equipment samples, operate the equipment and start timing. As time increases, equipment samples will continuously fail. Record the number of samples that fail in different time periods. The probability of failure is the number of samples that fail in the corresponding time period divided by the total number of samples n.

[0055] This application uses a maintenance optimization method to clearly determine whether and when maintenance downtime is needed, which has important guiding significance for production manufacturing, especially when order tasks are tight.

[0056] This application categorizes losses during maintenance into inevitable losses and impact losses, and quantifies each type of loss on a daily basis. The standardized unit facilitates comparison of various types of losses. Inevitable losses include: labor losses, parts replacement losses, and production stoppage losses during maintenance. Impact losses mainly include external losses, which refer to sudden shutdowns due to malfunctions without prior notification to customers, suppliers, etc.

[0057] Order cycle: The period from the start of production based on a customer order to the completion of the corresponding production for that order;

[0058] Fault interval: If no maintenance is performed at the fault location between two faults, then the interval between these two faults is called the fault interval.

[0059] Mean Time Between Failures (MTBF): Average of multiple failure intervals;

[0060] Impact and wear failures: During operation, equipment continuously impacts or wears its parts. The lifespan of a part can reflect the degree of impact or wear. In the same batch of parts, the time interval between failures caused by impact or wear is roughly the same.

[0061] Random faults: Faults caused by unforeseen factors, such as line faults.

[0062] Example 1 illustrates an impact-wear type of failure: In tobacco filter cutting devices, cutter wear failures frequently occur, causing the filter cutting surface to fail to meet process requirements. Without timely maintenance, the average interval H0 between these cutter wear failures is 50-60 days. When there are no failures, a single cutting machine can cut a total of 90,000 cigarettes per day, with a net profit of 0.1 yuan per cigarette. When this failure occurs, it requires 3 maintenance workers to spend 1 day cleaning up. The total manpower involved in the cigarette cutting process is 5 people. The daily expenses for 3 maintenance workers are 3,000 yuan, and the daily wages for 5 workers are 2,500 yuan. Therefore, the corresponding labor loss is 5,500 yuan, which is converted to 5,500 / 0.1 / 90,000 = 0.56 days.

[0063] This repair requires replacing the cutting blade. The cost of repairing the cutting blade is 500 yuan. Therefore, the number of days for calculating the cost of repairing the cutting blade as a replacement loss is: 500 / 0.1 / 90000 = 0.056 days.

[0064] A production stoppage during a 1-day maintenance period results in a 1-day loss.

[0065] The inevitable loss Y = labor loss + parts replacement loss + production downtime loss during maintenance = 1.62 days;

[0066] After calculation with the business department, it was found that due to the sudden shutdown of customer A without notification during the order cycle, it would cost 1,000 yuan to appease and compensate customer A. Therefore, the impact loss is X = 1,000 / 0.1 / 90,000 = 0.11 days.

[0067] k is set to 0.745; the value of k is inversely proportional to the impact loss, and the specific relationship can be X = 16.66 - 22.2 * k, with the value of k ranging between 0.1 and 1; the significance of the value of k is to balance the impact loss. In the case that maintenance cannot be performed before the start of the order cycle or after the end of the order cycle, the smaller the impact loss, the smaller the proportion of impact loss (additional loss) compared to normal maintenance during the order cycle, even if a failure causes a sudden shutdown during the order cycle. Therefore, it is more inclined to not shut down, and it is hoped that a failure shutdown will not occur during the order cycle. Even if it does occur, maintenance will be performed after the failure shutdown.

[0068] After calculation with the business department, H0 is set to 50 days;

[0069] When the order cycle h0 is 40 days, H0 > h0; maintenance is not recommended within the order cycle.

[0070] When the order cycle h0 is 60 days, then X = 0.11; kY = 0.745 * 1.62 = 1.21; X < kY; maintenance within the order cycle is not recommended.

[0071] Example 2 differs from Example 1 in that, after calculation with the business department, due to the sudden shutdown of customer B without notification during the order cycle, a cost of 20,000 yuan is required to appease and compensate customer B. This translates to an impact loss of X = 10,000 / 0.1 / 90,000 = 1.11 days; k refers to 0.7.

[0072] When the order cycle h0 is 40 days, H0 > h0; maintenance is not recommended within the order cycle.

[0073] When the order cycle h0 is 60 days, then X = 1.11; kY = 0.7 * 1.62 = 1.134; X < kY; maintenance within the order cycle is not recommended.

[0074] Example 3 differs from Example 1 in that, after calculation with the business department, due to the sudden shutdown of customer B without notification during the order cycle, a cost of 20,000 yuan is required to appease and compensate customer B. This is converted into an impact loss X = 15,000 / 0.1 / 90,000 = 1.67 days; k refers to 0.675.

[0075] When the order cycle h0 is 40 days, H0 > h0; maintenance is not recommended within the order cycle.

[0076] When the order cycle h0 is 60 days, then X = 1.67; kY = 0.675 * 1.62 = 1.09; X > kY; maintenance is recommended before the mean time between failures, that is, maintenance is recommended 50 days in advance.

[0077] Example 4 illustrates a random failure as follows: In a tobacco filter cutting device, one type of random failure is a shutdown due to excessive cutting debris. If maintenance is not performed in a timely manner, such shutdowns usually occur 30-40 days after the last maintenance. When there is no failure, a single cutting machine can cut a total of 90,000 cigarettes per day, with a net profit of 0.1 yuan per cigarette. When this failure occurs, it requires 3 maintenance workers to spend 1 day cleaning up. The total manpower involved in the cigarette cutting process is 5 people. The daily expenses for 3 maintenance workers are 3,000 yuan, and the daily wages for 5 workers are 2,500 yuan. Therefore, the corresponding labor loss is 5,500 yuan, which is converted to the number of days 5,500 / 0.1 / 90,000 = 0.56 days.

[0078] This repair requires replacing the debris suction pipe, which costs 80 yuan. Therefore, the cost of the debris suction pipe is calculated as the replacement loss in days as follows: 80 / 0.1 / 90000 = 0.0089 days.

[0079] A production stoppage during a 1-day maintenance period results in a 1-day loss.

[0080] The inevitable loss Y = labor loss + parts replacement loss + production downtime loss during maintenance period = 1.5689 days;

[0081] After calculation with the business department, it was found that due to the sudden shutdown without notifying the customer during the order cycle, it would cost 50,000 yuan to appease and compensate the customer. This would be converted into an impact loss of X = 50,000 / 0.1 / 90,000 = 5.56 days.

[0082] The probability of this type of failure is calculated as follows: The statistical sample consists of 10 devices, with a maintenance cycle of 30 days. Failure data within 3 maintenance cycles (equivalent to a sample size of 30) are used.

[0083]

[0084]

[0085] k is set to 0.5; the value of k is inversely proportional to the impact loss, specifically X = 16.66 - 22.2 * k, and the value of k ranges between 0.1 and 1; the significance of the value of k is to balance the impact loss. In the case that maintenance cannot be performed before the start of the order cycle or after the end of the order cycle, the smaller the impact loss, the smaller the proportion of impact loss (additional loss) compared to normal maintenance during the order cycle, even if a failure causes a sudden shutdown during the order cycle. Therefore, it is more likely that the system will not shut down, and it is hoped that a failure shutdown will not occur during the order cycle. Even if it does occur, maintenance will be performed after the failure shutdown.

[0086] When the order cycle is 10 days, then S = 1 / 30, S·X = (1 / 30)*5.56 = 0.185; kY = 0.5*1.5689 = 0.7845; S·X < kY; maintenance within the order cycle is not recommended.

[0087] When the order cycle is 15 days, then S = 1 / 15, S·X = (1 / 15)*5.56 = 0.371; kY = 0.5*1.5689 = 0.7845; S·X < kY; maintenance within the order cycle is not recommended.

[0088] When the order cycle is 20 days, then S = 2 / 15, S·X = (2 / 15)*5.56 = 0.741; kY = 0.5*1.5689 = 0.7845; S·X < kY; maintenance within the order cycle is not recommended.

[0089] When the order cycle is 25 days, then S = 4 / 15, S·X = (4 / 15)*5.56 = 1.482; kY = 0.5*1.5689 = 0.7845; S·X > kY; It is recommended to perform maintenance as early as possible before the highest probability event occurs, that is, to perform maintenance as soon as possible before the 21 days remaining until the last maintenance.

[0090] When the order cycle is 30 days, then S = 1 / 3, S·X = (1 / 3)*5.56 = 1.85; kY = 0.5*1.5689 = 0.7845; S·X > kY; It is recommended to perform maintenance as early as possible before the highest probability event occurs, that is, to perform maintenance as soon as possible before the 21 days remaining until the last maintenance.

[0091] When S·X=kY, S=0.141; this corresponds to approximately 21 days since the last maintenance.

Claims

1. A method for equipment maintenance optimization, the method comprising: The equipment maintenance optimization method comprises the following steps: Classify equipment failures into impact wear type failures and random type failures, and count the occurrence intervals of each type of failure and the maintenance time after failure; Obtain the average failure interval H0 of the impact wear type failure according to the statistics of the failure occurrence intervals; Compare the average failure interval H0 of the impact wear type failure with the order cycle h0; When H0 is greater than h0, it is not recommended to maintain within the order cycle; When H0 is less than h0, evaluate the certain loss Y and the impact loss X caused by the impact wear type failure, The certain loss includes labor loss, replacement part loss, and production stagnation loss during maintenance, which are all converted into days to comprehensively calculate the certain loss; The impact loss is mainly external loss, which refers to the loss caused by sudden shutdown without prior notification of customers or suppliers due to failure, and the external loss is converted into days to calculate the impact loss; When X is less than kY, it is not recommended to maintain within the order cycle; When X is greater than kY, it is recommended to maintain before the end of the average failure interval; K is a preset parameter, and k is negatively correlated with X, The equipment maintenance optimization method further comprises the following steps: Obtain the occurrence probability of the random type failure over time according to the statistics of the failure occurrence intervals; The calculation method of the occurrence probability of the random type failure comprises the following steps: take a total of n equipment samples, operate the equipment and start timing, as time increases, constantly have equipment samples fail, record the number of samples that fail in different time periods, and then the failure occurrence probability is the number of samples that fail in the corresponding time period divided by the total number of samples n; Find the maximum occurrence probability S of the random type failure within the order cycle h0; Evaluate the certain loss Y and the impact loss X caused by the random type failure; When S•X is less than kY, it is not recommended to maintain within the order cycle; When S•X is greater than kY, calculate S0 according to S0•X=kY, obtain the failure interval corresponding to S0 according to the statistics of the failure occurrence intervals, and recommend maintenance before the end of the failure interval corresponding to S0.

2. The method of claim 1, wherein, The failure that can be repaired without shutdown is not included in the failure occurrence interval statistics.

3. The method of claim 2, wherein, The failure that can be repaired without shutdown includes the failure caused by insufficient lubricating oil.

4. The method of claim 3, wherein, The order cycle refers to the period from starting to make goods according to a customer order to completing the goods corresponding to the order; the failure interval refers to the time between two failures without maintenance at the failure position.

5. The method of claim 4, wherein, The value range of k is between 0.1 and 1.

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