KR20220109796A - Automation monitoring system IoT-based traditional maintenance production process for smart factory construction - Google Patents

Abstract

The present invention relates to an IoT-based traditional production process automation monitoring system for building a smart factory. Each process required for traditional oil production is divided into modules for building a smart factory. Each module is divided into raw material transfer, roasting, transfer, dust collection, transfer, milking, milk collection, filtering, packaging, capping, labeling, and inspection. Each process divided into modules proceeds sequentially from raw material transfer to inspection. Devices and machines for each unit process operate in IoT-based interlocking. Each process is progressed while monitored. Therefore, the present invention uses a monitor to perform visualization and recording so that an operator can easily recognize and process a process state. By automatically outputting an alarm signal that can respond to abnormality detection, optimal products and production conditions are analyzed. The same is processed with an optimized setting value of a production process and performed automatically. Thus, product quality improvement and standardization are secured through reduction of working hours, productivity improvement, and systematic production management.

Description

Automation monitoring system IoT-based traditional maintenance production process for smart factory construction

The present invention relates to an automated monitoring system for the production process of traditional oils and fats, and more particularly, for the establishment of a smart factory system for the production of traditional oils and fats, the sensor for each type of unit, the setting of the process reference value and the flow of work, and between the sensors It relates to the reference value and processing method for interworking, namely, work weight and amount, temperature, humidity, operation speed and repetition number, rotation speed and rotation speed, heat quantity adjustment and setting, IoT interworking setting and control between machines by process unit , setting and controlling the amount per packaging unit, and automatically processing the amount of raw materials and production volume, and big dataization of data values for each process. By automatically outputting an alarm signal that can respond to It relates to a monitoring system of an automated production process for improvement and standardization.

In general, as traditional oils and fats are modernized, consumption increases, and the production process of traditional oils and fats is automated by smart factories. As an example of the prior patent technology, the registered patent publication No. 10-2127572 registered by the present applicant has an edible oil sales device installed in a store, and a server management system that integrates and manages real-time information collected from the edible oil sales device. In the IoT-based edible oil rancidity management and production prediction smart system, the sales device is a vending machine, and the vending machine has milking date, expiration date, country of origin indication, antioxidant, benzopyrene and nutrition label suitable for storage and sales environment of edible oil and fat, and roasting temperature. , milking method, acid value, peroxide value, and iodine value change regarding storage conditions of unsaturated fatty acids, tocopherol and lignan compound antioxidant changes It sets the degree of reduction, sets the degree of rancidity of the flesh protein component of sesame, which is sludge contained in fats and oils, when not refined, and sets whether the taste of fats and oils is changed by environmental factors, and the storage unit is It is divided into 5 lines and each line is set according to the temperature maintenance. The temperature is a Peltier element or a condenser installed. The screen is composed of , and orders and information can be provided at the same time. On the other hand, you can receive information about the production process as a visual image through a video, and you can receive the current production process with a real-time video. , set storage environmental conditions for each oil and fat, control acid value, peroxide value, and iodine value factors that determine rancidity, and perform antioxidant tests to change nutritional composition of unsaturated fatty acids

Controls changes in fats and oils, and applies sunlight or fluorescent light factors that cause rancidity to each fat and checks the acid value, iodine value, and peroxide value through safety tests. An IoT-based edible oil rancidity management and production prediction smart system, characterized by verifying the degree of rancidity by conducting an experiment, and verifying the acid value, iodine value, and peroxide value by applying direct heat to each oil and fat, is disclosed.

In addition, a pressurized edible oil refining device is disclosed in Korean Patent Publication No. 20-0365315.

However, the prior art still had disadvantages in that the quality of the product could not be improved and standardized because the operator could not easily recognize and process the process state, and thus could not quickly respond to abnormal detection.

Therefore, the present invention has been devised to solve the above problems, and the working weight and amount, temperature, humidity, operating speed and number of repetitions, number of rotations and Reduction of working time and labor by automatically processing and proceeding rotation speed, heat quantity control and setting, IoT interlocking setting and control between machines for each process unit, setting and control of the amount per packaging unit, and automatically processing and proceeding with the amount of raw material and production, in particular, more scientific and systematic production It aims to improve productivity with the environment.

In addition, an object of the present invention is to establish a systematic production management environment by visualizing and recording using a monitor so that the operator can easily recognize and process the process state.

In addition, an object of the present invention is to automatically output an alarm signal that can respond to abnormal detection for each process, stop or operate according to a set value, and reduce the defect rate and improve quality through rapid and systematic production management.

In addition, the present invention converts data values for each process set value and production result into big data, analyzes the optimal production environment conditions for each process according to work time, quality, and production volume, and applies it as an optimized set value for the production process By improving the systematic production environment, quality improvement and cost reduction are achieved, and based on this, the purpose is to establish big data of production process and management that can build an artificial intelligence production system.

The present invention relates to an IoT-based traditional oil production process automation monitoring system for building a smart factory, and each process required for traditional oil production is divided into modules for building a smart factory, and each module includes raw material transfer, roasting, It is divided into transport, dust collection, transfer, milking, milk collection, filtering, packaging, capping, labeling, and inspection. It operates by interworking based on IoT, and each process is characterized by being monitored.

Therefore, the present invention visualizes and records using a monitor so that the operator can easily recognize and process the process state, and automatically outputs an alarm signal that can respond to abnormal detection, analyzes the optimal product and production conditions, and produces it It has a remarkable effect of reducing work time, improving productivity, and improving product quality and standardization through systematic production management by processing with the optimized set value of the process and performing it automatically.

1 is a flow chart of the traditional maintenance production process for building a smart factory of the present invention;
Figure 2 is a 2 flow chart of the traditional maintenance production process for building a smart factory of the present invention
3 is a flow chart of the traditional maintenance production process for building a smart factory of the present invention;
4 is a block diagram of module interlocking according to the production process sequence of the present invention;
5 is a sensor, measurement, and control function diagram for each production process module of the present invention;
6 is a flow chart of the production process IoT interworking of the present invention

The present invention relates to an IoT-based traditional oil production process automation monitoring system for building a smart factory, and each process required for traditional oil production is divided into modules for building a smart factory, and each module includes raw material transfer, roasting, It is divided into transport, dust collection, transfer, milking, milk collection, filtering, packaging, capping, labeling, and inspection. It operates by interworking based on IoT, and each process is characterized by being monitored.

In addition, each process module is equipped with sensors required for mutual IoT interworking with process equipment or machines, quality improvement and work process environment improvement, optimized product production and process management,

In addition, a measurement module that processes the measurement signal input from the sensor, a control module that compares the signal value of the measurement module with a set reference signal and outputs an alarm signal or whether the process is in progress and automatically corrects it, and the module of each process A control module that automatically generates and records a status report and outputs a recognizable image so that operators and managers can process measurement signals and operation signals, collects and manages all measurement data to improve production process efficiency and product It is composed of a big data storage and processing module, and each module processed for each unit process is interlinked to implement an optimized production process, thereby increasing production efficiency.

The present invention specialized in the production of traditional oils and fats will be described in detail with reference to the accompanying drawings. Figure 1 is a traditional maintenance production process 1 flowchart for building a smart factory of the present invention, Figure 2 is a traditional maintenance production process 2 flowchart for building a smart factory of the present invention, Figure 3 is a tradition for building a smart factory of the present invention Oil and fat production process flow chart, Figure 4 is a module interlocking configuration diagram for each production process sequence of the present invention, Figure 5 is a sensor, measurement, and control function diagram for each production process module of the present invention, Figure 6 is a production process IoT interlocking flow chart of the present invention .

Each process required for traditional oil production is divided into modules for building a smart factory, and each module is divided into raw material transfer, roasting, transfer, dust collection, transfer, milking, milk collection, filtering, packaging, capping, labeling, and inspection. Each process divided into , modules proceeds sequentially from raw material transfer to inspection, and devices and machines for each unit process are operated through IoT-based interworking, and each process is monitored.

Each process module is equipped with a sensor required for mutual IoT interworking with process-specific equipment or machines, quality improvement and work process environment improvement, optimized product production and process management, and a measurement module that processes the measurement signal input from the sensor , A control module that compares the signal value of the measurement module with a set reference signal and outputs an alarm signal, or a control module that automatically corrects the progress of the process, and allows the operator and manager to process the measurement and operation signals that are interlocked with the modules of each process A control module that automatically generates and records a status report and outputs a recognizable image so that it can be recognized; It is composed of an artificial intelligence module that implements an optimized process system by itself based on the

The configuration of the module for each process is largely divided into a sensor for various measurements, a device that digitizes the received signal, and a control device that optimizes the progress and operation of each process. A humidity sensor is attached to measure the basic condition of the raw material, and the raw material is transferred to the roasting module of the next process by a transfer motor linked with IoT. At this time, the transfer amount and speed are set and controlled. (2) The roasting module is equipped with a temperature sensor, humidity sensor, heat sensor, and timer to measure the state of the roasting operation over time, control the rotational speed of the operating motor and the amount of heat supplying the roaster’s energy, and meet the emission standards. Set and control, and measure the final roasting time. (3) In the transfer module 2, the transfer motor transfers the desired amount of the raw material loaded in the buffer to the next process by the weight sensor, and at this time, the transfer amount and speed are controlled. (4) The dust collection module is the process of removing impurities from the roasted raw material again, and the state of the raw material is measured by the weight sensor, temperature sensor, humidity sensor, and wind sensor, and the dust collection force is controlled when dust is collected. (5) The transfer module 3 measures the state of the raw material selected by the temperature sensor and the humidity sensor, and is transferred from the buffer to the milking module again, and at this time, the transfer amount and speed are controlled by the weight sensor. (6) The milking module measures the basic working state by the temperature sensor and timer, and measures the amount of maintenance, weight, oil orientation, viscosity, and milking time. (7) The oil collecting module measures the amount, flavor, and viscosity of oil by weight sensor, concentration sensor, and flavor sensor. (8) The filtering module measures the holding amount, the holding direction, the viscosity, and the working time by the weight sensor, the concentration sensor, the flavor sensor, and the timer, and controls the working time. (9) The packaging module measures and controls the filling amount by the filling amount sensor, timer, and packaging unit counter, and counts the number of products. (10) The capping module accumulates the number of products produced by the counter and controls the desired number of products. (11) The labeling module checks the labeling and quantity of products with a label issuing machine and printing machine, and controls the date. (12) Inspection module inspects products produced by production schedule by color sensor, level sensor, label check, and counter, and checks production quantity and date.

IoT interconnection of machines and equipment for each process is essential for smart factory implementation. The set amount of raw material is automatically supplied to the roaster in the roasting process. (2) The roasting module is linked with the raw material transfer module 1, and when the raw material supply is not smoothly transferred from the raw material transfer module, it outputs an emergency signal to stop the operation, and after roasting is completed, the signal is used to check the buffer capacity to discharge (3) The transfer module 2 transfers the raw material loaded in the buffer to the dust collecting module by interlocking with the control system of the dust collecting module and controlling the transfer amount and speed by the transfer motor. (4) The dust collection module is interlocked with the buffer of transfer module 3 and transfers the raw material according to the effective capacity of the buffer. (5) The transfer module 3 is linked with the milking module and the transfer module 3, and receives a predetermined amount of raw material loaded in the buffer of the milking module and transfers the predetermined raw material to the buffer of the milking module. (6) The milking module is interlocked with the transfer module 3 and the oil collecting module, and if the raw material supply is not made in the transfer module 3 or the maintenance amount of the oil collecting module exceeds the limit value, the operation is stopped. Transfer the milked oil to the module. (7) The oil collecting module interlocks with the milking module and the filtering module, and while the milking module produces oil, it collects oil while checking its own amount of oil, receives a signal from the filtering module's work process, and transfers the collected oil to the filtering module. transport (8) The filtering module is interlocked with the oil collection module and the packaging module, and if the oil collection module does not supply a constant maintenance, the operation is stopped, and the filling status of the packaging module is checked and the filtering operation is carried out. (9) The packaging module interlocks with the filtering module and the capping module to establish a mutually optimal working environment, and stops work when an abnormal signal is detected between the filtering module and the capping module. (10)

The capping module automatically caps the filled container by interlocking with the packaging module and the labeling module, and transmits the container by the signal of the labeling module. (11) The labeling module automatically prints the working date, expiration date, etc. on the capped packaging container transmitted from the capping module, the inspection module, and the seniority and capping module, and performs labeling and transfers the container to the inspection module. (12) After interlocking with the labeling module and labeling, the inspection module inspects the contents and labeling status of the container to be transmitted, calculates the production amount and number of defects, and outputs a completion approval.

When any one of the modules outputs an alarm signal, the cause of the alarm occurrence is output to the control module for stopping and operating all process modules. At this time, the control module outputs a message asking the operator's intention, The process module can be stopped or the module to be stopped can be controlled. On the other hand, the packaging module can be operated in a quick control mode by the control unit of the control module, and the feedback signal is transmitted to the filtering module, which is the previous step, and transferred at the same time. It can also be transmitted to the milking model, which is a stage. Therefore, the milking model can control the milking amount by the direct signal of the pavement model, calculate the milk collecting stockpile of the milk collecting module, and transfer the milked oil to the milk collecting module. When the alarm signal of the inspection module occurs, the milking module stops operating, but if the stockpile of the oil collecting module is below a certain value, even when the alarm signal of the inspection module occurs, the raw materials that have already entered the milking process are removed. Milking is done in order to efficiently manage the raw materials entered into the milking machine.

As the process modules for each unit are interlinked and processed, the work status of the unit process is integrated, and when the work is in progress or when the work is finished, the progress status of each process and the production report after the end of production are recorded and output on the integrated monitor status board of the workplace. .Production report is output according to the input conditions set for each process, with unit machine and equipment names for each process and data data to be collected (products, temperature, humidity, production volume, production rate, defect rate, working hours, workers, production date).

The control module is processed according to the working condition value set by the module for each process unit, and the working condition value is optimized and updated. The updated data value processed by the control module is automatically collected and stored in the database, and the AI module It is used to calibrate the optimized process system.

In the space where each process equipment is installed, atmospheric sensors and microbial sensors that measure dust, gas, smoke, and dust generated and circulated during production are attached to dust collection facilities and equipment to check and improve the cleanliness and sanitary environment of the work space. The module is built separately. The environmental module is also linked to the integrated monitoring system, and when an abnormality occurs in the set work environment standard, the work is stopped or forcibly blocked to maintain the safety management priority work environment.

Therefore, the present invention visualizes and records using a monitor so that the operator can easily recognize and process the process state, and automatically outputs an alarm signal that can respond to abnormal detection, analyzes the optimal product and production conditions, and produces it It has a remarkable effect of reducing work time, improving productivity, and improving product quality and standardization through systematic production management by processing with the optimized set value of the process and performing it automatically.

Claims (3)

Each process required for traditional oil production is divided into modules for building a smart factory, and each module is divided into raw material transfer, roasting, transfer, dust collection, transfer, milking, milk collection, filtering, packaging, capping, labeling, and inspection. Each process divided into modules proceeds sequentially from raw material transfer to inspection, and devices and machines for each unit process are operated through IoT-based interworking, and each process is monitored while progressing. IoT-based traditional maintenance production process automation monitoring system for construction Each process-specific module is equipped with sensors required for mutual IoT interworking with process-specific equipment or machines, quality improvement and work process environment improvement, and optimized product production and process management. Traditional maintenance production process automation monitoring system According to claim 2, wherein the measurement module for processing the measurement signal input from the sensor, the control module for outputting an alarm signal by comparing the signal value of the measurement module with a set reference signal or whether the process is progressing and automatically correcting, and each process module A control module that automatically generates and records a status report and outputs a recognizable image so that the operator and manager can process the measurement and operation signals that are interlocked with the It is composed of big data storage and processing modules for product improvement, and each module processed by unit process is interconnected to implement an optimized production process, thereby increasing production efficiency. IoT-based tradition for building a smart factory Maintenance production process automation monitoring system

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