An Internet of Things-based product life cycle assessment system and method

Abstract

The present invention discloses an Internet of Things-based product life cycle assessment system and method, which relates to the technical field of product assessment. According to the order information, the transportation mode of the product is confirmed, and the influence result of the product storage loss uniformity on the transportation loss under the selected transportation mode is analyzed. Then, an outbound plan and a placement plan are formulated based on the influence result. During the transportation process, the vibration data of the product is monitored. When the set threshold is exceeded, the product stacking data is obtained to confirm the offset and damage conditions of the product. This solution improves the accuracy of product outbound selection, reduces the loss of subsequent products during transportation, and can also more deeply understand the situation of the product during transportation, improve the protection accuracy during transportation, reduce the impact on transportation efficiency, and ensure the safety of the product during transportation.

Description

Technical Field

[0001] The present invention relates to the technical field of product evaluation, and particularly to an Internet of Things-based product life cycle evaluation system and method. Background Art

[0002] Product life cycle evaluation based on the Internet of Things can collect data at all stages of the product's entire life cycle using Internet of Things technology, including the storage stage and the transportation stage, etc., and perform data analysis to evaluate the life loss of the product. Analyzing the storage stage and the transportation stage can provide a reference for the selection of product outbound and transportation plans for enterprises, ensure the safe transportation of products, and reduce losses.

[0003] In the prior art, during the product outbound and transportation stages, products to be outbound are mainly selected according to the ease of outbound and the length of storage time, and during the transportation stage, the vibration of the products is mainly monitored. Obviously, this outbound and transportation monitoring method has at least the following deficiencies: 1. The environment in the warehouse will affect the life of the products, but the storage time and the environment of the products in the warehouse are different, so the degree of influence on the product loss is also different. In addition, different transportation plans and placement plans have different degrees of influence on products with different losses. When the transportation method has a low impact on the product life under different losses, products with different degrees of loss can be selected for transportation, but when the transportation method has a high impact on the product life under different losses, products with relatively average storage losses are selected for transportation to reduce the loss of product life during transportation. However, the prior art lacks an analysis of the influence of storage loss uniformity on transportation loss and cannot provide an effective reference for the selection of product outbound, thus unable to reduce the subsequent loss of products during transportation.

[0004] 2. When the vibration during product transportation is too large, it may cause the placement position of the products to shift, resulting in phenomena such as extrusion between products, causing product damage. Therefore, when the vibration during transportation is too large, monitoring the offset and damage of the products can more deeply understand the situation of the products during transportation, improve the accuracy of protection during transportation, reduce the impact on transportation efficiency, and at the same time ensure the safety of the products during transportation. However, the prior art lacks further monitoring of the offset and damage of the products after vibration, thereby increasing the number of early warnings during transportation and reducing the transportation efficiency. Summary of the Invention

[0005] Aiming at the above-mentioned existing technical deficiencies, the purpose of the present invention is to provide an Internet of Things-based product life cycle evaluation system and method.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides an Internet of Things-based product life cycle assessment system, including the following modules: A data acquisition module, configured to acquire product orders, and acquire product inventory data, transportation data, and loss data for each batch of transported products.

[0007] A transportation selection module, configured to utilize the product inventory data, transportation data, and loss data for each batch of transported products to formulate an outbound plan and a transportation plan for the product order, and provide corresponding feedback.

[0008] A transportation tracking module, configured to track the transportation of the product order when the product order is being transported, acquire the tracking data of the product order, evaluate the product transportation status, and provide corresponding feedback.

[0009] In the second aspect, the present invention provides an Internet of Things-based product life cycle assessment method, including: S1. Data acquisition: Acquire product orders, and acquire product inventory data, transportation data, and loss data for each batch of transported products.

[0010] S2. Transportation selection: Utilize the product inventory data, transportation data, and loss data for each batch of transported products to formulate an outbound plan and a transportation plan for the product order, and provide corresponding feedback.

[0011] S3. Transportation tracking: When the product order is being transported, track the transportation of the product, acquire the tracking data of the product order, evaluate the product transportation status, and provide corresponding feedback.

[0012] The beneficial effects of the present invention are as follows: The present invention provides an Internet of Things-based product life cycle assessment system and method. According to the order information, the transportation method of the product is confirmed, and the influence result of the product storage loss uniformity on the transportation loss under the selected transportation method is analyzed. Then, an outbound plan and a placement plan are formulated based on the influence result. Then, during the transportation process, the vibration data of the product is monitored. When the set threshold is exceeded, the product stacking data is acquired to confirm the offset and damage conditions of the product. This solution improves the accuracy of product outbound selection, reduces the subsequent product loss during transportation, and at the same time can more deeply understand the situation of the product during transportation, improve the protection accuracy during transportation, reduce the impact on transportation efficiency, and ensure the safety of the product during transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0014] Figure 1 This is a schematic diagram of the connection of the system structure of the present invention.

[0015] Figure 2 This is a schematic diagram of the implementation steps of the method of the present invention. Specific implementation manners

[0016] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0017] Embodiment 1:

[0018] Please refer to Figure 1 As shown, an Internet of Things-based product life cycle assessment system includes the following modules: a data acquisition module, a transportation selection module, a transportation tracking module, and a database.

[0019] The data acquisition module is used to obtain product orders and obtain product inventory data, transportation data, and loss data for each batch of transportation.

[0020] It should be noted that product orders are obtained from the enterprise order management center; the product inventory data includes environmental data, extrusion data, and storage duration. A number of sensors are arranged in the warehouse to collect environmental data. The environmental sensors include temperature sensors, humidity sensors, etc., and the environmental data includes temperature, humidity, etc.; the extrusion data includes the pressure received by the product and the contact area with other products, etc. The pressure sensor is used to collect the pressure received by the product from other products, and the camera is used to collect the storage images of the product. The contact area between the product and other products is obtained from the storage images. The warehousing time and the outbound time of the product are recorded after the product is warehoused and out of the warehouse. The time interval between the warehousing time and the outbound time is the storage duration.

[0021] The transportation data includes transportation mode, placement plan, and road condition data. When the product is transported, the transportation mode and the placement plan are recorded. At the same time, the transportation route is generated using map software, and the real-scene image of the transportation route is obtained from the map software. The road condition data is obtained from the real-scene image, and the road condition data includes route length, number of concave areas, total area of concave areas, number of convex areas, and total area of convex areas, etc.

[0022] The loss data includes a transportation loss coefficient. After the product transportation is completed, manual inspection is carried out to screen out the products with large life losses and unable to be used normally as loss products. The number of loss products is counted and divided by the total number of products to obtain the transportation loss coefficient.

[0023] A transportation selection module, which is used to formulate an outbound plan and a transportation plan for product orders by using the product inventory data, transportation data, and loss data of each batch of transportation, and provide corresponding feedback.

[0024] In a specific embodiment, the process of formulating the outbound plan for product orders is as follows: Obtain the storage data of each product in each batch of transportation from the product inventory data of each batch of transportation, and calculate the storage loss coefficient of each product in each batch of transportation.

[0025] Preferably, the calculation process of the storage loss coefficient of each product in each batch of transportation is as follows: Obtain the environmental data, extrusion data, and storage duration from the storage data of each product in each batch of transportation, and denote them as , and , where v represents the number of each batch of transportation, v is a positive integer, and x represents the number of each product, x is a positive integer.

[0026] Using the calculation formula:

[0027] , obtain the storage loss coefficient of the xth product in the vth batch of transportation. In the formula, HJ represents the preset suitable storage environment data of the product, and JY represents the preset allowable extrusion data of the product.

[0028] It should be noted that the preset suitable storage environment data and allowable extrusion data of the product are formulated by the staff after quality testing of the product after production.

[0029] Obtain the transportation method, placement plan, and road condition data of each batch of transportation from the transportation data of each batch of transportation, and obtain the transportation loss coefficient of each product after each batch of transportation from the loss data of each batch of transportation.

[0030] Obtain the product quantity and the product transportation destination from the product order. Generate the product order transportation route according to the product transportation destination, and obtain the road condition data of the product order transportation route from the map. Compare the product quantity of the product order and the road condition data of the transportation route with the product quantity interval of each transportation method and the road condition data interval of the transportation route in the database respectively to confirm the transportation method of the product order.

[0031] It should be noted that the enterprise staff formulate the product quantity interval of each transportation method and the road condition data interval of the transportation route based on the consideration of transportation cost and transportation duration. When the product quantity of the product order and the road condition data of the transportation route are respectively within the product quantity interval of a certain transportation method and the road condition data interval of the transportation route, it indicates that this transportation method is the transportation method of the product order.

[0032] Select each batch of transportation with the same transportation method as that of the product order as each reference batch of transportation, and then extract the storage loss coefficient, placement plan, and transportation loss coefficient of each product in each reference batch of transportation, and calculate the influence result of the product storage loss uniformity on the transportation loss, where the influence result includes values of 1 and -1.

[0033] Preferably, the calculation process of the influence result of the product storage loss uniformity on the transportation loss is as follows: Using the storage loss coefficient in each reference batch of transportation, confirm the storage loss uniformity level of the products in each reference batch of transportation, and thus count the placement plan and the transportation loss coefficient of each product corresponding to each reference batch of transportation at each storage loss uniformity level, and accumulate the transportation loss coefficients of each product corresponding to each reference batch of transportation at each storage loss uniformity level to obtain the total product transportation loss coefficient corresponding to each reference batch of transportation at each storage loss uniformity level.

[0034] It should be noted that obtain the product loss coefficients corresponding to each storage loss uniformity level from the database, compare the storage loss coefficients in each reference batch of transportation with the product loss coefficients corresponding to each storage loss uniformity level, and obtain the storage loss uniformity level of the products in each reference batch of transportation. When the storage loss uniformity level is larger, it indicates that the storage losses between products are more average.

[0035] In the above, the product loss coefficients corresponding to each storage loss uniformity level are set by enterprise staff.

[0036] Using the placement plan and product transportation loss coefficient corresponding to each storage loss uniformity level for each reference batch of transportation, count the total product transportation loss coefficients in each placement plan corresponding to each storage loss uniformity level, denoted as , where y represents the number of each storage loss uniformity level, f represents the number of each placement plan, z represents the number of each total product transportation loss coefficient, and y, f, and z are all positive integers.

[0037] Influence evaluation model expression:

[0038] where represents the influence result of the product storage loss uniformity on the transportation loss, , , respectively represent the difference rate between the total product transportation loss coefficients in the placement plan, the difference rate between the total product transportation loss coefficients between the placement plans, and the difference rate between the total product transportation loss coefficients between the storage loss uniformity levels; is the preset permitted difference rate, , , They respectively represent the weight coefficient of the difference rate between the total product transportation loss coefficients in the set placement schemes, the weight coefficient of the difference rate of the total product transportation loss coefficients between the placement schemes, and the weight coefficient of the difference rate of the total product transportation loss coefficients between the storage loss uniformity levels.

[0039] It should be noted that the preset permitted difference rate is formulated by the enterprise staff using the enterprise's historical transportation-related data. 、 、 。

[0040] Among them,

[0041] 、

[0042] 、

[0043] , in the formula, represents the (z + 1)-th total product transportation loss coefficient corresponding to the f-th placement scheme of the y-th storage loss uniformity level, represents the z-th total product transportation loss coefficient corresponding to the (f + 1)-th placement scheme of the y-th storage loss uniformity level, represents the z-th total product transportation loss coefficient corresponding to the (f + 1)-th placement scheme of the (y + 1)-th storage loss uniformity level, represents the preset permitted difference of the total product transportation loss coefficient, and Y, F, and Z respectively represent the number of storage loss uniformity levels, the number of placement schemes, and the number of total product transportation loss coefficients.

[0044] It should be noted that the preset permitted difference of the total product transportation loss coefficient is formulated by the enterprise staff using the enterprise's historical transportation-related data.

[0045] When the influence result is 1, it indicates that the influence of storage loss uniformity on transportation loss is small; otherwise, it indicates that the influence of storage loss uniformity on transportation loss is large.

[0046] Based on the influence result of product storage loss uniformity on transportation loss, and obtaining the storage data of each product in the inventory from the inventory records, calculate the storage loss coefficient of each product in the inventory, and confirm the outbound plan of the product order according to the order quantity in the product order.

[0047] Preferably, the process of confirming the outbound plan of the product order is as follows: when the influence result of product storage loss uniformity on transportation loss is 1, sort the storage loss coefficients of each product in the inventory from large to small in sequence, and use the sorting result as the product selection order, and then select them in sequence until the number of selected products is the same as the order quantity in the product order, and then stop selecting.

[0048] When the influence result of the product storage loss uniformity on the transportation loss is -1, use the analysis formula: Obtain the difference rate of the total product transportation loss coefficient for the y-th storage loss uniformity level , and take each storage loss uniformity level with a total product transportation loss coefficient difference rate less than or equal to the preset allowable difference rate as each allowable storage loss uniformity level.

[0049] Obtain the product loss coefficient intervals corresponding to each allowable storage loss uniformity level from the database, then select the union as the allowable product loss coefficient interval, then take each product in the inventory with a storage loss coefficient within the allowable product loss coefficient interval as each candidate product, sort the candidate products in descending order according to the storage loss coefficient, and take the sorting result as the product selection order, then select them in turn until the number of selected candidate products is the same as the order quantity in the product order, and stop selecting.

[0050] If the number of candidate products is less than the order quantity in the product order, sort the remaining products other than the candidate products in ascending order according to the difference between the storage loss coefficient and the allowable product loss coefficient interval, and then select the remaining products in turn until the sum of the number of selected candidate products and the number of remaining products is the same as the order quantity in the product order, and stop selecting. Take the selected products as the outbound plan for the product order.

[0051] It should be noted that when the storage loss coefficient of a certain remaining product is greater than the upper limit value of the allowable product loss coefficient interval, the difference between the storage loss coefficient of the remaining product and the allowable product loss coefficient interval is the difference between the storage loss coefficient of the remaining product and the upper limit value of the allowable product transportation loss coefficient. Conversely, when the storage loss coefficient of a certain remaining product is less than the lower limit value of the allowable product loss coefficient interval, the difference between the storage loss coefficient of the remaining product and the allowable product loss coefficient interval is the difference between the storage loss coefficient of the remaining product and the lower limit value of the allowable product transportation loss coefficient.

[0052] In another specific embodiment, the process of formulating the transportation plan for the product order is as follows: S21. When the influence result of the product storage loss uniformity on the transportation loss is 1, use the calculation formula:

[0053] , obtain the difference rate between the total product transportation loss coefficients in the f-th placement plan , and select the placement plan with the smallest difference rate between the total product transportation loss coefficients as the target placement plan.

[0054] S22. When the influence result of the product storage loss uniformity on the transportation loss is -1, according to According to the calculation method, calculate the difference rate between the total product transportation loss coefficients in each placement plan at each allowable storage loss uniformity level, and select the placement plan with the smallest difference rate between the total product transportation loss coefficients at each allowable storage loss uniformity level as the target placement plan. Then, use the transportation method and the target placement plan as the transportation plan for the product order.

[0055] The transportation tracking module is used to track the product transportation when the product order is transported, obtain the tracking data of the product order, evaluate the product transportation status, and give corresponding feedback.

[0056] In a specific embodiment, the specific process of the product transportation tracking is as follows: Before the product transportation, use a camera to collect the initial product stacking image, and evenly arrange several vibration sensors among the products. Each vibration sensor detects the vibration data in real time. When the vibration data of at least one vibration sensor is greater than the preset vibration data threshold, use the camera in the carriage to collect the product stacking image until the transportation is completed. Then, use the initial product stacking image and each product stacking image during the transportation process as the tracking data of the product order.

[0057] In another specific embodiment, the process of evaluating the product transportation status is as follows: Extract the initial product stacking image from the tracking data, and then locate the initial center point position of each product in the initial product stacking image as the initial position of each product. Obtain the center point position of each product from each product stacking image as the position of each product in each product stacking image, and obtain the damage data of each product from each product stacking image, where r represents the number of each product stacking image, x represents the number of each product, and both r and x are positive integers.

[0058] According to the initial position of each product and the position of each product in each product stacking image, obtain the distance between the position of each product in each product stacking image and the initial position as the deviation distance of each product in each product stacking image. Normalize the damage data and deviation distance of each product in each product stacking image, and denote them as and .

[0059] Use the transportation status evaluation model to analyze the product transportation status value. The product transportation status value includes numerical values of 1 and -1. When the product transportation status value is 1, it indicates that the product transportation status is in a stable state and the product life loss is small. On the contrary, when the product transportation status value is -1, it indicates that the product transportation status is in an unstable state and the product life loss is large.

[0060] Preferably, the expression of the transportation status evaluation model is:

[0061] , where in the formula, It represents the product transportation status value, where SH and L respectively represent the preset allowable damage data and allowable deviation distance, and R and X respectively represent the number of product stacking images and the number of products.

[0062] A database for storing the product quantity intervals of each transportation mode, the road condition data intervals of the transportation routes, and the product loss coefficient intervals corresponding to each storage loss uniformity level.

[0063] Embodiment 2:

[0064] A method for evaluating the product life cycle based on the Internet of Things, including: S1. Data acquisition: Obtain product orders and acquire the product inventory data, transportation data, and loss data of each batch of transportation.

[0065] S2. Transportation selection: Utilize the product inventory data, transportation data, and loss data of each batch of transportation to formulate the outbound plan and transportation plan for the product order and give corresponding feedback.

[0066] S3. Transportation tracking: When the product order is in transportation, conduct product transportation tracking, obtain the tracking data of the product order, evaluate the product transportation status, and give corresponding feedback.

[0067] In the embodiment of the present invention, according to the order information, the transportation mode of the product is confirmed, and the influence result of the storage loss uniformity of the product under the selected transportation mode on the transportation loss is analyzed. Then, an outbound plan and a placement plan are formulated based on the influence result. Then, during the transportation process, the vibration data of the product is monitored. When the set threshold is exceeded, the product stacking data is obtained to confirm the offset and damage conditions of the product. This solution improves the accuracy of product outbound selection, reduces the subsequent product loss during transportation, and at the same time can more deeply understand the situation of the product during transportation, improve the protection accuracy during transportation, reduce the impact on transportation efficiency, and ensure the safety of the product during transportation.

[0068] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should fall within the protection scope of the present invention.

Claims

1. An Internet of Things-based product life cycle assessment system, characterized in that, It includes the following modules: A data acquisition module, which is used to acquire product orders and obtain product inventory data, transportation data, and loss data for each batch of transportation; A transportation selection module, which is used to formulate an outbound plan and a transportation plan for the product order by using the product inventory data, transportation data, and loss data for each batch of transportation, and provide corresponding feedback; The specific process of formulating the outbound plan for the product order is as follows: Obtain the storage data of each product in each batch of transportation from the product inventory data of each batch of transportation, and calculate the storage loss coefficient of each product in each batch of transportation; Obtain the transportation method, placement plan, and road condition data of each batch of transportation from the transportation data of each batch of transportation, and obtain the transportation loss coefficient of each product after each batch of transportation from the loss data of each batch of transportation; The loss data includes the transportation loss coefficient. After the product transportation is completed, manual inspection is carried out to screen out the products that cannot be used normally as loss products, count the number of loss products, and divide it by the total number of products to obtain the transportation loss coefficient; Obtain the road condition data of the transportation route of the product order and confirm the transportation method of the product order; use the transportation method of the product order to calculate the influence result of the storage loss uniformity of the product on the transportation loss, where the influence result includes values of 1 and -1; Based on the influence result of the storage loss uniformity of the product on the transportation loss, and obtain the storage data of each product in the inventory from the inventory record, calculate the storage loss coefficient of each product in the inventory, and confirm the outbound plan of the product order according to the order quantity in the product order; The calculation process of the storage loss coefficient of each product in each batch of transportation is as follows: Obtain the environmental data, extrusion data, and storage duration from the storage data of each product in each batch of transportation, and denote them as , and , where v represents the number of each batch of transportation, v is a positive integer, and x represents the number of each product, x is a positive integer; Use the calculation formula: ， Obtain the storage loss coefficient of the x-th product in the v-th batch of transportation , where HJ represents the preset suitable storage environment data of the product, and JY represents the preset allowable extrusion data of the product; The calculation process of the influence result of the storage loss uniformity of the product on the transportation loss is as follows: Use the storage loss coefficient in each reference batch of transportation to confirm the storage loss uniformity level of the products in each reference batch of transportation. Then, count the placement plan and the transportation loss coefficient of each product corresponding to each storage loss uniformity level during each reference batch of transportation, and then perform accumulation to obtain the total product transportation loss coefficient corresponding to each storage loss uniformity level during each reference batch of transportation; Using the placement plan corresponding to each storage loss uniformity level during the transportation of each reference batch and the product transportation loss coefficient, the total product transportation loss coefficients in each placement plan corresponding to each storage loss uniformity level are statistically calculated and denoted as , where y represents the number of each storage loss uniformity level, f represents the number of each placement plan, z represents the number of each total product transportation loss coefficient, y, f, and z are all positive integers. Then, it is input into the impact evaluation model expression to output the impact result of the product storage loss uniformity on the transportation loss; Influence evaluation model expression: ， In the formula, represents the influence result of the product storage loss uniformity on the transportation loss, , , respectively represent the difference rate between the total product transportation loss coefficients in the placement scheme, the difference rate of the total product transportation loss coefficients between the placement schemes, and the difference rate of the total product transportation loss coefficients between the storage loss uniformity levels; is the preset permitted difference rate, , , respectively represent the weight coefficients of the difference rate between the total product transportation loss coefficients in the set placement scheme, the weight coefficient of the difference rate of the total product transportation loss coefficients between the placement schemes, and the weight coefficient of the difference rate of the total product transportation loss coefficients between the storage loss uniformity levels; A transportation tracking module, which is used to track the product transportation when the product order is being transported, obtain the tracking data of the product order, evaluate the product transportation status, and provide corresponding feedback; The specific process of evaluating the product transportation status is as follows: Extract the initial product stacking image from the tracking data, and then locate the initial center point position of each product in the initial product stacking image as the initial position of each product. Obtain the center point position of each product from each product stacking image as the position of each product in each product stacking image, and obtain the damage data of each product from each product stacking image, where r represents the number of each product stacking image, x represents the number of each product, and both r and x are positive integers; According to the initial positions of each product and the positions of each product in each product stacking image, obtain the distance between the position of each product in each product stacking image and the initial position, and use it as the deviation distance of each product in each product stacking image. Normalize the damage data and deviation distance of each product in each product stacking image, and denote them as and ; Use the transportation status evaluation model to analyze the product transportation status value. The product transportation status value includes values of 1 and -1. When the product transportation status value is 1, it indicates that the product transportation status is in a stable state. On the contrary, when the product transportation status value is -1, it indicates that the product transportation status is in an unstable state; The expression of the transportation status evaluation model is as follows: ， In the formula, represents the product transportation status value, SH and L respectively represent the preset allowable damage data and allowable deviation distance, and R and X respectively represent the number of product stacking images and the number of products.

2. The product life cycle assessment system based on the Internet of Things according to claim 1, wherein, The specific process of confirming the outbound plan for the product order is as follows: When the influence result of the product storage loss uniformity on the transportation loss is 1, sort the storage loss coefficients of each product in the inventory from largest to smallest in sequence, and use the sorting result as the product selection order. Then select them in sequence until the number of selected products is the same as the order quantity in the product order, and stop selecting. When the influence result of the product storage loss uniformity on the transportation loss is -1, confirm the allowable product loss coefficient interval. Then, regard each product in the inventory with a storage loss coefficient within the allowable product loss coefficient interval as each candidate product. Sort the candidate products from largest to smallest according to the storage loss coefficient, and use the sorting result as the product selection order. Then select them in sequence until the number of selected candidate products is the same as the order quantity in the product order, and stop selecting. If the number of candidate products is less than the order quantity in the product order, sort the remaining products other than each candidate product in ascending order according to the difference between the storage loss coefficient and the allowable product loss coefficient interval. Then select the remaining products in sequence until the sum of the number of selected candidate products and the number of remaining products is the same as the order quantity in the product order, and stop selecting. Regard the selected products as the outbound plan for the product order.

3. The product life cycle assessment system based on the Internet of Things according to claim 2, characterized in that, The process of formulating the transportation plan for the product order is as follows: S21. When the influence result of the product storage loss uniformity on the transportation loss is 1, use the calculation formula to calculate the difference rate between the total product transportation loss coefficients in the placement plan, and select the placement plan with the smallest difference rate between the total product transportation loss coefficients as the target placement plan. S22. When the influence result of the product storage loss uniformity on the transportation loss is -1, calculate the difference rate between the total product transportation loss coefficients in each placement plan for each allowable storage loss uniformity level, select the placement plan with the smallest difference rate between the total product transportation loss coefficients as the target placement plan, and then regard the transportation method and the target placement plan as the transportation plan for the product order.

4. The product life cycle assessment system based on the Internet of Things according to claim 1, characterized in that The specific process of the product transportation tracking is as follows: Before the product is transported, use a camera to collect the initial product stacking image, and evenly arrange several vibration sensors among the products. Each vibration sensor detects vibration data in real time. When the vibration data of at least one vibration sensor is greater than the preset vibration data threshold, use the camera in the carriage to collect the product stacking image until the transportation is completed. Then regard the initial product stacking image and each product stacking image during the transportation process as the tracking data of the product order.

5. A product life cycle assessment method implemented using the Internet of Things-based product life cycle assessment system according to any one of claims 1-4, characterized in that Including: S1. Data acquisition: Obtain the product order, and obtain the product inventory data, transportation data, and loss data for each batch of transportation. S2. Transportation selection: Use the product inventory data, transportation data, and loss data for each batch of transportation to formulate the outbound plan and transportation plan for the product order, and give corresponding feedback. S3. Transportation tracking: When the product order is being transported, conduct product transportation tracking, obtain the tracking data of the product order, evaluate the product transportation status, and give corresponding feedback.

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