CN115358571A - Asset reliability assessment method - Google Patents
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Abstract
The invention belongs to the technical field of plant asset management, and particularly relates to an asset reliability assessment method, which comprises the following steps: acquiring inventory data of related production products in a production enterprise, maintenance management data of production equipment, fault data of the production equipment, process parameters of the production equipment and use data of a production management system; generating an inventory safety index, a maintenance management index, a diagnosis management index, a CPK index and an FE scoring index of the assets; and setting the weight and obtaining the reliability index of the assets of the production enterprise. The method and the device perform reliability assessment on the assets of the lithium battery production workshop, establish an accurate mathematical model, enable the asset reliability assessment to be more quantitative and have high accuracy, further determine whether the production is stable, reduce unnecessary resource waste, reasonably arrange production inventory and production quantity and reduce production cost.
Description
Technical Field
The invention belongs to the technical field of plant asset management, and particularly relates to an asset reliability assessment method.
Background
With the rapid development of social economy, intelligent equipment is more and more involved in the life of people, the operation of the intelligent equipment cannot be separated from a battery, and a lithium battery is a representative of a high-performance battery in the battery industry. In recent years, the lithium battery industry is developed rapidly, but the production environment and the production safety of the lithium battery are not paid enough attention, and the lagging production environment not only influences the product percent of pass, but also brings great potential safety hazard to production.
The production and manufacturing of the lithium battery are up to 50 working procedures, the related production equipment is numerous, and correspondingly, the parameter matching among the equipment is complicated; and the production of the lithium battery relates to the aspects of dangerous chemicals, pollution emission, fire safety and the like, so that the production and manufacturing factories of the lithium battery relate to a plurality of control parameters. Therefore, lithium battery production enterprises have the characteristics of numerous asset types, heterogeneous networks, heterogeneous data, strong space-time characteristics, high nonlinearity, strong characteristic coupling and the like, and key technologies and bottleneck problems of equipment interconnection and intercommunication, multi-mode perception, optimal control, asset health assessment diagnosis, preventive maintenance and the like are urgently needed to be solved.
For the asset health condition of lithium battery production enterprises, regular assessment and feedback are necessary to reduce asset management cost, operation and maintenance cost, reduce accessory loss and avoid major production accidents. The reliability assessment of an asset is particularly important in assessing the health of an asset, and is a measure of the ability of equipment within a manufacturing facility to perform specified functions under specified operating conditions and for specified periods of time.
In the prior art, an asset reliability assessment method developed for lithium battery production enterprises does not exist, and production enterprises of different products have different risk points and emphasis points and different factors considered when assessing asset reliability, so the asset reliability assessment method among different products cannot be used universally.
In summary, in order to accurately and effectively evaluate the asset reliability in the lithium battery production enterprise, the invention provides an asset reliability evaluation method suitable for the lithium battery production enterprise.
Disclosure of Invention
In order to solve the technical problem, the invention provides an asset reliability assessment method.
In order to achieve the purpose, the technical scheme of the invention is as follows:
an asset reliability assessment method comprising the steps of:
s1, acquiring inventory data of related production products in a production enterprise, maintenance management data of production equipment, fault data of the production equipment, process parameters of the production equipment and use data of a production management system;
s2, generating an inventory safety index, a maintenance management index, a diagnosis management index, a CPK index and an FE scoring index of the asset based on the data acquired in the S1;
s3, setting weights of the inventory safety index, the maintenance management index, the diagnosis management index, the CPK index and the FE scoring index in the asset reliability index;
and S4, obtaining the reliability index of the assets of the production enterprise according to the inventory safety index, the maintenance management index, the diagnosis management index, the CPK index, the FE scoring index and the corresponding weight of the FE scoring index.
Further, the stock safety index adopts a safety stock S r Indicating, safe stock quantity S r The calculation formula of (2) is as follows:
wherein L represents the advance time of product replenishment,
is an average value of the advance time L,
the average value of daily demand d of the product, z is the number of standard deviations under the service level, sigma d Standard deviation of daily demand d, σ L Is the standard deviation of the advance time L.
Further, if the advance time L is a constant value, then
Zero value, safe stock S r The calculation formula of (2) is as follows:
further, a unit period T of time is set, and the standard deviation of the demand in the unit period T is recorded as σ T Then the following relationship exists:
then, the safe stock S r Expressed as:
further, if the advance time L is variable, then
The value is not zero, and the setting is as follows:
then, the safety stock S r The calculation formula of (2) is as follows:
wherein k is a positive number.
Further, the maintenance management index includes a field management index and a maintenance index, and the calculation formula of the maintenance management index W is as follows:
W＝aW 1 +bW 2
wherein a and b are constants,representing the weight of the site management index and the repair index in the repair management index, W 1 Denotes a field management index, W 2 Indicating a repair index.
Further, the field management index is calculated by the formula:
W 1 ＝a 1 T K +b 1 T F
a 1 、b 1 is a constant, T K The method comprises the steps of representing average fault cognition time, namely average time from fault occurrence to the fault point which can be known by field management personnel; t is F The mean time to failure recovery time is expressed as the mean time to failure contact after failure occurred.
Further, the maintenance index is calculated by the formula:
W 2 ＝a 2 T F +b 2 T B
a 2 、b 2 is a constant, T B The mean-time between failures, i.e. the mean time between two consecutive failures, is indicated.
Further, the diagnosis management index comprises a fault prediction accuracy rate, a fault occurrence frequency, a fault missing report rate and a fault false report rate, wherein the fault prediction accuracy rate indicates that equipment parameters are abnormal but equipment is not shut down, and the ratio of the number of times of finding and removing faults in the regular maintenance to the total faults is calculated; the failure occurrence frequency is the reciprocal of the interval time of two adjacent failures; the failure missing report rate indicates that the failure has occurred but is not recorded in the production management system, and the occupation ratio of the failure in the total failure is high; the false fault alarm rate indicates that a fault has occurred but the information reported to the fault point of the maintenance personnel is wrong, and the proportion of the fault in the total fault is high.
Further, the CPK index represents the stability of the production process, and the calculation formula of the CPK index is as follows:
CPK＝C p ×(|1-C a |)
C a indicating the accuracy of the production process, C p Indicating the precision of the production process.
Further, the FE score index is obtained by scoring table.
The FE comprehensive index is mainly embodied in the use part of the whole system and the use part of plant equipment. The scoring is carried out by the equipment to the party B for maintenance according to a main judging means, sudden abnormality cannot occur, the environment and production are influenced, a 5s scoring table can be adopted for scoring each link, and finally, the comprehensive weight is adopted for solving the index.
Compared with the prior art, the invention has the beneficial effects that:
the method and the device perform reliability assessment on the assets of the lithium battery production workshop, establish an accurate mathematical model, enable the assessment of the asset reliability to be more quantitative and have high accuracy, further determine whether the production is stably operated, reduce unnecessary resource waste, reasonably arrange production inventory and production quantity and reduce production cost.
Detailed Description
The technical solutions of the present invention will be described in detail below, it is obvious that the described embodiments are not all embodiments of the present invention, and all other embodiments obtained by those skilled in the art without creative efforts belong to the protection scope of the present invention.
An asset reliability assessment method comprising the steps of:
s1, acquiring inventory data of related production products in a production enterprise, maintenance management data of production equipment, fault data of the production equipment, process parameters of the production equipment and use data of a production management system;
s2, generating an inventory safety index, a maintenance management index, a diagnosis management index, a CPK index and an FE scoring index of the asset based on the data acquired in the S1;
s3, setting weights of the inventory safety index, the maintenance management index, the diagnosis management index, the CPK index and the FE scoring index in the asset reliability index;
and S4, obtaining the reliability index of the production enterprise assets according to the inventory safety index, the maintenance management index, the diagnosis management index, the CPK index, the FE scoring index and the corresponding weight of the FE scoring index.
Further, the stock safety index adopts a safety stock S r Indicating, safe stock quantity S r The calculation formula of (c) is:
wherein L represents the advance time of product replenishment,
is an average value of the advance time L,
is the average value of daily demand d of the product, z is the number of standard deviations at the service level, sigma d Standard deviation of daily demand d, σ L Is the standard deviation of the advance time L. Where the service level may be understood as an inventory performance goal as determined by the enterprise management layer, the z-value typically takes on the value of 3.
The stock safety index is used to indicate whether the stock of a product is proper or not, and is the expected insurance reserve volume for preventing uncertainty factors (such as a large sudden order, a sudden delay of delivery date, an increase in temporary usage, delivery error, and the like). Zero inventory production, which is the goal pursued by each enterprise. However, zero inventory production requires a higher level of management. Because daily demand, delivery time and the coordination degree of suppliers have more uncertain factors, and if the factors are not well controlled, the production of enterprises is easily influenced by goods failure, and further the delivery of the enterprises is influenced, so that the loss of the enterprises is caused. All services face uncertainties, which vary in origin. From the needs or consumer side, the uncertainty relates to how much and when the consumer purchases. One common practice to deal with uncertainty is to predict demand, but never accurately predict the size of the demand. From a supply perspective, the uncertainty is the needs of the acquiring retailer or manufacturer, and the time it takes to complete the order. Uncertainty may arise from transportation in terms of reliability of delivery, as well as other reasons. The consequences of uncertainty are generally the same, and enterprises are stocked with safety stock to buffer. Given safety stock, the average inventory may be described in terms of one-half of the ordered lot and safety stock. The safe warehouse is not used under normal conditions, and can be used only when the stock is used excessively or the delivery is delayed.
Safe stock S r The calculation of (b) is complicated in actual practice because the amount of difficulty in collecting data is large, and for example, for a manufacturing enterprise or a large and medium-sized retail enterprise having several thousands to several tens of thousands of materials, the difficulty in collecting data on the daily demand and lead time of the materials or products is expected to be large, so that the calculation formula of the safety inventory amount needs to be simplified.
If the lead time L is a constant value, then
Zero value, safe stock S r The calculation formula of (2) is as follows:
at present, many enterprises pay attention to supply chain management, emphasize rapid response and collaborative prediction, implement ERP (enterprise resource planning), SCM (supply chain management system) and electronic commerce to enhance information exchange, greatly improve transportation conditions and on-time delivery, and emphasize management of advanced variation, so that advanced variation can be regarded as small. Under the assumption that the demands are randomly distributed and obey normal distribution and the lead period is unchanged,
the value is zero.
Setting a time unit period T, wherein the unit period T can be one week, one month or one quarter, and the standard deviation of the demand in the unit period T is recorded as sigma T Then the following relationship exists:
then, the safe stock S r Expressed as:
if the lead time L is variable, then
If the value is not zero, setting:
then, the safe stock S r The calculation formula of (2) is as follows:
wherein k is a positive number.
The maintenance management index comprises a field management index and a maintenance index, and the calculation formula of the maintenance management index W is as follows:
W＝aW 1 +bW 2
wherein a and b are constants representing the weights of the field management index and the maintenance index in the maintenance management index, W 1 Denotes a field management index, W 2 Indicating a repair index.
The field management index is calculated by the following formula:
W 1 ＝a 1 T K +b 1 T F
a 1 、b 1 is a constant, T K The method comprises the following steps of (1) representing average fault cognition time, namely the average time from the fault occurrence to the fault point which can be known by field management personnel; t is F Indicating mean time to fail, as to failure occurrenceMean time to fault contact.
The maintenance index is calculated by the formula:
W 2 ＝a 2 T F +b 2 T B
a 2 、b 2 is a constant, T B The mean-time fault interval, i.e. the mean time of the time interval between two adjacent faults, is indicated.
If the fault interval time is prolonged and the fault repairing time is shortened, the equipment has more time to be in a stable working state, and the stability of the equipment or the production line is correspondingly improved.
The diagnosis management index comprises failure prediction accuracy, failure occurrence frequency, failure missing report rate and failure false report rate, wherein the failure prediction accuracy indicates that the equipment parameters are abnormal but the equipment is not shut down, and the ratio of the number of times of finding and removing the failure in the regular maintenance to the total failure is high; the failure occurrence frequency is the reciprocal of the interval time between two adjacent failures; the failure missing report rate indicates that the failure has occurred but is not recorded in the production management system, and the occupation ratio of the failure in the total failure is high; the false fault alarm rate indicates that a fault has occurred but the information reported to the fault point of the maintenance personnel is wrong, and the proportion of the fault in the total fault is high.
The CPK index represents the stability of the production process, and the calculation formula of the CPK index is as follows:
CPK＝C p ×(|1-C a |
C a indicating the accuracy of the production process, C p Indicating the precision of the production process. Collecting process parameters in a production process, wherein the accuracy of the production process refers to the difference between a measured value and a standard value, and the higher the accuracy is, the smaller the difference between the measured value and the standard value is; the precision of the production process refers to the closeness between the measured values of a plurality of parallel measurements, and the higher the precision, the closer the measured values of the plurality of parallel measurements are. The specific calculation method of the CPK can be performed by using the prior art.
Further, the FE score index is obtained by scoring table. The FE comprehensive index is mainly embodied in the use part of the whole system and the use part of plant equipment. The scoring is carried out by giving the equipment to the party B for maintenance according to a main judging means, sudden abnormity cannot occur, the influence on environment and the influence on production are caused, 5s scoring tables can be adopted to score each link, 5s is divided into 5 grades, different grades are represented by different scores, and finally, comprehensive weights are adopted to obtain indexes. Each link comprises all links involved in lithium battery production, and the specific method for scoring each link comprises the following steps: the equipment in each production link is used, and after the equipment is used, scoring is carried out according to the experience feeling of the personnel on the second party, wherein the experience feeling comprises whether the equipment is easy to get on hand and the product quality qualified rate after the equipment is used.
Although the present invention has been described in detail with reference to examples, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present invention.
Claims (9)
1. An asset reliability assessment method, comprising the steps of:
s1, acquiring inventory data of related production products in a production enterprise, maintenance management data of production equipment, fault data of the production equipment, process parameters of the production equipment and use data of a production management system;
s2, generating an inventory safety index, a maintenance management index, a diagnosis management index, a CPK index and an FE scoring index of the asset based on the data acquired in the S1;
s3, setting weights of the inventory safety index, the maintenance management index, the diagnosis management index, the CPK index and the FE scoring index in the asset reliability index;
and S4, obtaining the reliability index of the assets of the production enterprise according to the inventory safety index, the maintenance management index, the diagnosis management index, the CPK index, the FE scoring index and the corresponding weight of the FE scoring index.
2. The asset reliability assessment method according to claim 1, wherein said inventory safety index employs a safe inventory amount S r Indicating, safety stock S r The calculation formula of (2) is as follows:
wherein L represents the advance time of product replenishment,
d is an average of the advance time L, and represents the daily demand of the product,
the average value of daily demand d of the product, z is the number of standard deviations under the service level, sigma d Standard deviation of daily demand d, σ L Is the standard deviation of the advance time L.
3. The asset reliability assessment method according to claim 2, wherein if the advance time L is a constant value, then
Value is zero, safe stock S r The calculation formula of (c) is:
4. the asset reliability assessment method according to claim 3, wherein a unit period T of time is set, and the standard deviation of the demand in the unit period T is denoted as σ T Then the following relationship exists:
then, the safety stock S r Expressed as:
5. the asset reliability assessment method according to claim 4, wherein if the advance time L is variable, then
The value is not zero, and the following steps are set:
then, the safe stock S r The calculation formula of (2) is as follows:
wherein k is a positive number.
6. The asset reliability assessment method according to claim 1, wherein the maintenance management index comprises a field management index and a maintenance index, and the maintenance management index W is calculated by the formula:
W＝aW 1 +bW 2
wherein a and b are constants and represent weights of the site management index and the maintenance index in the maintenance management index, and W 1 Denotes a field management index, W 2 Indicating a repair index.
7. The asset reliability assessment method according to claim 6, wherein the field management index is calculated by the formula:
W 1 ＝a 1 T K +b 1 T F
a 1 、b 1 is a constant, T K The method comprises the following steps of (1) representing average fault cognition time, namely the average time from the fault occurrence to the fault point which can be known by field management personnel; t is F The mean time to failure repair is expressed as the mean time to failure contact after failure occurs.
8. The asset reliability assessment method according to claim 7, wherein the maintenance index is calculated by the formula:
W 2 ＝a 2 T F +b 2 T B
a 2 、b 2 is a constant, T B The mean-time fault interval, i.e. the mean time of the time interval between two adjacent faults, is indicated.
9. The asset reliability assessment method according to claim 1, wherein the diagnostic management index comprises a failure prediction accuracy rate, a failure occurrence frequency, a failure false alarm rate and a failure false alarm rate, wherein the failure prediction accuracy rate indicates the proportion of the number of times that equipment parameters have become abnormal but have not resulted in equipment shutdown, and that failures are found and removed in the periodic maintenance to the total failures; the failure occurrence frequency is the reciprocal of the interval time between two adjacent failures; the failure missing report rate indicates that the failure has occurred but is not recorded in the production management system, and the occupation ratio of the failure in the total failure is high; the false fault alarm rate indicates that a fault has occurred but the information reported to the fault point of the maintenance personnel is wrong, and the proportion of the fault in the total fault is high.
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