CN113255023A - Automatic design method of special-shaped packaging carton based on model and computer device - Google Patents
Automatic design method of special-shaped packaging carton based on model and computer device Download PDFInfo
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Abstract
The application discloses a model-based automatic design method and a computer device for a special-shaped packaging carton, which are characterized by comprising the steps of firstly obtaining attribute information and quantity of commodities to be sent, further determining the packaging performance requirements of the commodities, then determining optional carton models meeting the packaging performance requirements and the required quantity of the optional carton models from a carton model library, then obtaining production data generated by unit production quantity of each optional carton model, then calculating contribution values of the production data of each optional carton model to each evaluation item, carrying out fuzzy evaluation on the contribution values of each evaluation item to obtain a fuzzy evaluation matrix, and finally obtaining an optimal carton model from the optional carton models based on the evaluation weight, the fuzzy evaluation matrix and the required carton quantity of the evaluation items. The method realizes the evaluation of the carton model based on the fuzzy evaluation and the weight coefficient, ensures the applicability and comprehensiveness of the evaluation, and improves the authenticity of the evaluation result.
Description
Technical Field
The application relates to the technical field of paper product design, in particular to a model-based automatic design method and a computer device for a special-shaped packaging carton.
Background
The paper product processing industry is one of the important industries in China, both corrugated boards for packing boxes and paper towels used as sanitary articles are indispensable daily articles in daily life, and most of packages of products, commodities and other articles are wrapped and contained by packing boxes formed by paper products.
At present, most users purchase goods on an e-commerce platform, and after the users place orders, the goods are delivered to the users by the offline warehouse of the merchant, for example, the merchant is only an agent and does not actually produce the goods, that is, the production factory of one or more goods may only have one, but the goods produced by the production factory can be sent to the offline warehouse of one merchant or even a plurality of different merchants located in a plurality of regions in the country, and after the users in different regions place orders, the offline warehouse of the corresponding region delivers the goods instead of directly delivering the goods to all the users from the production factory, so that the delivery time of the goods from the ordering of the users to the delivery can be reduced. In this mode of production and distribution, after a large number of commodities are produced by a production factory every day, a packing carton is used to transport the commodities in a batch to an off-line warehouse where the commodities are needed.
In the process of conveying commodities from a production factory to a warehouse of a merchant, the production factory needs cartons for packaging the commodities so as to deliver the commodities to the merchant, and the commodities are branded commodities (substitute processed commodities), and the merchant needs to print patterns of own brands on the surfaces of the cartons, so that the ordering of the cartons is taken charge of by the merchant, but when the merchant places a bill to a carton manufacturer to purchase a special-shaped corrugated paper packaging box, the merchant cannot provide specific specifications of the required cartons because the specifications and packaging capacity of different types of cartons are unknown, and only information about the packaged commodities can be provided, so that the problem of considering how to select the carton which can meet the needs of the merchant and is most beneficial to the carton manufacturer is solved.
The method adopted at present is to select the carton with the lowest material cost to produce and deliver to customers, but the method only considers the material cost, and the consideration on the production cost is single, so the obtained result is more comprehensive and possibly deviates from reality.
Disclosure of Invention
Based on this, in order to improve the diversity of carton production evaluation factors and obtain a more real carton evaluation result, thereby selecting the most reasonable carton for carton manufacturers to produce, the following technical scheme is disclosed in the application.
On the one hand, the automatic design method of the special-shaped packing carton based on the model comprises the following steps:
acquiring attribute information and quantity of commodities to be sent, and further determining the packaging performance requirements of the commodities;
optional carton models meeting the packaging performance requirements and the required number of the optional carton models are determined from a carton model library;
obtaining production data generated by unit production capacity of each optional carton model;
calculating the contribution value of the production data of each optional carton model to each evaluation item, and carrying out fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix;
and optimizing the carton model from the optional carton models based on the evaluation weight of the evaluation item, the fuzzy evaluation matrix and the required carton number.
In one possible embodiment, the attribute information includes size information, weight information, and shape information, and the packaging performance requirements include length, width, height of the inner diameter, rated load bearing, specific function;
the determining of the packaging performance requirements of the commodity comprises: and carrying out arrangement combination in at least one direction of length, width and height on the commodities to be sent according to the shape information, obtaining size information and weight information of the commodity combination obtained after the arrangement combination according to the size information and the weight information of the commodities to be sent, and further determining the respective packaging performance requirements of the commodity combination and the single commodities to be sent.
In one possible embodiment, the production data includes the type of raw material and its consumption, the type of energy and its consumption, the time consumption, the type of recycling species in the by-product and its production, and the type of waste material and its production.
In one possible embodiment, the evaluation terms include a material cost term, an energy cost term, a time cost term, a pollution cost term, and a cost savings term.
In a possible embodiment, the contribution value is calculated by:
wherein Gi is the contribution value of the ith evaluation item, Ji is the type number of the production data corresponding to the ith evaluation item, Dj is the data value of the jth data item, Wij is the evaluation influence coefficient of the jth production data on the ith evaluation item, and,
。
in a possible embodiment, the performing fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix includes:
obtaining the evaluation level of each evaluation item and the corresponding standard value range;
obtaining a membership degree judging chart corresponding to the contribution value, and obtaining a membership degree vector according to the membership degree judging chart;
and obtaining a fuzzy evaluation matrix according to the membership vector.
In one possible embodiment, the evaluation weight of the evaluation term is determined by:
determining a parent item to which each evaluation item belongs, and calculating the weight of the parent item;
and calculating the evaluation item weight of each child evaluation item included in each parent item according to the parent item weight.
In one possible embodiment, the manner of calculating the class term and the evaluation term weight includes:
acquiring all participation items to obtain a participation set, and determining the key degree grade of each participation item relative to other participation items in the participation set to obtain a key degree matrix;
normalizing each row of the criticality matrix, summing each row of the grade matrix to obtain a column matrix, and normalizing elements in the column matrix to obtain the weight of each participating category item.
On the other hand, still provide a dysmorphism packing carton automatic design computer means based on model, include:
the performance requirement determining module is used for acquiring the attribute information and the quantity of the commodities to be sent so as to determine the packaging performance requirements of the commodities;
the carton model determining module is used for determining the optional carton models meeting the packaging performance requirements and the required number of the optional carton models from a carton model library;
a production data acquisition module for acquiring production data generated by unit production volume of each of the selectable carton models;
the fuzzy evaluation calculation module is used for calculating the contribution value of the production data of each optional carton model to each evaluation item and carrying out fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix;
and the evaluation result calculation module is used for optimizing the carton model from the optional carton models based on the evaluation weight of the evaluation item, the fuzzy evaluation matrix and the required carton number.
In one possible embodiment, the attribute information includes size information, weight information, and shape information, and the packaging performance requirements include length, width, height of the inner diameter, rated load bearing, specific function;
the performance requirement determination module comprises:
the arrangement combination unit is used for carrying out arrangement combination on the goods to be sent in at least one direction of length, width and height according to the shape information;
and the requirement determining unit is used for obtaining the size information and the weight information of the commodity combination obtained after the arrangement and the combination according to the size information and the weight information of the commodity to be sent, and further determining the packaging performance requirements of the commodity combination and the single commodity to be sent.
In one possible embodiment, the production data includes the type of raw material and its consumption, the type of energy and its consumption, the time consumption, the type of recycling species in the by-product and its production, and the type of waste material and its production.
In one possible embodiment, the evaluation terms include a material cost term, an energy cost term, a time cost term, a pollution cost term, and a cost savings term.
In one possible embodiment, the fuzzy evaluation calculation module calculates the contribution value by:
wherein Gi is the contribution value of the ith evaluation item, Ji is the type number of the production data corresponding to the ith evaluation item, Dj is the data value of the jth data item, Wij is the evaluation influence coefficient of the jth production data on the ith evaluation item, and,
。
in a possible implementation manner, the fuzzy evaluation calculation module performs fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix through the following steps:
obtaining the evaluation level of each evaluation item and the corresponding standard value range;
obtaining a membership degree judging chart corresponding to the contribution value, and obtaining a membership degree vector according to the membership degree judging chart;
and obtaining a fuzzy evaluation matrix according to the membership vector.
In one possible embodiment, the fuzzy evaluation calculation module determines the evaluation weight of the evaluation item by:
determining a parent item to which each evaluation item belongs, and calculating the weight of the parent item;
and calculating the evaluation item weight of each child evaluation item included in each parent item according to the parent item weight.
In one possible embodiment, the fuzzy evaluation calculation module calculates the class term and the evaluation term weight by:
acquiring all participation items to obtain a participation set, and determining the key degree grade of each participation item relative to other participation items in the participation set to obtain a key degree matrix;
normalizing each row of the criticality matrix, summing each row of the grade matrix to obtain a column matrix, and normalizing elements in the column matrix to obtain the weight of each participating category item.
According to the model-based automatic design method and the computer device for the special-shaped packaging carton, cost consumption of different carton models is calculated, so that the carton model with the optimal production scheme and the lowest cost is selected from the cartons capable of meeting user requirements for production, a manufacturer can determine the most reasonable carton type only by sending goods with the tape given by a merchant, multiple cost factors are considered in the process of evaluating the carton model, consumption cost and gain cost are included, contribution values of the different cost factors are subjected to fuzzy evaluation, weight distribution is performed on evaluation items, evaluation of the carton model is achieved based on the fuzzy evaluation and the weight coefficient, applicability and comprehensiveness of the evaluation are guaranteed, and authenticity of an evaluation result is improved.
Drawings
The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining and illustrating the present application and should not be construed as limiting the scope of the present application.
Fig. 1 is a schematic flow chart of an embodiment of an automatic design method for a model-based special-shaped packing carton disclosed in the application.
Fig. 2 is a diagram of the association between production data and evaluation items in the carton production process.
FIG. 3 is a schematic diagram showing calculation of the contribution values of the ozone layer depletion evaluation term.
Fig. 4 is a block diagram of an embodiment of the model-based automatic design computer device for the irregular packaging cartons disclosed in the present application.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application.
The following describes an embodiment of the automatic design method of the model-based special-shaped packing carton disclosed by the application in detail with reference to fig. 1-3. As shown in fig. 1, the method disclosed in this embodiment includes the following steps 100 to 500.
Step 100, the performance requirement determining module obtains the attribute information and the quantity of the commodities to be sent, and further determines the packaging performance requirements of the commodities.
Assuming that a merchant orders a plurality of series of books from a manufacturer, a packaging box capable of packaging the series of books is purchased from a carton manufacturer, the carton manufacturer sends the packaging box to the manufacturer after the packaging box is produced, and the manufacturer packs the series of books and sends the packaged series of books to an off-line warehouse of the merchant.
The performance requirement determining module acquires attribute information and quantity of series of books serving as goods to be sent, which are provided by a merchant, wherein the attribute information comprises the following components: the series of book clusters are formed by plastic packaging of a plurality of books, each book cluster is 20cm long, 25cm wide, 30cm high, 4Kg net weight and 600 book clusters.
After obtaining the attribute information and the quantity, the performance requirement determining module analyzes the attribute information and the quantity, and determines the following packaging performance requirements XQ 1: the length of the inner diameter of the carton is more than 20cm, the width of the inner diameter is more than 25cm, the height of the inner diameter is more than 30cm, and the rated load is more than 4 Kg.
The carton model library is pre-established, the model library comprises a plurality of different types of carton models, the specification parameters of each type of carton model are not completely the same as those of other carton models, the specification parameters comprise the tooth shape, the ridge shape, the layer number (the layer number corresponds to the core paper number), the size, specific functions and the like of corrugated boards, and the carton model library also comprises the box types of the cartons, such as a slotted carton, a sleeved carton, a folded carton, a sliding cover carton, a fixed carton, an automatic carton and other box types with different structures and use forms.
After the packaging performance requirements of the commodities are obtained, the carton model determining module screens out carton models which can meet the performance requirements from the model library, and the screened models are usually multiple, so that the models at the moment are all selectable carton models, and the required production quantity can be different due to different specification parameters of different models. For example, a variety of carton models were screened for the above requirement XQ1, three of which were as follows: the model M1 is an optional carton model with the size of C1 and formed by a single-layer A-shaped corrugated board, one model M1 can be used for containing 1 set of commodities and 600 cartons are needed; the model M2 is an optional carton model with the size of C2 and formed by single-layer B-edge corrugated boards, one model M2 can be used for containing 1 set of commodities and 600 cartons are needed; the model M3 is an optional carton model of C3 size and composed of double layers of BC corrugated cardboard, and one model M3 can be used for containing 1 set of commodities, and 600 cartons are needed.
It should be noted that the optional carton model identified, in addition to meeting the packaging performance requirements, cannot exceed the packaging performance requirements too much, for example, a carton having a size of 100cm by 100cm is too large for requirement XQ1, and thus will not be considered as an optional model although meeting the requirements. Specifically, a floating interval may be set for each specification item, for example, the floating interval of the size is greater than the required size but less than 1.1 times the required size, so that the size of the selected carton model does not exceed 1.1 times the required size, C1 to C3 are all located in the floating interval of the size, and so on for other specification items.
In step 300, the production data acquisition module acquires production data generated by unit production volume of each of the selectable carton models.
Unit throughput refers to the production of cartons from a single, selectable carton mold. In one embodiment, the production data refers to the type of raw material and its consumption, the type of energy and its consumption, the time consumption, the type of recycling species in the by-product and its production, and the type of waste and its production required in the process of producing the individual cartons. Different carton models can meet different packaging performance requirements, so that the process chains, the adopted raw materials, the consumed production time and the like adopted in the production and processing processes of the carton models are different, so that the data items related to the production data of the different carton models and the data values of the data items are different, the raw material types, the energy types, the time, the recycling material types and the waste material types are data items, and the raw material consumption, the energy consumption, the time consumption, the recycling material generation and the waste material generation are data values of the data items.
Specifically, the data items are obtained by dividing the data items according to parent items, and each parent item also comprises different types of child items, for example, the types of raw materials are raw materials required in the process of producing the carton, including the child items of pulp, adhesive and the like, but the production and the manufacture of the raw materials are not included, because the raw materials used in the process of producing the carton are finished products, and the raw materials do not need to be firstly produced on site to produce the carton; similarly, the energy types comprise sub-items such as water, electricity, steam and the like required in the carton production process; the recycling substance types comprise recyclable intermediate products and other sub-items generated in the carton production process; the waste material category comprises sub-categories of solid waste, waste gas, liquid hazardous waste and the like generated in the process of producing the carton, such as coal slag, particulate matters and ink waste water.
For example, the process steps for producing the calcium-plastic corrugated paper include a calcium-plastic raw material plasticizing step, a calcium-plastic sheet forming step, and a calcium-plastic paper cutting production step, which are unique to production of the calcium-plastic corrugated paper, so that under the condition that other steps are completely the same, the raw material type of the calcium-plastic corrugated paper is increased, energy resources are required to consume more water, electricity, steam and the like to implement the unique step, time of the unique step is also required to be counted, the unique step can generate certain specific types of waste materials and certain specific types of recycled materials, and therefore, data items and data values of production data of the calcium-plastic corrugated paper are different compared with those of common corrugated paper.
It can be understood that even if the calcium-plastic corrugated paper has only three more unique steps compared with the common corrugated paper in the process steps, the input and output in the process steps are different, so that the subsequent common steps may be different, and the data values of the data items in the common steps are different. For example, steps such as preheating, corrugating, bonding, gluing, drying and the like are involved in the subsequent steps of the unique step of the calcium-plastic corrugated paper (namely, the common step with the common corrugated paper), but because the physicochemical properties of the calcium-plastic paper are different from those of the common paper, process parameters in the common steps such as drying temperature, gluing amount and the like can be changed, so that the data values of the data items in the common step are different, and the common step and the unique step are added together to form the overall difference of the production data of the calcium-plastic corrugated paper and the common corrugated paper.
And 400, calculating the contribution value of the production data of each optional carton model to each evaluation item by the fuzzy evaluation calculation module, and performing fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix.
The evaluation items are used to evaluate whether the carton model is an optimal solution, and in one embodiment, the evaluation items include a material cost item, an energy cost item, a time cost item, a pollution cost item, and a cost savings item. The evaluation items are combined to determine which of the alternative carton models is the optimal model, i.e. the model that is ultimately produced.
Specifically, the five evaluation items are obtained by dividing according to a parent item, and each parent item further includes different types of child items, for example, the material cost item refers to the materials used in the whole process flow from the initial production of pulp until the final finished carton is obtained, and includes the child items of plant fibers for producing pulp, starch for producing adhesive and the like; the time cost item comprises the time consumption of the whole production process; the pollution cost items comprise sub-items of land ecotoxicity, ozone layer damage, photochemical smog, photochemical oxidation, water eutrophication, aquatic ecotoxicity, land ecotoxicity, soil acidification and the like generated or caused in the whole process flow; the cost saving items include sub-items such as adhesives obtained after secondary processing of recycled materials generated in the whole process flow. It is understood that the above-mentioned division of the sub-class items does not represent all the sub-class items, and the sub-class items can be divided into more fine-grained sub-class items or less coarse-grained sub-class items according to the requirement of granularity refinement, and the content of the sub-class items is also set according to the products actually occurring in the production process.
Specifically, referring to fig. 2, only a part of the specific connection lines of the association relationship between the evaluation items and the corresponding production data items are shown in fig. 2, and the rest of the production data items and the evaluation items, which are not shown, are replaced by ellipses.
The contribution value is a gain value generated by the production data to the evaluation item, and the present embodiment calculates the contribution value according to the sub-item of the evaluation item. For example, in the production of models M1, M2, and M3, the amount of pulp consumed is different depending on the size of the model, and the amounts of pulp consumed are ZJ1, ZJ2, and ZJ3, respectively. For another example, the binder used in the model M1 is different from the binders used in M2 and M3 in that the binder used in M1 generates a certain amount of mucilage wastewater in the manufacturing process, the mucilage wastewater can be further used as water resource for glue manufacturing after chemical treatment, while the binders used in M2 and M3 generate solid waste, and the solid waste cannot be recycled, so that M1 contributes to the saving cost, but M2 and M3 do not contribute to the saving cost, and particularly, the solid waste generated in M2 and M3 contributes to the land ecotoxicity and soil acidification in the pollution cost.
And 500, the evaluation result calculation module optimizes the carton model from the optional carton models based on the evaluation weight of the evaluation item, the fuzzy evaluation matrix and the required carton number.
The evaluation item weight indicates the degree of influence of each evaluation item on the final evaluation result, and the larger the weight is, the larger the influence of the evaluation item on the evaluation result is. For example, under the condition that the price of the raw material is remarkably increased, the emphasis is placed on adopting an evaluation system taking the material cost as a key point, and the weight of a material cost evaluation item is relatively maximum; under the condition that the environmental pollution problem is strengthened to be standard, the emphasis is placed on adopting an evaluation system taking pollution cost as a key point, and the weight of the pollution cost evaluation item is relatively maximum.
The evaluation item weight of each evaluation item is determined by this step, and can be expressed by a row vector, and assuming that N evaluation items are shared, the evaluation item weight set a = (a1, a2, …, aN), where a is the evaluation item weight and N is the number of evaluation items. The contribution value of each evaluation item is obtained through step 400, expressed in a matrix form including N × 4, and the final environmental protection evaluation result is obtained by multiplying the two.
Expressing the calculation process in the form of a formula, the following is:
wherein Ql is an evaluation result of the ith selectable model, e is a weight of a subclass evaluation item, N is a number of evaluation items, h is a membership degree, and r is a number of evaluation levels, and in this embodiment, r =4 is divided into four evaluation levels, i.e., a very strong evaluation level, a medium evaluation level, and a weak evaluation level. From the above formula, the evaluation result is a row vector containing r elements. Assuming that the evaluation result obtained by the optional carton model Q1 is [0.53, 0.26, 0.12, 0.09], the evaluation result vector is multiplied by a column vector composed of weights of the four evaluation levels, for example, the column vector is [0.4, 0.3, 0.2, 0.1], the multiplication result is 0.212+0.078+0.024+0.009=0.323, and the multiplication result is multiplied by the required production quantity of each carton model obtained in step 200 to obtain a final comprehensive evaluation result, and the higher the value of the comprehensive evaluation result is, the larger the cost consumption is, and therefore, the optional carton model with the smallest comprehensive evaluation result is taken as the optimal carton model.
According to the method, the carton models with the optimal production scheme and the lowest cost are selected from the cartons which can meet the requirements of users for production by calculating the cost consumption of different carton models, so that a manufacturer can determine the most reasonable carton types only by sending goods with the help of merchants, in the process of evaluating the carton models, various cost factors are considered, including consumption cost and gain cost, so that the contribution values of different cost factors are subjected to fuzzy evaluation, the evaluation items are subjected to weight distribution, the evaluation of the carton models is realized based on the fuzzy evaluation and the weight coefficients, the applicability and the comprehensiveness of the evaluation are ensured, and the authenticity of the evaluation results is improved.
In one embodiment, the attribute information includes size information, weight information, and shape information, and the packaging performance requirements include length, width, height of an inner diameter, rated load bearing, specific function. The size information is the length, width and height of the smallest rectangular parallelepiped capable of packaging the commodity, and the shape information is the approximate shape of the commodity.
The performance requirement determining module determines the packaging performance requirement of the commodity through the permutation and combination unit and the requirement determining unit. The arranging and combining unit is used for arranging and combining the commodities to be sent in at least one direction of length, width and height according to the shape information. By analyzing the shape information, a plurality of commodities can be arranged and combined, so that the commodities can be packaged in the same carton to form a new packaging scheme. The demand determining unit obtains size information and weight information of a commodity combination obtained after the commodity combination is arranged and combined according to the size information and the weight information of the commodity to be sent, and further determines the respective packaging performance demands of the commodity combination and the single commodity to be sent. For example, the optional carton models M2 and M3 selected in the foregoing description of step 200 are carton models that are arranged and combined to contain multiple sets of products, and specifically, for series books, the shapes are substantially rectangular, and therefore the differences in the shapes and the sizes are small, and therefore the carton models can be arranged in the length and the width to obtain the size (40 cm x 50cm x 30 cm) and the weight (16 Kg) of the product combination in the 2 x 2 arrangement, where the packaging performance requirement XQ2 is: the length of the inner diameter of the carton is more than 40cm, the width of the inner diameter is more than 50cm, the height of the inner diameter is more than 30cm, and the rated load is more than 16 Kg; it is also possible to arrange the product in length, width and height simultaneously to obtain the combined size (40 cm x 75cm x 60 cm) and weight (48 Kg) of the product in a2 x 3 x 2 arrangement, where the packaging performance requirement XQ3 is: the length of the inner diameter of the carton is more than 40cm, the width of the inner diameter is more than 75cm, the height of the inner diameter is more than 60cm, the rated load is more than 48Kg, and the anti-skid capacity is more than FH 1. It will be appreciated that there are many ways of arranging the combination, and that different arrangements may have different performance requirements for the package, and these are only some examples.
Regarding the anti-slip capability in the above requirement XQ3, since the density of the commodity is large and the weight of a single box exceeds a set weight value, the carton needs to have a certain anti-slip capability to avoid collision and extrusion of people or objects in the surrounding environment caused by slip when the carton is placed at a sloping position. The antiskid capacity belongs to a specific function in corrugated paper specification parameters, and the specific function required is determined according to the density of commodities and the load of a single box.
When the optional carton models are determined subsequently, the models determined by different arrangement modes are different, for example, the requirement XQ2 can determine a plurality of optional carton models including the model M4, wherein the model M4 is an optional carton model with the size of C4, is composed of single-layer B-flute corrugated boards, and has the anti-slip capability of FH2 level, and one model M4 can be used for containing 4 sets of commodities and needs 150 cartons in total; the requirement XQ3 can identify various optional carton models including model M5, wherein model M5 is an optional carton model with C5 size, is composed of double layers of BC-corrugated calcium plastic corrugated paper boards, and has the anti-slip capability of FH3 grade, and one model M5 can be used for containing 12 sets of commodities, and 50 cartons are needed. Both C4 and C5 are located in a size floating interval that calculates a size value by a factor of 1.1 based on the size of the combination of commodities after the permutation and combination. Different arrangement modes correspond to different performance requirements, and each type corresponds to a plurality of selectable models, so that a plurality of models can be selected.
In one embodiment, the fuzzy evaluation calculation module calculates the contribution value by:
wherein Gi is a contribution value of the i-th seed item evaluation item, the contribution value set Gtotal = (G1, G2, …, Gm), m is the number of the subclass item evaluation items (abbreviated as subclass evaluation items), J is the number of data items of production data, and fig. 2 shows only the production data items Ji of pulp, binder, water, electricity, steam, hydrocarbon, mucilage wastewater, coal slag, particulate matter and the like as the number of types of production data corresponding to the i-th evaluation item, for example, for the subclass evaluation item "plant fiber", J1=2 is respectively pulp 1 and pulp 2, and pulp 1 and pulp 2 are respectively two types of pulp made of different plant fibers; for another example, the subclass of the evaluation term "ozone depletion" is ranked as the 15 th evaluation term, and J15=2, which are hydrocarbon compounds and nitrogen oxides, respectively. Dj is the data value of the jth data item, and Wij is the evaluation influence coefficient of the jth production data on the ith evaluation item, that is, Wij is the evaluation influence coefficient of Dj. The following constraints are imposed on the evaluation influence coefficient:
the constraint is such that for the ith evaluation term, the sum of the various evaluation impact coefficients equals 1.
The calculation process of the contribution value of the evaluation item is described by taking ozone depletion as an example. Referring to fig. 3, assuming that only hydrocarbon compounds and nitrogen oxides among all production data cause ozone layer destruction (J15 = 2) and ozone layer destruction is the 15 th evaluation item, assuming that the model of the optional carton produced is model M4, M4 has two processes G1 and G2 producing hydrocarbon compounds in amounts of 0.1 and 0.2, respectively, and three processes G1, G2 and G3 producing nitrogen oxides in amounts of 0.1, 0.05 and 0.05, respectively, which all contribute to ozone layer destruction, so that when a plurality of production data items all contribute to the same evaluation item, the value of the evaluation item is the sum of the data values of the respective production data items, the hydrocarbon compound is the 21 st item among all the production data items, and the 22 nd item among all the production data items, the production data of the hydrocarbon compound is D22=0.1+0.2=0.3, the production data of nitrogen oxides is D23=0.1+0.05+0.05= 0.2.
Since hydrocarbon compounds have a greater effect on ozone layer depletion than nitrogen oxides, assuming that hydrocarbon compounds have an evaluation influence coefficient w15,22=0.8 on ozone layer depletion and nitrogen oxides have an evaluation influence coefficient w15,23=0.2 on ozone layer depletion, the sum of the two is equal to 1, the specific evaluation influence coefficient depends on the degree of influence of the production data item on the evaluation item, and since only the two cause ozone layer depletion, the evaluation influence coefficients of the other production data are both 0. Contribution value of ozone layer depletion at this time:
G15=D22*w15,22+D23*w15,23=0.3*0.8+0.2*0.2=0.28。
in the above calculation process, assuming that nitrogen oxide has an effect not only on ozone layer destruction but also on global warming of the 14 th seed evaluation item, when calculating D14, production data of nitrogen oxide should be included, except that the evaluation influence coefficients w14,23 of nitrogen oxide on ozone layer destruction may be different from the evaluation influence coefficients w15,23 on ozone layer destruction, and thus the values of D23 w15,23 are different from the values of D23 w14,23, so that the contribution value of nitrogen oxide on global warming is different from the contribution value on ozone layer destruction.
It should be noted that, in each evaluation item, material cost, energy cost, pollution cost, and time cost are all costs of consumption type, the smaller the cost is, the more favorable the production is, the cost saving is gain type cost, the larger the cost is, the more favorable the production is, therefore, the positive and negative signs of the weight of cost saving are opposite to those of other evaluation items, and a negative value form is adopted to participate in the calculation.
In one embodiment, the fuzzy evaluation calculation module performs fuzzy evaluation on the contribution value of each evaluation item through the following steps 410 to 430 to obtain a fuzzy evaluation matrix:
and step 410, acquiring the evaluation level of each evaluation item and the corresponding standard value range thereof.
Continuing to take the above-mentioned contribution value of ozone layer depletion as an example, assume that the evaluation level of ozone layer depletion has four levels, namely strong, medium and weak, and the standard value range of the strong evaluation level is that the contribution value is not less than 1, the standard value range of the strong evaluation level is that the contribution value is less than 1 and not less than 0.5, the standard value range of the medium evaluation level is that the contribution value is less than 0.5 and not less than 0.1, and the standard value range of the weak evaluation level is that the contribution value is less than 0.1. And other evaluation items are provided with corresponding evaluation levels and standard value ranges.
And 420, acquiring a membership degree judgment chart corresponding to the contribution value, and obtaining a membership degree vector according to the membership degree judgment chart.
When the value of contribution of ozone depletion calculated in the above is 0.28, the evaluation level of ozone depletion is moderate. However, in order to make the calculation result more accurate, the final fuzzy evaluation result is performed by means of the membership function.
Different contribution values are provided with different membership degree determination charts, the membership degree determination charts are obtained by taking a membership degree function as a core, and the membership degree function can be a Gaussian membership degree function, a generalized bell-shaped membership degree function, a S-shaped membership degree function, a trapezoidal membership degree function, a triangular membership degree function, a Z-shaped membership degree function and the like. The line shape (curve) of the membership function is similar to the normal distribution, the contribution value is taken as the highest point of the function curve, and a certain length of expansion is performed on the X axis, for example, the calculated contribution value of the ozone depletion is 0.28, in the membership determination chart of the Gaussian membership function of 0.28, the expansion distance of the highest point towards the positive direction and the negative direction of the X axis is 0.1, the expansion distance interval of 0.28 is 0.18 to 0.38, and the expansion distance is 0.1 or less and 0.18<0.28<0.38<0.5, so the membership is all located in the middle evaluation level. Assuming that the expansion distance is 0.2, the expansion distance interval of 0.28 is 0.08 to 0.48, where 0.08<0.1, the membership in this case includes not only medium but also weak, and the values of both can be calculated as the ratio of the areas of the curve in the associated evaluation level standard value range, and also as the ratio of the X-axis length of the curve in the associated evaluation level standard value range, for example, in the latter manner, the X-axis length of the expansion distance in the medium standard value range is 0.38, and the X-axis length in the weak standard value range is 0.02, so that the ozone layer destruction membership vector is [0, 0, 0.95, 0.05], where 0.95 is the membership of the "medium" evaluation level, calculated from 0.38/(0.2.2), and 0.05 is the membership of the "weak" evaluation level, calculated from 0.02/(0.2X 2).
And 430, obtaining a fuzzy evaluation matrix according to the membership vector.
Assuming that there are N evaluation terms, each evaluation term has a membership row vector including four elements, and thus, the evaluation terms are collected to obtain a fuzzy evaluation matrix of N rows and 4 columns. It can be understood that no matter how the standard value range of the evaluation items is selected or set, the number of the evaluation levels of each evaluation item is the same, and taking the above four-level evaluation levels from stronger to weaker as an example, the evaluation levels of all the evaluation items are four levels.
In one embodiment, the fuzzy evaluation calculation module determines the evaluation weight of the evaluation item through the following steps 510 to 520.
Step 510, determining the parent item to which each evaluation item belongs, and calculating the parent item weight of the parent item.
As can be seen from the foregoing description of step 400, the present embodiment determines the parent items of the five evaluation items, which are respectively the material cost item, the energy cost item, the cost saving item, the pollution cost item, and the time cost item. The parent item weights of the five parent items are calculated as follows.
Firstly, acquiring all participation items to obtain a participation set, determining the key degree grade of each participation item relative to other participation items in the participation set, and acquiring a key degree matrix.
For the calculation of the parent class weight, the participating class entries are the five parent class entries, and the participating set B = (B1, B2, …, B5). The criticality grade is a numerical value used for comparing criticality among all the participating category items belonging to the same level, and the higher the criticality grade is, the greater the influence of the comparing party on the upper object of the evaluation item is compared with the compared party. Specifically, since the participating class item at this time is a parent class item in the evaluation item, a higher-order object of the participating class item is the overall evaluation value a.
Table 1 is a parent item criticality rating table, which uses the foregoing emphasis on using an evaluation system with material cost as a key, so that the material cost parent item b1 is most critical, b1 is 1 relative to its criticality rating, and 1 represents that two parent items to be compared are equally important. b1 has a criticality rating of 1.5 relative to the energy cost parent, b2, 3 relative to the cost savings parent, t3, 2 relative to the pollution cost parent, t4, and 1.5 relative to the time cost parent, t 4. When the comparing party and the compared party exchange the comparison position, the key degree grades are reciprocal. As can be seen from table 1, the key levels are: b1> b2= b5> b4> b 3.
TABLE 1 level table of criticality of parent item
A criticality matrix F is obtained according to each criticality level in table 1:
the variable values of the diagonal line in the criticality matrix are all 1, and the upper right and lower left of the diagonal line are symmetrical relative to the diagonal line.
Then, normalizing each row of the criticality matrix, summing each row of the grade matrix to obtain a column matrix, and normalizing elements in the column matrix to obtain the weight of each evaluation item.
Normalizing F to obtain a normalized matrix Hf, summing the normalized matrix Hf according to rows to obtain five elements in the column matrixes Hf 'and Hf', normalizing the five elements to obtain the weights of the five father items, and sequentially sequencing the weights in the normalized column matrixes.
And 520, calculating the evaluation item weight of each child evaluation item included in each parent item according to the parent item weight.
The evaluation item weight of each sub-class evaluation item is obtained by the product of the self weight and the weight of the parent class item to which the evaluation item weight belongs, the self weight of each sub-class evaluation item is the same as the calculation method of the weight of the parent class item, the water, electricity and coal sub-class items contained in the energy cost parent class item are taken as an example, all the sub-class evaluation items are firstly obtained to obtain a participation set, the participation set at the moment is water, electricity and coal, then the key degree grade of each sub-class item in the three sub-class items relative to other sub-class items in the participation set is determined to obtain a key degree matrix, then each row of the key degree matrix is normalized, each row of the grade matrix is summed to obtain a column matrix, and elements in the column matrix are normalized to obtain the weight of each sub-class item. And finally, multiplying the obtained weight of each subclass item by the weight of the parent item of b2 to obtain the final weight of the subclass evaluation items of the three subclass items. The subclass evaluation term weight is finally expressed in the form of a single row vector containing N elements, where N is the number of subclass evaluation terms.
An embodiment of the model-based automated design computer device for shaped packaging cartons disclosed in the present application is described in detail below with reference to fig. 4. The embodiment is a device for implementing the automatic design method of the special-shaped packaging carton.
As shown in fig. 4, the computer apparatus disclosed in this embodiment mainly includes:
the performance requirement determining module is used for acquiring the attribute information and the quantity of the commodities to be sent so as to determine the packaging performance requirements of the commodities;
the carton model determining module is used for determining the optional carton models meeting the packaging performance requirements and the required number of the optional carton models from a carton model library;
a production data acquisition module for acquiring production data generated by unit production volume of each of the selectable carton models;
the fuzzy evaluation calculation module is used for calculating the contribution value of the production data of each optional carton model to each evaluation item and carrying out fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix;
and the evaluation result calculation module is used for optimizing the carton model from the optional carton models based on the evaluation weight of the evaluation item, the fuzzy evaluation matrix and the required carton number.
In one embodiment, the attribute information includes size information, weight information, and shape information, and the packaging performance requirements include length, width, height of an inner diameter, rated load bearing, specific function;
the performance requirement determination module comprises:
the arrangement combination unit is used for carrying out arrangement combination on the goods to be sent in at least one direction of length, width and height according to the shape information;
and the requirement determining unit is used for obtaining the size information and the weight information of the commodity combination obtained after the arrangement and the combination according to the size information and the weight information of the commodity to be sent, and further determining the packaging performance requirements of the commodity combination and the single commodity to be sent.
In one embodiment, the production data includes a raw material type and a consumption amount thereof, an energy type and a consumption amount thereof, a time consumption amount, a recycling species in the by-product and a generation amount thereof, and a waste material type and a generation amount thereof.
In one embodiment, the evaluation terms include a material cost term, an energy cost term, a time cost term, a pollution cost term, and a cost savings term.
In one embodiment, the fuzzy evaluation calculation module calculates the contribution value by:
wherein Gi is the contribution value of the ith evaluation item, Ji is the type number of the production data corresponding to the ith evaluation item, Dj is the data value of the jth data item, Wij is the evaluation influence coefficient of the jth production data on the ith evaluation item, and,
。
in one embodiment, the fuzzy evaluation calculation module performs fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix by the following steps:
obtaining the evaluation level of each evaluation item and the corresponding standard value range;
obtaining a membership degree judging chart corresponding to the contribution value, and obtaining a membership degree vector according to the membership degree judging chart;
and obtaining a fuzzy evaluation matrix according to the membership vector.
In one embodiment, the fuzzy evaluation calculation module determines the evaluation weight of the evaluation item by:
determining a parent item to which each evaluation item belongs, and calculating the weight of the parent item;
and calculating the evaluation item weight of each child evaluation item included in each parent item according to the parent item weight.
In one embodiment, the fuzzy evaluation calculation module calculates the class term and the evaluation term weight by:
acquiring all participation items to obtain a participation set, and determining the key degree grade of each participation item relative to other participation items in the participation set to obtain a key degree matrix;
normalizing each row of the criticality matrix, summing each row of the grade matrix to obtain a column matrix, and normalizing elements in the column matrix to obtain the weight of each participating category item.
The division of modules, units or components herein is merely a logical division, and other divisions may be possible in an actual implementation, for example, a plurality of modules and/or units may be combined or integrated in another system. Modules, units, or components described as separate parts may or may not be physically separate. The components displayed as cells may or may not be physical cells, and may be located in a specific place or distributed in grid cells. Therefore, some or all of the units can be selected according to actual needs to implement the scheme of the embodiment.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for automatically designing a special-shaped packaging carton based on a model is characterized by comprising the following steps:
acquiring attribute information and quantity of commodities to be sent, and further determining the packaging performance requirements of the commodities;
optional carton models meeting the packaging performance requirements and the required number of the optional carton models are determined from a carton model library;
obtaining production data generated by unit production capacity of each optional carton model;
calculating the contribution value of the production data of each optional carton model to each evaluation item, and carrying out fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix;
and optimizing the carton model from the optional carton models based on the evaluation weight of the evaluation item, the fuzzy evaluation matrix and the required carton number.
2. The automatic design method for the special-shaped packaging carton according to claim 1, wherein the attribute information comprises size information, weight information and shape information, and the packaging performance requirements comprise length, width, height of inner diameter, rated load bearing, specific function;
the determining of the packaging performance requirements of the commodity comprises: and carrying out arrangement combination in at least one direction of length, width and height on the commodities to be sent according to the shape information, obtaining size information and weight information of the commodity combination obtained after the arrangement combination according to the size information and the weight information of the commodities to be sent, and further determining the respective packaging performance requirements of the commodity combination and the single commodities to be sent.
3. The automatic design method of the special-shaped packaging carton according to claim 1, wherein the production data comprises the types of raw materials and the consumption amount thereof, the types of energy and the consumption amount thereof, the consumption amount of time, the types of recycling species in the byproducts and the generation amount thereof, and the types of waste materials and the generation amount thereof.
4. The automatic design method of the special-shaped packaging carton according to claim 1, wherein the contribution value is calculated by the following formula:
wherein Gi is the contribution value of the ith evaluation item, Ji is the type number of the production data corresponding to the ith evaluation item, Dj is the data value of the jth data item, Wij is the evaluation influence coefficient of the jth production data on the ith evaluation item, and,
。
5. the automatic design method for the special-shaped packaging carton according to claim 4, wherein the fuzzy evaluation of the contribution value of each evaluation item to obtain a fuzzy evaluation matrix comprises the following steps:
obtaining the evaluation level of each evaluation item and the corresponding standard value range;
obtaining a membership degree judging chart corresponding to the contribution value, and obtaining a membership degree vector according to the membership degree judging chart;
and obtaining a fuzzy evaluation matrix according to the membership vector.
6. A model-based automatic design computer device for special-shaped packaging cartons, which is characterized by comprising:
the performance requirement determining module is used for acquiring the attribute information and the quantity of the commodities to be sent so as to determine the packaging performance requirements of the commodities;
the carton model determining module is used for determining the optional carton models meeting the packaging performance requirements and the required number of the optional carton models from a carton model library;
a production data acquisition module for acquiring production data generated by unit production volume of each of the selectable carton models;
the fuzzy evaluation calculation module is used for calculating the contribution value of the production data of each optional carton model to each evaluation item and carrying out fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix;
and the evaluation result calculation module is used for optimizing the carton model from the optional carton models based on the evaluation weight of the evaluation item, the fuzzy evaluation matrix and the required carton number.
7. The automated design computer device for shaped packaging cartons as claimed in claim 6, wherein the attribute information includes size information, weight information and shape information, and the packaging performance requirements include length, width, height of inside diameter, rated load bearing, specific function;
the performance requirement determination module comprises:
the arrangement combination unit is used for carrying out arrangement combination on the goods to be sent in at least one direction of length, width and height according to the shape information;
and the requirement determining unit is used for obtaining the size information and the weight information of the commodity combination obtained after the arrangement and the combination according to the size information and the weight information of the commodity to be sent, and further determining the packaging performance requirements of the commodity combination and the single commodity to be sent.
8. The automatic design computer device for the special-shaped packaging carton as claimed in claim 6, wherein the production data comprises the types of raw materials and the consumption amount thereof, the types of energy and the consumption amount thereof, the consumption amount of time, the types of recycling species in the by-products and the generation amount thereof, and the types of waste materials and the generation amount thereof.
9. The automated design computer apparatus for shaped packaging cartons as claimed in claim 6, wherein said fuzzy evaluation calculation module calculates the contribution value by the following formula:
wherein Gi is the contribution value of the ith evaluation item, Ji is the type number of the production data corresponding to the ith evaluation item, Dj is the data value of the jth data item, Wij is the evaluation influence coefficient of the jth production data on the ith evaluation item, and,
。
10. the automatic design computer device for the special-shaped packaging cartons as claimed in claim 9, wherein the fuzzy evaluation calculation module performs fuzzy evaluation on the contribution value of each evaluation item to obtain a fuzzy evaluation matrix by the following steps:
obtaining the evaluation level of each evaluation item and the corresponding standard value range;
obtaining a membership degree judging chart corresponding to the contribution value, and obtaining a membership degree vector according to the membership degree judging chart;
and obtaining a fuzzy evaluation matrix according to the membership vector.
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