KR20190076544A - Systems supporting production innovation in smart factories - Google Patents

Abstract

An objective of the present invention is to provide a system supporting production innovation of a smart factory to realize productivity improvement and optimized operation of an entire factory. The system supporting production innovation of a smart factory comprises: at least one facility installed in a factory; and at least one sensing device to collect state data for man, machine, material, method, and energy (4M1E) information of the factory; a KPI index management device to receive the state data to generate KPI index-oriented data; and a factory evaluation management device to use the KPI index-oriented data to perform factory evaluation work.

Description

Systems supporting production innovation in smart factories.

The present invention relates to at least one facility installed in a factory by generating plant efficiency indicators, quality indicators, capacity indicators, environmental indicators, inventory management indicators, and maintenance indicators; At least one sensing device for collecting status data on 4M1E (Man, Machine, Material, Method, Energy) information of the factory; A KPI indicator management device receiving the status data and generating data centered on the KPI indicator; And a factory evaluation management apparatus for performing factory quality evaluation, delivery time evaluation, and cost evaluation work using data centered on the KPI index, and a system for supporting production innovation of a smart factory.

Recent manufacturing has faced a global disorganized factory operation due to the expansion of the global market. This presents a challenge for the operation of multiple plants dispersed throughout the world. It is demanded that the system can be operated as a single factory with the efficiency of remote maintenance of expensive machines installed in dispersed factories and the scattered factories.

In order to efficiently support these globally dispersed factories, it is necessary to introduce Manufacturing Execution Systems (MES).

MES measures real-time production resources 4M1E (Man, Machine, Material, Method, and Energy), which is changing instantly, and provides real time information on decision making information, customer and delivery information, It is a system that realizes improvement of productivity and optimization operation of the whole, and it is necessary to introduce it as essential for factory management.

Specifically, production innovation needs to be promoted through KPI, which is a quantitative indicator of factory quality, delivery, and cost management.

As described above, the present invention collects status data of plant facilities in real time and extracts KPI index to realize plant efficiency, quality, capacity, environment, inventory management and maintenance It is aimed to provide a system that supports production innovation of smart factories that are in charge of evaluation of remuneration.

The technical problem to be solved by the present invention is not limited to the above-mentioned technical problems, and various technical problems can be included within the scope of what is well known to a person skilled in the art from the following description.

According to an aspect of the present invention, there is provided a system for supporting production innovation of a smart factory, comprising: at least one facility installed in a factory; At least one sensing device for collecting status data on 4M1E (Man, Machine, Material, Method, Energy) information of the factory; A KPI indicator management device receiving the status data and generating data centered on the KPI indicator; And a factory evaluation management apparatus for conducting a factory evaluation work using data centered on the KPI index.

In addition, the KPI index management apparatus according to an embodiment of the present invention is characterized in that a KPI index is extracted by weighting necessary information among the 4M1E information.

Further, the KPI index management apparatus according to an embodiment of the present invention is characterized by setting the range and kind of the KPI index to be extracted according to the type of the facility.

Further, the KPI index management apparatus according to an embodiment of the present invention is characterized by setting the range and kind of the KPI index to be extracted according to the manufacturing process, even if the same equipment is used.

In addition, the KPI index management apparatus according to an embodiment of the present invention is characterized by dividing facilities installed in the factory into a plurality of predetermined layers, and extracting a KPI index according to each layer, And is distributed to the first to fourth levels.

Also, the KPI index management apparatus according to an embodiment of the present invention grasps the total energy usage amount of factory facilities, and uses data centered on the KPI index having the largest correlation with the energy usage amount, .

In addition, the factory evaluation management apparatus according to an embodiment of the present invention performs energy management using data centered on KPIs having the largest correlation among energy usage amounts of facilities installed in the plant.

As described above, the present invention collects status data of plant facilities in real time and extracts KPI index to realize plant efficiency, quality, capacity, environment, inventory management and maintenance It is possible to provide a system for supporting the production innovation of the smart factory which is in charge of the evaluation of the repair.

The effects of the present invention are not limited to the above-mentioned technical problems, and various technical problems may be included within the scope of what will be apparent to a person skilled in the art from the following description.

Figure 1 is an exemplary diagram illustrating the configuration of a system supporting production innovation of a smart factory of the present invention.
Fig. 2 is an example of sensing from a facility of a sensing device of a system supporting production innovation of a smart factory of the present invention. Fig.
3 is an exemplary diagram illustrating the configuration of a system supporting production innovation of the smart factory of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a system 100 for supporting production innovation of a smart factory according to the present invention will be described in detail with reference to the accompanying drawings. The present invention is not limited to the above-described embodiments, and various changes and modifications may be made without departing from the scope of the present invention. In addition, the matters described in the attached drawings may be different from those actually implemented by the schematic drawings to easily describe the embodiments of the present invention.

In the meantime, each constituent unit described below is only an example for implementing the present invention. Thus, in other implementations of the present invention, other components may be used without departing from the spirit and scope of the present invention.

Also, the expression " comprising " is intended to merely denote that such elements are present as an expression of " open ", and should not be understood to exclude additional elements.

Also, the expressions such as 'first, second', etc. are used only to distinguish between plural configurations, and do not limit the order or other features among the configurations.

In the description of the embodiments, it is to be understood that each layer (film), area, pattern or structure may be referred to as being "on" or "under / under" Quot; includes all that is formed directly or through another layer. The criteria for top / bottom or bottom / bottom of each layer are described with reference to the drawings.

 When a part is "connected" to another part, it includes not only "directly connected" but also "indirectly connected" with another part in between. Also, when an element is referred to as "comprising ", it means that it can include other elements, not excluding other elements unless specifically stated otherwise.

1 is an exemplary diagram illustrating a configuration of a system 100 for supporting production innovation of a smart factory of the present invention.

Figure 2 is an exemplary diagram of sensing devices 130, 131, 132, 133 and 134 of a system 100 supporting the production innovation of a smart factory of the present invention from facilities 120, 121, 122, 123 and 124 to be.

3 is an exemplary diagram illustrating a configuration of a system 100 for supporting production innovation of a smart factory of the present invention.

1, a system 100 for supporting the production innovation of a smart factory of the present invention includes a facility 120, 121, 122, 123 and 124, a sensing device 130, 131, 132, 133 and 134, The factory evaluation management apparatus 150 (150), the database 160, the facility management apparatus 170, and the KPI index management apparatus 180.

The facilities 120, 121, 122, 123 and 124 may be installed in the factory 110 and the equipment 120, 121, 122, 123 and 124 may include all the equipment that is generally installed in the factory 110 have. For example, equipment necessary for injection, pressing, casting, painting, assembling, and melting of the plant 110 may be used. In addition, the plant 110 energy management system of the present invention can be applied to facilities 120, 121, 122, 123, and 124 that can be generally used, such as a generator, a machine tool, a mold machine, a lot,

The sensing devices 130, 131, 132, 133 and 134 may collect status data of the facilities 120, 121, 122, 123 and 124. Referring to FIG. 2, an embodiment in which the sensing devices 130, 131, 132, 133, and 134 of the factory evaluation management apparatus 150 of the present invention detect from the facilities 120, 121, 122, . In this case, the sensing devices 130, 131, 132, 133 and 134 may be directly attached to the facilities 120, 121, 122, 123 and 124 as shown in FIG. 133, and 134 may be installed on the facilities 120, 121, 122, 123, and 124 and receive and collect status data from the facilities 120, 121, 122, 123 and 124.

The status data collected by the sensing devices 130, 131, 132, 133 and 134 includes operator productivity, batch rating, yield, batch efficiency, efficiency, OEE index, NEE index, availability and validity. At least one of a quality efficiency, a technical usage level, a waste grade, a first passed yield, a disposal rate, a rework ratio, an initial failure rate, a mechanical capability indicator, an important mechanical capability indicator, and a capability index.

Worker productivity is information on the ratio of the worker's work time to the total work time of the worker.

The formula is as follows.

Worker Productivity = PAZ (Worker Work Time) / GAZ (Total Worker Work Time)

The placement grade is related to the time all work hours are combined in the existing periodic time zone of the work instruction. Placement level refers to the level of resource circulation, including maintenance and breakdown time, in manufacturing (reconditioning and reconditioning).

The formula is as follows.

Allocation degree = BLZ (process time) / DLZ (time required)

The output rate is an index for the performance of the process, such as the quantity of production per unit time.

The formula is as follows.

Throughput = PM (production quantity) / DLZ (time required)

Placement efficiency is the ratio between the time planned for machine placement and the actual placement time of the machine.

The formula is as follows.

Allocation efficiency = BLZ (Work Order Directed Work) / PBZ (Planned Directed Work)

Efficiency is a measure of the productivity of a machine as part of its main usage time at an existing deployment time.

The formula is as follows.

Efficiency = HNZ (waiting time) / BLZ (working time for work instruction)

Overall Equipment Effectiveness (OEE) is a measure of the efficiency of a process line, plant or machine consisting of an existing assembly line or multiple machines.

The formula is as follows.

OEE = Availability (availability) * Effectiveness * Quality rate (quality efficiency)

NEE indicators provide clues about plant shutdowns, cycle times and losses incurred and product rework incidents.

The formula is as follows.

NEE = BAZ (process time) / PBZ (work time for planned work instructions) * Effectiveness * Quality rate *

Availability represents how valuable a function is to a machine versus a plan.

The formula is as follows.

Availability = HNZ (Production Time) / PBZ (Working Time for Planned Work Order)

Validity measures the strength of the process. Display target cycle and actual cycle linkage

The formula is as follows.

ffectiveness = PEZ (production time by workshop) * PM (production quantity) / HNZ (production time)

Quality efficiency refers to the proportion of the appropriate quantity to the quantity produced.

The formula is as follows.

Quality Rate = GM (Good Quality) / PM (Good Quality)

The level of technical usage is the level of efficiency of the machine.

The formula is as follows.

Technical Usage Level = HNZ (production time) / (HNZ (production time) + SU (waiting time))

Waste class defines boundaries for review and waste of compliance.

The formula is as follows.

Wastage Degree = AM (discarded quantity) / GAM (planned discarded quantity)

The first accepted yield is a specific figure for direct process quality for workplaces and products.

The formula is as follows.

FPY (first passed yield) = GT (good quantity) / PT (good)

The waste rate is discarded in production and provides a rate.

The formula is as follows.

Wastage Ratio = AM (Disposal Quantity) / PM (Production Quantity)

The rework rate provides a percentage of rework in production.

The formula is as follows.

Reworking Ratio = NM (rework quantity) / PM (production quantity)

The initial failure rate is an index applied to the continuous process. It generates future waste products in the background of the next process based on the main product (eg module or main board) produced in the first production stage.

The formula is as follows.

Fall off Rate = AM (waste quantity) / PM (production quantity in the first process)

Machine capability indicators show the machine or work machine capabilities that can be produced with the required quality.

The formula is as follows.

Cm (machine capability indicator) = (OGW (upper limit) - UGW (lower limit)) / (6 * s (standard deviation))

Critical machine capability indicators show the ability of machines or work tools to produce good products.

The formula is as follows.

Cmko (upper limit of important mechanical capacity index) = (OGW (upper limit value) - xqq) / (3 * s (standard deviation))

Cmku (lower limit of the important mechanical capacity index) = (Xqq - UGW (lower limit value) / (3 * s (standard deviation))

The state data may include a real time power consumption, a voltage, a current, a flow rate, a pressure amount of the facilities 120, 121, 122, 123 and 124, 121, 122, 123, 124), the operation state of the facilities (120, 121, 122, 123, 124) 121, 122, 123, 124), the operation time of the equipments (120, 121, 122, 123, 124) 124, and the product names of the facilities 120, 121, 122, 123, 124, and the like. The plant 110 energy management system of the present invention allows such state data to be compared and analyzed as raw data.

At this time, the sensing devices 130, 131, 132, 133, and 134 may collect the status data by at least one of an automatic collection method, a semi-automatic collection method, and a manual collection method. In the case of the factory 110 managed by the plant 110 energy management system of the present invention, it is possible to use a sensing device 130, 131, 132, 133, 134 for automatically collecting according to a predetermined method in real time, The user may operate the sensing devices 130, 131, 132, 133 and 134, directly input the data, and transmit the data to the factory evaluation management apparatus. You can also collect status data semi-automatically, such as collecting some automatically and collecting some manually.

In addition, the sensing devices 130, 131, 132, 133 and 134 of the present invention can collect status data on 4M1E (Man, Machine, Material, Method, Energy) 4M1E information refers to various data such as facilities (120, 121, 122, 123, 124), processes, materials, people, environment and the like, and means data necessary for evaluating factories in smart factories.

The KPI index management device 180 receives the status data and generates data centered on the KPI index.

Key Performance Indicators (KPIs) are indicators that measure the degree to which an organization achieves its goals and can be used to indicate the current business state and can be used to predict what will happen to future countermeasures.

KPI indicators can be used to quantify difficult quantitative measures such as leadership development, employment, service, and customer satisfaction. In addition, KPIs can indicate important parts of the measurement subject in terms of organization direction, benchmark, goal, and time series.

In particular, the KPI indicator is a key performance indicator and the key indicator among the performance indicators. The importance of KPIs is to systematically overcome situations that do not worry about what "performance indicators" typically have. In other words, it should be selected from among the performance measurement indexes that are currently being utilized, and should be compressed only by the core ones. Therefore, the selection criteria should be 'important to achieve the goal', and the number should be 'enough to fit in the hand'.

Many companies have used financial performance, such as sales and expenses, as main indicators so far, mainly in terms of measurability. However, since financial performance is a result of past activities, there is a limitation that it can not give information on what activities to achieve. Companies that recognize that there is a problem in measuring these financial performance indicators are establishing KPIs in a new way to solve the problems of existing performance indicators.

For example, Sears, which has experienced a management crisis, builds and operates a KPI called Total Performance Indicator (TPI) based on the causal relationship between 'employee-customer-benefit'.

In this way, companies that are trying to establish KPIs in common are to rebuild KPIs from the BSC (Balanced Scorecard) perspective. In other words, it reflects the company's vision and strategic direction, considering the causal relationship between each KPI, and establishes a KPI from a balanced perspective such as customer, process and learning capabilities, as well as financial performance.

The KPI index management apparatus 180 of the present invention can extract the KPI index of the facilities 120, 121, 122, 123, and 124 from which the status data is collected by receiving the status data. It is possible to receive various data generated from a plurality of facilities (120, 121, 122, 123, 124) in a smart factory and extract necessary KPI indices from those data and use them.

The factory evaluation management apparatus 150 can perform the factory evaluation work using the data centered on the KPI index. The KPI indicator is a key performance indicator and corresponds to an indicator that measures the degree of achievement of the goal. In particular, it can be used to quantify difficult quantitative metrics, and KPI indices can be derived by taking into account the management importance / controllability / measurability. The factory evaluation management apparatus 150 receives and analyzes the data centered on the KPI index.

The factory evaluation management apparatus 150 also receives the status data and determines the worker productivity, the placement grade, the calculation rate, the placement efficiency, the efficiency, the OEE index, the NEE index, the availability, The factory evaluation can be carried out by analyzing the quality efficiency, the technical usage level, the waste grade, the first passed yield, the disposal rate, the rework rate, the initial failure rate, the machine capability indicator, the important machine capability indicator and the process capability indicator.

In addition, the KPI index management apparatus 180 of the present invention is characterized in that the KPI index is extracted by weighting necessary information among the 4M1E information. Among the KPIs that the user needs among the people, materials, facilities (120, 121, 122, 123, 124), method, environment, there may be the most important KPI indicator. For example, the KPI index management apparatus 180 of the present invention can extract a KPI index with a weight in 'material' to evaluate a smart factory later.

The KPI index management apparatus 180 of the present invention is characterized by setting the range and type of the KPI index to be extracted according to the types of the facilities 120, 121, 122, 123, and 124. Since the smart factory may have various facilities 120, 121, 122, 123 and 124, it is possible to extract a KPI index suitable for the various facilities 120, 121, 122, 123 and 124 such as press, casting, can do.

The KPI index management device 180 is characterized by setting the range and kind of the KPI index to be extracted according to the manufacturing process even if the same facility 120, 121, 122, 123, or 124 is used. The transportation facilities 120, 121, 122, 123 and 124 in the manufacturing process and in the transportation process play different roles even when the same transportation facilities 120, 121, 122, 123 and 124 are used. Accordingly, different KPI indexes can be extracted according to the process, and the factory evaluation management apparatus 150 can evaluate the factory based on the KPI index.

The KPI index includes a factory efficiency index, a quality index, a capacity index, an environmental index, an inventory index, and a maintenance index, and the factory evaluation management apparatus 150 includes a factory efficiency index, a quality index, a capacity index, , Inventory control index, and maintenance index.

The KPI index management apparatus 180 divides the facilities 120, 121, 122, 123 and 124 installed in the factory 110 into a plurality of predetermined layers and extracts the KPI index according to each layer , And is divided into 1 level to 4 levels according to functional layers. A table is a hierarchical structure that can display data showing the hierarchical relation of each item on the nature of data. In the case of having a meaning in dividing data in a structure and having a common attribute in a horizontal direction, It is necessary to group them into a hierarchical structure. If the original data structure is a tree structure, if it is hierarchical tree structure, if it is a mesh structure, it is called hierarchical network structure. Two-dimensional, three-dimensional or more n-dimensional arrays, and the like can be considered as one of the structures.

In addition, the KPI index management apparatus 180 of the present invention has two levels, that is, one level for sensing and controlling the production process, two levels for monitoring, supervising and controlling the production process, and controlling the workflow for producing the required final product Level, production, use of materials, delivery, and packaging.

In addition, the KPI index management apparatus 180 of the present invention has two levels, that is, one level for sensing and controlling the production process, two levels for monitoring, supervising and controlling the production process, and controlling the workflow for producing the required final product Level, production, use of materials, delivery, and packaging.

The KPI index management apparatus 180 is configured to grasp the total energy usage amount of the plant 110 facilities 120, 121, 122, 123 and 124 and to use the data centered on the KPI index having the largest correlation with the energy usage amount And generates data centered on the KPI index.

The factory evaluation management apparatus 150 uses the KPI index center data having the largest correlation among the energy usage amounts of the facilities 120, 121, 122, 123, and 124 installed in the factory 110, , Capacity, environment, inventory management, and maintenance management.

In the case of KPI indicators, various KPI indicators related to the facilities 120, 121, 122, 123, and 124 can be generated. The factory evaluation management apparatus 150 can perform energy management using the KPIs can do. The present invention is not limited to this, and can perform factory efficiency, quality, capacity, environment, inventory management, and maintenance management. The degree of correlation may be set as a predetermined item, and the factory evaluation management apparatus 150 of the present invention may automatically set the correlation and extract the KPI index.

The factory evaluation management apparatus 150 hierarchically divides the facilities 120, 121, 122, 123 and 124 and applies weights according to the hierarchy of the facilities 120, 121, 122, 123 and 124 The factory evaluation work can be carried out. The present invention is not limited to this, and it is possible to carry out evaluation of factory efficiency, quality, capacity, environment, inventory management and maintenance. At this time, the manufacturing process can be classified into a plurality of level modules as well as the facilities 120, 121, 122, 123 and 124, and when the manufacturing process is classified into a plurality of level modules, Module, a third level module, and a fourth level module. For example, the first level module may be a data acquisition and processing (A) acquisition, the second level module may be a field execution module (P), the third level module may be a management module (M) Can be classified into a plurality of level modules based on the functions of the ERP area (IERP; Interface, EXTN; extend).

Further, the KPI index management apparatus 180 of the present invention is configured to calculate at each level, and the KPI index using the parameters is extracted. Since the smart factory processes at each level can be implemented differently, the KPI indicator management device 180 of the present invention can extract KPI indices at each level differently.

The database 160 of the present invention may store state data or data centered on the KPI indicator. Since the facilities (120, 121, 122, 123, 124) installed in the smart factory produce a large number of status data and KPI data, a memory or database 160 capable of efficiently storing the data is required. Transmits and receives data in real time to the sensing devices 130, 131, 132, 133, and 134 and the KPI index management device 180, and stores the data in the database 160.

The system 100 for supporting the production innovation of the smart factory according to the present invention may further comprise a mobile management module 190.

The mobile management module 190 of the present invention can manage the state data stored in the database 160 or the data centered on the KPI index to provide to the mobile application. The mobile application corresponds to a program that allows a user or an administrator to process a plurality of facilities (120, 121, 122, 123, 124) installed in a smart factory, and can provide an interface for easy operation.

The mobile management module 190 can graphically display the state data and the KPI index-oriented data in a graphical or 3D graphical format, and can efficiently manage the usage data by a user, an administrator, a customer, or a manager.

In addition, in an embodiment of the present invention, a system 100 for supporting the production innovation of a smart factory may be configured such that the mobile management module 190 updates the state of the mobile application in which the state data or the data centered on the KPI index is transmitted and received .

In addition, in one embodiment of the present invention, a system 100 for supporting production innovation of a smart factory may be configured such that the mobile management module 190 senses the transmission or reception of the status data or the data centered on the KPI indicator in real time , And managing the integrated framework of the manufacturing site that the smart factory includes.

In addition, a system 100 supporting production innovation of the smart factory of the present invention may be configured such that the mobile management module 190 receives unique communication protocol information of the facility 120, 121, 122, 123, 124, And provides the mobile application with the status data or the data centered on the KPI index according to a unique communication protocol.

The energy consumption efficiency may be extracted in comparison with the production amounts of the equipments 120, 121, 122, 123 and 124 with respect to the amount of power input to the equipments 120, 121, 122, 123, 121, 122, 123, and 124 installed in the plant 110 in consideration of the standard energy consumption efficiency of the power plants 122, 123, For example, when the predetermined energy consumption efficiency is 30%, the energy consumption efficiency of the generator is 40%, the energy consumption efficiency of the machine tool is 50%, and the energy consumption efficiency of the mold machine is 25% The management apparatus 150 allows the < &lt; / RTI &gt;

It is also possible to grasp the increase and decrease in the load of the facilities 120, 121, 122, 123 and 124 having the low energy consumption efficiency and calculate the utility amount of the power source supplied to the facilities 120, 121, 122, 123, Can be adjusted. The utility refers to a heating source, a cooling source, a power source, and the like necessary for processing or manufacturing raw materials. The utilities are used to prevent malfunction or shutdown of the facilities 120, 121, 122, 123 and 124 The system should be fully managed.

It is also possible to grasp the increase and decrease in the load of the facilities 120, 121, 122, 123 and 124 having the low energy consumption efficiency and to control the operation process of the facilities 120, 121, 122, 123 and 124 . In the case of an operation process of the factory 110 that can be generally used, a process including at least one of common, injection, press, casting, painting, assembling, and melting can be set. Each process is represented by DEF (Default), INJ (Injection), PRS (Press), Diecasting Process, PNT (Paint), Assembly (ASY) .

At this time, the process can be controlled to control the energy efficiency. For example, when energy efficiency is judged to be the lowest when the facilities 120, 121, 122, 123 and 124 of the present invention correspond to the <injection> process, the factory evaluation management apparatus 150 of the present invention performs < Energy efficiency can be optimized by allowing the process to proceed first or by minimizing the &lt; injection &gt; process.

In addition, production scheduling of the facilities 120, 121, 122, 123, and 124 can be performed according to the current energy consumption status. The production scheduling determines the order of work to be processed, so that the factory evaluation management apparatus 150 of the present invention can designate production scheduling to optimize energy consumption. In addition, since it is possible to control the process of the factory 110 in the shortest time through the production scheduling of the facilities 110, 120, 121, 122, 123 and 124, Through one scheduling, the plant 110 administrator may control the facility 120, 121, 122, 123, 124.

In addition, peak interval information according to the energy consumption time of the equipments 120, 121, 122, 123, and 124 can be extracted. The demand for electric power is higher in summer and lower in power demand. In the case of a system for generating power, the system 100 for supporting the production innovation of the smart factory of the present invention can connect to the power generation system to obtain peak section information And the energy saving is performed.

At this time, if the priority of the facilities (120, 121, 122, 123, 124) is designated and it is determined that the operation time of the facilities (120, 121, 122, 123, 124) The amount of energy supplied to each of the facilities 120, 121, 122, 123, and 124 can be adjusted according to the priority. Since the facilities 120, 121, 122, 123, and 124 installed in the factory 110 can also be prioritized according to their importance, the factory evaluation management apparatus 150 of the present invention assigns priorities, Can be controlled.

For example, you can set the generator to rank 1, the mold machine to rank 2, and the lot machine to rank 3. After confirming that the operation times of the equipments 120, 121, 122, 123 and 124 are located in the peak interval received from the power generation system, the equipments 120, 121, 122, 123 , 124) can be saved. For example, the supply power of the lot machine can be reduced to 70%, and the supply power of the mold machine can be reduced to 80%, thereby efficiently consuming the entire plant 110 energy efficiently.

121, 122, 123, and 124 of the entire facility 120, 121, 122, 123, and 124, the energy schematics of the entire facilities 120, 121, , 123, and 124 can be reflected in real time on the energy diagram. Since the facilities 120, 121, 122, 123 and 124 of the plant 110 are organically linked, it is important to confirm the flow of energy. Accordingly, the system 100 for supporting the production innovation of the smart factory of the present invention can generate an energy diagram corresponding to the flow between energy and energy of the facilities 120, 121, 122, 123, .

 The factory evaluation management apparatus 150 of the present invention can confirm whether or not it is valid information among the status data and can remove unnecessary data. Since the status data received by the factory evaluation management apparatus 150 of the present invention corresponds to raw data, only necessary data among the raw data should be sorted and effectively classified. Therefore, the factory evaluation management apparatus 150 of the present invention makes it possible to determine whether or not it is valid according to a predetermined criterion, and then to remove unnecessary data.

The factory evaluation management apparatus 150 of the present invention receives status data of the facilities 120, 121, 122, 123, and 124 to identify current energy consumption status, The facilities 120, 121, 122, 123, 124 having the efficiency can be extracted. Since the factory evaluation management apparatus 150 of the present invention is required to check the energy consumption efficiency of the present facilities 120, 121, 122, 123, and 124 in order to perform energy saving, Only the low equipment (120, 121, 122, 123, 124) is extracted.

The system 100 for supporting the production innovation of the smart factory according to an embodiment of the present invention may be configured such that the facility management apparatus 160 is installed only in the facilities 120, 121, 122, 123, 121, 122, 123, and 124 that do not use power for a predetermined period of time, and do not supply power to the facilities 120, 121, 122, 123,

In addition, the system 100 for supporting the production innovation of the smart factory according to an embodiment of the present invention is characterized in that the factory evaluation management apparatus 150 has a power threshold value for each of the facilities 120, 121, 122, 123, And the facility management device 160 stops the operation of the facility 120, 121, 122, 123, 124 when the power critical point is reached.

In addition, a system 100 for supporting the production innovation of a smart factory according to an embodiment of the present invention may be configured such that the factory evaluation management apparatus 150 performs a simulation so that the facilities 120, 121, 122, 123, And a power threshold of the power control unit.

In addition, a system 100 for supporting the production innovation of a smart factory according to an embodiment of the present invention is characterized in that the sensing device 130, 131, 132, 133, 134 is connected to the facilities 120, 121, 122, 123 The facility management apparatus 160 collects environmental characteristic data of the facilities 124, 124, and the facility management apparatus 160 controls energy supply to the facilities 120, 121, 122, 123, 124 according to the environmental characteristic data.

In addition, the system 100 for supporting the production innovation of the smart factory according to an embodiment of the present invention is characterized in that the sensing devices 130, 131, 132, 133, and 134 have peak periods And the facility management apparatus 160 controls the facilities 120, 121, 122, 123, and 124 at peak intervals according to the factory evaluation work.

In addition, the system 100 for supporting the production innovation of the smart factory according to an embodiment of the present invention is characterized in that the sensing device 130, 131, 132, 133, 134 collects external situation information, The apparatus 160 is characterized in that the amount of energy supplied to the facilities 120, 121, 122, 123, and 124 is adjusted according to the external situation information.

The system 100 for supporting the production innovation of the smart factory according to the embodiment of the present invention is characterized in that the factory evaluation management apparatus 150 is configured to perform the factory evaluation management on the facilities 120, 121, 122, 123, 124), and the facility management device (160) is configured to sequentially adjust the energy supply amount in accordance with the priority order.

In addition, the system 100 for supporting the production innovation of a smart factory according to an exemplary embodiment of the present invention is characterized in that the sensing devices 130, 131, 132, 133 and 134 detect the grid frequency in real time , And the facility management apparatus (160) controls the energy supply amount when an abnormality of the system frequency occurs.

In addition, in the system 100 for supporting the production innovation of the smart factory according to the embodiment of the present invention, the facility management device 160 controls the energy supply amount according to the real-time transaction price of the energy trading market monitored in real- .

In addition, the system 100 for supporting the production innovation of the smart factory according to an embodiment of the present invention is characterized in that the facility management apparatus 160 is configured to supply energy to the plant 110 when the energy of the production system is insufficient And to provide energy in conjunction with a smart grid or a micro grid.

In this case, the energy consumption efficiency may be extracted in comparison with the production amounts of the facilities 120, 121, 122, 123 and 124 with respect to the amount of power input to the facilities 120, 121, 122, 123, 121, 122, 123, and 124 installed in the plant 110 in consideration of the standard energy consumption efficiency of the plant 120, 121, 122, 123, For example, when the predetermined energy consumption efficiency is 30%, the energy consumption efficiency of the generator is 40%, the energy consumption efficiency of the machine tool is 50%, and the energy consumption efficiency of the mold machine is 25% The management apparatus 150 allows the < &lt; / RTI &gt;

The factory evaluation management apparatus 150 of the present invention grasps the load increase and decrease of the facilities 120, 121, 122, 123 and 124 having the low energy consumption efficiency and controls the equipments 120, 121, 122, 123 , 124) of the power source. The utility refers to a heating source, a cooling source, a power source, and the like necessary for processing or manufacturing raw materials. The utilities are used to prevent malfunction or shutdown of the facilities 120, 121, 122, 123 and 124 The system should be fully managed.

The factory evaluation management apparatus 150 of the present invention grasps the load increase and decrease of the facilities 120, 121, 122, 123 and 124 having the low energy consumption efficiency and controls the equipments 120, 121, 122, 123 And 124 can be controlled. In the case of an operation process of the factory 110 that can be generally used, a process including at least one of common, injection, press, casting, painting, assembling, and melting can be set. Each process is represented by DEF (Default), INJ (Injection), PRS (Press), Diecasting Process, PNT (Paint), Assembly (ASY) .

At this time, the factory evaluation management apparatus 150 of the present invention can control the process for energy efficiency control. For example, when energy efficiency is judged to be the lowest when the facilities 120, 121, 122, 123 and 124 of the present invention correspond to the <injection> process, the factory evaluation management apparatus 150 of the present invention performs < Energy efficiency can be optimized by allowing the process to proceed first or by minimizing the &lt; injection &gt; process.

In addition, the factory evaluation management apparatus 150 of the present invention can perform production scheduling of the facilities 120, 121, 122, 123, and 124 in accordance with the current energy consumption status. The production scheduling determines the order of work to be processed, so that the factory evaluation management apparatus 150 of the present invention can designate production scheduling to optimize energy consumption. In addition, since it is possible to control the process of the factory 110 in the shortest time through the production scheduling of the facilities 110, 120, 121, 122, 123 and 124, Through one scheduling, the plant 110 administrator may control the facility 120, 121, 122, 123, 124.

In addition, the factory evaluation management apparatus 150 of the present invention can extract peak section information according to the energy consumption time of the facilities 120, 121, 122, 123, and 124. The demand for electric power is higher in summer and lower in power demand. The factory evaluation management apparatus 150 of the present invention connects to the power generation system and extracts the peak section information to save energy, .

At this time, the factory evaluation management apparatus 150 of the present invention specifies the priorities of the facilities 120, 121, 122, 123, 124 and controls the operation of the facilities 120, 121, 122, 123, 124 121, 122, 123, and 124 may be adjusted according to the priority when it is determined that the time is in the peak period. Since the facilities 120, 121, 122, 123, and 124 installed in the factory 110 can also be prioritized according to their importance, the factory evaluation management apparatus 150 of the present invention assigns priorities, Can be controlled.

For example, the factory evaluation management apparatus 150 of the present invention may set the generators in the first order, the mold machines in the second order, and the lot machines in the third order. After confirming that the operation times of the equipments 120, 121, 122, 123 and 124 are located in the peak interval received from the power generation system, the equipments 120, 121, 122, 123 , 124) can be saved. For example, the supply power of the lot machine can be reduced to 70%, and the supply power of the mold machine can be reduced to 80%, thereby efficiently consuming the entire plant 110 energy efficiently.

In addition, the factory evaluation management apparatus 150 of the present invention detects the grid frequency in real time, and when it is determined that an abnormality occurs in the power supply of the system, ) Can be adjusted. The grid can be connected to the power plant, the load concentrated on it, and the transmission line that connects it to the grid, and the overall power production and consumption status can be confirmed. At this time, the system should keep the voltage value and the frequency constant, and keep it from power failure. The factory evaluation management apparatus 150 of the present invention can determine whether or not an abnormality has occurred by detecting the system frequency in real time and checking the state of the system frequency by connecting to the system.

The plant 110 energy management system of the present invention may further include a renewable energy source for supplying renewable energy to the facilities 120, 121, 122, 123, and 124. Renewable energy refers to energy created in the natural state, and can include various energies such as solar energy, wind energy, hydro energy, biomass energy, geothermal energy, tidal energy, and wave energy. In the factory 110, a new or renewable energy source can be used to assist the generator or the power system, and energy can be supplied through the renewable energy source.

At this time, the factory evaluation management apparatus 150 of the present invention can extract a period in which the power consumption of the facilities 120, 121, 122, 123, and 124 is the maximum, and adjust the supply of the renewable energy. For example, in the case of solar energy installed in the plant 110, the energy source produced by the solar energy can be supplied to the facilities 120, 121, 122, 123 and 124. In the case of the maximum power consumption (about 14 hours to 16 hours), the power generated from the solar energy source can be maximized and supplied to the facilities (120, 121, 122, 123 and 124) The driving power of the energy source can be reduced.

The factory evaluation management apparatus 150 of the present invention generates energy diagrams for the entire facilities 120, 121, 122, 123 and 124 of the factory 110 and controls the entire facilities 120, 121, 122 and 123 The state data for the main facilities 120, 121, 122, 123, and 124 among the power plants 124, 124 can be reflected in the energy diagram in real time. Since the facilities 120, 121, 122, 123 and 124 of the plant 110 are organically linked, it is important to confirm the flow of energy. Therefore, the factory evaluation management apparatus 150 of the present invention can generate an energy diagram corresponding to the flow between energy and energy of the equipments 120, 121, 122, 123, 124 and reflect it in real time.

On the other hand, the smart factory evaluation management apparatus of the present invention may further include a simulation apparatus. The simulation apparatus may perform a simulation for the factory evaluation operation, and the simulation apparatus may generate simulation state data identical to the state data and input the same to the smart factory evaluation management apparatus. Since a fatal economic loss may occur if the driving time of the plant 110 is reduced, a simulation apparatus should be used to determine whether the plant 110 energy management system is operating normally.

The simulation apparatus of the present invention can generate simulation state data by simulating the same signal as the state data generated from the equipments 120, 121, 122, 123 and 124, and supplies the simulation state data to the factory evaluation management apparatus 150 So that it can be determined whether the factory evaluation management apparatus 150 operates properly.

The smart factory energy management system of the present invention detects the operation of the equipments 120, 121, 122, 123, 124 by sensing devices 130, 131, 132, 133 and 134, Collecting state data and consuming low power by itself.

At least several tens of information collectors are connected to each of the on-site facilities 120, 121, 122, 123, and 124 in the case of data collection centered on the conventional on-site facilities 120, 121, 122, , And one field server is connected in a spider web manner. This means that the information collector is used for all the facilities 120, 121, 122, 123 and 124, so that the total power consumed by the operation of the plant 110 facilities 120, 121, 122, 123, It increases exponentially. For example, when one on-site server and 30 information collectors are running and collecting data, about 650Wh of power is consumed.

The smart factory energy management system according to the present invention collects status data by turning on / off each time data transmission / reception of equipment is required to realize low power, so energy saving can be effective. For example, when transmitting and receiving various data such as the energy consumption of the facilities 120, 121, 122, 123 and 124, the usage amount of the cooling and heating equipment, the internal environment information and the basic 4M information, It is possible to collect status data. More specifically, when one M2M machine and 30 IoT machines are used, smart power management can be carried out with a power of about 90Wh due to the implementation of a wireless sensor based compact low power system.

The embodiments of the present invention described above are disclosed for the purpose of illustration, and the present invention is not limited thereto. It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit and scope of the invention.

100: System supporting production innovation of smart factories
110: Factory
120, 121, 122, 123, 124: Equipment
130, 131, 132, 133, 134:
140: Factory evaluation management device
150; Database
160: facility management device
170: grid
180: KPI indicator management device
190: mobile management module

Claims (7)

At least one facility installed in a factory;
At least one sensing device for collecting status data on 4M1E (Man, Machine, Material, Method, Energy) information of the factory;
A KPI indicator management device receiving the status data and generating data centered on the KPI indicator;
A factory evaluation management apparatus for conducting a factory evaluation work using data centered on the KPI index;
A system that supports the production innovation of smart factories including.
The method according to claim 1,
The KPI index management apparatus includes:
And a KPI index is extracted by weighting necessary information among the 4M1E information.
The method according to claim 1,
The KPI index management apparatus includes:
Wherein the range and kind of the KPI index to be extracted are set according to the type of the facility.
The method according to claim 1,
The KPI index management apparatus includes:
A system for supporting the production innovation of a smart factory, characterized in that the range and kind of the KPI index to be extracted are set according to the manufacturing process even if the same equipment is used.
The method according to claim 1,
The KPI index management apparatus includes:
Wherein the facility installed in the factory is divided into a plurality of predetermined layers and a KPI index is extracted according to each layer,
The system for supporting the production innovation of the smart factory, characterized in that the system is divided into one to four levels according to the functional hierarchy.
The method according to claim 1,
The KPI index management apparatus includes:
And the KPI index-centric data is generated using data centered on the KPI index having the largest correlation with the energy usage.
The method according to claim 6,
The factory evaluation management apparatus,
Wherein the energy management is performed using data centered on KPIs having the largest correlation among energy usage of facilities installed in the plant.

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