“A SYSTEM AND METHOD TO GENERATE A MULTIDIMENSIONAL PROPERTY ARRAY FOR PRODUCING CONCRETE MATERIALS” FIELD OF THE INVENTION: The present invention relates to producing a concrete material with predictable quality and strength, wherein, the said concrete material is produced with implementation of various parameters and attributes such as environmental parameters, geographical parameters, concrete raw material parameters, binder attributes and/or concrete attributes. BACKGROUND OF THE INVENTION: Concrete is a heterogeneous composite, comprising of materials having various properties in terms of morphology, chemistry, and mechanical traits. The properties and behaviour of a homogeneous material such as steel is predictable to a greater degree. Hence, in the design of structures for instance, the material factor of safety applied for steel is just 1.15. Whereas for a heterogeneous material like concrete, the material factor of safety applied is 1.50. This is simply because the final properties of the material concrete depend on many variables including nature of raw materials used and their varying properties, the system and process by which concrete is made, supplied today, and/or lack of a scientific approach to handle the art of making and supplying concrete. There are many aspects in an intended fourth generation concrete production plant, which promises the perfect output material. However, quality of the output material, which satisfies the specific requirement of each construction activity/material as well as gives consistent results almost always, not only depends upon regularizing or idealizing materials, their classification and their properties, but the overall operational excellence depends upon the idealization of all the processes involved in the overall operation of the plant, starting from input material inspection, categorization and their classification, the subsequent quality flow, the machinery, their optimal performance mapping, predictive and preventive maintenance, and all other support function interdisciplinary activities. The IN288379 patent document defines a system and method for classification of concrete making materials based on their properties to achieve different concretes with varied properties to perfection. Further, IN292690 discloses concrete binder composition. IN307681 discloses method of producing a compact and highly dense construction material. IN319073 describes concrete engineered binder composition, a process to make it as well as using a mechanically and chemically modified component to make an engineered binder. However, the above granted patents are isolated processes to enhance the performance of concrete raw materials. Further, there are other drawbacks in the known systems and methods for producing a desired concrete material such drawbacks are with respect to non-consideration of certain critical parameters or properties of concrete materials such as variation in aggregate/binder ratios, water/binder ratios, variations in moisture contents of aggregates and their application, and lack of identification of a trend in the present system with respect to concrete performance criteria. Accordingly, there is a need of a system and a method for producing a concrete material which takes account of these factors and work on the principle of data integration, linear interpolation of data and to get a trend line based on such linear interpolation thus increasing the overall efficiency & effectiveness of the concrete production as well as to create a database of concrete mix designs from which accurate compositions can be identified as per the performance requirement of each specific infrastructure project. Further, there is a need for developing a system and method which can identify the perfect concrete material by calculating the properties of the raw materials, as well as by calculating the properties of various known concrete materials and thus identifying a pattern to predict the properties of next concrete material. OBJECTIVE OF THE INVENTION: An objective of the present invention is to make a dry mix concrete production plant having highly functional fourth generation technology. Further, the objective of the present invention is to combine and integrate the said dry mix concrete production plant with ERP/IIOT/AI, thus increasing the efficiency & effectiveness of the plant and to produce new concrete materials with the help of AI based patterns. The main objective of the present invention is to develop a system and method which can identify the perfect concrete material by using partial data available through experimentation, identifying close patterns in the available data, and extending the database considering variation in parameters of concrete, raw material combinations, binder types and contents to develop a new concrete material. SUMMARY OF THE INVENTION: The present disclosure related to a computer implemented method to generate a multidimensional property array to produce a concrete material with predictable quality and strength, wherein, the method includes generating a database of a plurality of binder attributes and a plurality of concrete attributes, wherein, the said binder attributes and the concrete attributes have a predefined value, a laboratory determined value, or a field trial value. Then generating a two-dimensional property matrix through a processing system, wherein, the said two-dimensional property matrix comprises a base column of binder attributes, and a base row of concrete attributes, thereby providing a plurality of concrete property parameter rows. Then generating a concrete property trend line through a processing system, wherein, the concrete property trend line is generated by linear interpolation of the said plurality of concrete property parameter rows, wherein, the said trend line provides the concrete material with desired quality and strength. Wherein, the plurality of binder attributes is selected from a binder type and/or a binder content in the concrete mix, a water binder ratio, an aggregate binder ratio, or a combination thereof. The binder type includes a hydraulic material, a pozzolanic material, a semi-hydraulic material, or a combination thereof. The binder type includes a mixture of cement and pozzolanic materials like fly ash, GGBS in a fixed ratio, and wherein, the binder content is 300 kgs/cu.m to fill up the first row of the primary 2- dimensional matrix. Wherein these binder type are in a particular ratio, pertaining to the primary 2- dimensional matrix. The water binder ratio is a first constant factor having a value of 0.5 and the water binder ratio progressively decreases with increase in binder content, wherein it is maintained that the product of the binder content and the water binder ratio gives almost a constant value in the primary 2-dimensional matrix tabulated along the column of the matrix. The aggregate binder ratio is a second constant factor having a value of 3.These constant factors are to facilitate that the rheological properties are almost the same for all concrete mixes represented by the primary 2-dimensional matrix. The plurality of concrete attributes is selected from a fresh concrete property, a compressive strength, a flexural strength, a splitting tensile strength, a plurality of durability parameters, or a combination thereof. Wherein, the fresh concrete property is a concrete slump property, a fresh concrete density, or an air content of a fresh concrete. The present disclosure also relates to a system to produce a concrete material with predictable quality and strength, wherein, the system includes a computing device connected with a concrete material production system. The computing device includes a data input unit, a data output unit, a power supply unit, a server unit, wherein, the server unit consist of a memory unit configured to store a data, and a data processing unit configured to process a data inputted through the data input unit, a data stored in the memory unit, or a combination thereof, and the data processing unit generate a multidimensional property matrix and a concrete property trend line through the said multidimensional property matrix. The concrete material production system, wherein, the computing device is connected with the concrete material production system, and the data output unit of the said computing device controls the working of the said concrete material production system. DETAILED DESCRIPTION OF THE DRAWINGS: The objects and features of the present disclosure, which are believed to be novel, are set forth with particularity in the appended claims. The present disclosure, both as to its organization and manner of operation, together with further objectives and advantages, may be best understood by reference to the following description, taken in connection with the accompanying drawings as set forth below: FIG. 1 is a schematic diagram of the system to produce a concrete material with predictable quality and strength; FIG. 2 is a diagram fly ash concrete strength v/s percentage of fly ash optimization curve; and FIG. 3 is a diagram of GGBS concrete strength v/s percentage of GGBS optimization curve. DETAILED DESCRIPTION OF THE INVENTION: The present disclosure related to a computer implemented method to generate a multidimensional property array to produce a concrete material with predictable quality and strength, wherein, the method includes generating a database of a plurality of binder attributes and a plurality of concrete attributes, wherein, the said binder attributes and the concrete attributes have a predefined value, a laboratory determined value, or a field trial value. Then generating a primary two-dimensional property matrix through a processing system, wherein, the said two-dimensional property matrix comprises a base column of binder attributes, and a base row of concrete attributes, thereby providing a plurality of concrete property parameter rows. Then generating a concrete property trend line through a processing system, wherein, the concrete property trend line is generated by linear interpolation of the said plurality of concrete property parameter rows, wherein, the said trend line provides the concrete material with desired quality and strength. Wherein, the plurality of binder attributes is selected from a binder type and/or a binder content in the concrete mix, a water binder ratio, an aggregate binder ratio, or a combination thereof. The binder type includes a hydraulic material, a pozzolanic material, a semi-hydraulic material, or a combination thereof. The binder type includes a mixture of cement and pozzolanic materials like fly ash, GGBS in a fixed ratio, and wherein, the binder content is 300 kgs/cu.m to fill up the first row of the primary 2- dimensional matrix. Wherein these binder type are in a particular ratio, pertaining to the primary 2- dimensional matrix. The water binder ratio is a first constant factor having a value of 0.5 and the water binder ratio progressively decreases with increase in binder content, wherein it is maintained that the product of the binder content and the water binder ratio gives almost a constant value in the primary 2-dimensional matrix tabulated along the column of the matrix. The aggregate binder ratio is a second constant factor having a value of 3. These constant factors are to facilitate that the rheological properties are almost the same for all concrete mixes represented by the primary 2-dimensional matrix. The plurality of concrete attributes is selected from a fresh concrete property, a compressive strength, a flexural strength, a splitting tensile strength, a plurality of durability parameters, or a combination thereof. Wherein, the fresh concrete property is a concrete slump property, a fresh concrete density, or an air content of a fresh concrete. In an exemplary embodiment, the compressive strength is a compressive strength of concrete at different time intervals such as but not limited to compressive strength of concrete at 1, 3, 7, 28 days respectively, which is 20, 26, 30, 43 Mpa respectively. Further, it should be understandable that the compressive strength varies from one concrete example to another concrete example. In an exemplary embodiment, the flexural strength is a flexural strength of concrete at 28 days from the initial setting of concrete, wherein, the flexural strength of concrete at 28 days is 4.5 Mpa. Further, it should be understandable that the flexural strength varies from one concrete example to another concrete example. In an exemplary embodiment, the splitting tensile strength is a splitting strength of concrete at 28 days from the initial setting of concrete, wherein, the splitting strength of concrete at 28 days is 2.8 Mpa. Further, it should be understandable that the splitting tensile strength varies from one concrete example to another concrete example. In an exemplary embodiment, the plurality of durability parameters is an RCPT parameter of 2000 coulombs, a water permeability parameter of 20 mm, an initial surface absorption parameter of 0.25 ml/m2/sec. Further, it should be understandable that the above-mentioned values of the durability parameters vary from one concrete example to another concrete example. The present disclosure also relates to a system to produce a concrete material with predictable quality and strength, wherein, the system includes a computing device connected with a concrete material production system. The computing device includes a data input unit, a data output unit, a power supply unit, a server unit. The data input unit comprises a data input unit selected from a keyboard, a sensory data input, or a combination thereof. The data output unit is selected from a graphical user interface, a hardware command unit, or a combination thereof. The power supply unit provides electric power to run the said computing device. The server unit consist of a memory unit configured to store a data, and a data processing unit configured to process a data inputted through the data input unit, a data stored in the memory unit, or a combination thereof. Further, the data processing unit generates a multidimensional property matrix and a concrete property trend line through the said multidimensional property matrix. Wherein, the multidimensional property matrix includes a plurality of concrete property parameter rows, and the concrete property trend line is generated by linear interpolation of the said plurality of concrete property parameter rows. The computing device is connected with the concrete material production system, and the data output unit of the said computing device controls the working of the said concrete material production system. The data processing unit generates a plurality of commands to the hardware command unit, wherein, the said plurality of commands are based on the concrete property trend line. The hardware command unit controls the working of the said concrete material production system to produce the concrete material with desired quality and strength. TWO DIMENSIONAL ARRAY/MATRIX: Initially for the primary combination, the variables affecting the binder/concrete database is to be generated with a pattern which is as follows: 1. Binders are selected from cements (C), fly ash (F), GGBS and the ratio of C1:C2:C3 fixed as 33.33 : 33.33 :33.33 and F1:F2 fixed as 50 : 50 2. Type of binders - B1, B2, B3, B4, B5, B6, B7, B8 - 8 BINDERS 3. Total binder content - 300, 310, 320, 330, 340, 350...........500 4. Water/binder ratio - first constant factor - X (for 300), X1 (for 310), X2 (for 320)......., Xn (for 500) 5. Aggregate/binder ratio - second constant factor - ‘A’ Herein C1, C2, C3 are referred as cement material 1, cement material 2, cement material 3 respectively and F1, F2 are the fly ash 1 and fly ash 2 respectively. So, since parameters 1, and 5 are fixed for this combination, the 2 - dimensional matrix generated for this fundamental combination for 1 single binder ‘B1’ is as follows in matrix 1. Matrix 1: primary two - dimensional matrix The above 2- dimensional matrix has the following denotations: x1, x2, x3....xn - Pre-determined water/binder ratios, corresponding to binder contents of 300, 310, 320......500 respectively. Further, to give the total water content, which is the product of the binder content and the water binder ratio, a fixed value of say, 150 lts/cu.m, which is the same for the whole 2-dimensional primary matrix. a, b, c (not limited to) - fresh properties of the concrete obtained by actual trials. d, e, f (not limited to) - Strength properties of the concrete at different ages g, h, i, j (not limited to) - Durability and performance criteria of the concrete a1, b1, .....c1, ....j1 - corresponding properties as similar to a,b,c...j, but for different binder contents and water/binder ratio combinations along the columns of the matrix. It is to be noted that this whole 2 - dimensional matrix has the following constraints of fixities: 1. This 2-d matrix corresponds to only 1 kind of binder, B1 2. This 2-d matrix corresponds to only 1 fixed water/binder ratio for each binder content. 3. This 2-d matrix corresponds to only 1 fixed A/B ratio. 4. This 2-d matrix corresponds to only 1 combination of C1 : C2 :C3 and F1 : F2, which is 33.33 : 33.33 : 33.33% ;; 50 : 50% respectively. In another embodiment, actual trials are conducted in the laboratory for say, row 1 of the matrix, and get all the properties and record them in the 1 ^st row of the matrix. No actual trials for the 2 ^nd row, but actual trials are conducted for the 3 ^rd , 5 ^th , 7 ^th , 9 ^th rows, and fill up the corresponding data in the respective rows. In another embodiment, by means of a suitable simple interpolation principles, the intermediate rows are filled up for all corresponding columns. After generating at least say, 10 rows full of data by the above principle or process, we see the trend of each of the data through a trendline equation. Likewise now, for the rest of the remaining rows (after the 10 ^th row), skip 3 rows instead of 1, and fill up the corresponding column data. Then, incorporating the trendline equation obtained from the first 10 rows for each column property, whether linear, or parabolic, power, exponential, or logarithmic, to the 13 ^th , 16 ^th , 19 ^th rows and check if the same equation is applicable for these rows, for each column property. If the trendline equation holds good, then applying this principle of skipping 2 rows until say, the 20 ^th row, and applying the same trendline equation. In the case, when this trendline holds good, from the 20 ^th row, we skip 4 ^th or 5 ^th rows instead of 1 ^st or 3 ^rd , and apply the same process. In another embodiment, if the values obtained in the 13 ^th , 16 ^th and 19 ^th rows are different from the trendline equation prediction, then come back to the original process of skipping 1 ^st row as done for the first 10 ^th rows. From this process, the system can fill up this primary 2-dimensional matrix with great speed and accuracy, saving time, resources, as well as creating a pattern in the obtained database. Matrix 1 Example: The fixed aggregate/binder ratio (A/b) in matrix 1 be A, e.g. 2.75. For each binder content, the water/binder ratio (w/b) correspondingly changes, higher the binder content (B) goes, lower the w/b ratio becomes, so that their product, that is, B * w/b is almost constant, e.g.150 ltrs/cu.m. Accordingly, 1 ^st row 1 ^st column will be 300, 0.50, 2.75, so that 300 * 0.50 = 150. 1 ^st column 2 ^nd row, will be 310, 0.485, 2.75, so that 310 * 0.485 = 150.35. keeping the water content as the same gives a trend and a means for comparison. 1 ^st column, 3 ^rd row will become 320, 0.47, 2.75, so that 320 * 0.47 = 150.4 and accordingly the same is applicable to other rows. The concrete trial is done for 1 ^st row 1 ^st column combination first, and all the parameters in the 1 ^st row are filled up as an array. For instance, as explained before, a, b, and c are fresh concrete properties, i.e., slump, fresh concrete density, and air content. From trial 1 corresponding to 1 ^st row 1 ^st column combination of 300, 0.50, 2.75, obtained a slump, fresh density and sir content of 80 mm, 2550 kg/m ³ , and 2.3% respectively, as measured in the lab through actual trials. This is completed with a fixed admixture dosage. Similarly, parameters d, e, f, g are compressive strengths at 1, 3, 7, 28 days respectively, which for examples are 20, 26, 30, 43 Mpa respectively, as measured in the lab. Similarly, parameter h is the flexural strength at 28 days, which for example is 4.5 Mpa, as measured in the lab. Similarly, parameter ‘i’ is the splitting tensile strength at 28 days, which for example is 2.8 Mpa, as measured in the lab. Similarly, j, k, l, and so on are durability parameters, selected from RCPT value, water permeability value, initial surface absorption, etc. which for example are 2000 coulombs, 20 mm, and 0.25 ml/m2/sec and so on. Similarly, other durability parameters are selected from……… Accordingly, the 1 ^st row will get completed and the values are shown in below matrix 2 which is as follows. 0.50, 2.75) 80 2550 20 26 30 43 4.5 2.8 2000 20 0.25.. Matrix 2: First row values of the primary two - dimensional matrix Now after filling up the 1 ^st row fully, an actual trial for the 3 ^rd row is completed, with the 320 * 0.47, and skipping the 2 ^ND row. The obtained values for the 3 ^rd row as follows: 320, 0.47, 2.75 70 2550 22 29 34 48 4.8 3.0 1800 18 0.22 Accordingly, after filling up the 3 ^rd row, we get a partial matrix filled up as follows: (300, 0.50, 2.75) 80 2550 20 26 30 43 4.5 2.8 2000 20 0.25.. 2 ^nd row blank\ (320, 0.47, 2.75) 70 2550 22 29 34 48 4.8 3.0 1800 18 0.22 4 ^th row blank ....... Matrix 3: First and third row values of the primary two - dimensional matrix Accordingly, by actual trials, data for alternate rows is filled up and thus completing the 50% of the 1 ^st , primary matrix. Accordingly, it can be observed that some parameters will be in an increasing trend and some will be in a decreasing trend and some might be constant also. Now, the gap in the values between the 1 ^st and 3 ^rd rows, and subsequently all consecutive alternate rows is so narrow, that they always follow a linear relationship of interpolation, that they can be automatically filled up with interpolated values, which can be processed through a computer processer. Accordingly, the 2 ^nd row becomes by linear interpolation and the values are provided in matrix 3 which is as follows: 1800 18 0.22 4 ^th row blank ....... Matrix 4: First to fourth row values of the primary two - dimensional matrix Accordingly, by the above explained method, the whole primary matrix is filed up in ‘x’ and ‘y’ axis. Multi-dimensional array/matrix: As illustrated above in the two dimensional array/matrix, many other variations of parameters and their values are provided into the computer database and used in by a computer processor to generate a multi-dimensional array, which are explained as below. 1. Water/binder ratio is fixed i.e., X (for 300), X1 (for 310), X2 (for 320)......., Xn (for 500) 2. Aggregate/binder ratio is denoted by ‘A’ 3. Various ratios of C1:C2:C3 apart from 33.33 : 33.33 : 33.33 and F1: F2 apart from 50 : 50 4. Type of binders - B1, B2, B3, B4, B5, B6, B7, B8 - 8 binders. Now, these variation in parameters provide matrix combinations in x, y and z axis. 1. Variation in water/binder ratio With the same binder content in each row, implement a water/binder ratio of ‘X + 0.01’, and X - 0.01’ for each binder content from the primary 2 - dimensional matrix. Accordingly, the extended matrices in the ‘+z’ and ‘-z’ directions become respectively as follows: Matrix in the ‘+z’ direction will be as below: . . . . . . . . . . . . 500,xn+0.01,A an bn cn dn en fn gn hn in jn Matrix 5: Three - Matrix in +z direction Matrix in the ‘-z ‘ direction will be as below: Matrix 6: Matrix in -z direction Accordingly, the next step is to create the ‘-z’ to ‘+z’ direction, which is just that in the 1 ^st row 1 ^st column, wherein it is considered 0.50 as the water/binder ratio, considered 0.51 in the ‘+z’ direction, and 0.49 in the ‘-z’ direction, along with 300 total binder only. Accordingly, this creates a scenario where the same binder content is used, but the total water content becomes 153 litres in ‘+z’ direction and 147 liters in the ‘-z’ direction. This creates a scenario, wherein, variation in all concrete fresh, strength and durability properties in both ‘+z’ and ‘-z’ directions is achieved. Further, this step also provides two separate matrix. Now, since the 3 ^rd and 4 ^th dimensions are subsets of the 1 ^st 2-dimensional matrix, the variation in each parameter along each row will be much more narrower, compared to what happened the 1 ^st 2-dimensional matrix. Hence, in these extended matrices, again 2 rows are skipped, or even 3 rows are skipped and do actual trials only in the 4 ^th , or 5 ^th row, and by simple interpolation techniques, thus the intermediate rows can be filled up. As the dimensions of the matrix extends to the 5 ^th and 6 ^th dimensions, with another small variation in the parameters, the rows can be filled up after trials only with 4, 5, or 6 consecutive rows, as differences between properties will be even narrower. Accordingly, wherever a new matrix has to be generated, the method as explained above is repeated. 2. Variation in Aggregate/binder ratio Further, an additional aggregate/binder ratio (aggregate/binder ratio) are introduced ‘A1’, against each of ‘X’, ‘X+0.01’, and ‘X-0.01’ in contrast to ‘A’. Accordingly, the computer processer will draw a multi-dimensional matrix, such as for ‘X’ water/binder ratio, the secondary array will become as below: . j4 . . . . . . . . . . . . . . . . . . . . . . 500,xn,A1 an bn cn dn en fn gn hn in jn Matrix 7: Matrix with variation in aggregate/binder ratio For ‘X + 0.01’ Water/binder ratio, the secondary array will become now as follow: an cn en gn Matrix 8: Matrix with variation in aggregate/binder ratio (0.01) For ‘X - 0.01’ Water/binder ratio, the secondary array will become now as follow: 500,xn-0.01,A1 an bn cn dn en fn gn hn in jn Matrix 9: Matrix with variation in aggregate/binder ratio (-0.01) The above matrix 8-9 shows the data values for XA, XA+00.1, XA-0.01 and XA1, XA1+0.01, XA-0.01 i.e. variation in aggregate/binder ratio). Again the row data is generated as per the process described in the fundamental primary 2-dimensional matrix. But for the first 10 rows now, only 2 rows are skipped for experimentation instead of 1 row which was implemented for the primary 2-dimensional matrix, and applying the same principles. As the database grows bigger and bigger due to the variations mentioned above, the differences in each property too narrow down, deeming the model to become more and more predictable by primary interpolation equations, governed by the data provided in the computer system, and the computer processor decide upon the extent of skipping actual trials. 3. Variationin ratio of C1:C2:C3 and F1:F2 and their permutations and combinations: The previous examples are based on 1 single combination of C1:C2:C3 and F1:F2, wherein, C1:C2:C3 is 33.33%:33.33%:33.33% and F1:F2 is 50%:50% i.e., mean combination – 1. Herein, C1 = lowest strength class of hydraulic material (L); C2 = medium strength class of hydraulic material(M); C3 = highest strength class of hydraulic material(H); and F1 = higher fineness class of pozzolanic materials (H1); F2 = lower fineness class of pozzolanic materials (L1). Now, this mean combination is placed in the center, then either side of the mean will be represented as: C1(L):C2(M):C3(H)::::C1(33.33):C2(33.33):C3(33.33)+F2(50):F1 (50)::::F2(H1):F1(L1) In an embodiment, there is one more class of fly ash, which can be called as F3, wherein, F1 and F2 can be rejoined and split again into F1, F2 and F3. The below mentioned table 1 provides various combinations of cement and fly ash. Table 1

Hence, for cement and fly ash combination the matrix will become as follows, accounting for this variation: Matrix 10: cement and fly ash matrix In the above cement and fly ash matrix, the combination marked at the center of the above matrix, (60, 4200) is the combination for which the whole database is shown in the previous sections for various parameter changes, involving various interpolation techniques. Now, the next step includes to develop and to extend the predicted fresh concrete properties, strength properties, as well as durability properties in the (-X to +X) direction and (-Y to +Y) directions. Since the variation in the -X to +X direction is based on a constant increase of a specific property, the process of laboratory experimentation involves just making 1 or 2 mixes in each category in the -X and +X directions, and equations can be developed to predict and fill up the matrix in this direction of combinations. In the -Y to +Y directions, however it is much easier for developing the matrix for predicting the fresh concrete properties, strength properties, as well as durability properties. Since it is just the strength properties of the hydraulic materials, which is in a constant increase pattern mode from the +Y to -Y directions (up to down). Accordingly, based on standard models available in the comparison between cement and concrete properties, the matrix can be directly fill up in this direction. However, to corroborate the present method, few laboratory experiments are conducted in the -X to +X directions and/or in the +Y to -Y directions. 4. Variation in binder type The various binders as illustrated reviousl are ex lained herein below in table 2 In the above table 2, totally 24 types of binders possible without changing the A/B ratio without introduction of 1 more Aggregate/Binder ratio, and the total concrete types will increase to 48, considering the same binder content. Since the variations in water/binder ratio (x+/-0.01), and aggregate/binder ratio (A/A1) have already been considered, there are totally 8 types of binders as in the illustrated example above. The multi-dimensional array/matrix considered until now is only for 1 type of binder, say, B1. However, the same matrix is extended to all other binders to generate a complete matrix to accurately predict the concrete properties. In another embodiment, it is provided that B1 is 100% OPC and 0% fly ash. For B2, it becomes 90% OPC and 10% fly ash. For B3 to B7, the OPC % is sequentially reduced by 10% and correspondingly, the fly ash content is increased by 10%. Though it looks that mathematically interpolation the properties of concrete would follow a linear trend by this linear decrease/increase of cement/fly ash, chemically it is not true, as the trend would follow a bell-curve, especially in terms of strength, wherein the strength would keep increasing up to a certain level of pozzolanic materials replacing hydraulic materials, after which it would decrease. Accordingly, based on the above parameters and the matrix, a multidimensional property array can be generated to produce a concrete material with predictable quality and strength. Further, figure 2 and figure 3 explains that the compressive strengths of concrete varies, by changing the percentage of fly ash or GGBS as a cement replacement in concrete. As shown in figures 2-3, when in the binder type, the various percentages of fly ash or GGBS as cement replacement varies, there is no linear trend. Accordingly, a new 2- dimensional matrix has to be separately created when the fly ash, GGBS percentage replacement changes, say, from c : f :: 100 : 0 to c : f :: 90 : 10. Accordingly, the whole exercise of generating a new multidimensional matrix for this binder type has to be done separately.