JP2024093052A - Data management device and database construction method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To appropriately manage information on plastic.

SOLUTION: A data management device 160 applied to a measurement system 1 comprises: an identification information generation unit 168 that generates identification information; a communication unit 162 that receives a measurement condition including a temperature condition in a first measurement device 140, a result of first measurement processing, a measurement condition in a second measurement device 150, a result of second measurement processing, and identification information provided in a sampling device 100; and a storage control unit 164 that stores, in a storage unit 166, the identification information, the result of the first measurement processing, and the measurement condition in the second measurement device 150 in association with each other.

SELECTED DRAWING: Figure 1

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present invention relates to a data management device and a database construction method.

As background technology in this technical field, the abstract of the following Patent Document 1 states, "Problem: To provide a manufacturing method for thermoplastic plastics that allows information about the manufacturing process to be obtained even after distribution. Solution: In multiple manufacturing processes involving melting of thermoplastic plastic 90, information about each manufacturing process is associated, and information-presenting substances 91 that emit fluorescence when irradiated with electromagnetic waves in a specific wavelength range are added and dispersed in sequence." In addition, the following Non-Patent Document 1 describes a material recycling technology for mixed plastics from used home appliances. In addition, the following Non-Patent Document 2 describes a technology related to recycling plastic materials. The descriptions in these documents are included as part of the specification of this application.

JP 2005-320439 A

Yuichi Matsuo and 5 others, "Material Recycling Technology for Mixed Plastics from Used Home Appliances," Journal of Japan Society of Material Cycles and Waste Management, Japan Society of Material Cycles and Waste Management, 2009, Vol. 20, No. 5, pp. 303-310 Shigeru Yao, Aya Tominaga, "New Technology Developments for Plastic Material Recycling", Journal of Japan Society of Material Cycles and Waste Management, Japan Society of Material Cycles and Waste Management, 2018, Vol. 29, No. 2, pp. 116-124

However, in the above-mentioned technology, there is a demand for more appropriate management of information on plastics and the like.
The present invention has been made in view of the above-mentioned circumstances, and an object of the present invention is to provide a data management device and a database construction method capable of appropriately managing information on plastics and the like.

In order to solve the above problem, the data management device of the present invention is a data management device applied to a measurement system including a sampling device that assigns designated identification information to a plastic sample, a first measuring device that performs a first measurement process to control the temperature of the sample to above its melting temperature and evaluate the characteristics of the sample in a heated state, and a second measuring device that performs a second measurement process to evaluate the characteristics of the sample that has been evaluated by the first measuring device and then solidified, and is characterized in that it includes an identification information generation unit that generates the identification information, a communication unit that receives measurement conditions including temperature conditions in the first measuring device, the results of the first measurement process, the measurement conditions in the second measuring device, the results of the second measurement process, and the identification information assigned by the sampling device, and a storage control unit that stores the identification information, the results of the first measurement process, and the measurement conditions in the second measuring device in association with each other in a storage unit.

The present invention allows for proper management of information on plastics, etc.

FIG. 1 is a block diagram of a measurement system according to a first embodiment. FIG. 1 is a block diagram of a computer. 4 is a flowchart showing the operation of the measurement system in the first embodiment. FIG. 12 is a diagram (1/2) showing an example of a database. FIG. 2 is a diagram (2/2) showing an example of a database. FIG. 11 is a diagram illustrating an example of another database. FIG. 13 is a diagram (1/3) showing an example of yet another database. FIG. 2 is a diagram (2/3) showing an example of yet another database. FIG. 3 is a diagram (3/3) showing an example of yet another database. 10 is a flowchart showing the operation of a measurement system in a second embodiment. 13 is a flowchart showing the operation of a measurement system in a third embodiment. 13 is a flowchart (1/2) showing the operation of the measurement system in the fourth embodiment. 13 is a flowchart (2/2) showing the operation of the measurement system in the fourth embodiment. FIG. 13 is a block diagram of a measurement system according to a fifth embodiment.

[Overview of the embodiment]
In recent years, environmental and resource issues have led to the demand for product-related businesses to address the recycling of resources such as plastics. Plastics are generally easy to process and mold, and can be made functional by compounding, so they are used in a wide variety of products. For this reason, plastic recycling also uses historical information such as the type and composition of the resin, product use, and usage history. Plastics are generally recycled and used by heating to melt them and then cooling and solidifying them, i.e. material recycling.

Here, the plastics applied as raw materials and samples in the embodiments described below will be described. The plastics are preferably thermoplastic resins that can be recycled, such as polyethylene (PE), polypropylene (PP), polystyrene (PS), acrylonitrile-butadiene-styrene copolymer synthetic resin (ABS), polyvinyl alcohol (PVA), polyvinyl chloride (PVC), polycarbonate (PC), polyethylene terephthalate (PET), polybutylene terephthalate (PBT), polyamide (PA), polyether ether ketone (PEEK), ethylene vinyl acetate copolymer (EVA), polylactic acid (PLA), polybutylene succinate (PBS), polybutylene adipate terephthalate resin (PBAT), plastic starch, polyhydroxybutyrate (PHB), 3-hydroxybutyrate-co-3-hydroxyhexanoate polymer (PHBP), It is constructed using polytetrafluoroethylene (PTFE), ethylene-tetrafluoroethylene (ETFE), perfluoroalkoxyalkane (PFA), ethyl trifluoroacetate (EFA), polychlorotrifluoroethylene (PCTFE), ethylene-chlorotrifluoroethylene copolymer (ECTFE), etc. as base materials. In the embodiment described below, it is preferable to apply the above-mentioned plastics to general-purpose resins such as polyethylene, polypropylene, polystyrene, acrylonitrile-butadiene-styrene copolymer synthetic resin, polyvinyl chloride, and polyethylene terephthalate, which are available in a wide variety of types depending on performance and use, and it is particularly preferable to apply the polypropylene recycled plastic.

In the field of materials technology, the design and development of materials using material informatics, which utilizes data on the physical properties and characteristics of materials and information science techniques such as machine learning, is becoming more widespread. When using material informatics (MI) in a data-driven manner that uses large amounts of data, large amounts of data and systematically accumulated databases are required.

When collecting data on recycled plastics, it becomes necessary to collect a wide variety of data depending on the type and composition of these materials, their history, and the material recycling process. For example, according to Non-Patent Document 1, it is believed that the physical properties and characteristics of recycled plastics are not constant but vary. Also, according to Non-Patent Document 2, it is believed that the physical properties and characteristics of plastics change depending on the processing method used in the heating and melting process in material recycling.

Possible methods for building a database include collecting data on characteristics and physical properties from public databases or literature. However, while there are public databases and literature on virgin plastics, there are almost no similar public databases or literature on recycled plastics.

Another method for constructing a database is to actually measure and collect data on characteristics and physical properties. However, the characteristics and physical properties of recycled plastics vary depending on their type, components and history, and are further influenced by a complex range of factors, such as the melting and solidification processing methods used in material recycling. Therefore, when constructing a database for recycled plastics, it is preferable to collect data on characteristics and physical properties that minimizes variations in characteristics and physical properties caused by the raw materials themselves, and also takes into account the contribution of variations due to processing methods used in material recycling.

In addition, when building a database based on measurements, tasks such as sample preparation and measurement are required. Furthermore, efficient collection of measurement data and expansion, such as increasing the number of types of measurement, are also required to accommodate a variety of uses and purposes. When increasing the types of measurement data at this time, it is necessary to take into account the aforementioned variability in the raw materials themselves in the case of recycled plastics. For this reason, for example, even if samples are prepared within the same lot for each measurement and each measurement is performed, it is difficult to ensure the identity of samples between measurement data.

The embodiment described below assumes the material recycling process for material recycled plastics, standardizes and controls the processing conditions to prepare samples for measurement, and obtains physical property and characteristic data while ensuring the identity of the samples. This realizes a data management system that realizes the efficient construction of a database using a wide variety of measurement data.

[First embodiment]
Configuration of the First Embodiment
FIG. 1 is a block diagram of a measurement system 1 according to the first embodiment.
1, the measurement system 1 includes a sampling device 100, a transport device 120, a first measuring device 140, a second measuring device 150, a management server 160 (data management device), and a network 180 connecting these. Here, the sampling device 100 includes a communication unit 102, a measurement unit 104, a processing unit 106, an auxiliary information acquisition unit 108, a storage unit 110, an environment management unit 112, a marking unit 114, a reading unit 116, and a control unit 118.

The transport device 120 also includes a communication unit 122, a storage unit 124, a portable unit 126, a measurement unit 128, a control unit 130, a reading unit 132, and a marking unit 134. The first measuring device 140 also includes a communication unit 142, a thermal analysis unit 144, an acquisition unit 146, and a control unit 148.

The second measuring device 150 also includes a communication unit 152, a nondestructive evaluation unit 154 (evaluation unit), a destructive evaluation unit 155 (evaluation unit), an acquisition unit 156, and a control unit 158. The management server 160 also includes a communication unit 162, a memory control unit 164, a memory unit 166, an identification information generation unit 168, and a process management unit 170. The communication units 102, 122, 142, 152, and 162 communicate data with each other via a network 180.

(Sampling device 100)
The measurement unit 104 in the sampling device 100 measures various characteristics of the recycled plastic raw material 20 and the sample 22 cut out from the raw material 20, and obtains measurement information D104. Here, the measurement information D104 includes, for example, the following items:
The shape, weight, color, appearance, and odor of the sample 22 and the raw material 20
-Contamination of the sample 22 and the raw material 20 and contamination with foreign matter

Of the above-mentioned measurement information D104, "shape" can be obtained by non-contact optical measurement using calipers, micrometers, thickness gauges, cameras, lasers, etc., contact measurement using a stylus, etc. "Weight" can be obtained by an electronic balance, etc. "Appearance" and "color tone" can be obtained by a CCD camera, CMOS camera, hyperspectral camera, etc. Furthermore, for "color tone", a colorimeter, spectrophotometer, color sample, etc. may be used. "Odor" can be obtained by a semiconductor odor sensor, gas chromatograph, olfactory measurement, etc. "Dirt and foreign matter" can be obtained by visual inspection, a camera, a hyperspectral camera, transmitted X-rays, fluorescent X-rays, X-ray diffraction, infrared spectroscopy, FT-IR, etc.

The processing unit 106 performs various processes on the sample 22 or raw material 20. For example, the processing unit 106 cuts the sample 22 from the raw material 20 according to the specifications for storing the sample 22 or raw material 20, the type of evaluation in the first measuring device 140 and the second measuring device 150, the evaluation conditions, etc. Then, the processing unit 106 collects the remaining raw material 20 after the sample 22 has been cut.

The incidental information acquisition unit 108 acquires incidental information D108 by scanning a label or the like (not shown) attached to the raw material 20 or its packaging. Here, incidental information D108 includes the provider, manufacturer, manufacturing date, acquisition date, type of plastic, inspection report at the time of shipment, and history of the raw material 20. Note that, if any of the items listed as the above-mentioned measurement information D104 can be acquired as incidental information D108, the measurement of that item by the measurement unit 104 may be omitted. The storage unit 110 stores the raw material 20. The environment management unit 112 controls the storage environment of the raw material 20, such as temperature and humidity.

The marking unit 114 receives the identification information IDM to be applied to the raw material 20 or its packaging material (not shown) and the identification information IDS to be applied to the sample 22 from the identification information generation unit 168 of the management server 160, and applies the identification information IDS, IDM to the sample 22 and raw material 20. The method of applying the identification information IDS, IDM by the marking unit 114 is selected depending on the raw material 20 or sample 22 after processing, and the packaging and packing method thereof. When printing the identification information IDS, IDM, it is preferable to use a barcode or two-dimensional barcode. This makes it possible to apply a large amount of information even if the printable area is small.

The marking unit 114 is preferably an on-demand device that can provide unique identification information IDS, IDM for each sample 22 and raw material 20. For example, an inkjet printer, thermal printer, laser marker, hot stamp, or wireless IC tag (e.g., RF-ID) can be used. The marking unit 114 may also have a function for issuing and inputting/outputting the identification information IDS, IDM. In addition, considering that evaluation data (described in detail below) will be obtained for each sample 22, it may be desirable to prevent the inclusion of objects used to provide the identification information IDS, IDM.

In such a case, it is preferable to print the identification information IDS, IDM on the raw material in the form of a character string, a geometric pattern, a two-dimensional code, etc., using a thermal printer, a laser marker, or a hot stamp. In order to impart the identification information IDS, IDM, an object having a certain size and mass is applied, and when the object continues to be imparted to the sample 22 even during the measurement process described below, it is preferable that the object has heat resistance above the melting temperature of the sample 22, more preferably above the decomposition temperature or combustion temperature, and is non-reactive with the sample 22.

The reading units 116, 132 in the sampling device 100 and the transport device 120 read the identification information IDS from the sample 22 and transmit the results to the management server 160. In the management server 160, the storage control unit 164 associates various information with the identification information IDS to construct a database and stores it in the storage unit 166. Note that the "database" here refers to database 300 (see Figures 4 and 5), database 400 (see Figure 6), and database 500 (see Figures 7 to 9). Details of these databases will be described later.

The reading unit 116 reads the identification information IDS, IDM that the marking unit 114 has assigned to the sample 22, raw material 20 or its packaging (not shown). A camera-equipped terminal such as a smartphone or handheld terminal can be used as the reading unit 116. These can be used to check and manage the contents of the identification information IDS, IDM by using a conversion program. The control unit 118 controls each part of the sampling device 100.

(Transportation device 120)
The transport device 120 is a device that transports the sample 22 and the raw material 20. Note that a plurality of transport devices 120 may be used depending on the arrangement and type of devices in the measurement system 1. The storage unit 124 in the transport device 120 stores the sample 22 and the raw material 20. The storage unit 124 may have a function of controlling and maintaining the environmental atmosphere such as gas, temperature, humidity, and illuminance, and a function of containing the raw material 20 and the sample 22 and transporting them to each device via the transport unit 126. In addition, the transport unit 126 transports the sample 22 and the raw material 20 between the sampling device 100, the first measuring device 140, the second measuring device 150, and these components.

The measurement unit 128 monitors various processes. That is, the measurement unit 128 has a function of measuring the environmental atmosphere such as temperature, humidity, illuminance, and gas concentration, and an imaging function of monitoring the state of the raw materials and samples. The measurement unit 128 may also have the same function as the measurement unit 104 of the sampling device 100. The control unit 130 controls each part of the transport device 120, and inputs and outputs information such as the raw materials 20, the sample 22, each process, and monitoring results via the communication unit 122 and the network 180.

The reading unit 132, like the reading unit 116 of the sampling device 100, acquires the identification information IDS, IDM assigned to the raw material 20 and the sample 22. The marking unit 134 has the same function as the marking unit 114 of the sampling device 100, and assigns unique identification information IDS, IDM to the raw material 20 and the sample 22, or their packaging materials.

(First Measuring Device 140)
The acquisition unit 146 in the first measuring device 140 acquires the sample 22 and the raw material 20 from the sampling device 100 via the transport device 120. The thermal analysis unit 144 has a function of heating the sample 22 and the raw material 20 while controlling the temperature, a function of evaluating the characteristics and performance of the sample 22 and the raw material 20 in the heated state, and a function of preparing the sample 22 and the raw material 20 after measurement.

Furthermore, the thermal analysis unit 144 has the function of evaluating the characteristics and physical properties of the sample 22 by differential scanning calorimetry, thermogravimetry, differential thermal analysis measurement, thermogravimetry, dry moisture content measurement, heated gas analysis, melt mass flow rate measurement, melt volume rate measurement, spiral flow measurement, or molding shrinkage rate measurement.

In particular, in this embodiment, the thermal analysis unit 144 includes a dry moisture meter (not shown). That is, the thermal analysis unit 144 heats the sample 22 to a temperature that does not cause chemical denaturation due to oxidation or thermal decomposition. At that time, the thermal analysis unit 144 controls the heating rate, the holding temperature, and the holding time.

The thermal analysis unit 144 also acquires the temperature change during cooling in association with the sample 22. The thermal analysis unit 144 then acquires the solidified sample 22 after measurement, and again assigns the above-mentioned identification information IDS to the solidified sample 22. The control unit 148 controls each unit in the first measuring device 140, and inputs and outputs various information related to the raw material 20, the sample 22, the evaluation conditions, the evaluation results, etc. via the communication unit 142 and the network 180.

(Second Measuring Device 150)
The acquisition unit 156 in the second measuring device 150, like the acquisition unit 146 in the first measuring device 140, acquires the sample 22 and the raw material 20 from the sampling device 100 via the transport device 120. The non-destructive evaluation unit 154 performs non-destructive evaluation of the characteristics and performance of the sample 22. In addition, the destructive evaluation unit 155 performs destructive evaluation of the characteristics and performance of the sample 22.

Here, "non-destructive evaluation" refers primarily to evaluation that does not alter the material of sample 22. Also, "destructive evaluation" refers primarily to evaluation that alters the material of sample 22, and is evaluation in which sample fragments are heated to an oxidation/thermal decomposition temperature or higher. In this embodiment, after non-destructive evaluation unit 154 performs non-destructive evaluation on sample 22, destructive evaluation unit 155 performs destructive evaluation. Also, non-destructive evaluation and destructive evaluation may each be performed on multiple evaluation items.

The non-destructive evaluation performed by the non-destructive evaluation unit 154 may, for example, employ one or more of the following items.
- Transmittance, reflectance, absorptance, or refractive index for ultraviolet rays, visible light, and infrared rays,
- Fluorescence emission spectrum,
・Measurement using FT-IR (Fourier Transform Infrared Spectroscopy) ・Transmission X-ray measurement, fluorescent X-ray measurement, XRD (X-ray diffraction),
・XPS (X-ray Photoelectron Spectroscopy)
- Color coordinates, chromaticity (color chart number and color code of the color sample),
Resistance value, surface resistivity, electrostatic capacitance, or charge rate when a DC voltage is applied,
- Impedance when AC voltage is applied, or a combination of the dielectric constant and the dielectric tangent (tan δ),
・Specific gravity, weight, shape,
- Surface roughness, contact angle

After the non-destructive evaluation is completed, the destructive evaluation unit 155 may divide the sample 22 into a plurality of fragments in accordance with the evaluation method, and perform destructive evaluation on each fragment. As the destructive evaluation, for example, one or more of the following items may be applied.
Thermogravimetric analysis (TG), differential thermal analysis (DTA), or both simultaneously (TG-DTA),
Differential scanning calorimetry, thermogravimetry, or dry moisture content measurement,
・Gas analysis, melt mass flow rate measurement, melt volume rate measurement, spiral flow measurement, softening point measurement, deflection temperature under load measurement,
Molecular weight measurement by thermal decomposition or dissolution,
・ICP (Inductively Coupled Plasma) testing ・MS (Mass Spectrometry) testing ・Mechanical property testing such as tensile, bending, impact, nanoindentation, creep, hardness, viscoelasticity, scratching, etc.
- Analysis of pyrolysis mass, volatilization and generated gas due to heating - Aging tests such as exposure to heat, humidification, ultraviolet rays, electromagnetic waves such as radiation, gas, etc. in controlled environments, outdoor exposure, repeated compression and tension, abrasion, temperature cycle (cold and hot shock), etc.
・Dielectric strength, arc resistance test,
・Chemical resistance (acid, alkali, solvent, etc.), adhesion testing,
Melt viscosity (MFR/MFI),
・Flame retardancy (UI) test

The above non-destructive and destructive evaluations are equivalent to simulating the process of the life cycle of manufacturing, use, disposal, and regeneration in material recycling, and each measurement data derived from and linked to the same sample is efficiently obtained. Then, the measurement data for one sample 22 can be increased, and efficient construction and expansion of databases 300, 400, and 500 (see Figures 4 to 9) can be realized. In addition, the identification information IDS can strengthen sample management, for example, by preventing sample mix-ups and duplicate measurements, and can prevent input errors into databases 300, 400, and 500. The control unit 158 controls each unit in the second measuring device 150, and inputs and outputs various information regarding the sample 22, evaluation conditions, evaluation results, etc. via the communication unit 152 and the network 180.

(Management Server 160)
The management server 160 collects the above-mentioned various information from each device in the measurement system 1 via the communication unit 162 and the network 180. The memory control unit 164 stores the databases 300, 400, and 500 (see FIGS. 4 to 9) in the memory unit 166. The identification information generation unit 168 generates the identification information IDM to be assigned to the raw material 20 and the identification information IDS to be assigned to the sample 22 based on the identification feature amount supplied from the sampling device 100, the transport device 120, or the first measuring device 140, and various other information.

The process management unit 170 generates information related to the processing steps and evaluation conditions in each device in the measurement system 1. The data analysis unit 172 extracts an identification feature of the sample 22 based on the information collected from each device. Furthermore, the data analysis unit 172 has a function of integrating the identification information IDS, each acquired piece of information, and the extracted identification feature, and systematizing the information resulting from the integration in a table format, a graph format, or the like. Here, the "identification feature" of the sample 22 is, for example, the quantities listed below.
- identification information IDM of the raw material 20 related to the sample 22;
- supplementary information D108 of the raw material 20 related to the sample 22;
Appearance information of the sample 22 (e.g., the shape, weight, chromaticity and color code of the sample 22, the number of foreign objects, or the dispersion state of the foreign objects),
- Information regarding the processing and weighing of sample 22;
Storage conditions of the raw materials 20 and samples 22;
Information obtained during the process of transporting and storing the raw materials 20 and samples 22;
- Pre-commencement evaluation results of the analysis and testing of raw materials 20 and samples 22.
Other physical properties of the raw material 20 and the sample 22

Here, the identification information generating unit 168 generates the identification information IDS as unique information in accordance with a predetermined generation algorithm so as to include the above-mentioned identification features and, for example, some or all of the information listed below.
- Unique information of the sampling device 100, the transport device 120, the first measuring device 140, or the second measuring device 150;
Measurement information D104 acquired by the measurement unit 104
The type and conditions of evaluation to be performed by the first measurement tool 140 or the second measurement tool 150;
The evaluation result of the evaluation performed by the first measuring device 140;

Here, a method of using the measurement information D104 to generate the identification information IDS will be described in more detail. As described above, the measurement information D104 acquired by the measurement unit 104 includes image data of the sample 22 captured by a camera.
Converting the luminance information of each pixel into binary data (e.g., "0" and "1") based on a comparison with a threshold;
Converting the luminance information of each pixel into grayscale (e.g., 256-level) signal intensity data;
- Converting each pixel into color information (e.g., color coding to RGB),
- Quantifying the signal intensity distribution (for example, in the case of binarization, finding the ratio of "0" and "1")
- Obtaining spatial frequency
- Quantify the data using machine learning according to a transformation algorithm created separately by persistent homology.
It is preferable to adopt a method such as the above and obtain the measurement information D104 based on the results obtained by these methods. For example, a method is considered in which the imaging information of the sample 22 is binarized and described in a matrix, and the matrix is arranged according to a rule.

In this way, by assigning a unique identification information IDS to the sample 22, it becomes possible to manage data for each individual sample 22. Furthermore, by using the inverse function of the generation algorithm, various information regarding the sample 22 can be obtained based on the identification information IDS. Furthermore, by including an encryption process in the generation algorithm, it is also possible to restrict the parties to whom the various information regarding the sample 22 is disclosed. The marking unit 114 assigns the identification information IDS to the sample 22 or to a storage container used for storing or transporting it by a method such as printing, engraving, or attaching a sticker.

(Computer)
2 is a block diagram of the computer 980. Each of the control units 118, 130, 148, 158 and the management server 160 shown in FIG. 1 includes one or more computers 980 shown in FIG.
2, the computer 980 includes a CPU 981, a storage unit 982, a communication I/F (interface) 983, an input/output I/F 984, and a media I/F 985. Here, the storage unit 982 includes a RAM 982a, a ROM 982b, and a HDD 982c. The communication I/F 983 is connected to a communication circuit 986. The input/output I/F 984 is connected to an input/output device 987. The media I/F 985 reads and writes data from a recording medium 988.

The ROM 982b stores an IPL (Initial Program Loader) executed by the CPU, etc. The HDD 982c stores application programs, various data, etc. The CPU 981 executes application programs, etc. loaded from the HDD 982c to the RAM 982a to realize various functions. The interior of the management server 160 shown in Figure 1 above is a block diagram showing the functions realized by application programs, etc.

<Operation of the First Embodiment>
FIG. 3 is a flowchart showing the operation of the measurement system 1.
3, when the process proceeds to step S202, the sampling device 100 acquires the raw material 20 and various information. That is, the storage unit 110 acquires the raw material 20, the incidental information acquisition unit 108 acquires incidental information D108, and the measurement unit 104 acquires measurement information D104. Next, the control unit 118 of the sampling device 100 supplies the measurement information D104 and the incidental information D108 to the management server 160. The memory unit 166 of the management server 160 stores this information.

Next, when the process proceeds to step S204 (identification information generation process), the identification information generation unit 168 of the management server 160 extracts identification features based on the measurement information D104 and the additional information D108, generates identification information IDS, IDM based on the extracted identification features and other information, and returns it to the sampling device 100. Next, the marking unit 114 in the sampling device 100 assigns identification information IDM to the raw material 20 or its packaging material, and assigns identification information IDS to the sample 22.

Next, when the process proceeds to step S206, the management server 160 determines the process and processing content to be executed by the sampling device 100 based on the identification information IDS, IDM, the measurement information D104, and the additional information D108. The management server 160 then supplies the sampling device 100 with a process/processing command D206 that specifies these processes and processing. The process/processing command D206 may include the date and time at which the process/processing is to be executed.

Next, when the process proceeds to step S208, the sampling device 100 executes the contents of the supplied process/processing command D206. For example, in step S208, the sampling device 100 executes some or all of the processes/processing listed below.
In the processing section 106 of the sampling device 100, a sample 22 having a specified shape and mass is obtained from the raw material 20 and prepared by processing or the like.
In the measuring section 104, the shape, weight and color of the sample 22 are measured again.
After the sample 22 is created, the remaining raw material 20 is wrapped and packaged as specified, and stored in a specified storage location and environment.

Furthermore, in step S208, the sampling device 100 outputs a process/processing report, which is a result report of the execution of the process/processing command D206, to the management server 160. The process/processing report includes, for example, some or all of the information listed below.
- Information regarding the processor, processing date, processing equipment, etc., and the processing results;
- Information regarding measurement results such as measurement data of the processed sample 22, the person who performed the measurement, the measuring device, etc.
-Information regarding storage, such as storage location, custodian, storage period, temperature, humidity, lighting conditions, packaging, etc.

Next, when the process proceeds to step S210 (reception process), the management server 160 outputs transport command information D210 to the transport device 120. Here, the transport command information D210 is information that commands the transport of the object to be transported from the source device to the destination device. In step S210, the transport command information D210 includes identification information IDS of the sample 22, which is the object to be transported, identification information of the sampling device 100, which is the source device, and identification information of the first measuring device 140, which is the destination device.

Next, when the process proceeds to step S212, the transport device 120 performs a transport process. That is, the transport device 120 transports the sample 22 from the sampling device 100 to the first measuring device 140 based on the transport command information D210.

Next, when the process proceeds to step S214, the transport device 120 transmits transport report information D214 reporting the transport result to the management server 160. The storage control unit 164 of the management server 160 stores the transport report information D214 in the storage unit 166. Here, the transport report information D214 includes, for example, some or all of the information listed below.
- Identification of the transporter and the transport device 120;
- Sample 22, its packaging or packaging condition;
- Containers and storage environments applied to actual transport and storage

If the sample 22, its packaging, or wrapping is damaged or missing, it may become inappropriate or impossible to evaluate the sample 22 in the first measuring device 140. In this case, the management server 160 stops the processing according to this flowchart. Alternatively, the management server 160 may return the sample 22 to the sampling device 100 and have the sample 22 processed again.

Next, when the process proceeds to step S216, the management server 160 outputs a first evaluation command D216 to the first measuring tool 140. The first evaluation command D216 includes, for example, some or all of the information listed below.
- identification information IDM of the raw material 20,
- identification information IDS of sample 22,
An evaluation date and time, which is the date and time when evaluation of sample 22 should take place.
-Evaluation conditions for sample 22.

Next, when the process proceeds to step S218, the first measuring device 140 performs a thermal analysis on the sample 22 based on the first evaluation command D216. That is, the thermal analysis unit 144 controls the temperature of the sample 22, and executes a process of heating it to at least its melting temperature or higher, and then cooling it to solidify it. The thermal analysis unit 144 then acquires the temperature and physical property/performance data of the sample 22 during that process.

Next, when the process proceeds to step S220, the first measuring device 140 transmits the first evaluation result D220 to the management server 160. Here, the first evaluation result D220 includes information such as the evaluator of the thermal analysis in step S218, the evaluation date and time, the evaluation equipment of the thermal analysis unit 144, the temperature history, and the evaluation results of the characteristics and performance. In the management server 160, the first evaluation result D220 is stored in the memory unit 166.

The sample 22 after thermal analysis has undergone a process similar to the material recycling of plastics. Therefore, the first evaluation result D220 also includes data on the temperature and characteristics/performance during that process. Therefore, it is possible to simulate the material recycling of raw materials, and obtain process control and evaluation results of the physical properties/performance during that process based on the first evaluation result D220. Furthermore, it is possible to obtain a sample 22 that simulates material recycling linked to the first evaluation result D220. This sample 22 after thermal analysis is used for evaluation in the second measuring device 150.

Next, when the process proceeds to step S222, the management server 160 outputs a transport command D222 to the transport device 120. Here, the transport command D222 is a command to transport the sample 22 from the first measuring device 140 to the second measuring device 150.

Next, when the process proceeds to step S224, the transport device 120 acquires and stores the sample 22 from the first measuring device 140 based on the transport command D222. The measurement unit 128 of the transport device 120 acquires information regarding the shape, weight, color, and appearance of the sample 22 acquired from the first measuring device 140. The transport device 120 then outputs information such as the transferee, the transport device 120, the date of transport, and the measurement results of the acquired sample 22 to the management server 160.

The identification information generation unit 168 of the management server 160 generates identification information IDS for linking information on the raw material 20 and the sample 22 based on the identification information IDM of the raw material 20, the first evaluation result D220, the measurement results of the sample 22, etc. The identification information IDS output from the management server 160, the various processes, processing contents, and processing conditions are input again to the transport device 120. Then, according to the input information, the transport device 120 obtains the sample 22 from the first measuring device 140, and measures, stores, and marks the sample 22.

Next, when the process proceeds to step S226, the management server 160 determines whether processing of the sample 22 is required. That is, it is possible that the shape and weight of the sample 22 obtained from the first measuring device 140 do not correspond to the evaluation content and number of evaluations to be performed by the second measuring device 150. In such a case, the determination in step S226 is "Yes" (processing is required), and the process proceeds to step S230.

In step S230, the management server 160 outputs a transport command to the transport device 120 and outputs a processing command to the sampling device 100. Next, when the process proceeds to step S232, the transport device 120 transports the sample 22 to the sampling device 100.

The sampling device 100 processes the sample 22 according to the processing command specified by the management server 160 (which includes the identification information IDS, processing date and time, processing content, processing conditions, etc.). In other words, the sampling device 100 divides and processes the sample 22 so that the sample 22 has a specified shape, weight, and quantity suitable for evaluation in the second measuring device 150. The measurement unit 104 of the sampling device 100 then remeasures the shape, weight, color, etc. of the sample 22 after processing. Furthermore, the sampling device 100 or the transport device 120 stores the divided sample 22 according to the specified period, storage location, environment, wrapping, packaging, etc.

Next, when the process proceeds to step S236, the sampling device 100 outputs a process report to the management server 160. This process report reports the details of the processing process executed in step S234, and includes information on the transporter and processor of the sample 22, the container used during actual transport and processing, the storage environment, the identification information IDS, and the like. When the management server 160 receives the process report, the memory control unit 164 stores the details in the memory unit 166 together with the identification information IDS.

After that, when the date and time arrives when the sample 22 should be transported to the second measuring device 150, the process proceeds to step S238, and the transport device 120 acquires the processed sample 22. Then, the process proceeds to step S240. Note that if the determination in step S226 above is "No" (no processing is required), the process proceeds from step S226 to step S240.

In step S240, the transport device 120 transports the sample 22 to the second measuring device 150. The transport device 120 then reports the transport result to the management server 160. Next, when the process proceeds to step S242, the management server 160 outputs an evaluation command for the sample 22 to the second measuring device 150, along with the identification information IDM, the identification information IDS, and the evaluation conditions.

Next, when the process proceeds to step S244, the second measuring device 150 evaluates the sample 22 according to the evaluation command, acquires the evaluation results, and reports them to the management server 160. To this end, the second measuring device 150 first receives the identification information IDS, the evaluation schedule, and the evaluation conditions from the management server 160. Next, the second measuring device 150 uses the acquisition unit 156 to identify and confirm the sample 22 acquired from the transport device 120. Then, the second measuring device 150 performs evaluation in the nondestructive evaluation unit 154 and the destructive evaluation unit 155. Information such as the identification information IDS, the evaluator, the evaluation date and time, the evaluation equipment in the nondestructive evaluation unit 154 and the destructive evaluation unit 155, the environmental history of the sample at the time of evaluation, and the evaluation results of the characteristics and performance are output to the management server 160 and stored in the memory unit 166.

Next, when the process proceeds to step S246, the transport device 120 collects the post-evaluation fragments of the sample 22 from the second measuring device 150 and stores them. The management server 160 then stores in the memory unit 166 information such as the identification information IDS, the evaluator, the evaluation date and time, the evaluation equipment of the non-destructive evaluation unit 154 and the destructive evaluation unit 155, the environmental history of the sample 22 at the time of evaluation, and the evaluation results of the characteristics and performance.

Next, when the process proceeds to step S248, the management server 160 integrates the identification information IDS, the identification information IDM, the analysis and evaluation flow, and various data. Next, when the process proceeds to step S250 (storage control process), the storage control unit 164 of the management server 160 constructs databases 300, 400, and 500 (see Figures 4 to 8) in the storage unit 166 based on the integrated data.

<Database Contents>
Next, the above-mentioned databases 300, 400, and 500 will be described.
4 and 5 are diagrams showing an example of the database 300. The database 300 is stored in the storage unit 166 by the storage control unit 164.
4 and 5 is a record, and each record has a one-to-one correspondence with a sample 22. In the illustrated example, the database 300 includes three records 301, 302, and 303.

Furthermore, each column in FIG. 4 and FIG. 5 corresponds to a data item for each sample 22. In the example of FIG. 4 and FIG. 5, the data items in the database 300 include a sample information group 310, a first sampling group 320, a thermal analysis group 330, a nondestructive evaluation group 340, a second sampling group 350, and a destructive evaluation group 360.

In FIG. 4, the sample information group 310 includes IDS management information 312 and material information 314. The IDS management information 312 includes the identification information IDS of the corresponding sample 22, the date the identification information IDS was assigned, and the date the identification information IDS was updated. The material information 314 includes the product name, manufacturer, manufacturing date, lot number, and material components of the corresponding sample 22.

The first sampling group 320 also stores data related to the first sampling process performed by the sampling device 100. In the illustrated example, the first sampling group 320 includes sampling process information 322, shape information 324, and identification feature information 326. The sampling process information 322 includes the size of the sample 22, the processing method, and information about the processor. The shape information 324 includes the dimensions and weight of the sample 22. The identification feature information 326 includes the identification feature of the sample 22.

The thermal analysis group 330 also stores data related to the thermal analysis performed by the first measuring device 140. In the illustrated example, the thermal analysis group 330 includes dry moisture measurement information 332, post-analysis shape information 334, and identification feature information 336. The dry moisture measurement information 332 includes the device used in the dry moisture measurement, the person who measured, the measurement date and time, the temperature conditions, the measurement values, and the physical properties. The post-analysis shape information 334 also includes the dimensions and weight of the sample 22 after the thermal analysis. The identification feature information 336 also includes the identification features based on the sample 22 after the thermal analysis.

The nondestructive evaluation group 340 also stores data related to the nondestructive evaluation performed by the second measuring device 150. In the illustrated example, the nondestructive evaluation group 340 includes FT-IR information 342. The FT-IR information 342 includes the measuring device, the person who performed the measurement, the measurement date and time, the temperature conditions, the measurement values, and the physical property values used in the FT-IR measurement.

In addition, in FIG. 5, the second sampling group 350 stores data related to the results of the second sampling process performed by the sampling device 100, i.e., the division and processing for evaluation by the second measuring device 150. Although some of the contents of the second sampling group 350 are not shown, the second sampling group 350 includes the same items as the first sampling group 320.

The destructive evaluation group 360 stores data related to the destructive evaluation performed by the second measuring device 150. In the illustrated example, the destructive evaluation group 360 includes bending test information 362, hardness test information 364, and aging test information 366. Here, the bending test information 362 includes the measuring device, the measurer, the measurement date and time, the temperature conditions, the measured values, and the physical properties in the bending test. The hardness test information 364 includes the measuring device, the measurer, the measurement date and time, the temperature conditions, the measured values, and the physical properties in the hardness test. The aging test information 366 includes the environmental test device, the work manager, the test start date and time, the environmental conditions, the measured values and the monitoring values of the test environment, the test stop date and time, etc.

6 is a diagram showing an example of another database 400 (a graph-format database). Database 400 is also stored in storage unit 166 by storage control unit 164. Database 400 is a graph-format database, and includes nodes 411 to 419b, nodes (without symbols) represented by circles in the other figures, and a number of edges (without symbols) represented by straight lines in the figure. These edges connect the nodes together.

Each node belongs to one of layers 410, 420, or 430. In layer 410 (first layer), each node corresponds to a process, and the order of the processes is indicated by the direction of the arrow. That is, in layer 410, information is linked in the order of the processes. Each node 411 to 419b in layer 410 contains information about the sampling process and its environmental information. In the illustrated example, the degradation characteristics can be evaluated by comparing the analysis results of the thermal analysis node 417a and the mechanical property node 417b before executing the aging test node 418b with the analysis results of the thermal analysis node 419a and the mechanical property node 419b after executing the aging test node 418b.

Each node in layer 420 (second layer) corresponds to the measurement results and measurement conditions shown in the nodes of layer 410. Furthermore, layer 430 corresponds to the measurement equipment that acquires the information shown in layer 420. For example, node 415 of "non-destructive evaluation" in layer 410 is connected to multiple nodes in layer 420. This indicates that sample 22 was divided into multiple pieces in the "non-destructive evaluation" process. In this way, the graph-format database 400 can also indicate the order of processes performed by each device, the division of sample 22, and the history of sample 22.

7 to 9 are diagrams showing an example of yet another database 500. The database 500 is also stored in the storage unit 166 by the storage control unit 164. Each row in Fig. 7 to 9 is a record, and each record corresponds one-to-one to a sample 22. In the illustrated example, the database 500 includes five records 501, 502, 503, and 504.
7 to 9 correspond to data items for each sample 22. In the example of Fig. 7 to 9, the data items of the database 500 include sampling groups 510, 560, and 590, a thermal analysis group 520, and analysis evaluation groups 540 and 580. Note that white circles in the figures indicate that some data is included.

In FIG. 7, the sampling group 510 includes associated information 512, processed shape information 514, and identification feature information 516. The associated information 512 includes the source, material type, and shape of the corresponding sample 22. The processed shape information 514 includes the size and amount. The "amount" may refer to weight, for example.

The identification feature information 516 includes identification features based on the sample 22 after thermal analysis. In other words, the identification feature information 516 is obtained by converting the measurement results of the thermal analysis into identification features. For example, the identification feature information 516 can be generated based on an appearance image that can be determined by image analysis, shape data and weight that can be obtained in advance by various analysis and evaluation devices, etc.

The identification feature information 516 can be expressed in the format of, for example, "ID-XXXX-YYYY-ZZZZ-TTTT-DSC." Here, "XXXX" is the longitudinal length of the sample 22, "YYYY" is the lateral length of the sample 22, "ZZZZ" is the weight of the sample 22, "TTTT" is the chromaticity of the sample 22, and "DSC" is the type code of the thermal analysis.

Thermal analysis group 520 indicates the results of the thermal analysis performed by the first measuring device 140, and includes device information 522, measurement data 524, post-measurement shape information 526, post-measurement weight information 528, sample shape information 530, and identification feature information 532. Device information 522 indicates the name of the device used in the thermal analysis performed by the first measuring device 140. Measurement data 524 indicates the type of measurement data obtained by the thermal analysis. Post-measurement shape information 526 indicates the shape of the sample 22 at the end of the thermal analysis.

Post-measurement weight information 528 is the weight of sample 22 at the end of the thermal analysis. Sample shape information 530 represents the shape of sample 22 before the thermal analysis is performed, and includes the size and amount (e.g., weight) of sample 22. Identification feature information 532 includes identification features based on sample 22 after thermal analysis, similar to identification feature information 516 described above.

In FIG. 8, the analysis evaluation group 540 indicates the contents of the non-destructive evaluation in the second measuring device 150, and includes multiple pieces of measurement information 542, 544, 546, 548, and 550. Each of these pieces of measurement information includes a "measurement method" and "measurement data." The sampling group 560 includes a processing/acquisition section 562 and identification feature information 564. The processing/acquisition section 562 includes the size and amount of the sample 22. The identification feature information 564 includes identification features based on the sample 22 after thermal analysis, similar to the above-mentioned identification feature information 516.

In FIG. 9, the analysis and evaluation group 580 indicates the contents of the destructive evaluation in the second measuring device 150, and includes multiple pieces of measurement information 582, 584, and 586. As with the analysis and evaluation group 540 (see FIG. 8), each piece of measurement information includes a "measurement method" and "measurement data." In addition, the sampling group 590 includes recovered sample information 592. The recovered sample information 592 includes the size and amount of the recovered sample 22.

[Second embodiment]
Next, a second embodiment will be described. In the following description, parts corresponding to those in the first embodiment described above are denoted by the same reference numerals, and the description thereof may be omitted.
The hardware configuration of the second embodiment is similar to that of the first embodiment (see FIGS. 1 and 2), except that the non-destructive evaluation unit 154 and the destructive evaluation unit 155 of the second measuring device 150 (see FIG. 1) each perform destructive evaluation for a plurality of evaluation items.

FIG. 10 is a flowchart showing the operation of the measurement system in the second embodiment.
10, the processes in steps S202 to S242 are the same as those in the first embodiment (see FIG. 3), and therefore the steps between the two are not shown.
10, as described in Fig. 3, the management server 160 outputs the identification information IDM, the identification information IDS, and information related to the evaluation conditions to the second measuring device 150. Then, in this embodiment, when step S242 ends, the process proceeds to step S260.

In step S260, the second measuring device 150 performs any nondestructive evaluation that has not been performed. The second measuring device 150 also transmits the results of the nondestructive evaluation to the management server 160. The management server 160 then stores the results of the nondestructive evaluation in the memory unit 166. Next, when the process proceeds to step S262, the second measuring device 150 determines whether or not all nondestructive evaluations to be performed have been completed. If the determination here is "No", the process returns to step S260, and the second measuring device 150 again performs any nondestructive evaluation that has not been performed. On the other hand, if all nondestructive evaluations to be performed have been completed, the determination in step S262 is "Yes", and the process proceeds to step S266.

In step S266, the second measuring device 150 performs any unperformed destructive evaluations. The second measuring device 150 also transmits the results of the destructive evaluations to the management server 160. The management server 160 then stores the results of the destructive evaluations in the memory unit 166. Next, when the process proceeds to step S268, the second measuring device 150 determines whether or not all destructive evaluations to be performed have been completed. If the determination here is "No", the process returns to step S266, and the second measuring device 150 again performs any unperformed destructive evaluations. On the other hand, if all destructive evaluations to be performed have been completed, the determination in step S268 is "Yes", and the process proceeds to step S270.

Next, when the process proceeds to step S270, similar to step S246 (see FIG. 3) described above, the transport device 120 collects the evaluated fragments of the sample 22 from the second measuring device 150 and stores them. The management server 160 then stores information such as the identification information IDS, the evaluator, the evaluation date and time, the evaluation equipment of the nondestructive evaluation unit 154 and the destructive evaluation unit 155, the environmental history of the sample 22 at the time of evaluation, and the evaluation results of the characteristics and performance in the memory unit 166.

Next, when the process proceeds to step S272, the management server 160 integrates the identification information IDS, the identification information IDM, the analysis evaluation flow, and various data, in the same manner as in step S248 (see FIG. 3) described above. Next, when the process proceeds to step S274, the storage control unit 164 of the management server 160 builds databases 300, 400, and 500 in the storage unit 166 based on the integrated data, in the same manner as in step S250 (see FIG. 3) described above.

[Third embodiment]
Next, a third embodiment will be described. In the following description, the same reference numerals are used to designate parts corresponding to those in the first embodiment, and the description thereof may be omitted.
The hardware configuration of the third embodiment is similar to that of the first embodiment (see FIGS. 1 and 2), except that the non-destructive evaluation unit 154 and the destructive evaluation unit 155 of the second measuring device 150 (see FIG. 1) each perform destructive evaluation for a plurality of evaluation items.

FIG. 11 is a flowchart showing the operation of the measurement system in the third embodiment.
11, the processes in steps S202 to S242 are the same as those in the first embodiment (see FIG. 3), and therefore the steps between the two are not shown.
11, as described in Fig. 3, the management server 160 outputs the identification information IDM, the identification information IDS, and information related to the evaluation conditions to the second measuring device 150. Then, in this embodiment, when step S242 ends, the process proceeds to step S280.

In step S280, the sampling device 100 divides and processes the sample 22 based on the processing command supplied from the management server 160, similar to the processing in step S234 described above. Thereafter, the second measuring device 150 performs non-destructive evaluation (steps S282, 284) and destructive evaluation (steps S286, 288) in parallel.

First, in step S282, the second measuring device 150 performs any unperformed nondestructive evaluations, similar to step S260 described above (see FIG. 10), and the management server 160 stores the results of the nondestructive evaluations in the memory unit 166.

Next, when the process proceeds to step S284, the second measuring device 150 determines whether or not all nondestructive evaluations to be performed have been completed. If the determination here is "No", the process returns to step S282, and the second measuring device 150 again performs any unperformed nondestructive evaluations. On the other hand, if all nondestructive evaluations to be performed have been completed, the determination in step S284 is "Yes", and the process proceeds to step S290.

In addition, in step S286, the second measuring device 150 performs any unperformed destructive evaluations, similar to step S266 described above (see FIG. 10), and the management server 160 stores the results of the destructive evaluations in the memory unit 166.

Next, when the process proceeds to step S288, the second measuring device 150 determines whether or not all destructive evaluations to be performed have been completed. If the determination here is "No", the process returns to step S286, and the second measuring device 150 again performs any unperformed destructive evaluations. On the other hand, if all destructive evaluations to be performed have been completed, the determination in step S288 is "Yes", and the process proceeds to step S290.

Next, when the process proceeds to step S290, similar to step S246 (see FIG. 3) described above, the transport device 120 collects the evaluated fragments of the sample 22 from the second measuring device 150 and stores them. The management server 160 then stores information such as the identification information IDS, the evaluator, the evaluation date and time, the evaluation equipment of the nondestructive evaluation unit 154 and the destructive evaluation unit 155, the environmental history of the sample 22 at the time of evaluation, and the evaluation results of the characteristics and performance in the memory unit 166.

Next, when the process proceeds to step S292, the management server 160 integrates the identification information IDS, the identification information IDM, the analysis evaluation flow, and various data, in the same manner as in step S248 (see FIG. 3) described above. Next, when the process proceeds to step S294, the storage control unit 164 of the management server 160 constructs a database in the storage unit 166 based on the integrated data, in the same manner as in step S250 (see FIG. 3) described above.

[Fourth embodiment]
Next, a fourth embodiment will be described. In the following description, the same reference numerals are used to designate parts corresponding to those in the first embodiment, and the description thereof may be omitted.
The hardware configuration of the fourth embodiment is similar to that of the first embodiment (see FIGS. 1 and 2), except that the non-destructive evaluation unit 154 and the destructive evaluation unit 155 of the second measuring device 150 (see FIG. 1) each perform destructive evaluation for a plurality of evaluation items.

12 and 13 are flowcharts showing the operation of the measurement system in the fourth embodiment.
12, when the process proceeds to step S302, the sampling device 100 acquires the raw material 20, D104, and D108. Next, when the process proceeds to step S304, the management server 160 and the sampling device 100 perform the same process as step S204 in the first embodiment. As a result, the sampling device 100 assigns identification information IDM to the raw material 20 or its packaging material, and assigns identification information IDS to the sample 22.

Next, when the process proceeds to step S306, the management server 160 and the sampling device 100 perform the same processes as steps S206 and S208 in the first embodiment. That is, the management server 160 supplies a process/processing command D206 to the sampling device 100, and the sampling device 100 executes the contents of the process/processing command D206. Next, when the process proceeds to step S308, the sampling device 100 performs a weighing process of the sample 22. That is, the sampling device 100 acquires the weight, dimensions, etc. of the sample 22.

Next, when the process proceeds to step S310, the management server 160 outputs the identification information IDS of the sample 22, the moisture measurement conditions, and other information related to the sample 22 to the sampling device 100. Next, when the process proceeds to step S312, the first measuring device 140 performs moisture measurement of the sample 22. At that time, the first measuring device 140 sets the maximum temperature of the sample 22 to be equal to or higher than the melting point of the sample 22, and equal to or lower than the oxidation temperature and the thermal decomposition temperature.

Next, when the process proceeds to step S314, the first measuring device 140 acquires the post-analysis sample 22. Next, when the process proceeds to step S316, the first measuring device 140 observes and weighs the post-analysis sample 22.

Next, when the process proceeds to step S318, the management server 160 acquires the moisture measurement results and moisture measurement conditions of the sample 22. Next, the data analysis unit 172 of the management server 160 acquires an identification feature of the sample 22 based on the moisture measurement results, and generates identification information IDS based on the acquired identification feature.

Next, when the process proceeds to step S322, the first measuring device 140 measures the sample 22 and confirms the identification feature and the identification information IDS. Next, when the process proceeds to step S324, the first measuring device 140 measures the reflection absorption spectrum of the sample 22. Next, when the process proceeds to step S326, the first measuring device 140 acquires the sample 22 after performing the reflection absorption spectrum measurement.

Next, when the process proceeds to step S328, the first measuring device 140 outputs the reflection/absorption spectrum measurement results and the measurement conditions for the sample 22 to the management server 160. Next, when the process proceeds to step S329, the first measuring device 140 measures the sample 22 and confirms the identification feature and the identification information IDS, similar to the process of step S322.

Next, when the process proceeds to step S330, the first measuring device 140 performs an XRD measurement on the sample 22. Next, when the process proceeds to step S332, the first measuring device 140 acquires the sample 22 after the XRD measurement.

Next, when the process proceeds to step S334, the first measuring device 140 outputs the results of the XRD measurement of the sample 22 and the measurement conditions to the management server 160. Next, when the process proceeds to step S334, the first measuring device 140 measures the sample 22 and confirms the identification feature and the identification information IDS, similar to the process of step S322.

Next, when the process proceeds to step S338, the first measuring device 140 performs FT-IR measurement on the sample 22. Next, when the process proceeds to step S340, the first measuring device 140 acquires the sample 22 after performing the FT-IR measurement.

Next, when the process proceeds to step S342, the first measuring device 140 outputs the results of the FT-IR measurement of the sample 22 and the measurement conditions to the management server 160. Next, when the process proceeds to step S334 in FIG. 13, the first measuring device 140 measures the sample 22 and confirms the identification feature and identification information IDS, similar to the process of step S322.

Next, when the process proceeds to step S346, the second measuring device 150 processes and weighs the sample 22. Thereafter, the second measuring device 150 executes the processes of steps S350 to S354, S360 to S364, and S370 to S374 in parallel.

First, in step S350, the second measuring device 150 performs TG-DTA measurement on one piece of the sample 22. Next, when the process proceeds to step S352, the second measuring device 150 collects and stores the residue from the TG-DTA measurement. Next, when the process proceeds to step S354, the second measuring device 150 outputs the results of the TG-DTA measurement on the sample 22 and the measurement conditions to the management server 160.

Meanwhile, in step S360, the second measuring device 150 performs a bending test on the other piece of the sample 22. Next, when the process proceeds to step S362, the second measuring device 150 collects and stores the residue from the bending test. Next, when the process proceeds to step S364, the second measuring device 150 outputs the results of the bending test on the sample 22 and the measurement conditions to the management server 160.

Meanwhile, in step S370, the second measuring device 150 performs an MFR (Melt Flow Rate) test on another piece of sample 22. Next, when the process proceeds to step S372, the second measuring device 150 collects and stores the residue from the MFR test. Next, when the process proceeds to step S374, the second measuring device 150 outputs the results of the MFR test on sample 22 and the measurement conditions to the management server 160.

Next, when the process proceeds to step S380, the management server 160 integrates the identification information IDS, the identification information IDM, the analysis evaluation flow, and various data, in the same manner as in step S248 (see FIG. 3) described above. Next, when the process proceeds to step S382, the storage control unit 164 of the management server 160 constructs a database in the storage unit 166 based on the integrated data, in the same manner as in step S250 (see FIG. 3) described above.

[Fifth embodiment]
Next, a fifth embodiment will be described. In the following description, the same reference numerals are used to designate parts corresponding to those in the first embodiment, and the description thereof may be omitted.
FIG. 14 is a block diagram of a measurement system 7 according to the fifth embodiment.
14, the measurement system 7 includes a sampling device 200, measurement provider devices 220 and 240, a data management device 260, and a network 180 connecting these. The measurement provider device 220 and the measurement provider devices 220 and 240 are devices managed by different providers.

The sampling device 200 includes a communication unit 202, a sample acquisition unit 204, an ID issuing unit 206, a weighing unit 208, a processing unit 210, and a material/provider information acquisition unit 212. The measurement operator device 220 includes a communication unit 222, a thermal analysis unit 224, an identification data acquisition unit 226, and a sample acquisition unit 228.

The measurement provider device 240 also includes a communication unit 242, an evaluation unit 244, and a sample acquisition unit 246. The data management device 260 also includes a communication unit 262, a calculation unit 264, and a storage unit 266.

The communication units 202, 222, 242, and 262 communicate data with each other via the network 180. In the sampling device 200, the sample acquisition unit 204 acquires the sample 22 from the raw material 20. The ID issuing unit 206 issues identification information IDS and IDM. The weighing unit 208 performs various measurements on the raw material 20 and the sample 22. Furthermore, the weighing unit 208 also performs environmental measurements. The processing unit 210 processes the raw material 20 and the sample 22. The material/provider information acquisition unit 212 acquires information on the provider of the raw material 20. Furthermore, although not shown, the sampling device 200 includes elements similar to those of the sampling device 100 of the first embodiment (see FIG. 1). As a result, the sampling device 200 can achieve the same functions as the sampling device 100.

In the measurement provider device 220, the thermal analysis unit 224 has the same functions as the thermal analysis unit 144 in the first embodiment (see FIG. 1). The identification data acquisition unit 226 acquires various data for identification. The sample acquisition unit 228 acquires the sample 22. Furthermore, although not shown, the measurement provider device 220 has elements similar to those of the first measurement device 140 in the first embodiment. This allows the measurement provider device 220 to achieve the same functions as the first measurement device 140.

In the measurement provider device 240, the evaluation unit 244 has the same functions as the non-destructive evaluation unit 154 and the destructive evaluation unit 155 (see FIG. 1) in the first embodiment. The sample acquisition unit 246 acquires the sample 22. Furthermore, although not shown, the measurement provider device 240 has elements similar to those of the second measurement device 150 in the first embodiment. This allows the measurement provider device 240 to achieve the same functions as the second measurement device 150.

In the data management device 260, the memory unit 266 has the same functions as the memory unit 166 (see FIG. 1) in the first embodiment. In addition, the calculation unit 264 has the same functions as the memory control unit 164, the identification information generation unit 168, the process management unit 170, and the data analysis unit 172 in the first embodiment. This allows the data management device 260 to realize the same functions as the management server 160 in the first embodiment.

[Effects of the embodiment]
As described above, according to the embodiment, the data management device (160) includes an identification information generation unit 168 that generates identification information IDS, a communication unit 162 that receives measurement conditions including temperature conditions in the first measuring device 140, the results of the first measurement process, the measurement conditions in the second measuring device 150, the results of the second measurement process, and the identification information IDS assigned in the sampling device 100, and a memory control unit 164 that stores the identification information IDS, the results of the first measurement process, and the measurement conditions in the second measuring device 150 in correspondence with each other in the memory unit 166.

This allows information about plastics and the like to be managed appropriately. In other words, according to the above-described embodiment, it is possible to produce plastic samples 22 through heat treatment with the aim of material recycling, and to obtain detailed data on the processing steps and characteristics/physical properties.

Moreover, it is more preferable that the second measurement device 150 includes a plurality of evaluation units (154, 155) that analyze a plurality of characteristics or physical properties of the sample 22, the communication unit 162 receives the evaluation results of the plurality of evaluation units (154, 155) as the results of the second measurement process, and the memory control unit 164 stores the evaluation results of the plurality of evaluation units (154, 155) in the memory unit 166 in association with the identification information IDS and the results of the first measurement process.

This makes it possible to obtain multiple types of characteristic and physical property data based on analysis and evaluation of the same prepared sample 22 using different types of measurement equipment. In addition, by accumulating various types of characteristic and physical property data linked to the same sample 22, it is possible to suppress variation in measurement data caused by samples due to sampling, heat treatment during preparation, etc., and to build and expand a database. In addition, by generating and assigning identification information using the obtained characteristic and physical property data to each sample 22, it is possible to prevent errors in various handling of the sample 22 in real space and in data management in digital space. Furthermore, it is possible to build a systematic database that includes a series of processes such as sampling, measurement, and disposal of the sample 22.

Moreover, the multiple evaluation units (154, 155) include a nondestructive evaluation unit 154 that performs nondestructive evaluation and a destructive evaluation unit 155 that performs destructive evaluation, and the nondestructive evaluation unit 154 performs nondestructive evaluation before destructive evaluation, and it is more preferable that the memory control unit 164 stores the results of the nondestructive evaluation and the results of the destructive evaluation in the memory unit 166 in association with the identification information IDS. This allows for a more precise evaluation of the sample 22 based on both the nondestructive evaluation and the destructive evaluation.

Moreover, it is more preferable that the first measuring device 140 has a function of evaluating the characteristics or physical properties of the sample 22 by differential scanning calorimetry, thermogravimetry, differential thermal analysis measurement, dry moisture content measurement, heated gas analysis, melt mass flow rate measurement, melt volume rate measurement, spiral flow measurement, or molding shrinkage rate measurement. This allows for a more precise evaluation of the sample 22, especially in a heated state.

The nondestructive evaluation performed by the nondestructive evaluation unit 154 evaluates the electromagnetic wave characteristics, DC voltage application characteristics, AC voltage application characteristics, or appearance characteristics of the sample 22, and the electromagnetic wave characteristics are the transmission, reflection, absorption, or fluorescence spectrum characteristics of the sample 22 for X-rays, ultraviolet rays, visible light, and infrared rays, the DC voltage application characteristics are the resistance value, capacitance, or charge rate of the sample 22 when a DC voltage is applied, the AC voltage application characteristics are the impedance of the sample 22 when an AC voltage is applied, and the appearance characteristics are the contact angle, color coordinates, chromaticity, specific gravity, or weight of the sample 22. As a result, particularly in terms of nondestructive evaluation, it is possible to separate and extract different response signals due to the history and components from the input signal in the measurement of the sample 22 of recycled plastics, which often have diverse histories and are multi-component, and to realize even more precise evaluation.

The destructive evaluation performed by the destructive evaluation unit 155 is preferably differential scanning calorimetry, thermogravimetry, differential thermal analysis, dry moisture content measurement, heated gas analysis, melt mass flow rate measurement, melt volume rate measurement, spiral flow measurement, softening point measurement, deflection temperature under load measurement, molecular weight measurement by thermal decomposition or dissolution, ICP measurement, mechanical property test, or aging test, and the mechanical property test is a test of tensile strength, bending strength, impact strength, creep, hardness, viscoelasticity, and scratching, and the aging test is preferably a test of fatigue, wear, and temperature cycle due to exposure to heat, humidity, radiation, electromagnetic waves or gas, outdoors, etc. This makes it possible to achieve a more precise evaluation of the sample 22, particularly in terms of destructive evaluation, and to obtain measurement data on the physical properties, characteristics, and performance of the sample 22 throughout its life cycle from manufacture to use, reuse, and disposal.

Moreover, the memory control unit 164 constructs a graph-format database (400) described in a graph format for the memory unit 166, and it is even more preferable that the graph-format database (400) includes a first layer (410) related to the measurement results by the first measuring device 140, the measurement results by the second measuring device 150, the sampling process in the sampling device 100 and its environmental information, and a second layer (420) related to the measurement results in the first measuring device 140, the measurement conditions including the temperature control conditions for the sample 22, and information related to the results of the processing in the sampling device 100. This makes it possible to systematically store various measurement results in the memory unit 166.

It is also preferable that the information in the first layer (410) is linked in the order of the processes. This allows the various measurement results to be managed according to the order of the processes.

[Modification]
The present invention is not limited to the above-mentioned embodiment, and various modifications are possible. The above-mentioned embodiment is exemplified to explain the present invention in an easy-to-understand manner, and is not necessarily limited to those having all the configurations described. In addition, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. In addition, it is possible to delete a part of the configuration of each embodiment, or to add or replace other configurations. In addition, the control lines and information lines shown in the figure show those that are considered necessary for explanation, and do not necessarily show all control lines and information lines necessary on the product. In reality, it may be considered that almost all configurations are connected to each other. Possible modifications of the above-mentioned embodiment are, for example, as follows.

(1) The hardware of the management server 160 and data management device 260 in the above embodiment can be realized by a general computer, so the flowcharts shown in Figures 3 and 10 to 13 and other programs that execute the various processes described above may be stored on a storage medium (a computer-readable recording medium on which a program is recorded) or distributed via a transmission path.

(2) In the above embodiment, the processes shown in Figures 3, 10 to 13, and the other processes described above are described as software processes using a program, but some or all of them may be replaced with hardware processes using an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array), etc.

(3) The memory unit 166 may be located in another storage device (not shown) connected to the network 180 and may not be included in the management server 160.

1 Measurement system 22 Sample 100 Sampling device 140 First measurement device 150 Second measurement device 154 Non-destructive evaluation section (evaluation section)
155 Destruction Evaluation Department (Evaluation Department)
160 Management server (data management device)
162 Communication unit 164 Storage control unit 166 Storage unit 168 Identification information generation unit 400 Database (Graph format database)
410 Layer (First Layer)
420 Layer (Second Layer)
IDS Identification Information S204 Step (Identification Information Generation Process)
Step S210 (receiving process)
Step S250 (Memory Control Process)

Claims (9)

A sampling device that provides a designated identification to a sample that is a plastic;
a first measuring device that performs a first measurement process by controlling the temperature of the sample to a temperature equal to or higher than the melting temperature of the sample and evaluating characteristics of the sample in a heated state;
a second measurement device that performs a second measurement process to evaluate characteristics of the sample that has been evaluated by the first measurement device and then solidified,
an identification information generation unit that generates the identification information;
a communication unit that receives measurement conditions including temperature conditions in the first measuring device, a result of the first measurement process, measurement conditions in the second measuring device, a result of the second measurement process, and the identification information assigned in the sampling device;
a storage control unit that causes a storage unit to store the identification information, a result of the first measurement process, and a measurement condition for the second measurement device in association with each other. the second measurement device includes a plurality of evaluation units for analyzing a plurality of characteristics or properties of the sample;
the communication unit receives evaluation results from the plurality of evaluation units as a result of the second measurement process;
The data management device according to claim 1 , wherein the storage control unit stores the evaluation results from the plurality of evaluation units in the storage unit in association with the identification information and the result of the first measurement process. The plurality of evaluation units include a nondestructive evaluation unit that performs nondestructive evaluation and a destructive evaluation unit that performs destructive evaluation, and the nondestructive evaluation unit performs the nondestructive evaluation before the destructive evaluation,
3. The data management device according to claim 2, wherein the storage control unit stores the results of the non-destructive evaluation and the results of the destructive evaluation in the storage unit in association with the identification information. The data management device according to claim 1, characterized in that the first measuring device has a function of evaluating the characteristics or physical properties of the sample by differential scanning calorimetry, thermogravimetry, differential thermal analysis measurement, dry type moisture content measurement, heated gas analysis, melt mass flow rate measurement, melt volume rate measurement, spiral flow measurement, or molding shrinkage rate measurement. the nondestructive evaluation performed by the nondestructive evaluation unit evaluates electromagnetic wave characteristics, DC voltage application characteristics, AC voltage application characteristics, or appearance characteristics of the sample,
the electromagnetic properties being X-ray, ultraviolet, visible, infrared transmission, reflection, absorption or fluorescence spectral properties of the sample;
the DC voltage application characteristic is a resistance value, a capacitance, or a charge rate of the sample when a DC voltage is applied;
The AC voltage application characteristic is an impedance of the sample when an AC voltage is applied, or a combination of a relative dielectric constant and a dielectric loss tangent;
The data management device according to claim 3 , wherein the appearance characteristics are a contact angle, a color coordinate, a chromaticity, a specific gravity, a weight, or a surface roughness of the sample. The destructive evaluation performed by the destructive evaluation unit is differential scanning calorimetry, thermogravimetry, differential thermal analysis, dry type moisture content measurement, softening point measurement, deflection temperature under load measurement, thermal evolved gas analysis, melt mass flow rate measurement, melt volume rate measurement, spiral flow measurement, molecular weight measurement by thermal decomposition or dissolution, ICP measurement, mechanical property test, or aging test,
The mechanical property test is a test of tensile strength, flexural strength, impact strength, creep, hardness, viscoelasticity, or scratch;
4. The data management device according to claim 3, wherein the aging test is an aging test involving exposure to heat, humidity, radiation, electromagnetic waves or gas in a controlled environment, outdoor exposure, repeated compression and tension, abrasion, or temperature cycling. The storage control unit constructs a graph-format database described in a graph format in the storage unit,
The graph format database includes:
a first layer relating to a measurement result by the first measuring device, a measurement result by the second measuring device, a sampling process in the sampling device, and environmental information thereof;
The data management device according to claim 1, further comprising a second layer relating to measurement results from the first measurement device, measurement conditions including temperature control conditions for the sample, and information relating to processing results from the sampling device. 8. The data management device according to claim 7, wherein in the first layer, information is linked in the order of processes. providing designated identification information to a sample of plastic;
a first measurement process for controlling the temperature of the sample to which the identification information has been assigned to be equal to or higher than its melting point and evaluating characteristics of the sample in a heated state;
a second measurement process for evaluating characteristics of the sample solidified by the first measurement process;
a receiving step of receiving measurement conditions including a temperature condition in the first measurement process, a result of the first measurement process, measurement conditions in the second measurement process, a result of the second measurement process, and the identification information assigned to the sample;
a storage control step of causing a storage unit to store the identification information, a result of the first measurement processing step, and a measurement condition in the second measurement processing step in association with each other.