The present invention relates to a maintenance service method and a maintenance service system used in providing maintenance services.
Maintenance services in recent years have developed from time-based maintenance for replacing an apparatus in a fixed period into state-based maintenance for applying a machine failure diagnosis technique to monitor machine part states of an apparatus and replacing machine parts in order from a machine part that is most likely to fail and into risk-based maintenance for drawing up a replacement schedule taking into account a tradeoff between costs for replacing an apparatus and the magnitude of a risk in actual occurrence of a failure. Various maintenance service systems for efficiently performing maintenance services have been sophisticated.
As a background art in this technical field, there is JP-A-2008-9990 (Patent Literature 1) The publication has an object of “providing a technique that can reduce costs concerning maintenance pots and also reduce downtime of products” and describes, as one means for solving problems, “calculating, on the basis of a failure probability distribution of consumable supplies, a value in the vicinity of an interval at which the failure probability is predicted to be equal to or higher than a predetermined probability” as a replacement interval of machine parts
In general, even if it is attempted to estimate, concerning single machine parts of an apparatus, a failure probability distribution on the basis of maintenance history data, it is necessary to collect, as a data set to be used, failure instances by an amount corresponding to types of maintenance history data of machine parts in use. When a sufficient amount of failure instances cannot be collected, it is difficult to estimate an accurate failure probability from the maintenance history data For example, the maintenance history data is created for each of companies to which maintenance services are provided. Therefore, a sufficient amount of failure instances cannot be collected simply by calculating a failure probability in each of the companies. It is difficult to estimate an accurate failure probability.
In Patent Literature 1, on the basis of a failure probability distribution of consumable supplies, a value in the vicinity of an interval, at which the failure probability is predicted to be equal to or higher than a predetermined probability is calculated as a replacement interval of machine parts, in this case, concerning consumable supplies reaching the predetermined probability or more, replacement is carried out even if the consumable supplies are machine parts for which the replacement is unnecessary. Therefore, it is likely that the replacement of the machine parts is performed more than necessary.
Therefore, it is an object of the present invention to provide a maintenance service method capable of reducing the number of machine parts to be replaced while suppressing the number of times of failures of an apparatus even when an accurate failure probability distribution cannot be estimated concerning single machine parts.
In order solve the problems, the present invention is characterized by setting, according to at least one of a failure probability distribution and a performance deterioration probability distribution set for each of machine part types, the number of machine parts to be replaced, setting machine part replacement priority from at least one of the probability distribution and an operation situation or a machine part state, and listing, according to the machine part replacement priority, machine parts equivalent to the number of machine parts to be replaced.
Advantageous Effect of Invention
According to the present invention, even when an accurate failure probability distribution cannot be estimated concerning single machine parts, since machine parts having high failure probabilities or high performance deterioration probabilities of an apparatus among an entire machine part group are preferentially replaced, it is possible to suppress an increase in the number of failure or performance deterioration cases. Further, since replacement of an appropriate number of machine parts conforming to a failure probability or performance deterioration probability distribution is performed, it is possible to reduce the number of machine parts to be replaced and reduce maintenance costs.
Embodiments of the present invention are explained below with reference to the drawings. Note that the present invention can be applied to, for example, maintenance services for elevators and escalators and maintenance services in railroads, plants, buildings, factories, and the like.
First, functions of the maintenance client 1 are explained. The service-ID checking and registering unit 101 acquires, from a user of the maintenance client 1, a service identification number (hereinafter, service ID) of a maintenance target apparatus input from the input/output unit 105. By inquiring the service-ID managing unit 201 of the maintenance server 2 about the acquired service ID, the maintenance client 1 can acquire profile information of the maintenance service such as a type and a period of a contract, a maintenance target apparatus, and a replacement target machine part. When the service ID is not managed by the service-ID managing unit 201, the service ID can be registered as a new service ID together with the profile information of the maintenance service.
The machine-part-information updating unit 102 stores, in the operation information database 209, via the database managing unit 207 of the maintenance server 2, operation information necessary for a maintenance service such as operation times and the numbers of times of operation and average loads and cumulative loads of an apparatus and machine parts configuring the apparatus input by the user via the input/output unit 105. The machine-part-information updating unit 102 stores maintenance history information such as update periods of the machine parts in the maintenance history database 210. Further, the machine-part-information updating unit 102 stores, in the apparatus information database 208, apparatus information such as types and the numbers of machine parts configuring apparatuses, replacement target machine parts serving as replacement targets among the machine parts, and a failure or performance deterioration, probability distribution of each of machine part types of the replacement target machine part.
The machine-part-state setting unit 103 stores, in the machine part state database 212, via the database managing unit 207 of the maintenance server 2, information concerning machine part states such as a damage state and abnormality of machine parts obtained during maintenance work input, by the user via the input/output unit 105.
The maintenance-schedule acquiring and updating unit 104 acquires, via the database managing unit 207, maintenance schedule information such as an implementation planned period of maintenance work, a machine part replacement period, and a replacement target machine part stored in the maintenance schedule database 211. The maintenance-schedule acquiring and updating unit 104 stores, in the maintenance schedule database 211, maintenance schedule information obtained by the user changing the acquired maintenance schedule information via the input/output unit 105.
Functions not explained above among the functions of the maintenance server 2 are explained. The failure-or-performance-deterioration-rate-by-machine-part-type calculating unit 202 calculates, using a failure or performance deterioration probability distribution for each of machine part types stored in the apparatus information database 208, a failure rate at which an apparatus fails or causes performance deterioration because of machine parts of certain machine part type. The failure-or-performance-deterioration-rate-by-machine-part-type calculating unit 202 learns, using maintenance history information concerning whether replacement of a machine part was necessary in actual maintenance work stored in the maintenance schedule database 211, a failure or performance deterioration probability distribution of the machine part type. As a learning method, it is possible to learn the failure or performance deterioration probability distribution using general Bayesian learning. Other methods may be used. Consequently, it is possible to improve accuracy of the failure or performance deterioration probability distribution.
The maintenance-schedule creating unit 205 creates, using the order of the machine part replacement priority calculated by the machine-part-replacement-priority calculating unit 203 and the number of machine parts to be replaced calculated by the machine-part-replacement-number calculating unit 204, a maintenance schedule mainly including replacement periods of machine parts and replacement target machine parts. The series of processing by the functions is explained in detail below.
If the replacement of the machine part is not appropriate in step S108, in step S107, the machine-part-information updating unit 102 stores a difference between the replacement schedule and actual work in the maintenance history database 210. If a replacement schedule of a machine part is absent at the point of the maintenance work in step S104, in step S105, the maintenance operator checks an actual machine part state and checks whether replacement of the machine part is unnecessary If the replacement of the machine part is necessary in step S105, although the replacement of the machine part is absent in the work schedule, the maintenance operator replaces the machine part in step S106. In step S107, the machine-part-information updating unit 102 stores the difference between the replacement schedule and the actual work in the maintenance history database 210. If the check of the replacement schedule of the machine part and the machine part replacement end, in step S110, the machine-part-information updating unit 102 stores maintenance content in the maintenance history database 210 with the point of the maintenance work set as an update period and updates machine part information such as operation times and the numbers of times of operation and average loads and cumulative loads of the maintenance target apparatus and the replacement target machine parts and stores the machine part information in the operation information database 209. By adopting such a procedure, the maintenance operator can perform the maintenance work using the maintenance client 1.
In step S203, the maintenance-schedule creating unit 205 specifies a schedule creation unit period in which a maintenance schedule is created. In step S204, the failure-or-performance-deterioration-rate-by-machine-part-type calculating unit 202 calculates a failure ratio in the schedule creation unit period for each of machine parts from failure or performance deterioration probability distribution for each of machine part types. (In the following explanation, although description is omitted concerning a performance deterioration rate, the performance deterioration rate may be calculated using the performance deterioration probability distribution according to necessity.) The failure rate indicates at which rate the machine part fails in the schedule creation unit period. In step S205, the machine-part-replacement-number calculating unit 204 integrates the failure rate concerning all machine parts of the machine part type managed by a maintenance company. The integrated failure rate corresponds to an expected value of the number of machine parts failing in the schedule creation unit period of the machine parts of the machine part type. That is, if the machine parts are replaced by the number of this numerical value, even if replacement is not performed for the other machine parts, it is possible to suppress the number of machine parts that actually fail. In this calculation, failure instances concerning all the machine parts of the machine part type managed by the maintenance company can be utilized. Therefore, even when only client companies cannot collect a sufficient amount of failure instances, it is possible to provide a maintenance service with a more accurate probability distribution while suppressing the number of times of failure of the apparatus. Note that the present invention does not always have to be applied to all the machine parts of the machine part type managed by the maintenance company and may be applied to a part of the machine parts if a sufficient amount of instances to which the present invention can be applied are provided.
In step S206, the machine-part-replacement-priority calculating unit 203 calculates machine part replacement. priority of the machine parts in the schedule creation unit period using the failure rate and the information concerning the machine part state acquired from the machine part state database 212. Details of processing in step S204 to step S206 are explained below. The maintenance-schedule creating unit 205 allocates, according to the machine part replacement priority obtained in step S206, as replacement machine parts in the schedule creation unit period, the machine parts equivalent to the number of machine parts to be replaced obtained in step S205 (step S207). When the allocation of the replacement machine parts ends concerning all schedule creation periods in step S202, in step S208, the maintenance-schedule creating unit 205 outputs the allocation of the replacement machine parts as a replacement machine parts list. When the repetition for each of the machine part types in step S201 ends, in step S209, the maintenance operator adjusts a schedule using the replacement machine parts list of all the machine part types.
By adopting such a configuration, even when an accurate failure probability distribution cannot be estimated. concerning the single machine parts, by using the maintenance history database managed by the maintenance company, it is possible to reduce the number of machine parts to be replaced while suppressing the number of times of failure of the apparatus and reduce maintenance costs necessary for a maintenance job. Qualitatively, it is possible to reduce maintenance costs in all the machine parts managed by the maintenance company taking into account variations of the machine parts in the failure probability distribution of each of the machine part types using the failure probability distribution rather than reducing maintenance costs using variation of the failure probability distribution of each of the single machine parts.
Details are explained in order concerning the calculation of the failure rate in step S204, the calculation of the number of machine parts to be replaced in step S205, and the calculation of the machine part replacement priority in step S206.
In step S304, the failure-or-performance-deterioration-rate-by-machine-part-type calculating unit 202 acquires a failure or performance deterioration probability distribution of the machine part type of the machine part from the apparatus information database 208. In step S305, the failure-or-performance-deterioration-rate-by-machine-part-type calculating unit 202 calculates a failure rate in the schedule creation unit period of the machine part from an initial. load and an end time load of the probability distribution. The failure rate indicates at which rate the apparatus fails or is deteriorated in performance because of the machine part in the schedule creation unit period. As a specific calculation method, the failure rate is calculated as a rate of a probability that the apparatus fails or is deteriorated in performance from an initial load point to an end time load point of the cumulative load to a probability that the apparatus does not fail or is not deteriorated in performance before the initial load point of the cumulative load. An example of the failure rate in step S304 and step S305 is explained with reference to
The calculation of the number of machine parts to be replaced in step S205 is explained with reference to
The calculation of the machine part replacement priority in step S206 is explained with reference to
By adopting the configuration in step S205, while suppressing the number of failure occurrence cases, it is possible to use the machine parts for a long period and reduce maintenance costs compared with a maintenance service system for replacing all machine parts, the probability 403 of which reaches a fixed value.
In the calculation of the machine part replacement priority in step S206, by adopting such a configuration, it is possible to calculate machine part replacement priority concerning all the machine parts managed by the maintenance company. Besides, for example, it is also conceivable to adopt a method of performing grouping at the cumulative load points 404 of the machine parts and performing rearrangement of the machine parts belonging to each of groups. However, in that case, when the numbers of machine parts belonging to the groups are small, it is likely that imbalance occurs between the number of failure or performance deterioration cases to occur and the number of machine parts to be replaced. Therefore, it is desirable to calculate the machine part replacement priority concerning all the machine parts managed by the maintenance company.
A replacement machine parts list 601 shown in
These calculations are explained using a simple example. For example, it is assumed that a failure or performance deterioration probability in a certain machine part type is calculated as shown in
With the configuration explained above, according to the present invention, since the machine parts having high failure or performance deterioration probabilities in the entire machine part group are preferentially replaced, it is possible to suppress an increase in the number of failure or performance deterioration cases and it is possible to reduce maintenance costs for performing replacement of an appropriate number of machine parts conforming to a failure r performance deterioration probability distribution.
Filing Document | Filing Date | Country | Kind |
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PCT/JP2013/072939 | 8/28/2013 | WO | 00 |