Ready-mixed concrete quality prediction method, quality prediction program, ready-mixed concrete transport method, ready-mixed concrete manufacturing method, and ready-mixed concrete quality prediction system

Abstract

Improves prediction accuracy in quality control of transported ready-mix concrete. [Solution] A quality prediction method for predicting the fresh properties of fresh concrete while it is being stirred by the drum of an agitator vehicle or after the stirring, comprising: a measurement process for repeatedly obtaining index values ​​from a sensor installed inside the drum that indicate the degree of strain when the sensor passes through the fresh concrete as the drum rotates; an accumulation process for calculating the cumulative strain obtained by accumulating the index values ​​over a section in which the drum has rotated N times (N is a number greater than or equal to 2) as the cumulative strain of the object to be evaluated; and a prediction process for predicting the fresh properties of the fresh concrete being stirred by the drum by inputting the cumulative strain of the object to be evaluated calculated in the accumulation process into a relational equation that has been constructed in advance to indicate the relationship between the cumulative strain and the fresh properties of the fresh concrete.

Description

[Technical Field]

[0001] The present disclosure relates to a quality prediction method for ready-mixed concrete, a quality prediction program, a method for transporting ready-mixed concrete, a method for manufacturing ready-mixed concrete, and a quality prediction system for ready-mixed concrete. [Background technology]

[0002] Patent Document 1 discloses a method for predicting the quality of ready-mixed concrete based on input information including vibration information indicating the magnitude of vibration caused by the fall or flow of ready-mixed concrete produced by a mixer that mixes concrete materials, and a prediction model that has been constructed in advance using machine learning. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-103030 Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure provides a ready-mixed concrete quality prediction method, a quality prediction program, a ready-mixed concrete transportation method, a ready-mixed concrete manufacturing method, and a ready-mixed concrete quality prediction system that are useful for improving prediction accuracy in quality control of transported ready-mixed concrete. [Means for solving the problem]

[0005] [1] A quality prediction method for predicting the fresh properties of ready-mixed concrete while it is being stirred by the drum of an agitator vehicle or after the stirring, comprising: a measurement process for repeatedly obtaining index values ​​from a sensor installed inside the drum that indicate the degree of strain when the sensor passes over the fresh concrete as the drum rotates; an integration process for calculating the cumulative strain obtained by integrating the index values ​​over a section in which the drum has made N revolutions (N is a number equal to or greater than 2) as the cumulative strain of the object to be evaluated; and a prediction process for predicting the fresh properties of the ready-mixed concrete being stirred by the drum by inputting the cumulative strain of the object to be evaluated calculated in the integration process into a relational equation that has been constructed in advance to indicate the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete.

[0006] [2] The method for predicting the quality of ready-mixed concrete according to [1] above, wherein N is an integer of 2 or more.

[0007] [3] The method for predicting the quality of ready-mixed concrete according to [1] or [2] above, wherein the relational expression used in the prediction step is a linear function.

[0008] [4] A method for predicting the quality of ready-mixed concrete according to any one of [1] to [3] above, further comprising a measurement value output process in which the agitator vehicle outputs information indicating the index values ​​repeatedly acquired in the measurement process to an external communication network via wireless communication, and a result acquisition process in which a computer installed in equipment that produces ready-mixed concrete transported by the agitator vehicle acquires the prediction results in the prediction process.

[0009] [5] A method for predicting the quality of ready-mixed concrete according to any one of [1] to [3] above, further comprising a prediction value processing step, in which a computer installed in the agitator car executes the prediction step, and in which the computer installed in the agitator car at least one of displaying the prediction results in the prediction step on a monitor and recording the prediction results.

[0010] [6] A quality prediction program for causing a computer to execute the method for predicting the quality of ready-mixed concrete according to any one of [1] to [5] above.

[0011] [7] A method of transporting fresh concrete to a location where it will be used while stirring the fresh concrete inside a drum using an agitator vehicle having a drum, the method comprising: a measurement process of repeatedly obtaining index values ​​from a sensor installed inside the drum that indicate the degree of strain when the sensor passes through the fresh concrete as the drum rotates; an integration process of calculating the cumulative strain obtained by integrating the index values ​​over a section where the drum has rotated N times (N is a number equal to or greater than 2) as the cumulative strain of the object to be evaluated; and a prediction process of predicting the fresh properties of the fresh concrete being stirred in the drum by inputting the cumulative strain of the object to be evaluated calculated in the integration process into a relational equation that has been constructed in advance to indicate the relationship between the cumulative strain and the fresh properties of the fresh concrete.

[0012] [8] A method for manufacturing ready-mixed concrete, comprising: a production process in which concrete materials are mixed in a mixer to obtain ready-mixed concrete in a production facility; a transportation process in which the ready-mixed concrete is transported to a location where it will be used while being stirred in the drum by an agitator vehicle having a drum; a measurement process in which an index value indicating the degree of strain when the sensor installed inside the drum passes over the ready-mixed concrete as the drum rotates is repeatedly obtained; an integration process in which the index value is integrated over a section in which the drum has made N rotations (N is a number equal to or greater than 2) to calculate the cumulative strain obtained as the cumulative strain of the object to be evaluated; and a prediction process in which the cumulative strain of the object to be evaluated calculated in the integration process is input into a relational equation previously constructed to indicate the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete, thereby predicting the fresh properties of the ready-mixed concrete being stirred in the drum.

[0013] [9] A quality prediction system for predicting the fresh properties of ready-mixed concrete while it is being stirred by the drum of an agitator vehicle or after the stirring, comprising: a sensor installed inside the drum capable of measuring an index value indicating the degree of strain when the drum passes through the fresh concrete as it rotates; a measurement information acquisition unit that repeatedly acquires the index value from the sensor; an integration calculation unit that calculates the cumulative strain obtained by integrating the index values ​​over a section in which the drum has rotated N times (N is a number greater than or equal to 2) as the cumulative strain of the object to be evaluated; and a quality prediction unit that predicts the fresh properties of the ready-mixed concrete being stirred by the drum by inputting the cumulative strain of the object to be evaluated calculated by the integration calculation unit into a relational equation previously constructed to indicate the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete. [Effects of the Invention]

[0014] According to the present disclosure, there are provided a quality prediction method for ready-mixed concrete, a quality prediction program, a method for transporting ready-mixed concrete, a method for manufacturing ready-mixed concrete, and a quality prediction system for ready-mixed concrete, which are useful for improving prediction accuracy in quality control of transported ready-mixed concrete. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a schematic diagram illustrating a ready-mixed concrete manufacturing system. [Figure 2] Fig. 2(a) is a schematic diagram illustrating an agitator vehicle, and Fig. 2(b) is a schematic diagram illustrating a sensor and a management device mounted on the agitator vehicle. [Figure 3] FIG. 3 is a block diagram illustrating an example of the functional configuration of the quality prediction system. [Figure 4] FIG. 4 is a graph showing an example of the change in the measured value of strain over time. [Figure 5] FIG. 5 is a schematic diagram illustrating the calculation process for obtaining a predicted value from the accumulated distortion. [Figure 6]FIG. 6 is a block diagram illustrating an example of a hardware configuration of the quality prediction system. [Figure 7] FIG. 7 is a flowchart illustrating a process flow executed in the preparation phase. [Figure 8] FIG. 8 is a flowchart illustrating a process flow executed in the evaluation phase. [Figure 9] FIG. 9 is a block diagram illustrating an example of the functional configuration of the quality prediction system. [Figure 10] FIG. 10 is a schematic diagram showing the tilting mixer used in the verification. [Figure 11] FIG. 11 is a graph showing measured values ​​of strain and actual measured values ​​of slump. [Figure 12] FIG. 12 is a graph showing the corrected strain values ​​and the measured slump values. [Figure 13] Figure 13(a) is a graph showing the time change of strain for five rotations, and Figure 13(b) is a graph showing the time change of cumulative strain for five rotations. [Figure 14] Figure 14(a) is a graph showing a relational expression constructed from the accumulated strain for one rotation, and Figure 14(b) is a graph showing a relational expression constructed from the accumulated strain for two rotations. [Figure 15] Figure 15(a) is a graph showing a relational expression constructed from the accumulated strain for three rotations, and Figure 15(b) is a graph showing a relational expression constructed from the accumulated strain for five rotations. [Figure 16] FIG. 16 is a graph showing the relationship between the cumulative number of rotations and the coefficient of determination. DETAILED DESCRIPTION OF THE INVENTION

[0016] An embodiment will be described below with reference to the drawings. In the description, the same elements or elements having the same functions are designated by the same reference numerals, and redundant description will be omitted.

[0017] [Ready-mix concrete manufacturing system] FIG. 1 schematically shows a ready-mixed concrete manufacturing system equipped with a quality prediction system according to one embodiment. The manufacturing system 1 (ready-mixed concrete manufacturing system) shown in FIG. 1 is a system that manufactures ready-mixed concrete through a process of mixing concrete ingredients and a process of transporting the ready-mixed concrete obtained by mixing while stirring. In the present disclosure, the manufacture of ready-mixed concrete includes not only obtaining ready-mixed concrete by mixing concrete ingredients in a production facility, but also shipping and transporting the obtained ready-mixed concrete. The quality of ready-mixed concrete fluctuates even during transportation, and the transportation process can be considered to be one step in the manufacturing process.

[0018] A part of the manufacturing system 1 is installed in a facility for producing ready-mixed concrete (hereinafter referred to as "production facility S1"). The production facility S1 is a factory that produces ready-mixed concrete. The manufacturing system 1 includes, for example, a manufacturing device 10, an agitator vehicle 20, and a production management device 50.

[0019] The manufacturing apparatus 10 is an apparatus that executes a process of mixing concrete materials, and is provided in the production facility S1. The concrete materials used in the manufacturing apparatus 10 include cement, admixtures, coarse aggregate, fine aggregate, water, and admixtures. The use of the ready-mix concrete produced by the manufacturing apparatus 10 (the type of concrete after hardening) is not particularly limited. The types of various concrete materials mixed by the manufacturing apparatus 10 are also not particularly limited. The manufacturing apparatus 10 includes, for example, a storage bottle 11, a measuring bottle 12, a collecting hopper 13, a mixer 14, and a loading hopper 15.

[0020] The storage bottles 11 temporarily store various types of concrete materials. Various types of concrete materials are transported to the storage bottles 11 from the material storage area by a transport device. The storage bottles 11 are configured to store various types of concrete materials individually. Hereinafter, "concrete materials" may be simply referred to as "materials." The various materials stored in the storage bottles 11 are supplied to the measuring bottles 12 as needed.

[0021] Measuring bottle 12 is disposed below storage bottle 11. Measuring bottle 12 operates based on operational instructions from a control device provided in manufacturing system 1, and individually measures various materials. When measuring bottle 12 detects the target amount of material instructed by the control device, it supplies the material to collecting hopper 13. When water is supplied to measuring bottle 12, an admixture may be mixed into the water. Collecting hopper 13 is disposed below measuring bottle 12. Collecting hopper 13 collects the various materials discharged from measuring bottle 12 and supplies the collected various materials to mixer 14. Note that manufacturing apparatus 10 does not necessarily have to be equipped with collecting hopper 13, and various materials may be supplied to mixer 14 from measuring bottle 12.

[0022] The mixer 14 is disposed below the collecting hopper 13. The mixer 14 is a device for mixing concrete materials. The mixer 14 mixes (kneads) fine aggregate, coarse aggregate, cement, water, admixtures, etc. to prepare ready-mixed concrete. The ready-mixed concrete is discharged from the bottom of the mixer 14 into a loading hopper 15. The mixer 14 may be a tilting mixer, a horizontal single-shaft mixer, a horizontal twin-shaft mixer, or a pan-type mixer. The mixer 14 includes, for example, two stirring members 14a and a mixer drive unit 14b.

[0023] The agitating members 14a are members that agitate the various materials supplied to the mixer 14. The two agitating members 14a are arranged side by side inside the main body (container portion) of the mixer 14 and are rotatable. Each of the two agitating members 14a includes a rotation shaft that extends horizontally in one direction. The mixer driving unit 14b rotates the rotation shafts of the two agitating members 14a based on operation instructions from the control device. The mixer driving unit 14b includes, for example, a driving source such as a motor that applies driving force to the agitating members 14a.

[0024] An opening is provided at the bottom of the main body of the mixer 14 for discharging the produced ready-mixed concrete into a loading hopper 15. The loading hopper 15 is located below the mixer 14 and temporarily stores the ready-mixed concrete. The loading hopper 15 supplies the temporarily stored ready-mixed concrete to an agitator vehicle 20. In this way, the ready-mixed concrete is loaded into the agitator vehicle 20.

[0025] The agitator vehicle 20 is a vehicle (transport vehicle) that transports ready-mixed concrete while stirring it. The agitator vehicle 20 is also called a mixer vehicle. The agitator vehicle 20 has a drum 22. The agitator vehicle 20 transports the ready-mixed concrete to a location where the ready-mixed concrete will be used (hereinafter referred to as "use location S2") while stirring the ready-mixed concrete inside the drum 22. The use location S2 is a construction site where construction or work using ready-mixed concrete is carried out. In FIG. 1, a transport route TP from the production facility S1 to the use location S2 is shown, and the agitator vehicle 20 moves, for example, along the predetermined transport route TP.

[0026] As described above, ready-mixed concrete (ready-mixed concrete before transportation) is obtained in the production facility S1, and then loaded onto the agitator vehicle 20 and shipped. The ready-mixed concrete (ready-mixed concrete during transportation) is transported from the production facility S1 to the usage location S2 while being agitated by the agitator vehicle 20. Then, at the usage location S2, the ready-mixed concrete after transportation is unloaded.

[0027] The manufacturing system 1 may produce ready-mixed concrete using the manufacturing apparatus 10 in the production facility S1 so as to satisfy the required quality (required quality at the time of unloading) set for each use location S2 (site). For example, an operator of the manufacturing apparatus 10 determines the production conditions for ready-mixed concrete so as to satisfy the required quality, and inputs the determined production conditions into the control device as operation instructions. The production conditions for ready-mixed concrete may include, for example, the mix of concrete materials, the amount mixed by the mixer 14, and the operating conditions of each component included in the manufacturing apparatus 10, such as the mixer 14.

[0028] In one example, the production facility S1 controls (inspects, etc.) the quality of the ready-mixed concrete at the time of shipment so that the required quality at the time of unloading (receiving) of the ready-mixed concrete set for each use location S2 is met. In order to control the quality of the ready-mixed concrete at the time of shipment, a target quality of the ready-mixed concrete at the time of shipment may be set based on the required quality at the time of unloading of the ready-mixed concrete. The quality of ready-mixed concrete includes fresh properties. Specific examples of fresh properties include slump, slump flow, the ratio of slump flow to slump, and air content.

[0029] The production control device 50 is a device for controlling the production (production) of ready-mixed concrete in the production facility S1. The production control device 50 is installed in the production facility S1. A part of the control device that controls the production device 10 may function as the production control device 50. The production control device 50 is configured by one or more computers. The management of production (management of production) includes, for example, evaluating the quality of ready-mixed concrete. The management of ready-mixed concrete production may be performed in cooperation between the production control device 50 and an operator such as a worker. Details of the functions of the production control device 50 will be described later.

[0030] FIG. 2(a) schematically shows the details of the agitator vehicle 20, and FIG. 2(b) schematically shows the connection relationship of the devices mounted on the agitator vehicle 20. In the manufacturing system 1, the agitator vehicle 20 is also provided with a device for managing the production of ready-mixed concrete. The manufacturing system 1 includes, for example, a sensor 40 and a transportation management device 30. The sensor 40 and the transportation management device 30 may be connected so as to be able to communicate with each other via wireless communication.

[0031] The sensor 40 is installed inside the drum 22. Installed inside the drum 22 means that at least a portion of the sensor 40 is located inside the drum 22. The sensor 40 is a sensor that can measure a value indicating the degree of strain when the sensor 40 passes through the ready-mixed concrete as the drum 22 rotates. Hereinafter, the value indicating the degree of strain will be referred to as a "strain index value." The sensor 40 includes a strain gauge and measures, for example, the strain itself as the strain index value. The sensor 40 may measure pressure as the strain index value instead of the strain itself (it may be a pressure sensor with a built-in strain gauge).

[0032] The sensor 40 may have a detection unit 42 and a processing unit 44. The detection unit 42 is a part that performs sensing. The detection unit 42 is formed in a rod shape. The detection unit 42 is installed so as to extend from the inner surface of the peripheral wall of the drum 22 toward the center of rotation of the drum 22. In the detection unit 42, a strain gauge may be installed on the surface of a rod-shaped base member, or a strain gauge may be installed inside the rod-shaped base member. The processing unit 44 is a part that receives the signal detected by the detection unit 42 and is configured, for example, by a computer. The processing unit 44 has the function of transferring the detected signal to the transportation management device 30.

[0033] The transportation management device 30 is a device for managing the state of ready-mixed concrete during and after transportation. The transportation management device 30 is composed of one or more computers. The transportation management device 30 is installed on the agitator vehicle 20. That is, the transportation management device 30 moves along with the agitator vehicle 20 as it moves. The transportation management device 30 may be connectable to an external communication network via wireless communication. Managing the state of ready-mixed concrete during and after transportation includes, for example, evaluating the quality of the ready-mixed concrete at least either during or after transportation. Ready-mixed concrete after transportation refers to the ready-mixed concrete when it is unloaded after transportation by the agitator vehicle 20, and can also be referred to as the ready-mixed concrete after mixing by the drum 22. Details of the functions of the transportation management device 30 will be described later.

[0034] In the manufacturing system 1, a quality prediction system 100 is configured by a material handling management device 30, a sensor 40, and a production management device 50. That is, the manufacturing system 1 is equipped with the quality prediction system 100, which includes the material handling management device 30, the sensor 40, and the production management device 50. The material handling management device 30 and the production management device 50 are connected to each other so as to be able to communicate with each other via an external communication network.

[0035] The quality prediction system 100 is a system that predicts the fresh properties of ready-mixed concrete while it is being mixed by the drum 22 of the agitator vehicle 20 or after the mixing. The quality prediction system 100 may predict one or more qualities of slump, slump flow, and air content as the fresh properties. The quality prediction system 100 may predict two or more qualities of slump, slump flow, and air content as the fresh properties of ready-mixed concrete during or after mixing. The quality prediction system 100 may calculate the ratio of slump flow to slump as the fresh properties of ready-mixed concrete during or after mixing. Workability, consistency, etc. can be evaluated based on the ratio of slump flow to slump.

[0036] The quality prediction system 100 may predict index values ​​other than slump, slump flow, and air content as fresh properties of ready-mixed concrete. Examples of indexes of fresh properties other than slump, slump flow, and air content include the 500 mm flow time, flow stop time, presence or absence of material separation, temperature, bleeding amount, bleeding rate, setting time, unit water content, plastic viscosity, yield value, funnel flow time, compactibility, deformability, packability, and void passability.

[0037] 3 shows the functional configurations (referred to as "functional blocks" in this disclosure) of the material handling management device 30 and the production management device 50 included in the quality prediction system 100. A monitor 50a may be connected to the production management device 50. The material handling management device 30 has, as functional blocks, for example, a measurement information acquisition unit 32 and a data transfer unit 34. The processes executed by the measurement information acquisition unit 32 and the data transfer unit 34 correspond to the processes executed by the material handling management device 30.

[0038] The measurement information acquiring unit 32 repeatedly acquires strain index values ​​from the sensor 40. The measurement information acquiring unit 32 may repeatedly acquire strain index values ​​from the sensor 40 at a predetermined measurement period. The measurement period may be set arbitrarily, and may be 0.5 to 3 seconds (for example, 1 second). Each measurement value obtained by the measurement information acquiring unit 32 may be linked to the time of measurement, or may be linked to information indicating the rotational position of the drum 22 (for example, the rotation angle from a reference position). Information from a drive unit that drives the drum 22 may be input to the transportation management device 30.

[0039] The data transfer unit 34 transfers the strain index value obtained by the measurement information acquisition unit 32 to another device via an external communication network. The data transfer unit 34 may transfer the strain index value together with information associated with the strain index value (e.g., the time of measurement or the rotational position of the drum 22). The data transfer unit 34 may repeatedly transfer data on the strain index value obtained within the measurement period, either at the same period as the measurement period or at a period longer than the measurement period. The data transfer unit 34 may transfer data on the strain index value each time the number of rotations of the drum 22 reaches a set number. The data from the data transfer unit 34 is transferred to the production management device 50, for example, via an external communication network.

[0040] In addition to the strain index value data, the data transfer unit 34 may transfer additional information to the transportation management device 30. Examples of the additional information include information indicating the position of the agitator vehicle 20 (longitude and latitude coordinate information, distance information between the production facility S1 or the use location S2 and the agitator vehicle 20), the remaining travel time to the use location S2, meteorological information (temperature, humidity, weather), and vehicle information (manufacturer, product name, maximum loading capacity, etc.).

[0041] The production management device 50 includes, as functional blocks, a data accumulation unit 52, a relational equation construction unit 62, a relational equation storage unit 64, an integration calculation unit 54, a quality prediction unit 56, a prediction value processing unit 58, and a prediction information recording unit 60. The processes executed by the data accumulation unit 52, the integration calculation unit 54, the quality prediction unit 56, the prediction value processing unit 58, the prediction information recording unit 60, the relational equation construction unit 62, and the relational equation storage unit 64 correspond to the processes executed by the production management device 50.

[0042] The data storage unit 52 stores data on the strain index values ​​transferred from the transportation management device 30. The data storage unit 52 may store the strain index values ​​and information linked to the strain index values. By storing the measurement time or the rotational position of the drum 22 together with the strain index values ​​as information linked to the strain index values, it is possible for the production management device 50 to generate (reproduce) time-series data on the strain index values.

[0043] FIG. 4 illustrates time-series data of strain index values. The time-series data of strain index values ​​represents changes in the strain index value over time. In the graph illustrated in FIG. 4, the horizontal axis represents elapsed time (seconds), and the vertical axis represents strain (με), which is a type of strain index value. While the drum 22 continues to rotate, a state in which the fresh concrete in the drum 22 contacts the sensor 40 (detection unit 42) and a state in which the fresh concrete in the drum 22 does not contact the sensor 40 (detection unit 42) are alternately repeated. Therefore, in the time-series data of the strain index value, the strain index value fluctuates periodically, with peaks and valleys alternately repeated. The strain index value may be a value obtained by correcting the value detected by the sensor 40. For example, the value of the valley (when the sensor 40 is not in contact with the fresh concrete) is corrected so that it approaches zero. Note that even if the strain index value is corrected, the corrected value is still an index value indicating the degree of strain.

[0044] In the graph shown in FIG. 4, "T" represents the period of one rotation of the drum 22. The period of one rotation (one revolution) can also be called a "period." When the drum 22 is rotating at a constant speed, the period T corresponding to one rotation is constant. The period of one rotation of the drum 22 is determined by the rotation speed of the drum 22, and is, for example, 3 to 120 seconds, 5 to 100 seconds, or 10 to 50 seconds.

[0045] Here, an overview of the method for predicting fresh properties will be described. As a result of verification by the present inventors, it was found that there is a strong correlation between the value obtained by accumulating strain index values ​​in a section where the drum 22 has made N revolutions (N is a number equal to or greater than 2) and the fresh properties of ready-mixed concrete. Hereinafter, the value obtained by accumulating strain index values ​​will be referred to as "cumulative strain." Figure 4 illustrates an example of a section where the drum 22 has made N revolutions (a section where N is 3). The quality prediction system 100 predicts fresh properties using a relational expression that shows the relationship between the cumulative strain in a section where the drum 22 has made N revolutions and the fresh properties of ready-mixed concrete during or after mixing.

[0046] Returning to Figure 3, the relational equation constructing unit 62 constructs a relational equation that shows the relationship between the accumulated strain in the section where the drum 22 has made N revolutions and the fresh properties of the ready-mixed concrete. Hereinafter, unless otherwise specified, "accumulated strain" means the accumulated strain in the section where the drum 22 has made N revolutions, and the relational equation that shows the relationship between the accumulated strain and the fresh properties of the ready-mixed concrete will be referred to as "relational equation RE."

[0047] The relational equation RE is a regression equation that outputs a predicted value of the fresh property (e.g., slump) in response to an input of the accumulated strain in the section where the drum 22 has made N revolutions. The relational equation RE is, for example, a linear function. In this case, when "x" is the accumulated strain, "y" is the fresh property, and "a" and "b" are constants, the relational equation RE is expressed as y=ax+b. The relational equation constructing unit 62 may construct the relational equation RE by the least squares method based on multiple data sets consisting of multiple combinations of the accumulated strain and the fresh property. The relational equation RE may be a higher-order function (higher-order polynomial) of second or higher order instead of a linear function.

[0048] The relational equation constructing unit 62 may construct the relational equation RE based on instructions from an operator or the like via an input device connected to the production management apparatus 50. When the cumulative strain and the correct value of the fresh property associated with the cumulative strain are considered as one data set, multiple data sets may be input to the production management apparatus 50 by an operator or the like. The correct values ​​of the fresh property differ from each other in at least some of the multiple data sets. Note that the correct value of the fresh property may include not only the actual measurement value itself but also an interpolated value (corrected value) obtained from multiple actual measurement values.

[0049] The correct value of the fresh property may be a value indicating the fresh property of fresh concrete at the start of the interval for calculating the cumulative strain, or may be a value indicating the fresh property of fresh concrete at the end of the interval for calculating the cumulative strain. Alternatively, the correct value of the fresh property may be a value indicating the fresh property of fresh concrete at any intermediate point in the interval for calculating the cumulative strain. The relational equation constructing unit 62 may construct the relational equation RE for each type of fresh property. The relational equation constructing unit 62 may construct the relational equation RE for each mix proportion, which is one type of production condition of ready-mixed concrete.

[0050] The relational equation storage unit 64 stores (holds) the relational equation RE constructed by the relational equation construction unit 62. The relational equation storage unit 64 may store the relational equation RE for each type of fresh property and / or for each blend. Note that the production management device 50 may not have the relational equation construction unit 62, and the relational equation RE constructed outside the production management device 50 may be input to the production management device 50, and the relational equation RE may then be stored in the relational equation storage unit 64. The stage of preparing the relational equation RE can be referred to as the "preparation phase." The stage of predicting the fresh property using the relational equation RE after the preparation phase can be referred to as the "evaluation phase."

[0051] In the evaluation phase, the integration calculation unit 54 calculates the cumulative strain of the evaluation object in the section where the drum 22 has made N revolutions. The cumulative strain of the evaluation object means the cumulative strain whose fresh properties are unknown. N is set to the same value during the evaluation phase and the preparation phase. N may be any number equal to or greater than 2, and may be a finite decimal (non-integer). N may be a number equal to or greater than 3. N may be a number equal to or less than 5000, 2000, 1000, 500, 100, 50, 20, or 10. N may be set to an integer equal to or greater than 2, or an integer equal to or greater than 3.

[0052] In the evaluation phase, the start point of the interval over which the strain index values ​​are accumulated may be determined arbitrarily. The accumulation calculation unit 54 may calculate the cumulative strain by accumulating (summing up) the interval over which the strain index values ​​are accumulated. The accumulation calculation unit 54 may calculate the cumulative strain by integrating the interval over which the strain index values ​​are accumulated.

[0053] In the evaluation phase, the quality prediction unit 56 predicts the fresh properties of the ready-mixed concrete being mixed in the drum 22 by inputting the cumulative strain of the evaluation target calculated by the integration calculation unit 54 into the relational formula RE. The quality prediction unit 56 acquires the calculation result of the relational formula RE when the cumulative strain of the evaluation target is input into the relational formula RE as a predicted value. The quality prediction unit 56 may acquire a predicted value of the fresh property for each type of fresh property using the corresponding relational formula RE. Figure 5 schematically shows the calculation process in the evaluation phase, from time-series data of strain index values ​​to obtaining a predicted value of the fresh property using the relational formula RE.

[0054] The predicted value processing unit 58 executes at least one of displaying the predicted value acquired by the quality prediction unit 56 on the monitor 50a and recording the predicted value in the prediction information recording unit 60. The predicted value processing unit 58 may display the predicted value acquired by the quality prediction unit 56 on the monitor 50a and record the predicted value in the prediction information recording unit 60. The predicted value processing unit 58 may record the predicted value of the fresh property in an external device different from the production management device 50.

[0055] 6 shows a schematic diagram of the hardware configuration of the quality prediction system 100. The material handling management device 30 included in the quality prediction system 100 has a processor 131, a memory 132, a storage 133, an input / output port 134, and a communication port 135. The storage 133 is composed of one or more non-volatile memory devices such as flash memory or a hard disk. The storage 133 stores at least programs for configuring each functional block of the material handling management device 30. The memory 132 is composed of one or more volatile memory devices such as a random access memory. The memory 132 temporarily stores programs loaded from the storage 133.

[0056] The processor 131 is composed of one or more arithmetic devices such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The processor 131 configures each functional block of the transportation management device 30 by executing a program loaded into the memory 132. The calculation results by the processor 131 are temporarily stored in the memory 132. The input / output port 134 inputs and outputs electrical signals to and from the sensor 40, etc., in accordance with instructions from the processor 131. The communication port 135 communicates with the production management device 50 via a communication network NW (network line) in accordance with instructions from the processor 131.

[0057] The production management device 50 included in the quality prediction system 100 has a processor 151, a memory 152, a storage 153, an input / output port 154, and a communication port 155. The storage 153 is configured with one or more non-volatile memory devices such as a flash memory or a hard disk. The storage 153 stores at least programs for configuring each functional block of the production management device 50. The memory 152 is configured with one or more volatile memory devices such as a random access memory. The memory 152 temporarily stores programs loaded from the storage 153.

[0058] The processor 151 is composed of one or more arithmetic devices such as a CPU or a GPU. The processor 151 configures each functional block of the production management device 50 by executing a program loaded into the memory 152. The calculation results by the processor 151 are temporarily stored in the memory 152. The input / output port 154 inputs and outputs electrical signals to and from the monitor 50a, etc., in accordance with instructions from the processor 151. The communication port 155 communicates with the transportation management device 30 via the communication network NW in accordance with instructions from the processor 151.

[0059] In each of the transportation management device 30 and the production management device 50, the functional blocks are not limited to those realized by executing a program, but may also be realized by dedicated electrical circuits (e.g., logic circuits) or integrated circuits (ASIC: Application Specific Integrated Circuit) that integrate these.

[0060] [Ready-mix concrete manufacturing method] Next, as an example of a method for manufacturing ready-mixed concrete, a manufacturing method executed in the manufacturing system 1 will be described. This manufacturing method includes a production process, a transportation process, a measurement process, an integration process, and a prediction process. In addition to these processes, the manufacturing method may also include a measurement value output process and a result acquisition process.

[0061] The production process is a process in which concrete materials are mixed in a mixer 14 in the production facility S1 to obtain ready-mix concrete. The production process may include a transporting process, a measuring process, a charging process, a mixing process, a discharging process, a loading process, and an inspection process. In the transporting process, various concrete materials are transported to storage bottles 11 by a transport device such as a belt conveyor, and the various materials are individually supplied to the storage bottles 11.

[0062] In the measuring process, various materials are individually supplied from storage bottles 11 to measuring bottles 12, and the various materials are measured in measuring bottles 12. In the measuring process, when the measured amount for each material reaches a predetermined set amount, the material is discharged into collecting hopper 13. In the feeding process, after all types of materials have been collected in collecting hopper 13, the materials in collecting hopper 13 are fed (supplied) into mixer 14. In the mixing process, the concrete materials are mixed by mixer 14.

[0063] In the discharging process, after mixing of the concrete materials is completed in the mixer 14, the ready-mixed concrete is discharged from the mixer 14 into the loading hopper 15. In the loading process, the ready-mixed concrete discharged into the loading hopper 15 is loaded into the agitator vehicle 20 (inside the drum 22). In the inspection process, the quality of the ready-mixed concrete is measured to obtain an actual measured value of the quality before shipping the ready-mixed concrete. The inspection process may be performed by a worker.

[0064] The transporting process is a process in which the agitator vehicle 20 having the drum 22 transports the ready-mixed concrete to a use location S2 (a site where the ready-mixed concrete is used) while stirring the ready-mixed concrete inside the drum 22. The transporting process is performed by a worker operating the agitator vehicle 20. In the transporting process, the worker may operate the agitator vehicle 20 so that it moves on a predetermined travel route TP. The worker may operate the agitator vehicle 20 so that it rotates the drum 22 in accordance with predetermined transport conditions.

[0065] The measuring step, the measurement value output step, the integration step, the prediction step, and the result acquisition step are performed during a period overlapping at least a part of the period during which the transporting step is performed. The measuring step, the measurement value output step, the integration step, the prediction step, and the result acquisition step are performed in the evaluation phase. In other words, these steps are performed after the preparation phase, which includes the construction of the relational equation RE, is completed.

[0066] The measurement process is a process of repeatedly acquiring, from the sensor 40 installed inside the drum 22, an index value (the above-mentioned strain index value) that indicates the degree of strain when the sensor 40 passes through the ready-mixed concrete as the drum 22 rotates. The measurement process may be performed by the measurement information acquisition unit 32 of the transportation management device 30. The measurement value output process is a process of outputting information (data) that indicates the strain index value repeatedly acquired in the measurement process from the agitator vehicle 20 to an external communication network NW via wireless communication. The data of the strain index value acquired in the measurement process may be transferred to the production management device 50 via the communication network NW. The measurement value output process may be performed by the data transfer unit 34 of the transportation management device 30.

[0067] The integrating step is a step of integrating index values ​​(strain index values) in a section where the drum 22 has made N revolutions to calculate the accumulated strain as the accumulated strain of the evaluation object. In the integrating step, the accumulated strain of the evaluation object may be calculated from the corrected strain index value. In this case, the relational expression RE is also constructed to indicate the relationship between the corrected strain index value and the fresh properties. The integration calculation unit 54 of the production management device 50 may perform the integrating step. As described above, N is a number equal to or greater than 2, and N may be an integer equal to or greater than 2.

[0068] The prediction process is a process of predicting the fresh properties of the ready-mixed concrete being mixed in the drum 22 by inputting the cumulative strain of the evaluation target calculated in the integration process into the relational expression RE. As described above, the relational expression RE may be a linear function. The prediction process may be executed by the quality prediction unit 56 of the production management device 50. The result acquisition process is a process in which the production management device 50, which is a computer installed in the production facility S1, acquires the prediction results in the prediction process. When the quality prediction unit 56 executes the prediction process, the result acquisition process is also executed by the quality prediction unit 56 executing the prediction process.

[0069] The manufacturing method executed in the manufacturing system 1 includes a quality prediction method for ready-mixed concrete. This quality prediction method is a method for predicting the fresh properties of ready-mixed concrete while it is being agitated by the drum 22 of the agitator vehicle 20 or after the agitation. The quality prediction method includes a measurement process, an accumulation process, and a prediction process. In addition to these processes, the quality prediction method may include a measurement value output process and a result acquisition process. The manufacturing method executed in the manufacturing system 1 includes a method for transporting ready-mixed concrete. This transportation method is a method for transporting ready-mixed concrete to a use location S2 by an agitator vehicle 20 having a drum 22 while agitating the ready-mixed concrete inside the drum 22. The transportation method includes a measurement process, an accumulation process, and a prediction process. In addition to these processes, the transportation method may include a measurement value output process and a result acquisition process.

[0070] Next, an example of a process flow executed in a method for predicting the quality of ready-mixed concrete will be described with reference to Figs. 7 and 8. Fig. 7 illustrates an example of a process flow executed in a preparation phase. In the process flow in the preparation phase, various processes may be executed in cooperation between workers and the quality prediction system 100 (for example, the production management device 50). In the preparation phase, a "test ready-mixed concrete" obtained under the same production conditions as those in the evaluation phase may be used. Also, a "test drum" of the same model (type) as the drum 22 of the agitator vehicle 20 used in the evaluation phase may be used. In one example, the process flow in the preparation phase is executed in the production facility S1. A sensor 40 may be installed inside the test drum, and the production management device 50 may control the test drum and the sensor 40.

[0071] In the preparation phase, step S11 is executed with the test ready-mixed concrete contained in the test drum. In step S11, for example, a worker or the like actually measures the fresh properties of the test ready-mixed concrete. In one example, the worker or the like measures one or more of the slump, slump flow, and air content of the test ready-mixed concrete. The actual measured values ​​of the fresh properties measured by the worker or the like may be input into the production management device 50.

[0072] Next, step S12 is executed. In step S12, the production management device 50 starts rotating the test drum based on instructions from, for example, an operator. In other words, the test drum starts agitating the ready-mixed concrete. The rotation speed of the test drum may be set to be approximately the same as the rotation speed of the drum 22 of the agitator vehicle 20 that transports the ready-mixed concrete in the evaluation phase.

[0073] Next, step S13 is executed. In step S13, for example, a sensor 40 installed inside the test drum measures the strain. Information indicating the strain measured by the sensor 40 may be input to the production management device 50.

[0074] Next, step S14 is executed. In step S14, for example, the production management device 50 determines whether the test drum has made X rotations (X is a number equal to or greater than N) since the start of execution of step S12. "X," which represents the number of rotations, is set in advance by an operator or the like. For example, X is set so that the test drum continues to rotate for 1 to 60 minutes, 2 to 45 minutes, or 3 to 30 minutes. If it is determined that the test drum has not made X rotations (step S14: NO), step S13 is executed again. As a result, step S13 is repeated until the test drum has made X rotations.

[0075] In step S14, if it is determined that the drum has rotated X times (step S14: YES), step S15 is executed. In step S15, for example, the production management device 50 stops the test drum.

[0076] Next, step S16 is executed. In step S16, for example, the production management device 50 calculates the cumulative strain in the section from the start point to N rotations from the time-series data of strain obtained by repeating step S13. Then, the production management device 50 stores the calculated cumulative strain and the actual measured value (correct value) of the fresh property obtained by executing step S11 in association with each other. This results in a single data set including the cumulative strain and the actual measured value of the fresh property associated with the cumulative strain.

[0077] Next, step S17 is executed. In step S17, for example, the production management device 50 determines whether the set period has ended, starting from the start of the processing flow. If it is determined that the set period has not ended (step S17: NO), the series of processes in steps S11 to S16 is executed again. The set period may be set in advance by an operator or the like, and is set, for example, so that the number of data sets for constructing the relational formula RE is 3 or more, 4 or more, 5 or more, 7 or more, or 10 or more. The set period may also be set so that the number of data sets for constructing the relational formula RE is 100 or less, 50 or less, or 20 or less.

[0078] If it is determined in step S17 that the set period has ended (step S17: YES), step S18 is executed. In step S18, for example, the relational equation constructing unit 62 of the production management device 50 constructs the relational equation RE based on a plurality of data sets configured by associating the cumulative strain with the fresh property for each data set. In one example, the relational equation constructing unit 62 constructs the relational equation RE, which is a linear function, by the least squares method based on the plurality of data sets. Then, the relational equation storage unit 64 stores the relational equation RE constructed by the relational equation constructing unit 62.

[0079] Fig. 8 illustrates an example of a processing flow executed in the evaluation phase. The processing flow in the evaluation phase is executed, for example, by the quality prediction system 100. The processing flow shown in Fig. 8 is executed by the quality prediction system 100 while ready-mixed concrete is produced in the production facility S1 and is being transported by the agitator vehicle 20. While the processing flow shown in Fig. 8 is being executed, the sensor 40 installed in the drum 22 repeatedly measures a strain index value (for example, strain [με]) at a predetermined measurement interval. The measured value of the strain index value is then input to the transportation management device 30 mounted on the agitator vehicle 20.

[0080] In the evaluation phase, the quality prediction system 100 first executes step S21. In step S21, for example, the quality prediction system 100 waits until a predetermined evaluation timing arrives. The evaluation timing is the timing at which the fresh properties of ready-mixed concrete during transportation are evaluated (predicted), and is determined in advance by a worker or the like. The evaluation timing may be set so that the evaluation of the fresh properties is repeated every 1 to 60 minutes, every 2 to 45 minutes, or every 3 to 30 minutes after the agitator vehicle 20 departs from the production facility S1, for example.

[0081] Next, the quality prediction system 100 executes steps S22 and S23. In step S22, for example, the data transfer unit 34 of the material handling device 30 waits from the evaluation timing of step S21 until the drum 22 has made N rotations. In step S23, for example, the data transfer unit 34 transfers the time-series data of the strain index values ​​for N rotations to the production management device 50 via the external communication network NW. The transferred time-series data may be accumulated (stored) in the data accumulation unit 52 of the production management device 50.

[0082] Next, the quality prediction system 100 executes step S24. In step S24, for example, the integration calculation unit 54 of the production management device 50 calculates the cumulative strain of the evaluation object from the data transferred in step S23 (time-series data of the strain index values ​​for N rotations). The integration calculation unit 54 may calculate the sum of the strain index values ​​for N rotations as the cumulative strain of the evaluation object, or may calculate the integral of the strain index values ​​for N rotations as the cumulative strain of the evaluation object.

[0083] Next, the quality prediction system 100 executes step S25. In step S25, for example, the quality prediction unit 56 of the production management device 50 predicts the fresh properties (e.g., slump) of the ready-mixed concrete at the evaluation timing based on the cumulative strain of the evaluation target calculated in step S24 and the relational equation RE stored in the relational equation storage unit 64.

[0084] Next, the quality prediction system 100 executes step S26. In step S26, for example, the predicted value processing unit 58 of the production management device 50 displays the fresh properties predicted in step S25 (predicted values ​​of the fresh properties) on the monitor 50a and records them in the prediction information recording unit 60. By executing step S26, for example, a worker such as an operator in the production facility S1 can grasp the state of the ready-mixed concrete during transportation.

[0085] The quality prediction system 100 may also execute the series of processes from steps S22 to S26 at the next evaluation timing. The quality prediction system 100 may also execute the series of processes from steps S22 to S26 every time an evaluation timing occurs. A certain evaluation timing may be set to the timing when the agitator vehicle 20 arrives at the usage location S2 and unloads the ready-mixed concrete.

[0086] [Quality Prediction Program] The various functional blocks of the quality prediction system 100 are realized, for example, by a quality prediction program. The quality prediction program is a program that causes a computer to execute a measurement process, an integration process, and a prediction process. In addition to these processes, the quality prediction program may also cause a computer to execute a measurement value output process and a result acquisition process. The quality prediction program may be provided by being permanently recorded on a non-transitory recording medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory. Alternatively, the quality prediction program may be provided via a communication network as a data signal superimposed on a carrier wave.

[0087] [Variations] The process flows shown in Figures 7 and 8 are merely examples and can be modified as appropriate. In the process flows, one step and the next step may be executed in parallel, or some steps may be executed in an order different from that of the above-described example. Steps with content different from that of the above-described example may be executed instead of at least some of the steps of the process flows, or in addition to all of the steps of the process flows.

[0088] 7, step S11 (actual measurement of fresh properties) may be executed after step S15 and before step S17. In this case, in step S16, the cumulative strain may be calculated using data for N rotations starting from the end point out of the time-series data of strain index values ​​for X rotations.

[0089] 7, in addition to step S11, actual measurement of the fresh properties may be performed again after step S15 and before step S17. In this case, the correct value of the fresh properties may be obtained based on the actual measurement values ​​before and after the period in which the test drum is rotated X times. Furthermore, when returning to step S11 after the judgment in step S17, step S11 may be omitted.

[0090] 8, in the evaluation phase, the transportation management device 30 may transfer data related to the measured strain index values ​​to the production management device 50 at a measurement cycle or at a cycle longer than the measurement cycle, regardless of the evaluation timing. In this case, the production management device 50 may calculate the cumulative strain and predict the fresh properties each time the evaluation timing arrives, using time-series data of the strain index values ​​for the N rotations immediately prior to the evaluation timing.

[0091] 3, a computer (e.g., a server, including a cloud server) separate from the production management device 50 and installed outside the production facility S1 may include the data accumulation unit 52, the integration calculation unit 54, the quality prediction unit 56, and the relational equation storage unit 64. The server may be communicably connected to the material handling management device 30 and the production management device 50 via a communication network NW. In this case, the server executes a prediction step, which is a step of predicting freshness properties using the relational equation RE, and the production management device 50 (e.g., a prediction value processing unit 58) executes a prediction value acquisition step, which is a step of acquiring the prediction result in the prediction step, by obtaining the prediction result from the server.

[0092] The server provided outside the production facility S1 may have the relational equation storage unit 64. In this case, the quality prediction unit 56 included in the production management device 50 may transmit the cumulative strain calculated by the integration calculation unit 54 to the server, and acquire the predicted value of the fresh property calculated by the server. In this configuration, the quality prediction unit 56 acquires the predicted value of the fresh property from the server, thereby executing the predicted value acquisition step.

[0093] 3, the material handling management device 30 installed on the agitator vehicle 20 may have a data accumulation unit 52, an integration calculation unit 54, a quality prediction unit 56, and a relational equation storage unit 64. In this case, the material handling management device 30 executes the prediction process, and the production management device 50 (e.g., a prediction value processing unit 58) executes the prediction value acquisition process by obtaining the prediction result from the material handling management device 30.

[0094] Unlike the functional configuration shown in Fig. 3, the transportation management device 30 may have an integration calculation unit 54, and the data transfer unit 34 may transfer the calculation results of the accumulated strain for N rotations to the production management device 50. The data transfer unit 34 may transfer the calculation results of the accumulated strain for N rotations to the production management device 50 at each evaluation timing for evaluating the fresh properties of ready-mixed concrete during transportation.

[0095] The quality prediction system may be configured using only the devices and components mounted on the agitator vehicle 20. Fig. 9 illustrates a quality prediction system 100A that is different from the quality prediction system 100. The quality prediction system 100A differs from the quality prediction system 100 in that it does not have the production management device 50, and has a material handling management device 30A instead of the material handling management device 30.

[0096] The material handling management device 30A differs from the material handling management device 30 in that it does not have a data transfer unit 34, but instead has a data accumulation unit 52, an integration calculation unit 54, a quality prediction unit 56, a predicted value processing unit 58, a predicted information recording unit 60, a relational equation construction unit 62, and a relational equation storage unit 64. A monitor 31 is connected to the material handling management device 30A. The monitor 31 is installed, for example, in a position where it can be seen by the driver of the agitator vehicle 20.

[0097] In the quality prediction method executed using the quality prediction system 100A, a material handling and management device 30A, which is a computer installed in the agitator vehicle 20, executes a prediction step. A predicted value processing step is also executed, in which the material handling and management device 30A performs at least one of displaying the prediction results of the prediction step on a monitor 31 and recording the prediction results. The various functional blocks of the quality prediction system 100A are realized, for example, by a quality prediction program. The quality prediction program may cause the computer to execute a predicted value processing step in addition to the measurement step, integration step, and prediction step.

[0098] Even when the quality prediction system 100A is used, a processing flow similar to the processing flow shown in Fig. 7 may be executed in the preparation phase. Also, a processing flow similar to the processing flow shown in Fig. 8 may be executed in the evaluation phase. In the processing flow similar to the processing flow shown in Fig. 8, step S23 is omitted.

[0099] The number of computers that implement the various functional blocks illustrated in Figure 3 or 9, the locations where the computers are installed, and which computers have which functions may be set in any manner. In one of the various examples described above, at least some of the matters described in other examples may be combined to the extent that they are not contradictory.

[0100] [Verification example] Next, we will demonstrate the usefulness of calculating cumulative strain from time-series data of strain index values ​​for N rotations and predicting fresh properties from that cumulative strain using the relational expression RE. In this verification, we used a tilting mixer ("Portable Tilting Mixer, Model No. KC-216-B" manufactured by Kansai Machinery Manufacturing Co., Ltd.) that imitates the drum 22 of the agitator vehicle 20.

[0101] FIG. 10 shows a schematic diagram of the tilting mixer 222 used in the verification. The tilting mixer 222 includes a drum body 222a and a support portion 222b. The drum body 222a is capable of containing ready-mixed concrete and has a circular opening at one end in its extension direction. The support portion 222b supports the drum body 222a so that it can rotate around the rotation axis Ax and the tilt angle of the drum body 222a (rotation axis Ax) can be changed. A sensor 240 corresponding to the sensor 40 was installed inside the drum body 222a. For the sensor 240, a detection portion corresponding to the detection portion 42 was formed by attaching a strain gauge ("General-purpose strain gauge, model number: FLAB-5-11-3LJCT-F" manufactured by Tokyo Measuring Instruments Laboratory Co., Ltd.) to the surface of a rod-shaped base member.

[0102] The rotation speed of the drum body 222a was set so that it would complete one rotation (one revolution) in approximately 70 seconds. While the drum body 222a continued to rotate, the strain (με), which was a measurement value from the sensor 240, was recorded at 1-second intervals. The time series data of the measured strain (με) is shown in FIG. 11. The rotation of the drum body 222a was stopped at approximately 30-minute intervals, and the slump of the ready-mix concrete for verification was measured. The graph in FIG. 11 also shows the measured slump (cm). At time "t1," after 120 minutes had elapsed, a high-range water-reducing agent was added for verification purposes. Note that the data from 30 minutes before the elapsed time was measured for a purpose other than verifying the invention of the present disclosure.

[0103] Although it is presumed to be the influence of disturbances, a certain amount of strain (με) was detected even when fresh concrete was not in contact with the sensor 240. Therefore, the time between the time when the actual slump measurement value was obtained and the time when the next actual slump measurement value was obtained was treated as one block, and correction was performed for each block so that the time when fresh concrete was not in contact with the sensor 240 approached zero. Figure 12 shows the time series data of strain (με) after correction.

[0104] Observing the entire graph shown in Figure 12 (or Figure 11), it can be seen that as the slump (cm) decreases, the strain (με) tends to increase, and as the slump (cm) increases with the addition of a high-performance AE water-reducing agent, the strain (με) decreases accordingly.

[0105] In FIG. 12, "T1," "T2," "T3," and "T4" represent periods of approximately five minutes immediately after the actual slump measurement. Period T1 is the period approximately five minutes immediately after the actual slump measurement of 18.5 cm is obtained, and period T2 is the period approximately five minutes immediately after the actual slump measurement of 13.0 cm is obtained. Period T3 is the period approximately five minutes immediately after the actual slump measurement of 9.0 cm is obtained, and period T4 is the period approximately five minutes immediately after the actual slump measurement of 6.0 cm is obtained. During these approximately five minutes, the drum body 222a rotates five times, and strain time-series data for five rotations (five cycles) can be extracted.

[0106] Figure 13(a) shows time-series data of strain (με) for periods T1, T2, T3, and T4. Focusing on each period reveals that there is variation in the peak position and magnitude over the five rotations. Focusing on the first rotation period (the first approximately 70 seconds), the peak in period T3 (measured slump: 9.0 cm) is larger than the peak in period T4 (measured slump: 6.0 cm).

[0107] Figure 13(b) shows the time evolution of the calculated cumulative strain (με) for periods T1, T2, T3, and T4. Note that the "cumulative strain (με)" described in the verification example is not limited to the integrated value for the N rotations. Focusing on the first rotation period (the first approximately 70 seconds), the cumulative strain for period T3 (measured slump: 9.0 cm) is larger than the cumulative strain for period T4 (measured slump: 6.0 cm). On the other hand, after two rotations (approximately 140 seconds), the cumulative strain (με) is in the order of period T4, period T3, period T2, and period T1. In other words, after two rotations (approximately 140 seconds), the larger the slump, the smaller the cumulative strain (με).

[0108] To further verify, a linear function showing the relationship between cumulative strain (με) and slump (cm) was constructed by changing the number of rotations, which represents the period for accumulating strain (με), and then the coefficient of determination R 2 was calculated as an evaluation index. In addition to the data for periods T1 to T4, data for periods T5 and T6 shown in Fig. 12 was also used. Periods T5 and T6 were set in the same manner as periods T1 to T4.

[0109] FIG. 14(a) shows the relational expression rE1 constructed by integrating the strain (με) over a period of one rotation. Since periods T1 to T6 include a period of five rotations (five cycles), the relational expression rE1 was constructed by integrating the strain (με) over each of the first, second, third, fourth, and fifth rotations. FIG. 14(b) shows the relational expression rE2 constructed by integrating the strain (με) over a period of two consecutive rotations. The relational expression rE2 was constructed by integrating the strain (με) over each of the periods between the first and second rotations, between the second and third rotations, between the third and fourth rotations, and between the fourth and fifth rotations.

[0110] Figure 15(a) shows the relational expression rE3 constructed by integrating the strain (με) over a period of three consecutive rotations. The relational expression rE3 was constructed by integrating the strain (με) over each of the periods from the first to third rotation, the second to fourth rotation, and the third to fifth rotation. Figure 15(b) shows the relational expression rE4 constructed by integrating the strain (με) over each of the periods from the first to fourth rotation, and the second to fifth rotation. The relational expression rE4 was constructed by integrating the strain (με) over each of the periods from the first to fourth rotation, and the second to fifth rotation.

[0111] Although the graph is omitted, the strain (με) was integrated over a period of five consecutive rotations (1st to 5th rotations) and the relational expression rE5 was constructed. Figure 16 shows the coefficient of determination R for each changed number of rotations (number of cycles). 2 The evaluation results are shown on the graph. For example, when the horizontal axis indicates the number of rotations (cycles) as 1, the plot is 2The plot when the number of rotations (periods) is 2 is the coefficient of determination R obtained from the relation rE2. 2 is.

[0112] From the results shown in Figure 16, the coefficient of determination R 2 It can be seen that the coefficient of determination R 2 In other words, it can be seen that a relational expression with higher prediction accuracy is obtained.

[0113] Summary of this disclosure The above-described method for predicting the quality of ready-mixed concrete is a method for predicting the fresh properties of ready-mixed concrete during or after mixing by the drum (22) of the agitator wheel (20). This quality prediction method includes a measurement step of repeatedly obtaining, from a sensor (40) installed inside the drum (22), an index value (strain index value) indicating the degree of strain when the sensor (40) passes through the fresh concrete as the drum (22) rotates, an integration step of calculating, as an accumulated strain to be evaluated, the accumulated strain obtained by integrating the index value (strain index value) over a period of N rotations of the drum (22) (N is a number equal to or greater than 2), and a prediction step of predicting the fresh properties of the ready-mixed concrete being mixed by the drum (22) by inputting the accumulated strain to be evaluated calculated in the integration step into a relational expression (RE) previously constructed to indicate the relationship between the accumulated strain and the fresh properties of the ready-mixed concrete. As mentioned above, it was found that when focusing on a section covering only one rotation, the strain index value and fresh properties may show a tendency different from the expected relationship. In this method, fresh properties are predicted from the cumulative strain obtained by integrating the strain index value over a section covering at least two rotations. As a result, fresh properties can be predicted with high accuracy. Therefore, this quality prediction method is useful for improving prediction accuracy in the quality control of transported ready-mixed concrete.

[0114] In the method for predicting the quality of ready-mixed concrete described above, N may be an integer of 2 or more. In this case, it is possible to simplify the construction of the relational expression in the preparation phase and the acquisition of the cumulative strain of the evaluation target in the evaluation phase.

[0115] In the method for predicting the quality of ready-mixed concrete described above, the relational expression (RE) used in the prediction step may be a linear function. As mentioned in the verification example above, by using the cumulative strain in the section rotated at least twice, the coefficient of determination R of the linear function relation (RE) can be calculated. 2 can be made larger.

[0116] The quality prediction method for ready-mixed concrete described above may further include a measurement value output process in which the agitator vehicle (20) outputs information indicating the index value (strain index value) repeatedly acquired in the measurement process to an external communication network (NW) via wireless communication, and a result acquisition process in which a computer (50) installed in a facility (S1) that produces ready-mixed concrete transported by the agitator vehicle (20) acquires the prediction result in the prediction process. In this case, the quality of the ready-mixed concrete can be grasped during or after transportation at the place (S1) where the ready-mixed concrete is produced.

[0117] The above-described method for predicting the quality of ready-mixed concrete may further include a predicted value processing step. A computer (30A) installed in the agitator vehicle (20) may execute the prediction step. In the predicted value processing step, the computer (30A) installed in the agitator vehicle (20) may execute at least one of displaying the prediction result in the prediction step on a monitor (31) and recording the prediction result. In this case, since the prediction result can be obtained in the agitator wheel (20), the configuration of the device for making the prediction can be simplified.

[0118] The quality prediction program described above is a program for causing a computer to execute the above-described method for predicting the quality of ready-mixed concrete. This quality prediction program, like the above quality prediction method, is useful for improving prediction accuracy in quality control of transported ready-mixed concrete.

[0119] The above-described method for transporting ready-mixed concrete is a method for transporting the ready-mixed concrete to a place (S2) where the ready-mixed concrete is used while being agitated in the drum (22) by an agitator vehicle (20) having a drum (22). This method includes a measurement step of repeatedly obtaining, from a sensor (40) installed inside the drum (22), an index value (strain index value) indicating the degree of strain when the sensor (40) passes over the ready-mixed concrete as the drum (22) rotates, an integration step of calculating, as an accumulated strain to be evaluated, the accumulated strain obtained by integrating the index value (strain index value) over a section where the drum (22) has made N rotations (N is a number equal to or greater than 2), and a prediction step of predicting the fresh properties of the ready-mixed concrete being agitated in the drum (22) by inputting the accumulated strain to be evaluated calculated in the integration step into a relational expression (RE) previously constructed to indicate the relationship between the accumulated strain and the fresh properties of the ready-mixed concrete. This transportation method, like the above-described quality prediction method, is useful for improving prediction accuracy in quality control of transported ready-mixed concrete.

[0120] The method for producing ready-mixed concrete described above includes a production step in which concrete materials are mixed in a mixer (14) in a production facility (S1) to obtain ready-mixed concrete, a transport step in which the ready-mixed concrete is transported to a place (S2) where the ready-mixed concrete is to be used while being agitated in the drum (22) by an agitator vehicle (20) having a drum (22), and a step in which an index value (strain index) indicating the degree of strain when the sensor (40) installed inside the drum (22) passes through the ready-mixed concrete as the drum (22) rotates is detected from the sensor (40). The method includes a measuring step of repeatedly obtaining index values ​​(strain index values) for N revolutions of the drum (22) (N is a number equal to or greater than 2), an integrating step of calculating the cumulative strain obtained by integrating the index values ​​(strain index values) for a section where the drum (22) has made N revolutions (N is a number equal to or greater than 2) as the cumulative strain of the object to be evaluated, and a prediction step of predicting the fresh properties of the ready-mixed concrete being stirred in the drum (22) by inputting the cumulative strain of the object to be evaluated calculated in the integrating step into a relational expression (RE) that is preliminarily constructed so as to show the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete. This manufacturing method, like the above-mentioned quality prediction method, is useful for improving prediction accuracy in quality control of transported ready-mixed concrete.

[0121] The quality prediction system (100, 100A) for ready-mixed concrete described above is a system for predicting the fresh properties of ready-mixed concrete while it is being agitated by the drum (22) of the agitator vehicle (20) or after the agitation. This quality prediction system (100, 100A) includes a sensor (40) installed inside the drum (22) and capable of measuring an index value (strain index value) indicating the degree of strain when the drum (22) passes through fresh concrete as it rotates, a measurement information acquisition unit (32) that repeatedly acquires the index value (strain index value) from the sensor (40), an integration calculation unit (54) that calculates, as the cumulative strain of the object to be evaluated, the cumulative strain obtained by integrating the index values ​​(strain index values) over a section in which the drum (22) has made N rotations (N is a number equal to or greater than 2), and a quality prediction unit (56) that predicts the fresh properties of the fresh concrete being stirred in the drum (22) by inputting the cumulative strain of the object to be evaluated calculated by the integration calculation unit (54) into a relational expression (RE) that has been constructed in advance to indicate the relationship between the cumulative strain and the fresh properties of the fresh concrete. This quality prediction system (100, 100A), like the above quality prediction method, is useful for improving prediction accuracy in quality control of transported ready-mixed concrete. [Explanation of symbols]

[0122] 1...ready-mixed concrete manufacturing system, 10...manufacturing equipment, 20...agitator vehicle, 100, 100A...quality prediction system, 30, 30A...transportation management device, 32...measurement information acquisition unit, 34...data transfer unit, 40...sensor, 50...production management device, 52...data storage unit, 54...integration calculation unit, 56...quality prediction unit, 58...prediction value processing unit, 60...prediction information recording unit, 62...relational equation construction unit, 64...relational equation memory unit, RE...relational equation.

Claims

1. A quality prediction method for predicting the fresh properties of ready-mixed concrete while it is being agitated by the drum of an agitator vehicle or after the agitation, a measuring step of repeatedly acquiring, from a sensor installed inside the drum, an index value indicating the degree of strain when the sensor passes through the fresh concrete as the drum rotates; an integrating step of integrating the index values ​​in a section where the drum has rotated N times (N is a number equal to or greater than 2) to calculate a cumulative strain as a cumulative strain to be evaluated; a prediction step of predicting the fresh properties of the ready-mixed concrete being stirred in the drum by inputting the cumulative strain of the evaluation target calculated in the integration step into a relational equation previously constructed to indicate the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete; A method for predicting the quality of ready-mix concrete, including:

2. N is an integer equal to or greater than 2; The method for predicting the quality of ready-mixed concrete according to claim 1.

3. The relational expression used in the prediction step is a linear function. The method for predicting the quality of ready-mixed concrete according to claim 1.

4. a measurement value output step of outputting information indicating the index value repeatedly acquired in the measurement step from the agitator vehicle to an external communication network via wireless communication; a result acquisition process in which a computer installed in a facility that produces ready-mixed concrete transported by the agitator vehicle acquires a prediction result in the prediction process; The method for predicting quality of ready-mixed concrete according to any one of claims 1 to 3, further comprising:

5. Further comprising a predicted value processing step, a computer installed in the agitator vehicle executes the prediction step; In the predicted value processing step, a computer installed in the agitator car executes at least one of displaying the predicted result in the prediction step on a monitor and recording the predicted result. The method for predicting the quality of ready-mixed concrete according to any one of claims 1 to 3.

6. A quality prediction program for causing a computer to execute the ready-mixed concrete quality prediction method according to any one of claims 1 to 3.

7. A transportation method in which ready-mixed concrete is transported to a place where it is to be used by an agitator vehicle having a drum while stirring the ready-mixed concrete in the drum, a measuring step of repeatedly acquiring, from a sensor installed inside the drum, an index value indicating the degree of strain when the sensor passes through the fresh concrete as the drum rotates; an integrating step of integrating the index values ​​in a section where the drum has rotated N times (N is a number equal to or greater than 2) to calculate a cumulative strain as a cumulative strain to be evaluated; a prediction step of predicting the fresh properties of the ready-mixed concrete being stirred in the drum by inputting the cumulative strain of the evaluation target calculated in the integration step into a relational equation previously constructed to indicate the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete; A method for transporting ready-mixed concrete, including:

8. A production process in which concrete materials are mixed in a mixer to obtain ready-mix concrete in the production facility; A transporting process in which the ready-mixed concrete is transported to a place where it is to be used by an agitator vehicle having a drum while stirring the ready-mixed concrete in the drum; a measuring step of repeatedly acquiring, from a sensor installed inside the drum, an index value indicating the degree of strain when the sensor passes through the fresh concrete as the drum rotates; an integrating step of integrating the index values ​​in a section where the drum has rotated N times (N is a number equal to or greater than 2) to calculate a cumulative strain as a cumulative strain to be evaluated; a prediction step of predicting the fresh properties of the ready-mixed concrete being stirred in the drum by inputting the cumulative strain of the evaluation target calculated in the integration step into a relational equation previously constructed to indicate the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete; A method for producing ready-mixed concrete, comprising:

9. A quality prediction system that predicts the fresh properties of ready-mixed concrete while it is being mixed in the drum of an agitator vehicle or after the mixing, a sensor installed inside the drum and capable of measuring an index value indicating the degree of strain when the drum passes through the ready-mixed concrete as the drum rotates; a measurement information acquisition unit that repeatedly acquires the index value from the sensor; an integration calculation unit that calculates, as the cumulative strain of the evaluation target, a cumulative strain obtained by integrating the index values ​​in a section in which the drum has made N rotations (N is a number equal to or greater than 2); a quality prediction unit that predicts the fresh properties of the ready-mixed concrete being stirred in the drum by inputting the cumulative strain of the evaluation target calculated by the integration calculation unit into a relational equation that is previously constructed to indicate the relationship between the cumulative strain and the fresh properties of the ready-mixed concrete; A ready-mix concrete quality prediction system comprising:

Images