A material delivery route design method

Abstract

The application provides a material distribution path design method, comprising the following steps: step 1: counting the transportation demands that have not been loaded, arranging the transportation demands that have not been loaded according to the time sequence, and selecting the site corresponding to the transportation demand with the earliest time arrangement as the departure site; step 2: for a specific departure site, according to all the transportation demands of the site, sorting the transportation demands that have not been loaded of the site according to the priority, and traversing a plurality of car departure schemes; the priority of the transportation demands is in the order from high to low as follows: the overnight starting time point demand, the overnight other time point demand, the current day starting time point demand and the current day other time point demand. The application solves the problems of multiple material distribution demands and multiple sites according to the research and batch mixed line research characteristics of the discrete manufacturing workshop, improves the material distribution efficiency in the discrete manufacturing workshop, and reduces the material distribution cost.

Description

Technical Field

[0001] This invention belongs to the field of assembly and relates to a method for designing material delivery routes. Background Technology

[0002] Discrete manufacturing workshops are characterized by high-variety, low-batch production and mixed production lines. As manufacturing workshops move towards digitalization and intelligence, higher demands are being placed on material storage and distribution.

[0003] Material distribution in discrete manufacturing workshops is characterized by simultaneous calls from multiple workstations, simultaneous execution of multiple tasks, and simultaneous delivery of multiple materials. Material distribution route planning needs to comprehensively consider three key factors: material type, delivery location, and delivery time. Traditional material distribution systems generally rely on manual experience to calculate delivery routes, which is inaccurate and results in long waiting times at some workstations. Alternatively, they may obtain material distribution routes directly from the workshop manufacturing execution system. Both of these methods are inflexible, have high delivery costs, and can also affect workshop production efficiency. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a material delivery route design method, comprising the following steps:

[0005] Step 1: Count the transportation demands that have not yet been loaded onto the trucks, arrange the transportation demands that have not yet been loaded onto the trucks in chronological order, and select the station corresponding to the earliest transportation demand in the chronological order as the departure station.

[0006] Step 2: For a specific departure station, based on all the transportation needs of that station, sort the transportation needs that have not yet been loaded at that station according to priority, and iterate through several dispatch plans; the priority order of the transportation needs from high to low is as follows: overnight start time demand, overnight other time point demand, current day start time demand, and current day other time point demand.

[0007] Step 3: For a specific dispatch plan, iterate through each delivery vehicle;

[0008] Step 3.1: For a specific delivery vehicle, iterate through all transportation requests at the current station according to the priority of transportation needs;

[0009] Step 3.2: For a specific transportation demand, determine whether the current transportation demand is an overnight demand starting at the current time.

[0010] If the demand is for an overnight start time, the current delivery vehicle is checked for capacity based on the packing algorithm. If it can, all the boxes for the current demand are loaded into the current delivery vehicle. The transportation route is designed for all the boxes loaded on the delivery vehicle based on the path search algorithm. The process returns to step 3.1 and proceeds to the next specific transportation demand. This continues until all the boxes for all transportation demands at the current station are loaded into the delivery vehicle. The transportation route is then updated for all the boxes loaded on the delivery vehicle based on the path search algorithm, and the process returns to step 3.3. If not, the portion of the boxes that can fit into the current delivery vehicle is loaded into the current delivery vehicle. The process returns to step 3 and proceeds to the next delivery vehicle. This continues until all the boxes for all overnight start time demands at the current station are loaded into the vehicle. The transportation route is then updated for all the boxes loaded on the delivery vehicle based on the path search algorithm.

[0011] If the demand is not at the start time of the overnight period, then based on the packing algorithm, load the portion of the bins that can be loaded into the current delivery vehicle into the current delivery vehicle, return to step 3.1, and load all the transportation demands of the current station into the delivery vehicle in order of priority according to the transportation demand, until all the transportation demands of the current station have been loaded into the vehicle, update the transportation path for all the loaded bins on the delivery vehicle based on the path search algorithm, and proceed to step 3.3.

[0012] Step 3.3: Determine if there are any transportation needs at other stations that can be loaded into delivery vehicles under the current dispatch plan. If so, load them into the delivery vehicle. Update the transportation route for all loaded containers on the delivery vehicle based on the path search algorithm until there are no more transportation needs that can be loaded into delivery vehicles under the current dispatch plan. Return to Step 1 and start the loop to the next departure station until all containers for all transportation needs at all stations have been loaded into the vehicle. Calculate the dispatch cost; the dispatch cost is the total length of the transportation route.

[0013] Step 4: Compare all dispatch costs and input the dispatch plan with the lowest dispatch cost and its corresponding transportation route.

[0014] Furthermore, the packing algorithm takes the size and specifications of the bin, the size and specifications of the material, and the quantity of the material as input, traverses every packing sequence and every packing position of the material, outputs the bin space utilization rate if the bin is not full, and outputs the quantity and type of the material if the bin is full, and finally outputs the material packing sequence and packing position that maximizes the utilization of the bin storage space.

[0015] Furthermore, the path search algorithm takes the distance matrix of several stations and the transportation demand of each station as input, traverses every transportation path between stations, outputs the path length of each transportation path, and finally outputs the transportation order and route of the delivery vehicle at each station under the shortest transportation path.

[0016] Furthermore, the dispatch strategy takes the delivery vehicle model, the number of delivery vehicles, and the details of the material bins of each delivery vehicle as input, traverses several reasonable dispatch schemes, outputs the total length of the transportation path under each dispatch scheme, and finally outputs the dispatch scheme composed of the dispatch order under the shortest transportation path.

[0017] Compared with the prior art, the beneficial effects of this invention are as follows:

[0018] The material delivery path design method proposed in this invention obtains the shortest path and lowest delivery cost for material delivery within the workshop, solving the problems of multi-task execution, multi-workstation calling, and multi-material delivery. It efficiently connects the production of each workstation, significantly shortens the waiting time at workstations, and improves the production efficiency of the workshop. Attached Figure Description

[0019] Figure 1 This is a diagram illustrating an application example.

[0020] Figure 2 This is a component of the material delivery path design algorithm for discrete manufacturing. Detailed Implementation

[0021] The present invention will now be described in further detail with reference to the embodiments and the accompanying drawings.

[0022] like Figure 2 As shown, the material delivery path design method of the present invention is designed as two major modules: two basic algorithms and two major scheduling strategies.

[0023] The two basic algorithms are the bin packing algorithm and the path search algorithm.

[0024] ① The bin packing algorithm mainly aims to maximize the utilization of bin storage space. It takes bin dimensions (length, width, height), material dimensions, and material quantity as input, it iterates through each packing sequence and position. If the bin is not full, it outputs the bin space utilization rate; if the bin is full, it outputs the quantity and type of materials packed. Ultimately, it seeks the packing sequence and position that maximizes the utilization of bin storage space.

[0025] ② The path search algorithm mainly aims to optimize the material transportation route. Using the distance matrix of several stations and the transportation demand of each station as input, it iterates through every possible transportation route between stations, outputs the path length of each route, and finally seeks the transportation order and route of the delivery vehicles at each station under the shortest transportation path.

[0026] There are two main scheduling strategies:

[0027] ① Deployment strategy: Taking the delivery vehicle model, quantity of delivery vehicles, and material bin details of each delivery vehicle as input, iterate through several reasonable deployment schemes, output the total length of the transportation route under each deployment scheme, and finally find the deployment scheme composed of the deployment order under the shortest transportation route.

[0028] The dispatch strategy here only completes the selection and traversal of dispatch schemes for a certain station. The dispatch transportation route and cost under each dispatch scheme still need to be implemented in conjunction with the route planning strategy and two basic algorithms.

[0029] The first step is the transportation needs of a certain station, which refers to which station to which station, the type, quantity, specifications, etc. of the transported materials;

[0030] The second step is to match the specific model of the delivery vehicle with the loading capacity. Generally, the loading capacity of 1 small car is less than the loading capacity of 1 large car and less than the loading capacity of 2 small cars.

[0031] The third step is to take the minimum loading requirement as an example and iterate through the two dispatch plans: 1 large truck and 2 small trucks.

[0032] The fourth step involves calling the bin packing algorithm when dispatching one large vehicle to determine if it can fit; and calling the bin packing algorithm when dispatching two small vehicles to determine if it can fit.

[0033] Fifth, when there is a large demand for transportation, the loading can be traversed sequentially according to the loading standard of 1 small car < 1 large car < 2 small cars.

[0034] If there are different destination stations with the same departure time, the station with the greater distance will be determined as the departure station.

[0035] ② Route planning strategy: Taking a certain departure station as the starting point, and using the material details of all transportation needs at the current station and the list of existing materials on the delivery vehicle as input, search for the transportation needs of other stations on the workshop map, traverse and merge the material requirements of each transportation need, such as whether the material box is full and the length of the transportation path, and finally find the shortest transportation path under dynamic scheduling during the transportation process.

[0036] Combining packing algorithms, pathfinding algorithms, vehicle dispatch strategies, and route planning strategies, the final material delivery route design method includes the following steps:

[0037] A material distribution path design method for discrete manufacturing workshops includes the following steps:

[0038] Step 1: Count the transportation demands that have not yet been loaded onto the vehicles, arrange the transportation demands that have not yet been loaded onto the vehicles in chronological order, and select the station corresponding to the transportation demand with the earliest time in the order as the departure station.

[0039] Step 2: For a specific departure station, based on all the transportation needs at that station, prioritize the unloaded transportation needs and iterate through several dispatch plans, such as dispatching only one large delivery truck or dispatching two small delivery trucks. The priority order of the transportation needs from high to low is: overnight start time needs, overnight other time times needs, current day start time needs, and current day other time times needs.

[0040] Step 3: For a specific dispatch plan, iterate through each delivery vehicle;

[0041] Step 3.1: For a specific delivery vehicle, iterate through all transportation requests at the current station according to the priority of transportation needs;

[0042] Step 3.2: For a specific transportation demand, determine whether the current transportation demand is an overnight start time demand;

[0043] If the demand is for an overnight start time, the current delivery vehicle is checked based on the packing algorithm to see if it can fit all the boxes for the current transportation demand. If it can, all the boxes for the current demand are loaded into the current delivery vehicle. The transportation route is updated for all the boxes loaded on the delivery vehicle based on the path search algorithm. The process returns to step 3.1 and proceeds to the next specific transportation demand. This continues until all the boxes for all transportation demands at the current station are loaded into the delivery vehicle. The transportation route is updated for all the boxes loaded on the delivery vehicle based on the path search algorithm. The process then proceeds to step 3.3. If the demand cannot be met, the portion of the boxes that can fit into the current delivery vehicle is loaded into the current delivery vehicle. The process returns to step 3 and proceeds to the next delivery vehicle. This continues until all the boxes for all overnight start time demands at the current station are loaded into the delivery vehicle. The transportation route is updated for all the boxes loaded on the delivery vehicle based on the path search algorithm.

[0044] If the demand is not for the overnight start time, then based on the packing algorithm, load the portion of the current demand bins that can fit into the current delivery vehicle into the current delivery vehicle, return to step 3.1, and load all the transportation demands of the current station into the delivery vehicle in order of priority according to the transportation demand, until all the transportation demands of the current station have been loaded into the vehicle. Then, based on the path search algorithm, update the transportation path for all the loaded bins on the delivery vehicle, and proceed to step 3.3.

[0045] Step 3.3: Determine if there are any transportation needs at other stations that can be loaded into delivery vehicles under the current dispatch plan. If so, load them into the delivery vehicle. Update the transportation route for all loaded containers on the delivery vehicle based on the path search algorithm until there are no more transportation needs that can be loaded into delivery vehicles under the current dispatch plan. Return to Step 1 and start the loop to the next departure station until all containers for all transportation needs at all stations have been loaded into the vehicle. Calculate the dispatch cost; the dispatch cost is the total length of the transportation route.

[0046] Step 4: Compare all dispatch costs and input the dispatch plan with the lowest dispatch cost and its corresponding transportation route.

[0047] Based on the above method, the transportation demand cycle, delivery vehicle cycle, vehicle dispatch plan cycle, departure station cycle, and remaining transportation demand cycle are completed. The cycle is iterated until all cycles are completed, and finally all transportation plans and their total costs are determined. The optimal plan and the lowest cost are selected.

[0048] Figure 1 An embodiment for applying a material distribution path design method in a discrete manufacturing workshop and for further explanation of the material distribution path design method.

[0049] like Figure 1 The transportation needs within a discrete workshop, indicated by the middle arrow, are described as follows: Point A has 4 bins to be transported to points B, C, D, and E; point B has 1 bin to be transported to point C; point C has 1 bin to be transported to point D; and point D has 1 bin to be transported to point E. Furthermore, all transportation start and end times follow a straight line (the units on the coordinate axes in the figure represent time, not distance).

[0050] Therefore, in this embodiment:

[0051] Total transportation demand = [Transport 1 box from A to B, 1 box from A to C, 1 box from A to D, 1 box from A to E, 1 box from B to C, 1 box from C to D, 1 box from D to E]

[0052] Site n = [A, B, C, D, E]

[0053] The discrete workshop has two types of delivery vehicles: small and large. There are two dispatch plans: dispatching a single large delivery vehicle or dispatching a single small delivery vehicle. Under each dispatch plan, the delivery vehicle number is [1, 2].

[0054] Transportation demand types = [Overnight start time demand, overnight other time time demand, same day start time demand, same day other time time demand]

[0055] First, the packing methods for the two schemes were calculated based on the packing algorithm. After running the packing algorithm, it was found that the four allocated bins could simultaneously fit into one large delivery vehicle or one small delivery vehicle, with some capacity remaining.

[0056] Then, based on the path search algorithm, the shortest path is found to be the path that passes through AE in sequence. Therefore, the order of the delivery path is A, B, C, D, E, and the arrival time of each node meets the expectations.

[0057] By invoking a route planning strategy, a vehicle departing from point A can have its transportation needs from stations B, C, and D combined with those from point A, while also meeting the container loading requirements.

[0058] The results of this embodiment are consistent with conventional expectations, namely, that transportation demands along the same route can be merged, and the designed route is the shortest.

[0059] The material distribution route design method of this invention is composed of a basic algorithm and a scheduling strategy. The basic algorithm, as the fundamental functional module of the entire algorithm, maximizes the utilization of bin space and minimizes the path for multi-site distribution in the original distribution method. In response to the diverse transportation needs of stations during the distribution process, the flexible scheduling strategy dynamically satisfies the optimal packing method and the shortest distribution path under temporary transportation conditions, significantly reducing the material distribution cost of discrete manufacturing workshops.

[0060] This invention addresses the challenges of high material distribution demand and numerous workstations in discrete manufacturing workshops, which are characterized by multi-variety, small-batch production and mixed-production lines. It improves material distribution efficiency and reduces material distribution costs within the workshop. Furthermore, it enables timely coordination between different workstations on the production line, maximizing production efficiency.

[0061] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A material delivery path design method characterized by comprising: The method comprises the following steps: Step 1: statistics of the transport demand that has not been loaded, arranging the transport demand that has not been loaded according to the time sequence, selecting the site corresponding to the transport demand with the earliest time sequence as the departure site; Step 2: for a specific departure site, according to all the transport demands of the site, sorting the transport demands of the site that have not been loaded according to the priority, and traversing several car departure schemes; the priority of the transport demand is from high to low in turn: overnight starting time point demand, overnight other time point demand, current day starting time point demand and current day other time point demand; Step 3: for a specific car departure scheme, traverse each distribution vehicle; Step 3.1: for a specific distribution vehicle, traverse all the transport demands of the current site according to the priority of the transport demand; Step 3.2: for a specific transport demand, judge whether the current transport demand is the overnight starting time point demand, if it is the overnight starting time point demand, then based on the bin packing algorithm, judge whether the current distribution vehicle can load all the bins of the current transport demand, if yes, load all the bins of the current demand into the current distribution vehicle, design the transport path of all the loaded bins on the distribution vehicle based on the path search algorithm, return to step 3.1, enter the next specific transport demand, until all the bins of all the transport demands of the current site are loaded into the distribution vehicle, update the transport path of all the loaded bins on the distribution vehicle based on the path search algorithm, and enter step 3.3; if not, load the part of the bins of the current demand that can be loaded into the current distribution vehicle into the current distribution vehicle, return to step 3, enter the next distribution vehicle cycle, until all the bins of all the overnight starting time point demands of the current site are loaded, update the transport path of all the loaded bins on the distribution vehicle based on the path search algorithm; if it is not the overnight starting time point demand, then based on the bin packing algorithm, load the part of the bins of the current transport demand that can be loaded into the current distribution vehicle into the current distribution vehicle, return to step 3.1, load all the transport demands of the current site into the distribution vehicle according to the priority of the transport demand, until all the transport demands of the current site are loaded, update the transport path of all the loaded bins on the distribution vehicle based on the path search algorithm, and enter step 3.3; Step 3.3: judge whether there is a transport demand that can be loaded into the distribution vehicle under the current car departure scheme in other sites, if yes, load it into the distribution vehicle, update the transport path of all the loaded bins on the distribution vehicle based on the path search algorithm, until there is no transport demand that can be loaded into the distribution vehicle under the current car departure scheme, return to step 1, enter the next departure site cycle, until all the bins of all the transport demands of all the sites are loaded, and the car departure cost is calculated; the car departure cost is the total length of the transport path; Step 4: compare all the delivery costs, input the delivery scheme with the lowest delivery cost and its corresponding transportation path; the bin packing algorithm takes the size of the bin, the size of the material and the quantity of the material as input, traverses each packing order and each packing position of the material, if the bin is not full, outputs the space utilization rate of the bin, if the bin is full, outputs the quantity and type of the packed material, and finally outputs the packing order and packing position of the material that maximizes the utilization of the bin storage space.

2. The material dispensing path design method according to claim 1, characterized by, The path search algorithm takes the distance matrix of several sites and the transportation demand of each site as input, traverses each transportation path between sites, outputs the path length of each transportation path, and finally outputs the transportation sequence and route of the delivery vehicle at each site under the shortest transportation path.

3. The material dispensing path design method according to claim 2, characterized by, The delivery strategy takes the delivery vehicle model, the number of delivery vehicles and the bin details of each delivery vehicle as input, traverses several reasonable delivery schemes, outputs the total length of the transportation path under each delivery scheme, and finally outputs the delivery scheme composed of the delivery sequence under the shortest transportation path.

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