KR102366216B1 - System and method for qauality management of smart factory - Google Patents

Abstract

Disclosed are system and method for managing smart factory quality. According to the present invention, the present invention can greatly decrease an occurrence rate of a defective product in a short period of time and classify and detect defective product-related data according to a detailed factor, thereby having an advantage that can contribute to productivity improvement by increasing an yield of the defective product using related data and having an effect that can easily recognize how the defective product occurs from which unit process and under what situation.

Description

SYSTEM AND METHOD FOR QAUALITY MANAGEMENT OF SMART FACTORY

The present invention relates to a smart factory quality management system and method.

With the rapid spread of the Internet and the development of connection technology between things based on the Internet, the fourth industrial revolution is emerging. In the technology fields that lead the 4th industrial revolution, technologies related to smart factory, big data, and artificial intelligence (AI) can be selected.

The smart factory refers to the overall technology that connects and manages the machines and facilities of the factory easily. The convergence of new software technologies such as big data and AI into the hardware-connected system is a major factor accelerating the growth of the smart factory-related market. This is because it is none other than the power of software that makes smart factory management easier and makes the connection easier.

However, there are also problems with these new technologies. As too much information is placed in big data, it is very difficult to collect and analyze the necessary information. Companies form a separate solution team to solve these problems and operate them directly, but companies that do not have such resources are receiving external help through outsourcing. This problem was unexpected, and innovation in the field of information processing should be expected.

The advantage of smart factories is efficiency. However, there is a problem in that it is necessary to spend a lot of time and money to search for necessary information for quality control and to collect and analyze it in the field, and the present inventors have devised the present invention to solve these problems.

The present invention has been devised to solve the above-described problem, and the technical problem to be solved by the present invention is to provide a smart factory quality management system and method that can significantly reduce the occurrence of defective products within a short period of time.

Another technical problem to be solved by the present invention is to provide a smart factory quality management system and method that can easily determine in which unit process and under what conditions defective products occur.

Another technical problem to be solved by the present invention is to provide a smart factory quality management system and method that can detect defective product-related data according to its detailed factors and utilize it to increase the yield of good products.

Smart factory quality management system according to the present invention for achieving the above object,

A plurality of input units 100 through which defective product detection information is manually or/or automatically input through the visual inspection and/or inspection unit 400; In the quality management system of a smart factory having a database unit 200 and a control unit 300 for quality control,

The database unit 200 is provided with a defective product DB 210 having a defective product determination storage unit 211,

The control unit 300 is for identifying each defective product discovery information input through the plurality of input units 100 , and when defective product detection information is input through a specific input unit 100 , the input unit 100 is unique. It is characterized in that a defective product detail factor recognition module 310 is included to generate defective identification information obtained by further adding an identification code to the defective product detection information and store it in the defective product determination storage unit 211 .

At this time, in the defective product DB 210, the number of self-process detections in which defective products are generated and discovered within the unit process and the number of post-process discovery reports found in the post unit process that the defective product occurred in the previous unit process are in each unit process. A discovery rate information storage unit 212 that sums and stores stars is further provided,

The control unit 300 transmits the quantity of the post-process discovery report to the previous unit process, adds the quantity of the post-process discovery report and the self-process discovery quantity, and calculates the defective product discovery rate for each unit process based on this. It is characterized in that the discovery rate calculation module 320 for storing in the discovery rate information storage unit 212 is further included.

The defective product detail factor recognition module 310 generates the defective product identification information when the defective product discovery information input through the input unit 100 is generated in the previous unit process or found during the post unit process. is generated by adding a unique identification code only for the input unit 100 of , but it is counted as the number of post-process discovery reports and then stored in the discovery rate information storage unit 212 .

The defective product DB 210 is further provided with a defective rate information storage unit 213,

In the control unit 300, a defective rate calculation module ( 330) is preferably further included.

The database unit 200 further includes a non-defective product DB 220 having a non-defective product standard information storage unit 221 in which all information regarding the production standards of non-defective products is stored, and a non-defective product determination storage unit 222,

The control unit 300 includes a non-defective product detection module 340 for storing product information that has completed all unit processes without inputting defective product detection information through the input unit 100 in the non-defective product determination storage unit 222 . It is preferable to be

In the database unit 200, a solution DB having a problem book storage unit 230 in which defective product occurrence type information is recorded, and a solution storage unit 232 in which solution information for each problem recorded in the problem book storage unit 230 is stored. (230) is further included;

In the control unit 300, based on the defective rate stored in the defective rate information storage unit 213, the detailed factor of the defective rate, which occupies the largest proportion, is sequentially processed with the highest priority, and the detailed factor is the problem collection storage unit 230 After comparing and searching whether it is already stored in the , the solution information related thereto is detected in the solution storage unit 232, and then transmitted to the manager terminal 700 or/and the server 500, while corresponding to the detailed factors When the problem and/or solution information to be solved is not detected in the problem book storage unit 230 or/and the solution storage unit 232, the detailed factors are newly registered (stored) in the problem book storage unit 230 and then The fact is transmitted to the manager terminal 700 or / and the server 500, and the solution information on the newly registered detailed factors is stored in the solution storage unit 232 under the approval of the manager terminal 700 or the server 500. a solution module 350 that links them (the solution information and the problem) so that the solution information can be searched in connection with the problem when it is newly stored;

It is preferable that this is further included.

The database unit 200 further includes a history DB 240 in which search history information regarding good and/or defective products detected according to a command input to the manager terminal 700 or the server 500 is stored;

In the control unit 300, when a search command for a good product and/or a defective product is input through the manager terminal 700 or the server 500, the good product determination storage unit 222 and the defective product determination storage unit 211 a detection module 360 that detects only information that meets the search requirements based on the good product information or/and the defective identification information stored in the , and then stores the related information in the history DB 240;

It is preferable that this is further included.

The smart factory quality management method using the smart factory quality management system is

In the smart factory quality management method using the smart factory quality management system,

a) step of manually or/and automatically inputting defective product discovery information through the specific input unit 100;

b) generating and storing defective product identification information obtained by further adding a unique identification code of the specific input unit 100 to the defective product detection information;

It is characterized in that it is made so that detailed information regarding whether a specific defective product occurred in a specific unit process and a specific inspection step can be identified through the defect identification information.

On the other hand, in the smart factory quality management method using the smart factory quality management system,

a) step of manually or/and automatically inputting defective product discovery information through the specific input unit 100;

b) When a specific defective product is found within its own unit process and the defective product discovery information is generated within its own unit process, defective identification is performed by further adding a unique identification code of the specific input unit 100 to the defective product finding information. after generating the information, counting the defect identification information as the number of self-process discovery;

c) On the other hand, when a specific defective product is generated in the previous unit process and the defective product discovery information is generated in the post unit process as it is discovered in the post unit process, the defective product discovery information contains only the input unit 100 of the previous unit process. generating defect identification information obtained by further adding an identification code, and counting the defect identification information as a post-process discovery report quantity;

d) adding and storing the self-process discovery quantity and the post-process discovery report quantity in the previous unit process after the post-process discovery report quantity information is transmitted to the previous unit process and the post-process discovery report quantity information is received;

It is preferable to include

Preferably, in the smart factory quality control method using the smart factory system,

a) step of manually or/and automatically inputting defective product discovery information through the specific input unit 100;

b) generating and storing defective product identification information obtained by further adding a unique identification code of the specific input unit 100 to the defective product detection information;

c) calculating the occurrence frequency or ratio for each detailed factor among the failure identification information, and then transmitting it to the manager terminal 700 and/or the server 500;

It is preferable to include

Furthermore, in the smart factory quality management method using the smart factory quality management system,

a) step of manually or/and automatically inputting defective product discovery information through the specific input unit 100;

b) generating and storing defective product identification information obtained by further adding a unique identification code of the specific input unit 100 to the defective product detection information;

c) calculating the occurrence frequency or ratio for each detailed factor among the failure identification information, and transmitting it to the manager terminal 700 and/or the server 500;

d) Processed sequentially from the detailed factor accounting for the largest proportion in the calculated defective rate, but if the problem for each detailed factor and the solution are stored in advance, the solution is detected and the manager terminal 700 or/and the server 500 sending to;

It is preferable to include

After step c) or step d),

e) Process the detailed factors that account for the largest proportion in the calculated defective rate sequentially, but if the problem or/and the solution for each detailed factor is not stored in advance, the detailed factor is newly registered (stored) and then the fact Transmitting to the manager terminal 700 and / and server 500;

f) When the newly registered solution information of the detailed factor is newly registered (stored) under the approval of the manager terminal 700 or the server 500, the newly registered solution information is registered in connection with the newly registered detailed factor (save);

It is preferable to further include

According to the present invention as described above, it is possible to significantly lower the incidence of defective products within a short period of time, and it is possible to classify, search, and aggregate defective product-related data according to the detailed factors, and utilize the related data as data to increase the yield of good products. It has the advantage of being able to do this, and it has the effect of being able to easily determine in which unit process and under what circumstances the defective product occurred.

1 is a communication conceptual diagram of a smart factory quality management system according to the present invention.
Figure 2 is a process diagram of a smart factory quality management system according to the present invention.
3 is an exemplary configuration diagram of a quality management program mounted on a server.
4 is a block diagram schematically illustrating an execution mode of a quality control program according to the present invention.
5 is a schematic control flow chart of the 'production mode' shown in FIG.
6 is a schematic control flow diagram of the 'quality management mode' shown in FIG.
7 is a schematic control flow diagram of the 'solution mode' shown in FIG.

Hereinafter, with reference to the accompanying drawings, an embodiment of the present invention will be described in detail so that those skilled in the art can easily carry out the present invention. The present invention may be embodied in several different forms and is not limited to the embodiments described herein. In addition, in order to clearly explain the present invention, parts irrelevant to the description are omitted from the drawings, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. . Also, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated.

In the present specification, the term 'part' means a unit realized by hardware, a unit realized by software, a unit realized using both, as well as a single unit composed of a simple configuration to perform only a specific function. It was used as a concept including the device of In addition, one unit may be implemented using two or more hardware, and two or more units may be implemented by one hardware. Meanwhile, '~ unit' is not limited to software or hardware, and '~ unit' may be configured to be in an addressable storage medium or to reproduce one or more processors. Accordingly, as an example, '~' indicates components such as software components, object-oriented software components, class components, and task components, and processes, functions, properties, and procedures. , subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables, and a detection device for identifying defective products. do. The functions provided in the components and '~ units' may be combined into a smaller number of components and '~ units' or further separated into additional components and '~ units'. In addition, components and '~ units' may be implemented to play one or more CPUs in a device or secure multimedia card.

The "terminal" referred to below may be implemented as a computer or portable terminal that can access a server or other terminal through a network. Here, the computer may include, for example, a laptop equipped with a web browser, a desktop, a laptop, and a VR HMD (eg, HTC VIVE, Oculus Rift, GearVR, DayDream, PSVR, etc.). there is.

Here, the VR HMD is for PC (eg, HTC VIVE, Oculus Rift, FOVE, Deepon, etc.) and for mobile (eg, GearVR, DayDream, Storm Horse, Google Cardboard, etc.) and for console (PSVR) independently implemented Stand Alone models (eg Deepon, PICO, etc.) are all included. A portable terminal is, for example, a wireless communication device that guarantees portability and mobility, and includes not only a smart phone, a tablet PC, a wearable device, but also Bluetooth (Bluetooth Low Energy), NFC, RFID, Ultrasonic, and infrared rays. , Wi-Fi (WiFi), Li-Fi (LiFi) may include a variety of devices equipped with a communication module. In addition, "network" refers to a connection structure that allows information exchange between each node, such as a terminal and a server, and includes a local area network (LAN), a wide area network (WAN), and the Internet (WWW). : World Wide Web), wired and wireless data communication network, telephone network, wired and wireless television communication network, as well as big data implemented in the form of Internet network. Examples of wireless data communication networks include 3G, 4G, 5G, 3rd Generation Partnership Project (3GPP), Long Term Evolution (LTE), World Interoperability for Microwave Access (WIMAX), WiFi, Bluetooth communication, infrared communication, ultrasonic communication, visible light Communication (VLC: Visible Light Communication), Li-Fi (LiFi), etc. include, but are not limited thereto.

1 is a communication conceptual diagram of a smart factory quality management system 1 according to the present invention.
Referring to Figure 1, the smart factory quality management system 1 according to the present invention including a network 600 connection configuration, a server 500, one or more manager terminals 700, and one or more inspection A plurality of input units 100 are electrically connected to the inspection unit 400 consisting of the devices 410 and/or 420 and are provided for each unit process (P1, P2, ... Pn) through the network 600 through wired/wireless communication. connected The plurality of input units 100 is preferably implemented as an electronic terminal such as a PC. The input unit 100 implemented as an electronic terminal downloads and updates specific information such as set values for each unit process from the server 500 to control the production line and unit process for each unit process and update the server 500 communication is connected with The inspection unit 400, as shown in FIG. 1, consists of two inspection devices (410, 420).

2 is a process diagram of the smart factory quality management system 1 according to the present invention.
Referring to FIG. 2, it can be seen that the process line of the smart factory quality management system 1 according to the present invention consists of a plurality of unit processes (P1, P2, ..., Pn) connected to each other. Each unit process (P1, P2, ..., Pn) is provided with one input unit 100 and the inspection unit 400 electrically connected to the input unit 100 . The inspection unit 400 includes first and second inspection devices 410 and 420 . The first inspection device 410 is disposed at the front end of each unit process (P1, P2, ..., Pn), and the second inspection device 420 is the rear end of each unit process (P1, P2, ..., Pn). is placed on The inspection unit 400 is a component for sorting defective products within each unit process, and the first inspection device 410 located at the front end of each unit process P1, P2, ..., Pn is each unit process. It is a component for pre-inspection whether the material (or semi-finished product) input to the unit is suitable for the unit process (whether it is a defective product). The second inspection device 420 located at the rear end of each unit process (P1, P2, ..., Pn) inspects the suitability (whether it is a defective product) of the material (or semi-finished product) that has completed the unit process ( It is a component for inspection after completion of the process). As described above, the inspection unit 400 implemented in this way is electrically connected to the input device 100 implemented as a 'PC for unit process control'. The plurality of input units 100 allocated one for each unit process P1, P2, ..., Pn are communicatively connected to the server 500 through a network 600 as shown in FIG. 1 .

3 is an exemplary configuration diagram of the quality management program 1 mounted on the server 500 .
The control unit 300 shown in FIG. 3 is distinguished from a CPU (central control processing unit) as a hardware device of a computer in that it is a component of software. Referring to FIG. 3 , the server 500 is equipped with a quality control program 10 according to the present invention, and the quality control program 10 includes a database unit 200 and a control unit 300 . These components 200 and 300 may be installed on a storage medium (not shown) such as HDD or SSD, or these 200 and 300 may be mounted on a CD and function through a hardware device, ROM (Read only memory). It can be implemented so that The database unit 200 includes a defective product DB 210 , a good product DB 220 , a solution DB 240 , and a history DB 240 . The defective product DB 210 includes a defective product determination storage unit 211 , a discovery rate information storage unit 212 , and a defective rate information storage unit 213 . The non-defective DB 220 includes a non-defective standard information storage unit 221 and a non-defective product determination storage unit 222 . The solution DB 230 includes a problem book storage unit 231 and a solution storage unit 232 , and the history DB 240 stores search history information. The control unit 300 includes a defective product detail factor recognition module 310 , a discovery rate calculation module 320 , a defective rate calculation module 330 , a good product determination module 340 , a solution module 350 , and a detection module (360). A detailed description of the operation principle or effect such as interaction between the respective components of the database unit 200 and the control unit 300 will be described later.

Hereinafter, with reference to FIGS. 4 to 7, the operating principle or effect of the smart factory quality management system 1 according to the present invention will be described. For simplicity of explanation, unless there is a special case, the smart factory quality management system 1 according to the present invention refers to this as "system 1 according to the present invention", and the smart factory quality management method according to the present invention refers to it as " The quality control method according to the present invention” is abbreviated.

4 is a block diagram schematically illustrating an execution mode of the quality control program 10 according to the present invention. According to the command of the manager, the system 1 according to the present invention is driven, whereby the quality control program 10 is operated (process), the production mode (S10), the quality control mode (S20), and the solution mode (S30) is activated (see FIG. 4). The operating principle of the production mode (S10) will be described with reference to FIG. 5 as follows. In order to facilitate understanding, a method of dividing and explaining each of the aforementioned modes will be taken below.

[Production Mode (S10)]

5 is a schematic control flow diagram of the 'production mode' (S10) shown in FIG.
5, in the production mode (S10), the process preparation step (not shown), the first process operation step (S1), the second process operation step (S2), etc. are sequentially performed, and then the last process By operating the nth process (Sn), the finished product (good product) is shipped.

In detail, as the quality control program 10 according to the present invention is operated, when the production mode S10 is activated, the first process preparation step (reference numeral not shown) is processed. When the process preparation step (not shown) is started, the control unit 300 of the quality control program 10 stores the quality standard information storage unit 221 of the non-defective DB 220 for each unit process quality standard information ( All information suitable for determining non-defective products such as specifications of non-defective products) is detected, and the detected 'standard information of good products' for each unit process is transmitted to a plurality of input units 100 arranged in each unit process according to the command of the control unit 300, respectively. is sent The plurality of input units 100 finely adjust set values, such as current values of sensors configured in the first and second inspection devices 410 and 420 electrically connected to this 100, based on the received 'good quality standard information'. . Accordingly, the first and second inspection devices 410 and 420 disposed in each unit process are converted to a standby state, which is a state in which good products and defective products can be selected or detected in their own unit processes.

When this process preparation step (not shown) is completed, the completion signal is input to the server 500 through the plurality of input units 100, and quality control of the server 500 receiving the completion signal In the program 10, when the manager's production start command is input, the control unit 300 sequentially operates the first process (P1) to the nth process (Pn) based on the step-by-step sequence of product production (S30 to Sn). ). Accordingly, a good product (finished product) that has completed all unit processes starts to be shipped through the n-th process Pn.

However, it is not possible to increase the yield of good products only in the production mode S10, and thus the production efficiency cannot be improved. This is because it is not possible to determine whether the defective product occurs in which unit process and in which case with the above production mode (S10) alone, and the information collection and monitoring process for each detailed factor of the defective product that must be performed to improve the yield of the good product is omitted. because it has been Therefore, if only the above-described production mode (S10) is executed, a separate solution needs to be developed, and the developed solution has to collect and analyze data, and it faces a problem inevitably requiring a lot of time and money .

The present invention activates the quality control mode (S20) together with the production mode (S10) in order to solve the above-mentioned problem.

[Quality Control Mode (S20)]

6 is a schematic control flow diagram of the quality control mode (S20) shown in FIG.

Referring to FIG. 6 , in the quality control mode (S20) according to the present invention, the defective product discovery/aggregation step (S21), the defective identification information generation/storage step (S22), and the defective rate calculation/report step (S23) are sequential and clock processed thermally. Hereinafter, each step will be subdivided and described in detail with reference to FIGS. 1 to 4 .

- Defective product discovery/aggregation step (S21) · Defective identification information generation/save step (S22)

The plurality of input units 100 may be identified by the control unit 300 as a 'unique identification code' as shown in the example of [Table 1] below.

Identification target unique identification code Process classification Defective product details
(Defective product detection method) first input #One Step 1 "size" second input #2 2nd process "Fever" … … … … nth input #n nth process "Shout"

When a plurality of input units 100 are identified by the control unit 300 as shown in [Table 1], the control unit 300 determines which input unit ( 100), it is possible to determine whether input or transmission has been made, and it is possible to identify a problem (defective product detail factor) occurring in the input unit 100 . That is, for example, when it is determined that the detection signal transmitted through the second input unit of the second process to which the unique identification code "#2" is assigned is not suitable for the good product (if it is determined that the product is defective), the control unit 300 controls the defective product details It becomes possible to classify the factor as "fever".

In other words, the 'defective product detail factor' in [Table 1] means the 'defective product selection method' of the detection unit 400 for each unit process, and in the first process, the inspection unit 400 determines the "size" Defective products are selected based on , and in the second process, the inspection unit 400 selects defective products based on “heat”, and in the nth process, the detection unit 400 selects “elasticity” as the standard. Thus, it can be known that defective products are selected.

Accordingly, the control unit 300 can classify, aggregate, and search for the detection signal determined as defective by using the 'unique identification code' as the searcher or identifier. Furthermore, based on the above information, it is possible to obtain real-time automatic aggregation or statistics of defective rate information according to a specific classification criterion (eg, classification criterion for each detailed factor of defective goods) according to the frequency or rate of occurrence of defective products. Such analysis data can be used as data for improving the yield of good products.

With reference to [Table 1] and FIG. 2, the step of detecting/aggregating defective products (S21) and the step of generating/storing defective identification information (S22) will be described in detail.

For example, the second inspection device 420 of the second process P2 {a device located at the rear end of the unit process line and inspecting whether the material (or semi-finished product) that has completed the unit process (self-unit process) is defective} When the detection signal by the is transmitted to the server 500 through the input device 100 (unique identification code #2) of the second process P2, the quality control program 10 mounted on the server 500 is of good quality. The determination module 340 compares and determines whether the received detection signal matches the 'good product standard information' stored in the non-defective product standard information storage unit 221 , thereby selecting good products and defective products. If the determination result is positive (if the product is good), the non-defective product determination module 340 stores the corresponding detection signal in the non-defective storage unit 200 or only the non-determined detection signal that has completed all the final unit processes to determine good quality It is stored in the storage unit 200 .

On the other hand, if the determination result is negative (defective product), the defective product detail factor recognition module 310 of the quality control program 10 transmits the unique identification code “#2” of only the input unit 100 to the detection signal (defective product detection). information) is further added to generate 'defective identification information', and this ('defective identification information') is stored in the defective product determination storage unit 211 of the defective DB 210 .

At this time, the detection signal (defective product detection information) is transmitted to the first inspection device 410 of the second process P2 (for selecting defective products not found in the previous process, located at the front end of the process line and inputted material (or semi-finished product), the detection signal is transmitted to the server 500 in the same manner as above, and comparison judgment is made in the same manner as above. If the determination result is negative (defective products not found in the previous process), the discovery rate calculation module 320 of the quality control program 10 transmits the detection signal (defective product discovery information) to the first process (P1), which is the previous process. transmits it to the input unit 100 (unique identification code “#1”) of the The defect detection rate of the second process P2 is calculated in real time. The discovery rate calculation module 320 stores the calculated value thus obtained in the discovery rate information storage unit 212 of the defective DB 210 .

Here, since the detection signal (defective product discovery information) is generated in the first process (P1), which is a pre-process, or is found in the second process (P2), which is a post-process, the defective product detail factor recognition module 310 is related to 'defective' In generating 'identification information', a unique identification code "#1" of the input unit 100 of the first process P1, which is a previous process, is added. The 'defective identification information' generated in this way is stored in the defective product determination storage unit 211 of the defective DB 210 in the same manner as above by the defective product detailed factor recognition module 310 .

- Defect rate calculation/reporting step (S23)

The defective rate calculation/reporting step (S23) is processed based on the steps (S21, S22) described above. That is, the defective rate calculation module 330 of the quality control program 10 calculates the defective rate in real time based on the quantity of defective items stored in the defective product determination storage unit 211 for each detailed factor, and the calculated value is calculated in the defective rate information storage unit ( 213) is saved. The defect rate calculation module 330 reports the calculated value (defect rate) to the server 500 and/or the manager terminal 700 by transmitting the calculated value (defect rate) to the manager.

[Solution Mode (S30)]

7 is a schematic control flow diagram of the 'solution mode' (S30) shown in FIG.

7, it can be seen that the control flow of the solution mode (S30) consists of a detailed factor analysis step (S31), a solution detection step (S32), and a detailed factor/solution new registration step (S33).

The solution module 350 of the control unit 300 prioritizes the detailed factors of the defective rate, which occupies the largest proportion, based on the defective rate stored in the defective rate information storage unit 213 , and then sequentially/steps the lower ones Process the detailed factor analysis step (S31) processed by

Next, the solution module 350 processes the solution detection step (S32). In detail, the solution module 350 compares and searches whether or not the detailed factor of the defective product obtained through the detailed factor analysis step (S31) is stored in the problem book storage unit 230 of the solution DB 230, and then the defective product The solution information associated with the detailed factor is detected in the solution storage unit 232 of the solution DB 230 . The detection result is transmitted to the manager terminal 700 and/or the server 500 so that the manager can utilize it as reference material for problem solving.

However, if the same/similar problem or/and solution information as the defective product detail factor is not detected in the problem collection storage unit 230 or/and the solution storage unit 232, the solution module 350 is the defective product detail factor is newly registered (stored) in the problem book storage unit 230, and then the new registration is transmitted to the manager terminal 700 and/or the server 500, thereby reporting to the manager.

Thereafter, as described above, when the newly registered solution information on the detailed factor of the defective product is newly registered in the solution storage unit 232 through the manager terminal 700 or the server 500, the solution module 350 is the defective product. These (solution information and defective product detail factors) are linked so that detailed factors and solution information can be interlinked and detected.

On the other hand, when a search command related to a good product and/or a defective product is input through the manager terminal 700 , the server 500 or the input unit 100 , the detection module 360 of the control unit 300 is configured to store the good product determination unit. Based on the good product information or/and 'defective identification information' stored in 222 and the defective product determination storage unit 211, only information that meets the search requirements is detected, and the related information is the history DB of the database unit 200 It is stored in (240).

Looking at the quality control method according to the present invention based on the above description, the quality control method according to the present invention is,

a) the step of manually (in the case of visual detection) and/or automatically inputting defective product detection information through the specific input unit 100;

b) When the defective product discovery information is generated and discovered within its own unit process, the defective product detection information generates 'defective identification information' by further adding a unique identification code of the specific input unit 100 to the (defective) Counting identification information) as the number of self-process discovery;

c) On the other hand, when the defective product discovery information is generated in the previous unit process and is discovered in the subsequent unit process, the defective product discovery information is generated in the subsequent unit process, the defective product discovery information includes: generating 'defective identification information' by further adding a unique identification code only to the input unit 100 of the previous unit process and counting this (defective identification information) as the number of post-process discovery reports;

d) adding and storing the information on the quantity of the post-process discovery report with the quantity of self-process discovery of the previous unit process;

e) calculating the defective rate for each defective product detail factor based on the frequency or ratio of occurrence of each detailed factor among the 'defective identification information', and then transmitting it to the manager terminal 700 or/and the server 500;

f) Process the defective product detail factor that accounts for the largest proportion in the calculated defective product rate sequentially, but if the same or similar problem as each defective product detail factor and the solution are stored in advance, the solution is detected and the manager terminal 700 or / and transmitting to the server (500);

g) On the other hand, if the same or similar problem or/and its solution to the detailed factor of defective product is not stored in advance, the detailed factor of defective product is newly registered, and the fact is reported to the manager terminal 700 or/and the server 500 sending to;

h) When the newly registered solution information of the detailed defective product factor is newly registered through the manager terminal 700 or the server 500, the newly registered solution information is linked with the corresponding defective product detailed factor so that it can be detected registering in a linking manner;

It is preferably made of

1: Smart Factory Quality Management System 10: Quality Management Program
100: input unit (unit process PC) 200: database unit
210: defective product DB 211: defective product determination storage unit
212: discovery rate information storage unit 213: defect rate information storage unit
220: good product DB 221: good product standard information storage unit
222: good product judgment storage unit 230: solution DB
231: problem collection storage unit 232: solution storage unit
240: history DB 300: control unit
310: defective product detail factor recognition module 320: discovery rate calculation module
330: defective rate calculation module 340: good product determination module
350: solution module 360: detection module
400: inspection unit 410: first inspection device
420: second inspection device 500: server
600: network (big data) 700: manager terminal
P1: 1st process P2: 2nd process
Pn: nth process S10: production mode
S20: Quality control mode S30: Solution mode

Claims (12)

A plurality of input units 100 through which defective product detection information is manually or/or automatically input through the visual inspection and/or inspection unit 400; In the quality management system of a smart factory having a database unit 200 and a control unit 300 for quality control,
The inspection unit 400 includes a first inspection device 410 disposed at the front end of each unit process and a second inspection device 420 disposed at the rear end of each unit process,
The database unit 200 is provided with a defective product DB 210 having a defective product determination storage unit 211,
The control unit 300 is for identifying each defective product discovery information input through the plurality of input units 100, and when the defective product detection information is input through the specific input unit 100, only the specific input unit 100 A defective product detail factor recognition module 310 is included for generating defective identification information by further adding a unique identification code to the defective product detection information and storing it in the defective product determination storage unit 211,
In the defective product DB 210, the quantity of defective products generated and discovered in the unit process and the quantity of defective products generated in the previous unit process and the number of post-process discovery reports found in the post unit process are added up for each unit process. · A discovery rate information storage unit 212 to be stored is provided;
The control unit 300 transmits the quantity of the post-process discovery report to the previous unit process, adds the quantity of the post-process discovery report and the self-process discovery quantity, and calculates the defective product discovery rate for each unit process based on this. A discovery rate calculation module 320 for storing in the discovery rate information storage unit 212 is included,
The defective product detail factor identification module 310, when the defective product discovery information input through the input unit 100 is generated in the previous unit process or found during the post unit process, generates the defective product identification information A smart factory quality management system, characterized in that it is generated by adding a unique identification code only for the input unit 100 of the process, but is counted as a post-process discovery report quantity and then stored in the discovery rate information storage unit 212. delete delete According to claim 1,
The defective product DB 210 is further provided with a defective rate information storage unit 213,
In the control unit 300, a defective rate calculation module ( 330), the smart factory quality management system, characterized in that it is further included. 5. The method of claim 4,
The database unit 200 further includes a non-defective product DB 220 having a non-defective product standard information storage unit 221 in which all information regarding the production standards of non-defective products is stored, and a non-defective product determination storage unit 222,
The control unit 300 includes a non-defective product detection module 340 for storing product information that has completed all unit processes without inputting defective product detection information through the input unit 100 in the non-defective product determination storage unit 222 . A smart factory quality management system, characterized in that it becomes. 6. The method of claim 5,
In the database unit 200, a solution DB having a problem book storage unit 230 in which defective product occurrence type information is recorded, and a solution storage unit 232 in which solution information for each problem recorded in the problem book storage unit 230 is stored. (230) is further included;
In the control unit 300, based on the defective rate stored in the defective rate information storage unit 213, the detailed factor of the defective rate, which occupies the largest proportion, is sequentially processed with the highest priority, and the detailed factor is the problem collection storage unit 230 After comparing and searching whether it is already stored in the , the solution information related thereto is detected in the solution storage unit 232, and then transmitted to the manager terminal 700 or/and the server 500, while corresponding to the detailed factors When the problem and/or solution information to be solved is not detected in the problem book storage unit 230 or/and the solution storage unit 232, the detailed factors are newly registered (stored) in the problem book storage unit 230 and then The fact is transmitted to the manager terminal 700 or / and the server 500, and the solution information on the newly registered detailed factors is stored in the solution storage unit 232 under the approval of the manager terminal 700 or the server 500. When newly stored, the solution information is linked to the solution module 350 to link them (the solution information and the problem) so that the solution information can be searched in connection with the problem. Smart factory quality, characterized in that it further includes management system. 7. The method of claim 6,
The database unit 200 further includes a history DB 240 in which search history information regarding good and/or defective products detected according to a command input to the manager terminal 700 or the server 500 is stored;
In the control unit 300, when a search command for a good product and/or a defective product is input through the manager terminal 700 or the server 500, the good product determination storage unit 222 and the defective product determination storage unit 211 A detection module 360 that detects only information that meets the search requirements based on the good product information and/or defective identification information stored in each and then stores the related information in the history DB 240; characterized in that it further comprises , Smart Factory Quality Management System. In a smart factory quality control method using a smart factory quality management system including an inspection unit 400 having a first inspection device 410 disposed at the front end of each unit process and an inspection unit 400 having a second inspection device 420 disposed at the rear end in,
Manually and/or automatically inputting defective product discovery information through the specific input unit 100; and
Including; generating and storing defective identification information obtained by further adding a unique identification code of only the specific input unit 100 to the defective product detection information;
When a specific defective product is found within its own unit process and the defective product discovery information is generated within its own unit process, the defective product detection information is obtained by adding a unique identification code only for the specific input unit 100 to the defective product identification information. after generating, counting the defect identification information as the number of self-processing discoveries;
When a specific defective product occurred in the previous unit process and the defective product discovery information was generated in the post unit process as it was discovered in the post unit process, the unique identification code of the input unit 100 of the previous unit process is added to the defective product discovery information. after generating the added defect identification information, counting the defect identification information as a post-process discovery report quantity; and
The post-process discovery report quantity information is transmitted to the previous unit process, and in the previous unit process receiving the post-process discovery report quantity information, summing and storing the self-process discovery quantity and the post-process discovery report quantity; Characterized in the smart factory quality control method. delete 9. The method of claim 8,
Calculating the occurrence frequency or ratio for each detailed factor among the defect identification information, and then transmitting it to the manager terminal 700 or/and the server 500; Smart factory quality control method comprising: a. 11. The method of claim 10,
The detailed factors occupying the largest proportion in the calculated defective rate are processed sequentially, but if the problem for each detailed factor and the solution are stored in advance, the solution is detected and transmitted to the manager terminal 700 or / and the server 500 A smart factory quality control method comprising the; 12. The method of claim 11,
If the problem or / and the solution for each detailed factor is not stored in advance, the detailed factor is newly registered (stored), and then the fact is transmitted to the manager terminal 700 or / and the server 500;
When the newly registered solution information of the detailed factor is newly registered (stored) under the approval of the manager terminal 700 or the server 500, the newly registered solution information is registered (stored) in connection with the newly registered detailed factor. ) step; smart factory quality control method, characterized in that it further comprises.

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