JP4777964B2 - Safety management method for plant facilities - Google Patents

Description

  The present invention relates to a safety management method for a plant facility, and more particularly to a safety management method based on a method obtained by improving a known HAZOP method.

  Risk management methods are regarded as important in various industrial fields such as various plant facilities, financial institutions, insurance institutions, and are effectively used. There are various analysis methods for this risk management method. For example, FMEA analysis (defect mode effect analysis), event tree analysis, HACCP analysis (hazard analysis and important control points), HAZOP analysis (latency risk and Investigation and analysis of operability).

  Risk management based on the above HAZOP analysis in order to confirm the potential hazards in the process plant and the operability of the plant, especially the problems that occur when the operation deviates from the design specifications in the plant facilities such as gas and electric power. Has been implemented and has a certain effect.

  Here, HAZOP analysis (Hazard & Operability study) is a method for selecting potential locations (nodes) to be analyzed in the process and confirming potential hazards and operational problems due to deviations in design specifications using guide words. Yes, for example, it consists of the examination flow shown in FIG.

  In the figure, first, a PI diagram (process system diagram) showing devices, apparatuses, piping, and instrumentation is divided into study nodes, and selection of target nodes to be analyzed is first executed (step S1).

  Next, a deviation is assumed by combining the process parameters (flow rate of liquid flowing into XX, etc.) and the guide word at the selected target node (step S2). Here, the guide word is: if not, if ... is increased quantitatively, if ... is decreased quantitatively, ... is increased qualitatively ... is the quality If it decreases, it is a keyword such as when the reverse of... Or an unintended event occurs. These combinations are “when the flow rate of the liquid flowing into OO increases”.

  Next, the cause of the deviation is specified (step S3), and the influence of the deviation on the entire plant process is examined and evaluated (step S4).

  Next, confirm the countermeasures (safeguards) that are currently being implemented for the evaluated impact and evaluate the appropriateness of these countermeasures (step S5). Consider additional measures (step S6).

  One node examines step S1 to step S5, and possibly step S6, and the analysis result is recorded.

  Here, when there are a plurality of assumptions of deviation in step S2, when the analysis up to step S5 or step S6 for one kind of deviation is completed one by one, steps S2 to S5 or step are again performed for another deviation. The analysis up to S6 is repeated (route R1).

  The above flow is executed for one node, the study node is changed, and the analysis flow similar to the above is repeatedly executed (route R2).

  Although the risk management of the plant facility is performed by the conventional HAZOP analysis method described above, in this flow, in the above-described step S4, the influence on the system is examined, that is, the evaluation of the risk of the influence is performed by the evaluator. Because it depends on the subjectivity and the evaluation of the appropriateness of the measures currently taken in step S5 depends on the subjectivity of the evaluator, there are individual differences in the evaluation, and the analysis results are highly objective and reliable. Not necessarily.

  By the way, the technique regarding the apparatus which controls and monitors a plant is disclosed by patent document 1, and it is supposed that a HAZOP analysis method can be used as one of the control and monitoring methods using this apparatus. Looking at the description regarding the HAZOP analysis method in Patent Document 1, it is assumed that a certain range of management thresholds is set at a certain monitoring point, and that it is determined that a deviation has occurred when the threshold value range is exceeded, and this cause is assumed. However, this does not exceed the range of conventional HAZOP analysis techniques. The evaluation of the node components being analyzed still relies on the evaluator's subjectivity, and the safety of plant facilities based on the above issues, ie, HAZOP analysis techniques that yield more reliable analysis results. You cannot get a management method.

JP 2003-167624 A

  The present invention has been made in view of the above-described problems, and relates to a plant facility safety management method based on the HAZOP analysis method, and provides a plant facility safety management method capable of obtaining a more reliable analysis result. The purpose is to do.

  In order to achieve the above object, a plant facility safety management method according to the present invention is a method for executing plant facility safety management based on the HAZOP method, and in the HAZOP method, a plurality of nodes to be analyzed are extracted from a plant process. A first step of identifying and selecting, a second step of combining a process parameter and a guide word existing in the selected node to assume a deviation in the node, and a third step of identifying the cause of the deviation A step, a fourth step for evaluating the influence of the deviation on the entire plant process, and a fifth step for confirming the measures currently taken and evaluating the measures, and further measures Is necessary, it has a sixth step of specifying the additional countermeasure, and the second analysis is performed at the specified separate analysis target node. In the method of performing safety management of a plant facility by repeating the fifth step from the step, or repeating the sixth step from the second step, in the fourth step, the node component that causes the deviation The failure rate and the influence of the cause of the deviation on the plant safety and the influence of the cause of the deviation on the supply of the supply from the plant to the outside of the plant are quantitatively set. The security risk level is set from the influence on the safety and the risk level of the supply is set from the failure rate and the influence on the supply. In the fifth step, the current situation is applied. The measures evaluate the presence or absence of changes in the failure rate of the node components, the presence or absence of changes in the impact on security, and the presence or absence of changes in the impact on supply. Failure rate, the influence of the new security, in which quantitatively reconfigure respective effects on fresh feed, resets the risk level of the supply and risk level security.

  The safety management method of the present invention is improved by adding quantitative evaluation to the known HAZOP method, thereby removing the evaluator's subjectivity as much as possible from the analysis result by the HAZOP method, and improving the objectivity and reliability. The present invention relates to a safety management method for plant facilities based on the HAZOP method.

  In addition, as a plant facility to which the safety management method of the present invention is applied, a gas plant facility that supplies city gas in which LNG is vaporized, or a power plant facility that supplies electric power generated by thermal power generation, hydroelectric power generation, nuclear power generation, etc. It covers various plant facilities such as steel plant facilities and chemical plant facilities.

  In the safety management method of the present invention, in the fourth step of evaluating the influence of the deviation identified in the third step on the entire plant process, the failure rate of the node component causing the deviation and the node component The impact on safety in the event of a failure (failure of other components of the plant facility, the safety of the plant facility, etc.), and the impact of the supply in the event of failure of this node component (provided from the plant to the outside of the plant) (Effects on supply of supplied products such as gas and electric power) are evaluated quantitatively.

  The node constituent element is one in which any one of various devices constituting the node is specified by the analysis target node selected in the first step. For example, in an LNG gas plant facility, when seawater is provided to a vaporizer on the downstream side of the LNG payout line, and an analysis target node that supplies city gas in which LNG is vaporized by the seawater is taken up, Constituent elements include a suction strainer on the inlet side of the vaporizer, a flow meter on the inlet side of the vaporizer, a thermometer and pressure gauge on the outlet side of the vaporizer, an FCV (flow control valve) and an ESV (emergency shutdown valve) on the inlet side of the vaporizer, An example is a seawater pump.

  The failure rate of the specified node component is the manufacturer or past performance, for example, if there is a record that the number of devices that can be destroyed in one year out of 10 is one, the failure rate may be 10%, Objectively evaluate the failure rate of a node component based on past performance, etc., such as setting the failure rate to 10% when the track record of failure in one year was once in the past 10 years . Further, ranks may be classified for each range of the failure rate. For example, if the failure rate is less than 10%, the rank can be divided into ranks of 1 and 10 to 40%, the rank can be 2;

  On the other hand, when a specific deviation occurs due to a cause such as a failure of a certain node component, this degree of influence is set to 3 ranks to 5 with respect to how much this affects the security aspect and the supply aspect. The rank is divided into ranks in advance. With regard to the influence that a specific deviation caused by an arbitrary cause has on the security aspect and the supply aspect, it is assumed which rank in the rank corresponds to this, and the degree of each influence is quantitatively ranked. For example, assuming a seawater pump abnormality as a cause for a node shift that causes a decrease in seawater line flow rate, the degree of impact on security and supply when the seawater line flow rate is reduced due to an event that causes this Are quantitatively set such as influence rank 3 and influence rank 2 respectively.

  Since the failure rate of a certain node component is determined and the influence rank of the cause of the failure of the node component on the security and supply is determined, this failure rate (or rank based on the failure rate) and the security impact rank If the value multiplied by is less than or equal to an arbitrary threshold, the security risk level is A (for example, when the risk level is ranked 4 to A to D, the risk level A is the lowest risk evaluation, and B, C, Risk increases in the order of D). At the same time, the risk level on the supply side can be determined by comparing the threshold value with a value obtained by multiplying the failure rate and the supply influence rank.

  Each risk level for security and supply determined here is a risk level in the state that does not take into account the currently planned or already installed safeguards (currently implemented measures). Therefore, in the next fifth step, whether or not there is a change in the failure rate of the node component, whether or not there is a change in the impact on security, and whether or not there is a change in the impact on the supply is evaluated by the measures currently taken, The new failure rate after the countermeasure, the impact on the new security, and the impact on the new supply are quantitatively reset, and the security risk level and the supply risk level are reset.

  For example, a deviation in which the pressure (process parameter) of the LNG on the vaporizer inlet side increases (guide word) is assumed in the second step, and the cause of this deviation in the third step is the liquid seal before and after the FCV. , And the failure rate of this automatic valve is 40%, the impact on safety is 4 at the maximum, and the safety risk level is D and the highest risk level. In addition, if the safeguard that is actually planned sounds an alarm and thereby protects the piping by automatically or manually opening the safety valve, this safeguard eliminates the security risk. The impact on security when considering safeguards is reassessed as 1. On the other hand, although the failure rate of the automatic valve is unchanged because it does not change with this safeguard, the safety risk level that is multiplied by this failure rate and the re-evaluated impact rank 1 is lower than before safeguard consideration. Thus, it is possible to rise from rank D before safeguard to rank B.

  As described above, the risk level given to security and supply by a specific deviation deceived by the cause of any node component without taking into account the safeguard that is currently planned, etc. is quantitatively evaluated, and then the safeguard Based on an objective HAZOP method in which the subjectivity of the evaluator is eliminated by quantitatively reassessing the level of risk given to security and supply by a specific deviation deceived by the cause of the node component Safety management of plant facilities can be realized.

  In addition, by adopting this quantitative evaluation, it is possible to objectively confirm the necessity of safeguards, and when it is determined that any planned safeguards are unnecessary, the safeguard from the plant facility. This also leads to simplification of the facility.

  If the risk level for safety and supply is reassessed in consideration of the safeguard in the fifth step and the risk level assessment is to be increased (lower risk level), the sixth step Go to, consider additional measures, and identify them.

  The risk level related to security and supply will be quantitatively evaluated again by the specified additional measures, and it will be confirmed again whether the required risk level has improved.

  After the flow from the second step to the fifth step, as necessary, to the sixth step is completed, the cause of the same deviation is identified in the third step for the cause of the same deviation, The risk level on the security and supply sides is quantitatively evaluated again using the same flow.

  According to the safety management method of the present invention described above, a failure rate of an arbitrary node component specified for an arbitrary deviation, and a quantitative value regarding the degree of influence that the failure of the node component has on the security and supply aspects By taking the above into consideration, each risk level can be quantitatively evaluated to obtain a risk level with higher credibility and reliability. Further, by quantitatively reassessing the risk level in consideration of the currently planned safeguard, it is possible to objectively confirm whether the safeguard is necessary or not and whether the risk level has been improved.

  Note that the safety management method based on the improved HAZOP method described above may be performed by a group of a plurality of managers executing each step sequentially based on various data, or may be automatically analyzed by a computer. It may be a form. In the case of this automatic analysis, all data, for example, a plurality of analysis target nodes in the plant facility (an LNG delivery system from the LNG storage tank, an LNG receiving / dispensing system to the heat exchanger, a BOG reliquefaction system, The node components constituting the LNG gasification system in the vaporizer, the failure rate, the safety level of the failure of each node component, the influence level value on the supply side, etc. are stored as data in the storage means in the computer, Each examination step to be performed is also built in the computer, and when a desired analysis target node is selected, a process parameter and a guide word are combined and an assumed deviation is automatically output. The possible causes for the output deviation are listed, and for each listed cause, the corresponding node components and their defects are listed, and the above steps are executed sequentially.

  In another embodiment of the plant facility safety management method according to the present invention, the failure rate is updated as needed based on maintenance data of the node components.

  Various devices that are node components are regularly maintained, but in this embodiment, the failure rate at that time is re-evaluated from the state of the node component at the time of maintenance, and the above-mentioned The failure rate in step 4 is updated, and the HAZOP analysis is performed using the updated failure rate.

  Further, the maintenance data history described above may be stored as RBM (risk-based maintenance) data, and a failure rate based on the RBM data may be used as the failure rate of the node component.

  The history of maintenance data is used as data when the plant facility is safely managed by the RBM. Therefore, by using this data history when calculating the failure rate of the safety management by the improved HAZOP method described above, the failure rate of the node component can be calculated based on the data having more measurement matrix, It becomes possible to further improve the reliability of the failure rate.

  As can be understood from the above description, according to the plant facility safety management method according to the present invention, the risk level given to the security and supply aspects by the failure of any node component is quantitatively evaluated. Based on this, it is possible to carry out safety management of facilities with high reliability and objectivity.

  Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a flowchart illustrating an improved HAZOP method used in the safety management method of the present invention, FIG. 2 is a diagram illustrating a specific example of steps S2 to S4 in FIG. 1, and FIG. FIG. 4 is a diagram illustrating a specific example of steps S2 to S6 with respect to one cause of deviation in FIG. 4, and FIG. 4 is a schematic diagram illustrating each step of FIG. In the illustrated embodiment, the vicinity of the vaporizer in the LNG gas plant is used as an analysis target node. However, it goes without saying that the safety management method of the present invention can be applied to a safety management method for various power plants and the like. Moreover, the deviation specified in the figure and its cause are merely examples.

  FIG. 1 is a flowchart illustrating the improved HAZOP method used in the safety management method of the present invention. The difference from the conventional HAZOP method shown in FIG. 5 is that in step S4, the influence of the cause of the deviation specified in step S3 on the whole plant process is quantitatively evaluated, and in step S5, the present situation is applied. It is a point that measures (safeguard) are quantitatively evaluated in the same way. In addition, when an additional measure is required, the quantitative evaluation after this additional measure is also performed at step S6.

  The quantitative evaluation in steps S4 and S5 shown in FIG. 1 will be specifically described with reference to FIGS. Note that this embodiment is intended for an LNG gas plant facility, and FIG. 2 shows the vicinity of the carburetor as an analysis target node. In the more detailed embodiment of FIG. 3, a seawater line is provided around the carburetor. This is explained by taking a seawater pump abnormality (trip) that can be one of the causes for the deviation of the flow rate of the water.

  In safety management around the carburetor in the LNG gas plant facility, for example, as shown in FIG. 2, the LNG flow rate on the carburetor entry side decreases, the pressure on the carburetor entry side increases, the flow rate of the seawater line increases. Various deviations are assumed, such as decreasing.

  For example, when a deviation in which the LNG flow rate on the carburetor inlet side is reduced is assumed in step S2, the cause may be a clogging of an intake strainer, a check valve stuck, a carburetor inlet Causes such as side flow meter failure can be identified.

  The suction strainer clogging is thought to have no effect on the safety of the plant facilities, but the effect on the gas supply surface is that the clogging of the suction strainer directly leads to a decrease in the flow rate.

  Here, if an LNG strainer purchased from a specific manufacturer is taken as a node component, the failure rate is calculated to be 1.0% from the past results, and this is entered in the sheet.

  A failure rank of 1 is assigned to this failure rate of 1.0%. The failure rank is set in advance according to the failure rate. For example, the failure rank for a failure rate of less than 10% is 1, the failure rank for a failure rate of 10 to 40% is 2, and the failure rate is more than 40%. The failure rank is set to 3, and so on.

  On the other hand, when the LNG strainer breaks down and the flow rate of the carburetor decreases based on this, the impact on safety and the impact on (gas) supply are, for example, four of the impact ranks that are pre-ranked The influence rank is set on the assumption of which rank it corresponds to.

  In this embodiment, when an LNG strainer is selected as a node component and it fails and the flow rate of the carburetor is reduced due to this failure, the degree of influence on safety and supply is a quantitative value of ranks 1 and 3, respectively. Is determined (set).

  As described above, the risk quantitative evaluation is from the setting of the node component to the quantitative impact evaluation on security and supply.

  Failure rate in risk quantitative evaluation: Failure rank: 1 corresponding to 1.0%, safety impact rank: 1, and impact impact on supply: 1 and 3, respectively multiplied by 3, are calculated, With respect to these values, the risk level evaluation on the security side is specified as A rank, and the risk level evaluation on the supply side is specified as C rank. Here, each risk level evaluation is classified into, for example, five ranks A +, A, B, C, and D in ascending order of the risk level, and the risk level evaluation for the above multiplied value is security and supply. It may be the same or different on the surface. For example, even if the value obtained by multiplying the failure rank and the impact level is 2 for both security and supply, the risk level for safety is A rank, while that for supply is B rank. Sometimes. The definition of the risk level is not particularly limited, but can be defined as follows, for example. That is, the risk level: A + is a sufficiently acceptable level, and the current periodic inspection may be excessive, and the frequency of inspection needs to be reviewed. Risk level: A is acceptable Risk level: B is a condition that is acceptable under certain conditions, and needs to be improved in the current periodic inspection, etc. Risk level: C Is a level that requires a plan change, and the current periodic inspection is insufficient and requires significant improvement. Risk level D is an unacceptable level, and the current periodic inspection is extremely insufficient. In other words, it is necessary to take measures to reduce the risk level immediately.

  As another embodiment of risk level evaluation for security and supply, there is a method of using a risk matrix set in advance for each risk level evaluation. For example, by creating a risk matrix in which failure ranks 1 to 4 corresponding to failure rates of node components are set on the vertical axis of the matrix, and impact ranks 1 to 4 are set on the horizontal axis of the matrix In addition, a risk level evaluation rank is set in a cell corresponding to an arbitrary failure rank and a security influence rank. As an example, if both the failure rank and the influence rank on safety are both 1, A + having the lowest risk level is set in the cell corresponding to this, or if both are 4, it corresponds. When D having the highest risk level is set in the cell, or when the failure rank is 2 and the safety influence rank is 2, the risk level: B is set. It should be noted that the risk matrix related to the node components and the influence rank on supply can be created in the same manner.

  As described above, since the risk matrix is set in advance, the administrator can easily visually recognize the risk level for security and supply, which leads to an increase in the efficiency of the HAZOP analysis.

  The impact of the identified discrepancies on the entire plant process, specifically, the security risk level and the supply risk level are quantitatively evaluated based on the failure rate of the identified node components and planned In step S4, an impact evaluation is performed in a state where the existing safeguard is not taken into consideration.

  Quantitative evaluation will be performed in the same manner for the sticking of the check valve, which is another cause of the deviation.

  Step S5 for quantitatively evaluating the risk level again in consideration of the currently planned safeguard will be described in detail with reference to FIG. 3 and FIG. 4 schematically illustrating this.

  In FIG. 3, the risk quantitative evaluation (S4) when there is no safeguard and the current safeguard when the cause is determined to be due to the seawater pump abnormality for the deviation that the flow rate has decreased in the seawater line The risk quantitative evaluation (S5) when considering the above is shown.

  This will be explained with reference to FIG. 4. Cryogenic LNG delivered through a heat exchanger, a drum, etc. (not shown) is sent to the vaporizer 10 via the LNG inlet line 20 and loaded in the seawater S. Seawater S is sent from the installed seawater pump 40 to the carburetor 10 via the seawater supply line 50, and the LNG introduced into the carburetor 10 is sprayed with the seawater S to be vaporized into city gas. The gas is discharged through the gas discharge line 30.

  Here, the LNG inlet side line 20 is provided with an FCV (flow control valve 21) and an ESV (emergency shutdown valve 22), which are further provided with a vaporizer outlet side thermometer 31 provided in the city gas discharge line 30. It is connected to. The temperature of the city gas to be dispensed is provided with a two-stage threshold value (a temperature lower in the order of the first threshold value and the second threshold value), and the measured temperature of the vaporizer outlet-side thermometer 31 is higher than the second threshold value. However, when the temperature is equal to or lower than the first threshold, it is specified that sufficient seawater S is not supplied to the vaporizer 10, and the flow control valve 21 is closed or its opening degree is adjusted to vaporize. The amount of LNG flowing into the vessel 10 is limited.

  When the temperature measured by the vaporizer outlet thermometer 31 is an extremely low temperature equal to or lower than the second threshold, it is specified that the seawater is hardly supplied, and the emergency shutdown valve 22 is closed to the vaporizer 10. LNG inflow is completely stopped. As described above, FCV and ESV are controlled to be closed in conjunction with the vaporizer outlet-side thermometer 31.

  Returning to FIG. 3, the impact on safety that is assumed when the cause of the deviation is identified as a seawater pump abnormality is that the carburetor tube and the carburetor outlet piping are damaged by the cryogenic LNG. The effect is that the gas supply is stopped because city gas is difficult or not generated in the vaporizer.

  Here, when the seawater pump is used as the node component, the failure rate of the seawater pump used is 13.0%, for example, and 2 is assigned to the failure rank linked to this. Furthermore, the impact on safety when the seawater pump breaks down is 3 and the impact on supply is set to 3 together with a large impact rank, and the failure rank 2 is multiplied by the impact ranks 3 and 3, respectively. Quantitative risk evaluation is performed in a state where the safety risk level is C rank and the supply risk level is B rank and the safeguard is not considered.

  Next, the risk is quantitatively evaluated considering the two valves described in FIG. 4 as a safeguard. By taking these valves into consideration, the flow rate of LNG is limited or completely cut off in some cases, so that the carburetor tube and the outlet side of the vaporizer are not damaged by the cryogenic LNG. As a result, a value obtained by multiplying the failure rank 2 and the security impact rank 1 by 2 increases the security risk level evaluation to the A rank. As for the impact on supply, the supply level of city gas is still restricted by this safeguard, and in some cases the supply will be zero, so the risk level on the supply side when considering safeguard is rank B There is no change.

  The administrator in the present embodiment determines that the risk level evaluation result when this safeguard is taken into consideration is sufficient, and determines that an additional measure in step S6 is unnecessary. If you want to take additional measures and raise the risk level assessment on the supply side to rank A, consider additional measures other than safeguards that are not currently planned, and consider the risk when considering these additional measures. A quantitative evaluation and a risk level evaluation may be performed in the same manner.

  Further, by using the failure rate in which the maintenance data history is stored as RBM data as the failure rate shown in the figure, it is possible to perform an improved HAZOP analysis based on a more accurate failure rate.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and there are design changes and the like without departing from the gist of the present invention. They are also included in the present invention. For example, the safety management method based on the above-described improved HAZOP method may be automatically analyzed by a computer. In this case, various data and flows are stored in a storage unit in the computer, and the latest failure rate based on the maintenance data is also stored in this storage unit as needed. The calculation unit in the computer multiplies the rank data of the failure rate, the security aspect, and the supply aspect, and accumulates the values in the storage part. When an administrator selects an arbitrary node to be analyzed, the information shown in FIGS. 2 and 3 is displayed on the screen of the computer display unit, and the administrator performs safety management while checking the screen display. It is something that can be done. The storage unit, the calculation unit, and the display unit are connected by a bus in the computer and are controlled by the CPU.

It is the flowchart explaining the improved HAZOP method used with the safety management method of this invention. It is the figure explaining the specific example of step S2-step S4 in FIG. It is the figure explaining the specific example of step S2-step S6 with respect to the cause of one shift | offset | difference in FIG. It is the schematic diagram explaining each step of FIG. It is the flowchart explaining the HAZOP method used with the conventional safety management method.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 10 ... Vaporizer, 20 ... LPG inlet side line, 21 ... FCV (flow control valve), 22 ... ESV (emergency shutdown valve), 30 ... City gas discharge line, 31 ... Vaporizer outlet side thermometer, 40 ... Seawater pump 50 ... Seawater supply line

Claims (4)

A method for executing safety management of a plant facility based on the HAZOP method, wherein the HAZOP method includes a first step of identifying and selecting a plurality of nodes to be analyzed from a plant process, and existing in the selected node A second step of combining a process parameter and a guide word to assume a shift at the node, a third step of identifying the cause of the shift, and a fourth step of evaluating the effect of the shift on the entire plant process And at least a fifth step for confirming the currently implemented countermeasures and evaluating the countermeasures, and further including a sixth step for specifying the additional countermeasures when additional countermeasures are required And repeat the fifth step from the second step at the specified separate analysis target node, or from the second step By repeating the six steps of a method to perform safety management of the plant facilities,
In the fourth step, the failure rate of the node components that cause the deviation, the influence of the cause of the deviation on the plant security, and the supply of the supply from the plant to the outside of the plant. And setting the risk level of supply from the failure rate and the influence on the supply, and setting the risk level of supply from the failure rate and the influence on the supply. And
In the fifth step, the presence / absence of a change in the failure rate of the node component, the presence / absence of a change in the impact on security, and the presence / absence of a change in the impact on the supply are evaluated according to the measures currently taken. A plant facility that resets the security risk level and supply risk level quantitatively by resetting the new failure rate after countermeasures, new security impact, and new supply impact. Safety management method. When the safety management method includes the sixth step,
The additional measures evaluate the presence or absence of a change in the failure rate of the node component, the presence or absence of a change in the impact on security, and the presence or absence of a change in the effect on the supply. The safety of the plant facility according to claim 1, wherein the safety risk level and the supply risk level are further reset by quantitatively resetting each of the impact on safety and the impact on new supply. Management method.   The plant facility safety management method according to claim 1, wherein the failure rate is updated as needed based on maintenance data of the node component.   The safety management of the plant facility according to claim 3, wherein a history of the maintenance data is accumulated as RBM (risk-based maintenance) data, and a failure rate based on the RBM data is used as the failure rate of the node component. Method.

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