CN114742436A - Enterprise management system based on cloud computing and Internet of things - Google Patents
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Abstract
The invention discloses an enterprise management system based on cloud computing and Internet of things, which relates to the technical field of enterprise management and solves the technical problem that the enterprise management system in the prior art cannot accurately acquire the influence factors of the operation state of an enterprise to reduce the management efficiency of the enterprise; influence factor analysis is carried out on the operation abnormal object, and the reason for abnormal operation of the operation abnormal object is judged through the influence factor analysis, so that the management and control efficiency of an abnormal operation enterprise is improved, and the efficiency and the accuracy for recovering the abnormal operation state to the normal state are facilitated; and carrying out internal analysis management and control on the corresponding operation abnormal object according to the corresponding influence factor, and carrying out analysis control according to the influence factor can improve the stable efficiency of enterprise operation.
Description
Technical Field
The invention relates to the technical field of enterprise management, in particular to an enterprise management system based on cloud computing and the Internet of things.
Background
An enterprise management system refers to software which can embody most functions (including decision, planning, organization, leadership, monitoring, analysis and the like) of enterprise management, can provide real-time, relevant, accurate and complete data, and provides decision bases for managers. The enterprise management software can be divided into various types such as enterprise document management, financial management, workshop management, purchase, sale and stock management, asset management, cost management, equipment management, quality management, distribution resource planning management, human resource management, supply chain management, customer relationship management and the like by module division.
However, in the prior art, the enterprise management system cannot accurately acquire the influencing factors of the enterprise operation state, so that the enterprise management efficiency is reduced, the control of the enterprise operation stability is not facilitated, meanwhile, the enterprise influencing factors cannot be subjected to targeted management and control, and the operation stability recovery efficiency of the enterprise is low.
In view of the above technical drawbacks, a solution is proposed.
Disclosure of Invention
The invention aims to solve the problems, and provides an enterprise management system based on cloud computing and the internet of things, which monitors the operation state of an analysis object in real time and performs analysis and judgment when the operation state of the analysis object is abnormal, so that enterprise management and control are performed according to the analysis and judgment, the influence of the operation state on an enterprise is reduced, and the enterprise management efficiency is improved; influence factor analysis is carried out on the operation abnormal object, and the reason for abnormal operation of the operation abnormal object is judged through the influence factor analysis, so that the management and control efficiency of abnormal operation enterprises is improved, and the efficiency and the accuracy for recovering the abnormal operation state to be normal are facilitated.
The purpose of the invention can be realized by the following technical scheme:
the utility model provides an enterprise management system based on cloud calculates and thing networking, includes the cloud computing platform, and the cloud computing platform marks each enterprise as analysis object, and the cloud computing platform communication is connected with:
the enterprise operation analysis unit is used for carrying out operation analysis on the analysis object, monitoring the operation state of the analysis object in real time, generating an operation normal signal and an operation abnormal signal through the operation analysis, and sending the operation normal signal and the operation abnormal signal to the cloud computing platform; marking an analysis object corresponding to the operation abnormal signal as an operation abnormal object, analyzing the operation abnormal object to generate a self-influence signal and a non-self-influence signal, and sending the self-influence signal and the non-self-influence signal to the cloud computing platform;
the influence factor dividing unit is used for analyzing influence factors of the abnormal operation object, dividing the influence factors of the abnormal operation object into decision influence and execution influence through the influence factor analysis, and sending the abnormal operation object and the corresponding influence factors to the internal analysis management and control unit;
the internal analysis and control unit is used for carrying out internal analysis and control on the corresponding operation abnormal object according to the corresponding influence factors, carrying out analysis and control according to the corresponding type influence factors, simultaneously generating a decision-making controlled signal and an execution controlled signal, and sending the decision-making controlled signal and the execution controlled signal to the cloud computing platform;
and the feasibility prediction unit is used for performing feasibility prediction on the control of the corresponding operation abnormal object, generating a control abnormal signal and a control normal signal through the feasibility prediction, and correspondingly sending the control abnormal signal and the control normal signal to the internal analysis and control unit and the cloud computing platform.
As a preferred embodiment of the present invention, the operation process of the enterprise operation analysis unit is as follows:
setting an analysis time period, acquiring the current total business amount of an analysis object and the growth speed of the corresponding total business amount in the analysis time period, and comparing the current total business amount with a business amount threshold value and a growth speed threshold value respectively:
if the current total operation amount of the analysis object exceeds a turnover amount threshold value or the increase speed of the corresponding total operation amount exceeds an increase speed threshold value in the analysis time period, judging that the operation state of the corresponding analysis object is normal, generating an operation normal signal and sending the operation normal signal to the cloud computing platform; if the current total operation amount of the analysis object does not exceed the turnover amount threshold value within the analysis time period and the growth speed corresponding to the total operation amount does not exceed the growth speed threshold value, judging that the operation state of the corresponding analysis object is abnormal, generating an operation abnormal signal and sending the operation abnormal signal to the cloud computing platform;
marking an analysis object corresponding to the operation abnormal signal as an operation abnormal object, performing market analysis on the operation abnormal object, collecting enterprises of which the products are of the same type as the operation abnormal object and marking the enterprises as associated enterprises, collecting the profit frequency of the associated enterprises and the profit amount growth speed of the corresponding associated enterprises in an analysis time period, and respectively comparing the profit frequency threshold with the profit amount growth speed threshold:
if the profit frequency of the associated enterprises exceeds the profit frequency threshold value or the profit amount growth speed of the corresponding associated enterprises exceeds the profit amount growth speed threshold value within the analysis time period, judging that the operation abnormal object is self operation influence, generating self influence signals and sending the self influence signals and the corresponding operation abnormal object to the cloud computing platform; if the profit frequency of the associated enterprise does not exceed the profit frequency threshold value within the analysis time period and the profit amount growth speed of the corresponding associated enterprise does not exceed the profit amount growth speed threshold value, determining that the operation abnormal object is influenced by the market environment, generating a non-self-influence signal and sending the non-self-influence signal and the corresponding operation abnormal object to the cloud computing platform.
As a preferred embodiment of the present invention, the operation process of the influencing factor dividing unit is as follows:
collecting the abnormal operation time period of the abnormal operation object, analyzing the operation product of the abnormal operation object, collecting the number of the operation product production fault types of the abnormal operation object and the number of the operation products corresponding to the production fault types, and comparing the number threshold of the fault types with the number threshold of the operation products respectively:
if the number of the production fault types of the operation products of the operation abnormal object does not exceed the threshold value of the number of the fault types, or the number of the operation products corresponding to the production fault types exceeds the threshold value of the number of the operation products, judging the influence factors corresponding to the operation abnormal object as decision influence;
if the number of the production fault types of the operation products of the operation abnormal object exceeds the threshold value of the number of the fault types and the number of the operation products corresponding to the production fault types exceeds the threshold value of the number of the operation products, judging the influence factors corresponding to the operation abnormal object as the execution influence; and sending the operation abnormal object and the corresponding influence factor to an internal analysis and control unit.
As a preferred embodiment of the present invention, the operation process of the internal analysis management and control unit is as follows:
when the influence factor of the operation abnormal object is the decision influence, the rework frequency of the executive staff after the production instruction is issued by the management staff in the operation abnormal object and the frequency repeatedly issued by the production instruction corresponding to the management staff are collected, and the rework frequency of the executive staff after the production instruction is issued by the management staff in the operation abnormal object and the frequency repeatedly issued by the production instruction corresponding to the management staff are respectively compared with the rework frequency threshold and the frequency threshold repeatedly issued:
if the rework frequency of the executive personnel exceeds the rework frequency threshold after the production instruction is issued by the management personnel in the operation abnormal object, or the frequency repeatedly issued by the production instruction of the corresponding management personnel exceeds the frequency threshold repeatedly issued, judging that the current management personnel is not suitable for the corresponding post, replacing the management personnel of the corresponding post, generating a decision-made control signal after the replacement is finished, and sending the decision-made control signal to the cloud computing platform;
when the influence factor of the operation abnormal object is execution influence, acquiring the post replacement frequency of an executive in the operation abnormal object and the qualification rate of the executive after the post replacement for executing the production instruction, and comparing the post replacement frequency of the executive in the operation abnormal object and the qualification rate of the executive after the post replacement for executing the production instruction with a replacement frequency threshold and a qualification rate threshold respectively:
if the post replacement frequency of the executive personnel in the operation abnormal object exceeds the replacement frequency threshold value or the qualification rate of the executive personnel executing the production instruction after the post replacement does not exceed the qualification rate threshold value, judging that the working system of the current executive personnel is abnormal, controlling the post replacement frequency of the corresponding executive personnel, carrying out control on the qualification rate of the production product of the corresponding executive personnel, generating an execution control signal after the control is finished, and sending the execution control signal to the cloud computing platform.
As a preferred embodiment of the present invention, the feasibility prediction unit operates as follows:
setting a feasibility prediction time period, and acquiring the number of times of decision errors of managers operating abnormal objects and the maximum difference value of the production product yield of executives in the feasibility prediction time period; obtaining a feasibility prediction analysis coefficient X of the management and control of the abnormal operation object through analysis; comparing the feasibility prediction analysis coefficient X of the operation abnormal object control with a feasibility prediction analysis coefficient threshold value:
if the feasibility prediction analysis coefficient X of the management and control of the operation abnormal object exceeds the feasibility prediction analysis coefficient threshold, judging that the management and control feasibility of the operation abnormal object is low, generating a management and control abnormal signal and sending the management and control abnormal signal to an internal analysis and control unit; and if the feasibility prediction analysis coefficient X of the management and control of the abnormal operation object does not exceed the feasibility prediction analysis coefficient threshold, judging that the management and control feasibility of the abnormal operation object is high, generating a normal management and control signal and sending the normal management and control signal to the cloud computing platform.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the operation state of the analysis object is monitored in real time, and analysis and judgment are carried out when the operation state of the analysis object is abnormal, so that enterprise management and control are carried out according to the analysis and judgment, the influence of the operation state on an enterprise is reduced, and the enterprise management efficiency is improved; influence factor analysis is carried out on the operation abnormal object, and the reason for abnormal operation of the operation abnormal object is judged through the influence factor analysis, so that the management and control efficiency of an abnormal operation enterprise is improved, and the efficiency and the accuracy for recovering the abnormal operation state to the normal state are facilitated; the corresponding operation abnormal object is internally analyzed and controlled according to the corresponding influence factors, the efficiency of stable operation of an enterprise can be improved by analyzing and controlling according to the influence factors, the management intensity of the enterprise is enhanced, and meanwhile, the influence factors in the enterprise can be accurately and efficiently rectified; the feasibility prediction is carried out on the management and control of the corresponding operation abnormal object, the accuracy of the management and control of the operation abnormal object is facilitated, the problem that the management and control efficiency is abnormal and is not found in time is solved, the operation state of the operation abnormal object is unstable, and the low working efficiency of enterprise management is caused.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of an enterprise management system based on cloud computing and internet of things according to the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The enterprise management system can help enterprise managers to improve the work efficiency instead of increasing the burden of the enterprise managers; when the operation state of an enterprise is abnormal, factors influencing the operation state of the enterprise can be accurately analyzed through an enterprise management system, so that the operation efficiency of the enterprise is improved, and the influence of the abnormal operation state is reduced to the minimum; referring to fig. 1, an enterprise management system based on cloud computing and internet of things performs data transmission through the internet of things; each enterprise is marked as an analysis object through the cloud computing platform, a mark i is set, the i is a natural number larger than 1, meanwhile, the cloud computing platform generates enterprise operation analysis signals and sends the enterprise operation analysis signals to the enterprise operation analysis unit, the enterprise operation analysis unit carries out operation analysis on the analysis objects after receiving the enterprise operation analysis signals, the operation state of the analysis objects is monitored in real time, and analysis and judgment are carried out when the operation state of the analysis objects is abnormal, so that enterprise management and control are carried out according to the analysis and judgment, the influence of the operation state on the enterprises is reduced, and the enterprise management efficiency is improved;
setting an analysis time period, collecting the current total business amount of the analysis object and the growth speed of the corresponding total business amount in the analysis time period, and comparing the current total business amount of the analysis object and the growth speed of the corresponding total business amount in the analysis time period with a business amount threshold value and a growth speed threshold value respectively:
if the current total operation amount of the analysis object exceeds a turnover amount threshold value or the increase speed of the corresponding total operation amount exceeds an increase speed threshold value in the analysis time period, judging that the operation state of the corresponding analysis object is normal, generating an operation normal signal and sending the operation normal signal to the cloud computing platform; if the current total business amount of the analysis object does not exceed the turnover threshold value within the analysis time period and the growth speed corresponding to the total business amount does not exceed the growth speed threshold value, judging that the operation state of the corresponding analysis object is abnormal, generating an abnormal operation signal and sending the abnormal operation signal to the cloud computing platform;
marking an analysis object corresponding to the operation abnormal signal as an operation abnormal object, carrying out market analysis on the operation abnormal object, acquiring enterprises of the same type of products as the operation abnormal object as associated enterprises, acquiring the profit frequency of the associated enterprises and the profit amount growth speed of the corresponding associated enterprises in the analysis time period, and comparing the profit frequency of the associated enterprises and the profit amount growth speed of the corresponding associated enterprises in the analysis time period with the profit frequency threshold and the profit amount growth speed threshold respectively:
if the profit frequency of the associated enterprise exceeds the profit frequency threshold value or the profit amount growth speed of the corresponding associated enterprise exceeds the profit amount growth speed threshold value within the analysis time period, judging that the operation abnormal object is the operation influence of the operation abnormal object, generating a self influence signal and sending the self influence signal and the corresponding operation abnormal object to the cloud computing platform; if the profit frequency of the associated enterprise does not exceed the profit frequency threshold value within the analysis time period and the profit amount growth speed of the corresponding associated enterprise does not exceed the profit amount growth speed threshold value, judging that the operation abnormal object is influenced by the market environment, generating a non-self-influence signal and sending the non-self-influence signal and the corresponding operation abnormal object to the cloud computing platform;
after receiving the self influence signal and the corresponding operation abnormal object, the cloud computing platform generates an influence factor dividing signal and sends the influence factor dividing signal to the influence factor dividing unit, after receiving the influence factor dividing signal, the influence factor dividing unit analyzes the influence factor of the operation abnormal object, and judges the reason of abnormal operation of the operation abnormal object through the influence factor analysis, so that the management and control efficiency of an abnormal operation enterprise is improved, and the efficiency and the accuracy of recovering the abnormal operation state to the normal state are facilitated;
collecting the abnormal operation time period of the abnormal operation object, analyzing the operation product of the abnormal operation object, collecting the number of the operation product production fault types of the abnormal operation object and the number of the operation products corresponding to the production fault types, and comparing the fault type quantity threshold value of the operation product production fault types of the abnormal operation object and the number of the operation products corresponding to the production fault types with the operation product quantity threshold value respectively:
if the number of the production fault types of the operation products of the operation abnormal object does not exceed the threshold value of the number of the fault types, or the number of the operation products corresponding to the production fault types exceeds the threshold value of the number of the operation products, judging the influence factors corresponding to the operation abnormal object as decision influence; if the number of the production fault types of the operation products of the operation abnormal object exceeds the threshold value of the number of the fault types and the number of the operation products corresponding to the production fault types exceeds the threshold value of the number of the operation products, judging the influence factors corresponding to the operation abnormal object as the execution influence; the decision influence means that a manager makes a decision error in the production process of the operation product, so that the operation product has single fault and large quantity; the execution influence is expressed as that an executive worker has execution errors in the production process of the operation product, so that the operation product has more fault types but not large quantity;
sending the operation abnormal object and the corresponding influence factor to an internal analysis and control unit;
after receiving the operation abnormal object and the corresponding influence factor, the internal analysis and control unit carries out internal analysis and control on the corresponding operation abnormal object according to the corresponding influence factor, and analysis and control are carried out according to the influence factor, so that the efficiency of stable operation of an enterprise can be improved, the management intensity of the enterprise is enhanced, and meanwhile, the influence factor in the enterprise can be accurately and efficiently rectified;
when the influence factor of the operation abnormal object is the decision influence, the rework frequency of the executive staff after the production instruction is issued by the management staff in the operation abnormal object and the frequency repeatedly issued by the production instruction corresponding to the management staff are collected, and the rework frequency of the executive staff after the production instruction is issued by the management staff in the operation abnormal object and the frequency repeatedly issued by the production instruction corresponding to the management staff are respectively compared with the rework frequency threshold and the frequency threshold repeatedly issued:
if the rework frequency of an executive staff exceeds a rework frequency threshold after a production instruction is issued by a management staff in an operation abnormal object or the frequency repeatedly issued by the production instruction of a corresponding management staff exceeds a repeatedly issued frequency threshold, judging that the current management staff is not suitable for the corresponding post, replacing the management staff of the corresponding post, generating a decision-made control signal after replacement is completed and sending the decision-made control signal to a cloud computing platform;
if the rework frequency of the executive personnel does not exceed the rework frequency threshold after the production instruction is issued by the management personnel in the operation abnormal object and the frequency repeatedly issued by the production instruction of the corresponding management personnel does not exceed the frequency threshold repeatedly issued, judging that the current management personnel is suitable for the corresponding post;
when the influence factor of the operation abnormal object is execution influence, acquiring the post replacement frequency of an executive in the operation abnormal object and the qualification rate of the executive after the post replacement for executing the production instruction, and comparing the post replacement frequency of the executive in the operation abnormal object and the qualification rate of the executive after the post replacement for executing the production instruction with a replacement frequency threshold and a qualification rate threshold respectively:
if the post replacement frequency of an executive in the operation abnormal object exceeds a replacement frequency threshold or the qualification rate of the executive after post replacement for executing a production instruction does not exceed a qualification rate threshold, judging that the working system of the current executive is abnormal, controlling the post replacement frequency of the corresponding executive, carrying out control on the qualification rate of the production product of the corresponding executive, generating an execution control signal after the control is finished, and sending the execution control signal to a cloud computing platform; if the post replacement frequency of the executive personnel in the operation abnormal object does not exceed the replacement frequency threshold and the qualification rate of the executive personnel executing the production instruction after the post replacement exceeds the qualification rate threshold, judging that the working system of the current executive personnel is not abnormal;
after receiving the executed and controlled signal and the decision-made controlled signal, the cloud computing platform generates a feasibility prediction signal and sends the feasibility prediction signal to the feasibility prediction unit, and after receiving the feasibility prediction signal, the feasibility prediction unit performs feasibility prediction on the control of the corresponding operation abnormal object, so that the accuracy of the control of the operation abnormal object is facilitated, the control efficiency is prevented from being abnormal and not found in time, the operation state of the operation abnormal object is more unstable, and the working efficiency of enterprise management is low;
setting a feasibility prediction time period, acquiring the number of times of decision errors of managers operating abnormal objects and the maximum difference value of the production product qualification rate of executives in the feasibility prediction time period, and marking the number of times of decision errors of managers operating abnormal objects and the maximum difference value of the production product qualification rate of executives as JCC and HGC; obtaining a feasibility prediction analysis coefficient X of the management and control of the abnormal operation object by a formula X (JCC × a1+ HGC × a2), wherein a1 and a2 are both preset proportional coefficients, a1 is more than a2 is more than 0, and beta is an error correction factor, and the value of the error correction factor is 1.023;
comparing the feasibility prediction analysis coefficient X of the operation abnormal object control with a feasibility prediction analysis coefficient threshold value:
if the feasibility prediction analysis coefficient X of the management and control of the operation abnormal object exceeds the feasibility prediction analysis coefficient threshold, judging that the management and control feasibility of the operation abnormal object is low, generating a management and control abnormal signal and sending the management and control abnormal signal to an internal analysis and control unit, and after receiving the management and control abnormal signal, the internal analysis and control unit analyzes and controls the corresponding operation abnormal object again;
and if the feasibility prediction analysis coefficient X of the management and control of the abnormal operation object does not exceed the feasibility prediction analysis coefficient threshold, judging that the management and control feasibility of the abnormal operation object is high, generating a normal management and control signal and sending the normal management and control signal to the cloud computing platform.
The formulas are all obtained by acquiring a large amount of data and performing software simulation, and a formula close to a true value is selected, and coefficients in the formulas are set by a person skilled in the art according to actual conditions;
when the system is used, an analysis object is subjected to operation analysis through the enterprise operation analysis unit, the operation state of the analysis object is monitored in real time, an operation normal signal and an operation abnormal signal are generated through the operation analysis, and the operation normal signal and the operation abnormal signal are sent to the cloud computing platform; marking an analysis object corresponding to the operation abnormal signal as an operation abnormal object, analyzing the operation abnormal object to generate a self-influence signal and a non-self-influence signal, and sending the self-influence signal and the non-self-influence signal to the cloud computing platform; the influence factor analysis is carried out on the operation abnormal object through the influence factor dividing unit, and the influence factors of the operation abnormal object are divided into decision influence and execution influence through the influence factor analysis; performing internal analysis control on the corresponding operation abnormal object according to the corresponding influence factors through an internal analysis control unit, performing analysis control according to the corresponding type influence factors, and simultaneously generating a decision-making controlled signal and an execution controlled signal; and performing feasibility prediction on the control of the corresponding operation abnormal object through a feasibility prediction unit, and generating a control abnormal signal and a control normal signal through the feasibility prediction.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. The utility model provides an enterprise management system based on cloud calculates and thing networking, includes cloud computing platform, and cloud computing platform marks each enterprise as analysis object, its characterized in that, cloud computing platform communication connection has:
the enterprise operation analysis unit is used for carrying out operation analysis on the analysis object, monitoring the operation state of the analysis object in real time, generating an operation normal signal and an operation abnormal signal through the operation analysis, and sending the operation normal signal and the operation abnormal signal to the cloud computing platform; marking an analysis object corresponding to the operation abnormal signal as an operation abnormal object, analyzing the operation abnormal object to generate a self-influence signal and a non-self-influence signal, and sending the self-influence signal and the non-self-influence signal to the cloud computing platform;
the influence factor dividing unit is used for analyzing influence factors of the abnormal operation object, dividing the influence factors of the abnormal operation object into decision influence and execution influence through the influence factor analysis, and sending the abnormal operation object and the corresponding influence factors to the internal analysis management and control unit;
the internal analysis and control unit is used for carrying out internal analysis and control on the corresponding operation abnormal object according to the corresponding influence factors, carrying out analysis and control according to the corresponding type influence factors, simultaneously generating a decision-making controlled signal and an execution controlled signal, and sending the decision-making controlled signal and the execution controlled signal to the cloud computing platform;
and the feasibility prediction unit is used for performing feasibility prediction on the control of the corresponding operation abnormal object, generating a control abnormal signal and a control normal signal through the feasibility prediction, and correspondingly sending the control abnormal signal and the control normal signal to the internal analysis and control unit and the cloud computing platform.
2. The enterprise management system based on cloud computing and internet of things as claimed in claim 1, wherein the operation process of the enterprise operation analysis unit is as follows:
setting an analysis time period, acquiring the current total business amount of an analysis object and the growth speed of the corresponding total business amount in the analysis time period, and comparing the current total business amount with a business amount threshold value and a growth speed threshold value respectively:
if the current total operation amount of the analysis object exceeds a turnover amount threshold value or the increase speed of the corresponding total operation amount exceeds an increase speed threshold value in the analysis time period, judging that the operation state of the corresponding analysis object is normal, generating an operation normal signal and sending the operation normal signal to the cloud computing platform; if the current total operation amount of the analysis object does not exceed the turnover amount threshold value within the analysis time period and the growth speed corresponding to the total operation amount does not exceed the growth speed threshold value, judging that the operation state of the corresponding analysis object is abnormal, generating an operation abnormal signal and sending the operation abnormal signal to the cloud computing platform;
marking an analysis object corresponding to the operation abnormal signal as an operation abnormal object, carrying out market analysis on the operation abnormal object, acquiring enterprises of the same type of products as the operation abnormal object and marking the enterprises as related enterprises, acquiring the profit frequency of the related enterprises and the profit amount growth speed of the corresponding related enterprises in an analysis time period, and respectively comparing the profit frequency threshold with the profit amount growth speed threshold:
if the profit frequency of the associated enterprise exceeds the profit frequency threshold value or the profit amount growth speed of the corresponding associated enterprise exceeds the profit amount growth speed threshold value within the analysis time period, judging that the operation abnormal object is the operation influence of the operation abnormal object, generating a self influence signal and sending the self influence signal and the corresponding operation abnormal object to the cloud computing platform; if the profit frequency of the associated enterprise does not exceed the profit frequency threshold value within the analysis time period and the profit amount growth speed of the corresponding associated enterprise does not exceed the profit amount growth speed threshold value, determining that the operation abnormal object is influenced by the market environment, generating a non-self-influence signal and sending the non-self-influence signal and the corresponding operation abnormal object to the cloud computing platform.
3. The enterprise management system based on cloud computing and internet of things according to claim 1, wherein the operation process of the influence factor dividing unit is as follows:
collecting the abnormal operation time period of the abnormal operation object, analyzing the operation product of the abnormal operation object, collecting the number of the operation product production fault types of the abnormal operation object and the number of the operation products corresponding to the production fault types, and comparing the number threshold of the fault types with the number threshold of the operation products respectively:
if the number of the production fault types of the operation products of the operation abnormal object does not exceed the threshold value of the number of the fault types, or the number of the operation products corresponding to the production fault types exceeds the threshold value of the number of the operation products, judging the influence factors corresponding to the operation abnormal object as decision influence;
if the number of the production fault types of the operation products of the operation abnormal object exceeds the threshold value of the number of the fault types and the number of the operation products corresponding to the production fault types exceeds the threshold value of the number of the operation products, judging the influence factors corresponding to the operation abnormal object as the execution influence; and sending the operation abnormal object and the corresponding influence factor to an internal analysis and control unit.
4. The enterprise management system based on cloud computing and internet of things according to claim 1, wherein the operation process of the internal analysis management and control unit is as follows:
when the influence factor of the operation abnormal object is the decision influence, the rework frequency of the executive staff after the production instruction is issued by the management staff in the operation abnormal object and the frequency repeatedly issued by the production instruction corresponding to the management staff are collected, and the rework frequency of the executive staff after the production instruction is issued by the management staff in the operation abnormal object and the frequency repeatedly issued by the production instruction corresponding to the management staff are respectively compared with the rework frequency threshold and the frequency threshold repeatedly issued:
if the rework frequency of the executive personnel exceeds the rework frequency threshold after the production instruction is issued by the management personnel in the operation abnormal object, or the frequency repeatedly issued by the production instruction of the corresponding management personnel exceeds the frequency threshold repeatedly issued, judging that the current management personnel is not suitable for the corresponding post, replacing the management personnel of the corresponding post, generating a decision-made control signal after the replacement is finished, and sending the decision-made control signal to the cloud computing platform;
when the influence factor of the operation abnormal object is execution influence, acquiring the post replacement frequency of an executive in the operation abnormal object and the qualification rate of the executive after the post replacement for executing the production instruction, and comparing the post replacement frequency of the executive in the operation abnormal object and the qualification rate of the executive after the post replacement for executing the production instruction with a replacement frequency threshold and a qualification rate threshold respectively:
if the post replacement frequency of the executive personnel in the operation abnormal object exceeds the replacement frequency threshold value or the qualification rate of the executive personnel executing the production instruction after the post replacement does not exceed the qualification rate threshold value, judging that the work system of the current executive personnel is abnormal, controlling the post replacement frequency of the corresponding executive personnel, carrying out control on the qualification rate of the production product of the corresponding executive personnel, generating an execution control signal after the control is finished, and sending the execution control signal to the cloud computing platform.
5. The enterprise management system based on cloud computing and internet of things according to claim 1, wherein the feasibility prediction unit operates as follows:
setting a feasibility prediction time period, and acquiring the number of times of decision errors of managers operating abnormal objects and the maximum difference value of the production product yield of executives in the feasibility prediction time period; obtaining a feasibility prediction analysis coefficient X of the management and control of the abnormal operation object through analysis; comparing the feasibility prediction analysis coefficient X of the operation abnormal object control with a feasibility prediction analysis coefficient threshold value:
if the feasibility prediction analysis coefficient X of the management and control of the operation abnormal object exceeds the feasibility prediction analysis coefficient threshold, judging that the management and control feasibility of the operation abnormal object is low, generating a management and control abnormal signal and sending the management and control abnormal signal to an internal analysis and control unit; and if the feasibility prediction analysis coefficient X of the management and control of the abnormal operation object does not exceed the feasibility prediction analysis coefficient threshold, judging that the management and control feasibility of the abnormal operation object is high, generating a normal management and control signal and sending the normal management and control signal to the cloud computing platform.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115345585A (en) * | 2022-08-16 | 2022-11-15 | 清华大学苏州汽车研究院（吴江） | Supply chain intelligent management system for enterprise operation |
| CN115545495A (en) * | 2022-10-13 | 2022-12-30 | 武汉彤新科技有限公司 | Intelligent analysis system for service requirements of medium and small enterprises |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115345585A (en) * | 2022-08-16 | 2022-11-15 | 清华大学苏州汽车研究院（吴江） | Supply chain intelligent management system for enterprise operation |
| CN115545495A (en) * | 2022-10-13 | 2022-12-30 | 武汉彤新科技有限公司 | Intelligent analysis system for service requirements of medium and small enterprises |
| CN115545495B (en) * | 2022-10-13 | 2023-06-27 | 武汉彤新科技有限公司 | Intelligent analysis system for service requirements of small and medium enterprises |
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