KR101995275B1 - Method and system for optimizing production of clothes and operation of apparel production factory - Google Patents

Abstract

Disclosed is a method for optimizing production of apparel and operation of a factory. According to the present invention, working element monitoring data obtained by measuring one or more working elements related to apparel production according to a time is collected in a computer device, codewords of a predetermined format are generated by using the collected working element monitoring data, and the generated codewords are stored in a data storage. In addition, conditions for apparel production are inputted. Based on the apparel production information data and a predetermined rule, an optimal codeword matched with the conditions is searched and proposed among the codewords stored in the data storage. Also, configuration information of an optimal production line is generated by selecting an optimal worker and equipment based on the proposed optimal codeword. Thus, according to the present invention, an optimal production method for various complex situations generated in an apparel factory and important requirements for each order can be derived.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and system for optimizing production and operation of clothes manufacturing plants,

The present invention relates to a method and system capable of optimizing the production and operation of a garment in a garment production plant.

Apparel manufacturing is a traditional manpower-intensive industry and all work is being done by manpower. It is impossible to make large-scale investment to transform the production factory of Korean apparel producers into the labor-intensive work environment of the local workers (IoT) based on the Internet (IoT). In order to maximize work efficiency, productivity, and prevent accidents, it is necessary to closely monitor the work situation of the garment production equipment covered by the workers and the work environment in the factory.

The relationship between the amount of time required to produce a specific design of clothing and the number of equipment and workers required depends on the material (woven, knit) of the fabric, the style of clothing (top, bottom, etc.) do. When the bar production line is formed in the form of a line, after the production of one style of clothing is finished, in order to produce another style of clothing, the layout of the bar production line must be newly designed according to the new style. The layout of the production line is newly designed and it takes a long time for the production speed to reach a certain level.

It is common to produce different kinds of garments in one factory. In the garment factory, various orders can be received at the same time and the garment production work can be performed concurrently according to the conditions of each order. Depending on the order, the important factors may be different. For example, there may be orders that are most important to meet delivery deadlines, cost savings are more important than delivery deadlines, and in some cases there may be orders where quality assurance is more important than delivery or cost savings. Workers' ability to work is not uniform. There may be a large variation among workers in the speed of work and the incidence of failure. There may be variation among garment production equipment in terms of availability, failure rate, processing power, and so on. Taking these points into consideration, it is difficult to effectively respond to a specific order, and the productivity may be lowered, if the production line is not constructed flexibly according to the elements that are important in each order.

However, considering the requirements of each order, designing the layout of the optimal production line for it, and determining the optimal equipment and operators requires comprehensive information about equipment and workers in the plant. Existing garment factories are not equipped with such comprehensive information because they are equipped with simple automation or partial automation environment. Therefore, the layout of the optimal production line for each order, and the equipment and worker to be assigned to it, were determined by intuition based on the experience of an experienced manager or worker. It is not known whether the production line determined by intuition is optimal for the requirements of the order and the production information of the factory. There is a limit to accurately determining the production capacity of the plant, which makes it difficult to respond effectively to new orders.

Korean Patent Registration No. 10-1308202

The present invention encodes information on the collected production equipment and workers using various means, and automatically generates an optimal production line and work line information that can satisfy specific conditions and production information by using a machine learning technique And to provide a system and a method for optimizing a garment production and operation of a factory.

The present invention is not limited to the above-described embodiments, and various modifications may be made without departing from the spirit and scope of the invention.

According to another aspect of the present invention, there is provided a garment production factory in which a plurality of workers use a plurality of equipment for producing clothes to produce garments, the garment production factory comprising: (a) A monitoring data collection step of collecting, at a computer device, work element monitoring data obtained by measuring a plurality of work elements including a worker and equipment related to production over time; (b) a code word generation step of generating, in the computer device, a code word of a predetermined format relating to the plurality of work elements, each of which is obtained by coding the collected work element monitoring data based on a predetermined code generation rule; (c) a code word storing step of storing, in the computer device, a code word generated in the code word generating step so as to constitute a codebook, which is a set of codewords, combined with a codeword generated in the data store; (d) In the computer device, a requirement input step of inputting a requirement relating to garment production; And (e) in the computer apparatus, based on production information data and a predetermined rule, an optimum codeword matching the requirement is found in the codebook stored in the data repository, And a presentation step. The codeword of the predetermined format relating to the work elements may include monitoring information for each work element related to the work elements necessary for producing the garment in the garment production factory, A code representing each piece of information of equipment and worker's work level for producing clothes and a time stamp representing a generation time information of the corresponding code word.

In an exemplary embodiment, the garment production and factory operation optimization method comprises the steps of: (f) determining, at the computer device, a production line layout that includes optimal equipment placement information based on the optimal codeword, And an optimum production line generation step of generating and outputting optimal production line information including placement information of optimal workers to be input.

In an exemplary embodiment, the configuration information of the optimal production line may include optimal production line layout information including the arrangement of the optimal equipment combination, and optimal worker placement information for each of the optimum equipment.

In an exemplary embodiment, the configuration information of the optimal production line may further include information on a work environment and information on a work line arrangement.

In an exemplary embodiment, the optimal production line layout information includes a production line layout to ensure minimum production time, a production line layout to ensure minimum cost, a production line layout to ensure minimum energy consumption, a top quality A production line layout to ensure minimum disaster occurrence, and a production line layout to ensure minimal disaster occurrences.

In an exemplary embodiment, the monitoring information for each task element includes information on a monitoring source, a monitoring target, and characteristics of a monitoring target, the task status information includes an operator's unique number and status information, And status information, and information on the job content, and the job level information may include information on the level of the work performance of each of the worker and the equipment.

In an exemplary embodiment, the monitoring information for each working element may include energy monitoring data for each equipment.

In an exemplary embodiment, the energy monitoring data for each device may include information on the amount of power consumed by each device, monitoring information on the status of the equipment, and monitoring information on the operation time of the equipment.

In an exemplary embodiment, the monitoring information for each working element may further include at least one of environmental related monitoring data in the factory, worker activity monitoring data, and worker recognition data.

In an exemplary embodiment, the 'environment-related monitoring data' may include monitoring data regarding at least one of temperature, humidity, air pollution degree, illuminance, and noise in the garment production factory.

In the exemplary embodiment, the 'worker's activity monitoring data' may include at least a part of the information about the hand movement of the worker, the movement of the work, and the work movement line in the production line of the worker.

In an exemplary embodiment, the 'operator recognition data' may include information about the recognition (identification) of the operator, and the spatial matching between the operator and the equipment.

In an exemplary embodiment, the requirement is determined by reflecting a predetermined weight in each of the predetermined requirement input elements, and the predetermined requirement input element is selected from the group consisting of shortening delivery time, cost reduction, energy saving policy, quality assurance, Disaster and accident prevention.

In an exemplary embodiment, the predetermined rule includes at least a minimum amount of process information necessary for designing a garment production line, and a rule determined at the garment production management level, and at least a statutory working time information, And < / RTI >

In an exemplary embodiment, the production information data may include information on raw subsidiary material status, production order quantity, delivery date, factory operation date, and target quality.

In an exemplary embodiment, the step of presenting the optimal codeword comprises: classifying codewords of the codebook according to a codeword criterion conforming to the requirement; And reordering the categorized codewords to locate and present the optimal codeword.

In order to accomplish the above object, according to embodiments of the present invention, there is provided a garment production factory in which a plurality of workers use a plurality of equipment for producing clothes to produce clothes, A plurality of sensor units for generating work element monitoring data by measuring a plurality of work elements including an operator and equipment over time; And a computer device for receiving the work element monitoring data through wireless communication from the plurality of sensor units and presenting a production line for production of clothing and optimization of factory operation. The computer device includes: (a) a monitoring data collector for collecting work element monitoring data generated by the plurality of sensor units; (b) a code word generator for generating a code word of a predetermined format relating to the plurality of work elements in which the collected work element monitoring data is encoded and combined based on a predetermined code generation rule; (c) a codeword storage unit which receives the codeword generated from the codeword generation unit and combines the generated codeword and a codeword, which is a set of codewords, to form a codeword; (d) a requirements input section for inputting requirements relating to garment production; (e) a production information storage unit for storing production information data and a predetermined rule; And (f) a processor for finding an optimal code word in the codebook stored in the code word storage unit, based on the production information data and the predetermined rule, in accordance with the requirement. The codeword of the predetermined format relating to the work elements may include monitoring information for each work element related to the work elements necessary for producing the garment in the garment production factory, A code representing each piece of information of equipment and worker's work level for producing clothes and a time stamp representing a generation time information of the corresponding code word.

In an exemplary embodiment, the computer device may further include a production line layout including optimal equipment layout information, based on the optimal codeword found by the processing section, and layout information of optimal workers to be input to the production line layout And outputting the optimized production line information.

In an exemplary embodiment, the result display unit may further generate optimal work environment information, arrangement of work space, and copper line information of an operator and a work based on the optimal codeword in the factory.

In an exemplary embodiment, the optimal production line information includes at least one of a production line layout to ensure minimum production time, a production line layout to ensure minimum cost, a production line layout to ensure minimum energy consumption, A production line layout for ensuring minimum disaster occurrence, and a production line layout for ensuring minimum disaster occurrence.

In an exemplary embodiment, the monitoring information for each task element includes information on a monitoring source, a monitoring target, and a characteristic of a monitoring target, the task status information includes worker information, equipment information, and work content, The task level information may include information about the level of work performance of each of the worker and the equipment.

In an exemplary embodiment, the monitoring information for each working element includes at least one of (i) 'energy monitoring data for each equipment', including information on the amount of power consumed by each equipment, monitoring information on the status of the equipment, (ii) environment-related environmental monitoring data including monitoring data on at least one of temperature, humidity, air pollution degree, illuminance, and noise in the garment production factory, (iii) (Iii) information on the worker's work activity, including at least one of information on the worker's work line and information about the worker's work line in the worker's work line; and (iv) And ' operator identification data ' including information.

In an exemplary embodiment, the requirement is determined by reflecting a predetermined weight in each of the predetermined requirement input elements, and the predetermined requirement input element is selected from the group consisting of shortening delivery time, cost reduction, energy saving policy, quality assurance, Disaster and accident prevention.

In an exemplary embodiment, the predetermined rule may include at least a minimum amount of process information required for designing a garment production line, and at least a rule determined at the garment production management level and at least a statutory working time information, And at least one of the rules to be set.

In an exemplary embodiment, the production information data may include information on raw subsidiary material status, production order quantity, delivery date, factory operation date, and target quality.

In an exemplary embodiment, the processing unit classifies codewords of the codebook stored in the codeword storage unit according to a codeword criterion that meets the requirement, rearranges the codeword codewords to obtain an optimal codeword Can be found and presented.

In an exemplary embodiment, the processor may find the optimal codeword through machine learning and word recognition using a back-of-the-word (BoW) algorithm.

According to the method and system for manufacturing garments according to the present invention, it is possible to collect all the signals of the garment production site efficiently by using various data collection means such as energy monitoring, environmental monitoring, vision monitoring, and worker wearable apparatus. The collected data can be processed using the Bag of Words (BoW), which is a running technique, to present the results related to the layout of the production line best suited to the input conditions, the composition of the worker and equipment to be input. Therefore, it is possible to derive optimal production methods for various complex situations and order-specific requirements occurring in garment factories. In other words, it can offer the best alternative to various requirements that may occur in the garment production site, such as shortening delivery time, cost reduction, energy saving, defect reduction, and disaster prevention.

In addition, it is possible to construct the best production line by responding quickly and flexibly and systematically to the varying requirements for product production. Compared to the existing method of reliance on intuition, productivity can be greatly increased and costs can be reduced. It is possible to build a production environment that best meets the requirements of the order.

FIG. 1 shows the overall system environment of a garment factory for carrying out a garment production and a factory operation optimization method according to an embodiment of the present invention.
FIG. 2 is a flowchart showing a procedure for executing a method of optimizing clothing production and factory operation according to an embodiment of the present invention.
3 is a functional block diagram of an optimizing system for garment production and factory operation according to an embodiment of the present invention.
FIG. 4 is a diagram of a monitoring data classification system in which data collected by the data collection unit shown in FIG. 3 is classified.
5 illustrates a code format for coding data collected in a data collection unit according to an embodiment of the present invention.
6 shows an example of a codeword made in the code format of FIG.
FIG. 7 schematically shows data input to the processing unit shown in FIG.
FIG. 8 is a worker category diagram that classifies workers at the plant according to their work speed and quality level.
FIG. 9 is a table summarizing the relationship between the working element conditions for garment production and the preceding three digits of the codeword.
Fig. 10 shows an example of the layout of the optimum production line provided in the result display section of Fig.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The same reference numerals are used for the same constituent elements in the drawings and redundant explanations for the same constituent elements are omitted.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 shows the overall system environment of a garment factory for implementing a method for optimizing garment production and plant operation according to an embodiment of the present invention.

In the apparel manufacturing plant, the textile fabric is cut according to the design, and the cut pieces of the fabric are sewn together to make clothing. To this end, garment production equipment such as a large number of motorized sewing machines and motorized fabric cutting machines are installed and used in the factory. In addition, in the case of garment production using downy hair or goose down hair, a hair padding washing machine is necessary. In place of the stapling, a sim sealing machine for heating two fabrics by attaching heat, and other automation cam sewing machine, Can be operated. In FIG. 1, these garment production equipments are represented by reference numeral 21 in the form of a sewing machine. For example, there are thousands of electric sewing machines installed in a garment production factory of a certain size, and there are many equipments such as a motorized fabric cutting machine installed in more than a few tens.

Referring to FIG. 1, a garment production plant system 10 may include a sensor installed for each garment production equipment 21 and monitoring electric energy consumed in the garment production equipment 21. The amount of electric energy (electric power) used can be calculated by measuring the amount of electric current with time under the condition of knowing the voltage. The sensor may therefore be a current sensor 22. The current sensor 22 is installed on an electric wire connecting the socket and the clothes production equipment 21 and can measure the amount of electric current supplied to the clothes production equipment 21. [

According to an exemplary embodiment, the garment production plant system 10 may monitor, in addition to monitoring for use of electrical energy, work related factors that may affect garment production operations. To this end, the garment production plant system 100 may include an environmental sensor unit 30, which is a collection of various environment-related sensors for monitoring the environment in the factory, and a camera unit 35, for monitoring the work situation of the operator .

According to an exemplary embodiment, the garment production plant system 10 may also include a wearable device 25 configured to be worn by an operator with an embedded RFID tag or chip containing operator identification information, And a reader 24 that can be installed near the portable device 21 and configured to read the worker identification information embedded in the wearable device 25. [ When the worker wearing the wearable equipment 25 is located in the clothes production equipment 21, the reader 24 can read the worker identification information from the wearable equipment 25. [ Through this, it is possible to measure worker's working time and work characteristics.

The environmental sensor unit 30 may include a temperature sensor, a humidity sensor, an illuminance sensor, a noise sensor, and atmospheric sensors (carbon dioxide, fine dust, and air pollutants detection sensors). The wearable device 25 may be a wearable device that is built in an RFID tag or chip containing operator identification information and can be worn on the wearer's wrist or neck. The smartphone of the worker may be used in parallel with the wearable device 25 or as an identification means of the worker on behalf of the wearable device 25. [

These sensor devices 22, 24, 25, 30, and 35 may be communicably connected to the server computer 23 through a communication network. To this end, the sensor devices 22, 24, 25, 30, and 35 may themselves have separate communication modules (not shown) to communicate directly with the server computer 23, Lt; RTI ID = 0.0 > 23 < / RTI > The computer device 230 receives information on the state of the production line including the power consumption of the garment production equipment 21, the failure status, the worker's work time, etc. from the sensor devices 22, 24, 25, Can be obtained.

The computer device 23 may be communicatively coupled to the sensor devices 22, 24, 25, 30, 35 via a communication network 37 established at the factory. The communication network 37 may be configured using at least a part of a known local area wireless communication network (e.g., Wi-Fi communication), a wired communication network, the Internet, a mobile communication network, and the like. The computer device 23 determines whether or not the power consumption and failure of the entire apparel production equipment 21 from the sensor devices 22, 24, 25, 30 and 35, the work status of the operator, the environment in the factory, Can be received in real time. The computer device 23 can perform various processes to be described later with reference to FIG. 3 to automatically generate information on the optimal production line design and operator arrangement that can best meet the requirements.

FIG. 2 is a flowchart showing the overall execution sequence of a method for optimizing garment production and factory operation according to an embodiment of the present invention.

According to a method for optimizing garment production and factory operation according to an exemplary embodiment of the present invention, at least one or more work elements related to garment production may be provided to the sensor devices 22, 24, 25, 30, (S10), and the measured work element monitoring data may be collected by the computer device 23 (S20).

The computer device 23 can generate a code of a predetermined format using the collected work element monitoring data based on a predetermined code generation rule to be described later (S30).

The generated new code may be stored together with the existing code generated through the same process in the data storage of the computer device 230 together. Each of the stored codes becomes a code word, and the entire code words constitute a codebook (S40).

In the state where the codebook is provided, when a certain order about a garment production is received, the computer device 23 can receive a work element condition related to the garment production determined by the order. In addition, production information data necessary for the production of the clothes and rule / rule information of a managerial / policy level can be further inputted (S50). Rule information at the managerial / policy level can be an example of working time agreed upon between labor and management, legal working hours, and sanctions at the national level for energy saving.

In the computer device 23, an operation for finding an optimum code word matching the working element condition related to the garment production determined by the order, based on the inputted production information data and rule information on the managerial / policy level, (S60). The computation can be performed, for example, by applying an algorithm called Bag of Words, which is one of the machine learning techniques.

The computer device 23 can select an operator and an apparatus that are optimal for the work element condition based on the optimum code word found through computation and generate an optimal production line layout. The generated information can be output so that the user can know it (S70). This allows the user to automatically obtain information on the production line that is optimal for the requirements of a particular order. Since the optimal production line information is automatically generated by the computer device 23 through calculation based on the machine learning technique, the accuracy and promptness can be ensured, and the optimum production line can be constructed quickly and accurately.

The method of optimizing clothes production and factory operation according to the embodiment of the present invention described above will be described in more detail below. The method of the present invention may be implemented as a program executable by the computer device 23. The program may be stored in a computer-readable recording medium.

3 shows functional blocks of an optimizing system 100 for garment production and factory operation according to an embodiment of the present invention.

3, the exemplary optimization system 100 of the present invention includes a data collection unit 110, a code generation unit 120, a code storage unit 130, a production information storage unit 140, A condition input unit 150, a processing unit 160, and a result display unit 170. The optimization system 100 generates various data collected from various sensor devices 22, 24, 25, 30, and 35 in a garment production factory in a predetermined format code (for example, a numeric code) Therefore, it is possible to suggest a method to construct an optimal production line based on the BoW technique, which is one of the machine learning techniques.

The data collecting unit 110 may collect various work element monitoring data generated by the various sensor devices 22, 24, 25, 30, and 35. 4 is a diagram of a monitoring data classification scheme for classifying data related to work elements that the data collection unit 110 collects from the various sensor devices 22, 24, 25, 30,

4, the data collecting unit 110 includes an energy monitoring unit 112, an environment monitoring unit 114, a vision monitoring unit 116 such as a camera 35, and an operator recognizing unit 118 .

The energy monitoring unit 112 may collect the energy monitoring data related to the power consumption of each device through the current sensor 22. The environmental monitoring unit 114 can collect monitoring data on the environment in the plant through the environmental sensor unit 30. [ The work activity monitoring unit 116 can collect monitoring data on work activities performed by the worker using the equipment 21 through vision monitoring using the camera unit 35. [ The worker recognition unit 118 can collect data on the worker recognition using the data collection device such as the wearer's wearable device 25 or the mobile input device.

The collected data can be subdivided into a monitoring source (the first digit of a code to be described later), a monitoring target (a second digit of a code to be described later), and a monitoring target characteristic (a third digit of a code to be described later).

Energy monitoring (code: 1) by the energy monitoring unit 112 detects the amount of current supplied to the equipment by the current sensor 22 installed in each equipment, and the IoT-based smart And calculating the amount of power using a meter or the like. (Code: 1-1), equipment status monitoring information (code: 1-2), working time monitoring information (code: 1-3) And the operator characteristic monitoring information (code: 1-4). Such monitoring information may be further classified in one step as shown in FIG. 4, and three-digit codes may be assigned thereto.

For example, it is possible to extract more detailed information from the current amount information according to the time consumed by the specific equipment 21, that is, the energy use measurement information (code: 1-1). Specifically, the amount of energy consumption (code: 1-1-1), the amount of standby power consumption (code: 1-1-1), the amount of power consumption by time slot (code: 1-1 -3), daily and seasonal power consumption (codes: 1-1-4), and so on.

Further, information (code: 1-2) obtained by monitoring the state of the equipment can be extracted through current amount information or energy use information according to the time consumed by the specific equipment 21. More specifically, for example, information (code: 1-2-1) about whether the equipment is currently in a good state or a bad state, information on when maintenance is required (code: 1-2-2) (Code: 1-2-3) regarding whether or not the user indicates an abnormality symptom. That is, if the equipment in which the work is input is monitored as not using the current for a predetermined time or longer, it can be regarded as a state in which a failure has occurred, and the time when the total cumulative time spent in the work reaches the reference time can be calculated as the maintenance required time , It can be determined that an abnormal symptom occurs if the pattern of current consumption is not regular or not normal.

Further, it is possible to monitor the work time (code: 1-3) from the electric current amount or the electric energy amount information consumed by the electric sewing machine 21 with time. Specifically, the electric sewing machine performs work by consuming electric current. (Code: 1-3-1) can be calculated from the current amount information according to the time, and when any electric sewing machine 21 moves from one working step to another, the operation is stopped, It is possible to extract information (code: 1-3-2) concerning the delay time between work processes.

The operator's characteristic can also be monitored (code: 1-4) from the current amount information according to the time consumed by the motor-driven sewing machine 21. (Code: 1-4-1), the work characteristics (code: 1-4-2) performed by the worker in each time period, the daily work characteristics (code: 1) -4-3), and information about individual characteristics (codes 1-4-4) of each worker can be extracted.

The environmental monitoring (code: 2) by the environmental monitoring unit 114 uses the IoT-based environmental sensor unit 30 to measure the temperature and humidity (code: 2-1) -2), illuminance (code: 2-1), and noise (code: 2-1) can be measured over time. By comparing the measured data with the existing work efficiency data, the optimal working efficiency condition information (code: 2-0-1), safety hazard environment information (code: 2-0-2), and health hazard information (code: 2-0-3).

Vision monitoring (code: 3) collected by the work activity monitoring unit 116 is realized by processing a video captured by the camera unit 35 such as a webcam, a CCTV, and the like installed in each equipment 21 with computer vision technology, (Code: 3-1), worker monitoring information (code: 3-2), and work line and worker's line monitoring information (code: 3-3) in the production line. More specific information such as a failure occurrence condition, an accident occurrence condition, a movement distance, and the like can be extracted from these pieces of information.

More specifically, the defect occurrence condition (code: 3-1-1) and the accident occurrence condition (code: 3-1-2) information can be extracted from the workpiece monitoring information (code: 3-1). For example, when the sewing operation is performed by the electric sewing machine 21, the movement or the stuck state of the cloths can be analyzed through the image to determine whether the cloth is normal or not. That is, it is possible to determine from the photographed image whether the condition of the failure of the stapling operation or the condition that the accident occurs to the operator or the like.

3-2-1), fault occurrence condition (code: 3-2-2) and accident occurrence condition (code: 3-2-3) from the worker monitoring information (code: 3-2) Can be extracted. That is, it is possible to recognize the operator by photographing the hand gesture of the operator, and to determine whether the hand gesture of the operator corresponds to a hand gesture that can cause a defect, a dangerous hand gesture that may cause an accident, and the like.

(Code: 3-3-1) and an accident occurrence condition (code: 3-3-2) from the work copper wire monitoring information (code: 3-3).

The worker recognizing unit 118 can know who is the worker who has entered the specific equipment 21 (code: 4). Specifically, by recognizing an operator wearing the wearable device 25 by using the RFID chip built in the wearable device 25 in the form of a wrist or a necklace and the RFID reader (not shown) installed in each device, (Code: 4-0-1), or inputting worker information for each equipment (code: 4-0-2) by using an application or the like to a mobile device such as a mobile phone, Can be recognized.

The code generating unit 120 may generate the work element monitoring data collected by the data collecting unit 110 as a code of a predetermined format based on a predetermined code generation rule. Figure 5 illustrates a code format according to an exemplary embodiment of the present invention. 6 shows an example of a codeword made in the code format of FIG.

Referring to FIG. 5, an exemplary code format includes a monitoring source, a monitoring target, and an operation including information on monitoring information per work element including information on characteristics of the monitoring target, worker information, equipment information, Job level information, including status information, information about the level of workers and equipment; And a time stamp including code generation time information. According to an exemplary embodiment, the code may be a numeric code. Appropriate number of digits can be given for each item.

Specifically, the monitoring source 119-1 of the first stage, the monitoring object 119-2 of the second stage, and the characteristics 119-3 of the monitoring object of the third stage constituting the monitoring information for each working element, Can be given a single digit. The monitoring source 119-1 can be divided into energy monitoring, environmental monitoring, work activity monitoring, and operator recognition, and these four sources can be divided into single digits. Since the monitoring target 119-2 is divided into at most four types for each monitoring source 119-1 (for example, in the case of energy monitoring, four kinds of energy use measurement, equipment condition monitoring, work time monitoring, and operator characteristic monitoring) , And the monitoring target 119-2 can be given a single digit. Since characteristics (119-3) of the monitoring target are divided into at most four types for each monitoring target 119-2 (for example, the characteristics of the energy monitoring-energy use measurement are energy consumption, standby power consumption, Four kinds of seasonal consumption per day), one digit can be given.

The worker information constituting the work status information may include worker identification information (unique number) of the fourth step and worker status information of the fifth step. The worker identification information (unique number) may be given a number of digits considering the maximum number of workers and the maximum number of equipment in the factory. For example, if the number of workers is not more than ten thousand, four digits can be assigned. In the 4 digits of the worker identification information, a predetermined worker-specific number can be inputted. Since the worker state information can express states such as available, in-work, and unavailable, one position can be given. If the worker status is available, working, or not available, it can be expressed as numbers 1, 2, and 3 respectively.

The equipment information constituting the work status information may include the equipment identification information (unique number) of the sixth step and the equipment status information of the seventh step. If the device identification information (unique number) does not exceed ten thousand, four digits can be assigned. A pre-designated device-specific number may be entered in the 4 digits of the equipment identification information. Equipment status information can be given a single digit as long as it can represent state information such as availability, work in progress, inapplicability, and maintenance need. If the condition of the equipment is available, in operation, not available, or maintenance required, it can be expressed as numbers 1, 2, 3, and 4, respectively.

The work content of the eighth step constituting the work situation information may indicate a detailed process of the predefined garment production work. Since there are no more than 99 kinds of detailed processes of apparel production work, it is possible to give two digits to the work contents of the eighth step. In the two digits of the work contents, the detailed process number of the garment production work designated in advance can be inputted.

Equipment and operator level information can include operator level and equipment level. It may also include the level of combination of operator and equipment. It is considered that the work level may vary depending on the type of equipment used by a worker. A single digit may be assigned if the level of the operator 9 in the ninth stage, the level of the equipment in the tenth stage, and the level of the 'operator + equipment combination' in the eleventh stage are separately displayed in the levels 0 to 9. If you need to show the level in more detail, you should give it a number of digits rather than a single digit. The level of the operator, equipment, operator + equipment combination may be the level of the pre-designated third-level monitoring source and target specific characteristics. The state of the equipment, the productivity of the worker by the time of day, the condition of the accident occurrence, and the like, and the state of the equipment as an example can not be activated from the data collected from the plurality of monitoring sources in the data collection unit, 10 ', and the productivity of the worker can be from the lowest level' 0 'to the highest level' 10 '.

The time stamp is information indicating the time when the corresponding code is generated. For example, if it is set to display up to the second and the seventh digits, 14 digits can be given.

The code illustrated in FIG. 6 is a code consisting of a total of 18 digits from the monitoring source of the first stage to the level of the 'equipment + operator combination' of the eleventh step. For convenience, the drawing does not include a timestamp, but is actually included as part of the code. The code value illustrated in FIG. 6 is '113123421234255576'. The meaning of this code value is as follows.

(i) codes for measuring energy use by time period (1st stage 1, 2nd stage 1, 3rd stage 3);

(ii) the code generated by the worker 1234 in the current work (the fourth step 1234, the fifth step 2);

(iii) 55 operations are being performed with equipment 1234 (sixth step 1234, seventh step 2, eighth step 55);

(iv) the worker's energy consumption level is intermediate (level 9, step 5);

(v) The energy consumption level of the equipment is at the high level (10th step 7); And

(vi) The energy consumption level of the worker + equipment combination is slightly higher than the middle level (Step 11, Step 6).

Referring again to FIG. 3, the code storage unit 130 stores the newly generated new code in the code generating unit 120 together with the existing code that has already been generated. Each code stored in the code storage unit 130 can be regarded as a code word in the back-of-the-word (BoW) technique. The code storage unit 130 may be regarded as a code book including these codewords.

The code storage unit 130 may store a code generated from the code generator 120 and a newly generated code (codeword). A set of codewords combined with existing and new codes can serve as a codebook.

The production information storage unit 140 may store production information data and other data as information and rules. Specifically, the production information storage unit 140 may store the current status information related to the production information such as the raw material status, the production order quantity, the delivery date and the available date, and the target quality input by the manager in cooperation with the MES system. In addition, the production information storage unit 140 may store and store 'Rule' so that the consultation of the expert in garment production or the observation result of the manager can be applied as a reference of the 'processing facility'. The production information storage unit 140 may provide the stored information to the processing unit 160. [

The condition input unit 150 may receive conditions related to factors to be emphasized in the garment production factory production and operation optimization elements. The information inputted through the condition input unit 150 is information for presenting a goal of designing an optimum production process. For example, it is possible to input requirements such as whether the focus of the optimization is to be completely focused on delivery shortening, or to which ratio is to be allocated to cost reduction or quality guarantee. The condition can be entered by the user through the input device. That is, the manager of the factory can input the conditions regarding the optimum production and operation, which are determined based on the order, through the condition input unit 150. The target criteria of the optimization process design inputted to the condition input unit 150 may be provided to the processing unit 160. [

The condition input element can include delivery time, cost reduction (minimum line operation), policy (energy saving policy etc.), quality assurance (reduction of defect rate etc.), accident / disaster prevention. The contents of each condition input element are summarized in the following table.

Conditional element Contents Short delivery time (A) It is a condition that requires a way to shorten production time. If the purchaser requires a short production period, this condition can be used to produce a demand that can be produced in the shortest time. Cost savings (B) In order to operate economical factories, it is a condition that requires a way to produce clothes according to delivery time with minimum line operation. With this condition, it is possible to obtain the most economical plant operation result within conditions that increase the production cost or increase the inventory rate of the warehouse by operating more lines than necessary. Energy policy (C) Although energy savings are related to costs, it is a condition that requires measures to be implemented when energy conservation measures are to be implemented by the policies of the government and local governments. This condition can lead to a line operation result that can meet the energy saving policy. Quality assurance (D) It is a condition that requires a method to minimize the defect rate. Through these conditions, it is possible to derive the result of presenting the worker with the worst defect among the workers, the equipment of the good condition into the production line, and the plant environmental conditions that can reduce the defect rate. Disaster / accident prevention (E) It is a condition that requires measures to minimize safety accidents and disasters in clothing production factories. This condition can result in minimizing disasters or safety accidents during the production process.

The conditions may be entered as a single condition or as a complex condition. In the case of inputting a compound condition, it can be inputted by assigning weight according to condition. For example, when the delivery shortening (A) is entered under a single condition, A = 100% can be input. That is, for a single condition, the weight is 100%. Alternatively, for example, when three conditions of shortening delivery time (A), cost reduction (B), and energy policy (C) are inputted in combination, for example, A = 50%, B = 30%, C = 20% Weights can be assigned to each condition.

The processor 160 searches the code storage unit 130 for a code best suited to the requirement received from the condition input unit 150 based on the information and rules of the production information storage unit 140, can do. According to an exemplary embodiment, the optimal code can be found through machine learning and word recognition, basically applying a back-of-the-word (BoW) algorithm.

The BoW algorithm is a machine learning algorithm known as a technique for classifying the types of documents by looking at the distribution of words in a document to automatically classify the documents. BoW algorithm is widely used in image processing and computer vision in recent years. The procedure of the BoW algorithm is as follows.

The existing BoW algorithm first extracts the feature of the object. In the present invention, the object is codewords, since the codewords already include the features, this process can be omitted. The values of the code words of the codebook stored in the code storage unit 130 are regarded as features and clustering is performed on the characteristics to find the codewords. Typically, a k-means clustering technique can be used. A new codebook composed of the codewords found through clustering is generated. Each codeword included in the codebook is represented by a histogram. A generative method using a Bayesian probability classifying object histograms by object class as probabilities or a support vector machine (SVM) by analyzing a histogram value as a feature vector BoW-based learning and recognition can be performed using a discriminative method using a classifier such as SVM, which learns the class boundary by inserting it into a classifier.

According to an exemplary embodiment, the processing unit 160 may use this method to determine the work capability of each worker for any of the codewords stored in the codebook of the code storage unit 130, for example, . Workers can be categorized and each worker can be rearranged by category. 8 is a diagram in which workers are largely classified into four categories and rearranged. Referring to FIG. 8, workers having both high work speed and quality can be classified into category A, while workers having low work quality and high quality can be classified into category D. Workers with high quality level but low work speed are classified into category B, while those with low work quality are classified into category C, while work speed is high. In the state in which the operator category is secured, the conditions input through the condition input unit 150 require shortening of time (delivery time) (prompt work due to deadline) and quality assurance (production of a customized product requiring high quality) In this case, the processing unit 160 may classify the workers belonging to the category A as objects to be preferentially placed on the production line and provide the results to the result display unit 170.

With regard to equipment, you can also categorize them in the same way and construct production lines with equipment that is optimal for the input conditions.

FIG. 9 is a diagram showing how the first three digits of the code word 19, which is a criterion that is preferentially classified according to the requirements inputted through the condition input unit 150, among the code words stored in the code storage unit 130, .

Referring to FIG. 9, among the codes, for example, the code classification related to time (delivery date) (A) is as follows.

(i) 121: Energy monitoring - Equipment condition monitoring - Equipment good / bad

(ii) 131: Energy monitoring - Monitoring work time - Unit work quantity / hour

(iii) 132: Energy monitoring - Monitoring of work time - Delay between processes

(iv) 142: Energy monitoring - Monitoring of worker characteristics - Time characteristic work characteristics

(v) 143: Energy monitoring - Monitoring worker characteristics - Work characteristics by day

(vi) 144: Energy monitoring - Monitoring operator characteristics - Personal characteristics by job

(vii) 201: Environmental monitoring - Optimal operational efficiency conditions

(viii) 331: Vision monitoring - Monitoring work lines - Travel distance calculation

The processor 160 may classify the code according to the code criterion corresponding to the requirement inputted through the condition input unit 150 and re-rearrange the code to find the optimum condition.

The result display unit 170 displays the production line layout including the arrangement of the optimal equipment and the optimal layout information of the optimal worker to be input into the layout of the production line based on the ' It is possible to generate and output optimum production line information including layout information. In addition, the result display unit 170 further generates optimum work environment information in the factory, arrangement of the work space, and copper line information of the worker and the workpiece as information to be included in the optimum production line information based on the optimum code for the work element condition Can be output.

Information on the worker's work pattern, defect rate, etc., and the worker's ability to work can be given as basic data. And, if the worker needs to work quickly due to the deadline of delivery based on the work capacity of the determined worker, or if a small quantity of customized products requiring high quality is to be produced, The target worker who will be the target can be proposed.

The result display unit 170 can present a production line layout, a worker layout, a work line, a work environment, and the like, which can realize the minimum production time when the input requirement is the delivery time (time) (A). Likewise, if the input requirements are given as a single condition or a weighted composite condition of cost reduction (B), energy policy (C), quality assurance (D), and disaster / accident prevention (E) 170) will be able to generate and present optimal production line information that best meets those requirements.

For example, if it is determined that the process optimized for 100% shortened delivery time is the final product, the administrator can input a condition of 100% shortened delivery time in the condition input device unit 150. The processing unit 160 may extract the necessary information related to 100% of delivery time from the production information storage unit 140. The extraction object information may include information on an order quantity, a delivery date, an available date, a raw material discretion, and the like input from the department that received the order reception. As a 'rule', it can be a minimum framework (a process that must go through) necessary for designing a clothing production line, and a legal working time. The processing unit 160 extracts all the codewords related to the time factors that may affect the shortening of the delivery time, such as the production equipment and the personnel information, 130). ≪ / RTI > And provide the code word thus found to the result display unit 170. [ The result display unit 170 can design the worker and the equipment having the most outstanding results in shortening the delivery time and design the work to be placed on a production line that combines the processes to be performed.

10 is an example of the optimum production line information provided by the result display unit 170. FIG.

Referring to FIG. 10, the illustrated optimal production line information includes information on the layout of the optimum production line, the number of work lines, and the number of input workers. The garment to be produced is a garment which is straight-type. The proposed optimal production line layouts include lining, hood lining, hood sheel working, seam sealing & crossbar work, back & sleeve work , Cuff & tabs work, hand pocket & front work, join work, placket & collar work, and joining work. For example, it is a production line in which seven workers are arranged in the lining work, and an operator having the unique number 1001 is arranged in the work # 1 of the lining work.

Further, the processing unit 160 and the result display unit 170 compare the data received from the sensor devices 22, 24, 25, 30, and 35 with the existing accumulated data to determine the defect rate, Order, delay time per process, and work characteristics of each worker, it is possible to generate and present an optimal total production process in real time. For example, it is possible to analyze the defect rate for each process, to adjust the process sequence so that the defect rate can be minimized, or to propose that it can be replaced with a worker having high quality equipment or work ability. For example, if the cause of failure is a modular process sequence problem, it may be advisable to adjust the process sequence and, if equipment quality or operator capability issues, suggest a replacement with a higher quality equipment or worker . It is possible to suggest an optimal arrangement of the garment production equipment 21 or the worker according to the ordered clothing design. In this case, it is preferable that the clothes manufacturing equipment 21 such as a cutter or a sewing machine is mounted on a wheel or a movable panel so as to be able to move smoothly. As such, the garment production equipment 21 can be flexibly moved in the factory, so that the arrangement proposed by the big data-based artificial intelligence can be configured quickly. If two or more garments are produced at the same time, the optimal arrangement of the garment production equipment 21 and / or the operator may be proposed, taking into account the requirements for each garment production. Furthermore, it is possible to analyze the delay time of each process and propose optimal manpower placement by adjusting the number of input per process so that the delay time of each process can be minimized.

The functional blocks 110, 120, 130, 140, 150, 160, 170 of the optimization system 10 of FIG. 3 may include hardware components, software components, and / or combinations of hardware components and software components Lt; / RTI > For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA) A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded.

According to an exemplary embodiment, for example, the data collecting unit 110 may include communication means configured to communicate with various sensing devices and receive data from them, and an application program implementing the function of the data collecting unit 110 . According to an exemplary embodiment, the code storage unit 130 and the production information storage unit 130 may be connected to a nonvolatile storage medium (e.g., a hard disk device, a nonvolatile memory device, and the like) And can be implemented as a program necessary to perform an operation of reading and writing data. According to the exemplary embodiment, the processing unit 160 and the code generating unit 120 may be implemented by hardware, such as a CPU, a processor, a memory that provides an arithmetic processing space such as a microprocessor, and an arithmetic processing space, And may be implemented as an application program implementing the functions of the processing unit 160 and the code generating unit 120, respectively. According to the exemplary embodiment, the condition input unit 150 may be implemented as a user interface program for inputting input means such as a keyboard and condition information. According to an exemplary embodiment, the resulting display 170 may be implemented with hardware such as a computer monitor or printer and with an application program that implements the functionality of the result display 170.

In the above description, the invention has been described by taking a garment production factory as an example. However, the present invention can apply the method and system according to the present invention to most manufacturing and production plants such as a garment production plant as well as a machine parts production plant, thereby obtaining an optimal process system that best suits the requirements.

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 or scope of the invention as defined in the appended claims. It can be understood that it is possible. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced. Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

10: Apparel production plant system 21: Apparel production equipment
22: current sensor 23: computer device
24: RFID reader 25: wearable device
30: sensor unit 35: camera unit
100: Optimization system 110: Data collection unit
120: code generation unit 130: code storage unit
140: production information storage unit 150: condition input unit
160: Processing section 170: Result display section

Claims (28)

CLAIMS 1. A garment production plant in which a plurality of workers produce garments using a plurality of apparatuses for producing garments,
(a) a monitoring data collection step of collecting, at a computer device, work element monitoring data, which is a time-based measurement of a plurality of work elements including workers and equipment related to garment production;
(b) a code word generation step of generating, in the computer device, a code word of a predetermined format relating to the plurality of work elements, each of which is obtained by coding the collected work element monitoring data based on a predetermined code generation rule;
(c) a code word storing step of storing, in the computer device, a code word generated in the code word generating step so as to constitute a codebook, which is a set of codewords, in combination with a codeword generated in the data store;
(d) In the computer device, a requirement input step of inputting a requirement relating to garment production; And
(e) In the computer device, an optimum codeword matching the requirement is found in the codebook stored in the data storage, based on the production information data and a predetermined rule, ≪ / RTI >
The codeword of the predetermined format relating to the work elements may include monitoring information for each work element related to the work elements necessary for producing the garment in the garment production factory, Information representing a plurality of pieces of information about a plurality of pieces of information, and codes representing respective pieces of work level information of equipment and workers for producing clothes, and a time stamp representing a generation time information of the corresponding code word are combined into a single piece of data. Optimization method. The method of claim 1, further comprising the steps of: (f) calculating, by the computer apparatus, a production line layout including optimal equipment layout information based on the optimal codeword, and layout information of optimal workers to be input into the production line layout And generating an optimum production line information including the optimal production line information and outputting the optimized production line information. 3. The system of claim 2, wherein the configuration information of the optimal production line includes optimal production line layout information including placement of an optimal combination of equipments and optimal worker placement information for each of the optimal equipments. Operation Optimization Method. 4. The method of claim 3, wherein the configuration information of the optimum production line further includes information on a working environment and information on the arrangement of working copper wires. 4. The method of claim 3, wherein the optimal production line layout information comprises at least one of: a production line layout to ensure minimum production time; a production line layout to ensure minimum cost; a production line layout to ensure minimum energy consumption; And a production line layout for ensuring minimal occurrence of disasters. The method of claim 1, wherein the production line layout includes at least one of: The apparatus according to claim 1, wherein the monitoring information for each working element includes information on a monitoring source, a monitoring target, and characteristics of a monitoring target, the work status information includes an operator's unique number and status information, State information, and information on work contents, and the job level information includes information on a level of work performance of each of the worker and the equipment. 7. The method of claim 6, wherein the monitoring information for each working element includes energy monitoring data for each equipment. [8] The method of claim 7, wherein the energy monitoring data for each device includes information on the amount of power consumed by each device, monitoring information on the status of the equipment, and monitoring information on operation time of the equipment. The method according to claim 7, wherein the monitoring information for each working element further includes at least one of environmental monitoring data in the factory, worker activity monitoring data, and worker recognition data . 10. The clothes manufacturing system according to claim 9, wherein the 'environment-related monitoring data' includes monitoring data on at least one of temperature, humidity, air pollution degree, illuminance, Optimization method. [Claim 11] The method according to claim 9, wherein the 'worker's activity monitoring data' includes at least a part of the information about the hand movement of the worker, the movement of the work, Operation Optimization Method. The method of claim 9, wherein the 'operator recognition data' includes information on recognition (identification) of a worker and spatial matching between an operator and a machine. 2. The method of claim 1, wherein the requirement is determined by reflecting a predetermined weight on each of the predetermined requirement input elements, wherein the predetermined requirement input element is selected from the group consisting of shortening delivery time, cost reduction, And at least a part of accident prevention. The method according to claim 1, wherein the predetermined rule includes at least a minimum amount of process information necessary for designing a garment production line, and includes at least a rule set at a garment production management level and at least a statutory working time information Wherein the at least one of the at least one of the at least one of the at least one of the at least one of the at least one of the at least two of the plurality of the at least one of the at least one of the plurality The method according to claim 1, wherein the production information data includes information on a raw subsidiary material status, a production order quantity, a delivery date, a factory operation date, and a target quality. 2. The method of claim 1, wherein the step of presenting the optimal codeword comprises: classifying codewords of the codebook according to a codeword criterion conforming to the requirement; And rearranging the categorized codewords to locate and present the optimal codeword. ≪ Desc / Clms Page number 19 > CLAIMS 1. A garment production plant in which a plurality of workers produce garments using a plurality of apparatuses for producing garments,
A plurality of sensor units for generating work element monitoring data by measuring a plurality of work elements including an operator and equipment related to clothing production over time;
And a computer device for receiving the work element monitoring data through wireless communication from the plurality of sensor units and presenting a production line for production of clothing and optimization of factory operation,
The computer device comprising:
(a) a monitoring data collection unit for collecting the work element monitoring data generated by the plurality of sensor units;
(b) a code word generator for generating a code word of a predetermined format relating to the plurality of work elements in which the collected work element monitoring data is encoded and combined based on a predetermined code generation rule;
(c) a codeword storage unit which receives the codeword generated from the codeword generation unit and combines the generated codeword and a codeword, which is a set of codewords, to form a codeword;
(d) a requirements input section for inputting requirements relating to garment production;
(e) a production information storage unit for storing production information data and a predetermined rule; And
(f) a processor for finding an optimal codeword matching the requirement in the codebook stored in the codeword storage unit, based on the production information data and the predetermined rule,
The codeword of the predetermined format relating to the work elements may include monitoring information for each work element related to the work elements necessary for producing the garment in the garment production factory, Information representing a plurality of pieces of information about a plurality of pieces of information, and codes representing respective pieces of work level information of equipment and workers for producing clothes, and a time stamp representing a generation time information of the corresponding code word are combined into a single piece of data. Optimization system. 18. The computer-readable recording medium according to claim 17, wherein the computer apparatus further comprises: a production line layout including optimal equipment layout information, and a layout information of optimal workers to be inputted to the production line layout, based on the optimum codeword found by the processing section And generating and outputting the optimal production line information including the optimal production line information. 19. The system of claim 18, wherein the result display unit further generates optimal work environment information in the factory, arrangement of the work space, and copper line information of the worker and the work based on the optimum code word, Operation optimization system. 19. The method of claim 18, wherein the optimal production line information includes at least one of: a production line layout that ensures minimum production time; a production line layout that assures minimum cost; a production line layout that assures minimum energy consumption; And a production line layout for ensuring minimal occurrence of disasters. The system of claim 1, The system according to claim 17, wherein the monitoring information for each work element includes information on a monitoring source, a monitoring target, and characteristics of a monitoring target, the work status information includes worker information, equipment information, Wherein the operation level information includes information on the level of work performance of each of the worker and the equipment. The system according to claim 21, wherein the monitoring information for each working element includes at least one of (i) energy monitoring data for each apparatus, including information on power consumption of each apparatus, monitoring information on the status of the apparatus, ii) 'environment related environmental monitoring data' including monitoring data on at least one of temperature, humidity, air pollution degree, illuminance and noise in the garment production factory, (iii) information on the hand movement of the worker, (Iv) information on the spatial matching between the worker and the equipment, (iii) information on the worker's work activity monitoring data including at least one of the information about the worker's work line in the production line, And ' operator recognition data ' including at least one ' 18. The method of claim 17, wherein the requirement is determined by reflecting a predetermined weight on each of the predetermined requirement input elements, wherein the predetermined requirement input element is selected from the group consisting of shortening delivery time, cost reduction, And at least a part of accident prevention. 18. The method according to claim 17, wherein the predetermined rule includes at least a minimum amount of process information necessary for designing an apparel production line, and includes at least a rule determined at the apparel production management level and statutory working time information, Wherein the system includes at least one of the following rules. 18. The system of claim 17, wherein the production information data includes information on a raw subsidiary material status, a production order quantity, a delivery date, a factory operation date, and a target quality. 18. The apparatus of claim 17, wherein the processing unit classifies codewords of the codebook stored in the codeword storage unit according to a codeword criterion corresponding to the requirement, rearranges the codewords to find an optimal codeword Wherein said garment producing and plant operating optimization system is characterized in that said garment production and factory operation optimization system is characterized in that said system comprises: 18. The system of claim 17, wherein the processor finds the optimal code word through machine learning and word recognition using a back-of-the-word (BoW) algorithm. 17. A computer-executable program stored on a computer-readable medium for performing the method of claim 1 or claim 16,

Images