橡皮 发表于 2025-7-27 19:49:26

一维下料

本帖最后由 橡皮 于 2025-10-18 17:36 编辑



支持数据导入导出(CSV格式),格式参考测试文件或者直接导出查看。

方案区支持查看历史方案详情,点击即可在轨迹追踪去产看详细内容,鼠标右键可以选择导出

功能区可进行原料及切缝信息等等设置,计算效率极高(带切缝的最好采用快速模式),计算过程“随叫随停”,可自行体验。
一维下料软件(单原料)
库文件
插件:演示可查看这个帖子
适用于 ACAD 2025-2026
适用于 ACAD 2021-2025
适用于 ACAD 2019-2020
测试案例等:






橡皮 发表于 2025-7-27 22:21:53

本帖最后由 橡皮 于 2025-8-2 14:20 编辑

橡皮 发表于 2025-7-27 21:15
你这个原理是啥我都能猜出来,而且他会自动合并长度相同的项(或者说会自动修改原始数据)
...
效率对比:
测试数据:custom_items.csv
原料长堵:6000
切缝宽度:5
对比数据如下(利用率为零件总长/用料总长)

名称用料量用料总长模数利用率 (%)实际利用率 (%)时间(S)
pfc2959317755800029110099.508143
pfc速2959317755800031010099.5081.2
pfcExcel2980017880000035299.3798.82 6.0
pfcExcel22980017880000035299.3798.820.04
下料excel2980017880000035299.3798.82380
详细数据:
一般模式

快速模式

profilecuttingexcel


profilecuttingexcel 优化版

下料优化excel专业版


这个原理和上边应该一样,时间大概 380s 。






lengxiaxi 发表于 2025-7-29 19:34:42

去除料头长度 = 10毫米,刀具宽度 = 5毫米
->正在处理:A,银白
M:-1,L:0
M:0,L:1
使用定尺料 - 颜色:银白,去料头:10毫米
1)   18支,6    米::2680x2    ;200x3   ;料头:5
2)   2   支,6    米::2680x2    ;300x2   ;料头:10
3)   1   支,6    米::2680x1    ;2060x1    ;500x2   ;200x1   ;料头:25
4)   15支,6    米::2680x1    ;1600x2    ;料头:95
5)   1   支,6    米::2060x1    ;1600x1    ;500x4   ;300x1   ;料头:0
6)   6   支,6    米::2060x1    ;1600x2    ;500x1   ;料头:210
7)   6   支,6    米::2060x2    ;1600x1    ;料头:255
8)   1   支,6    米::1600x2    ;料头:2780
型材:A       数量:50   颜色:银白   定尺:6米   (0.3Kg/0.3Kg=97.46%)
需要型材重量=.3Kg, 实际使用重量=.3Kg, 实际材料总价=7.65元, 材料利用率=97.46%
##########by BFD 算法 ########


------------贪心算法---------------------
合计共用料:        52根        剩余料头:        19885mm        利用率:        93.63%       
序号        下料方法                                根数        每根剩余
1        2680mm×2500mm×1                                12        130
2        2680mm×2300mm×2                                2        25
3        2680mm×2300mm×1200mm×1                                1        125
4        2680mm×2200mm×3                                13        20
5        2060mm×21600mm×1200mm×1                                10        65
6        1600mm×3200mm×5                                1        165
7        1600mm×3                                12        1190
8        1600mm×2                                1        2795

橡皮 发表于 2025-7-27 21:15:57

本帖最后由 橡皮 于 2025-8-1 18:37 编辑

ㄘ丶转裑ㄧ灬 发表于 2025-7-27 20:56
试用30天,注册需要付费购买还是免费?
试用了下,提几点建议:
1、零件区的数据需要可从excel直接粘贴, ...
你这个原理是啥我都能猜出来,而且他会自动合并长度相同的项(或者说会自动修改原始数据)
我之前用相同原理写了个 excel 的插件

完全免费,安装就能用
界面

数据格式(计算的时候要激活也就是在当前表格进行)
data:image/png;base64,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
顺便说一下就是用他这个算法他这个效率也一般,当然我上传这个也一般,后边改了一般新的提速几倍到几十倍还是有的(数量越多越明显)。
还有就是,交互只是枝叶,我这个软件也是调用的我写的内核库文件。





gzxl 发表于 2025-7-27 20:36:24

这么久不见,原来是在憋大招。

橡皮 发表于 2025-7-27 20:49:59

本帖最后由 橡皮 于 2025-7-27 20:52 编辑

gzxl 发表于 2025-7-27 20:36
这么久不见,原来是在憋大招。
嘿嘿,上传一个支持多原料的演示

测试案例用的是文件夹里边
custom_items 和 custom_bins(2) 两个文件

结果:



ㄘ丶转裑ㄧ灬 发表于 2025-7-27 20:56:19

试用30天,注册需要付费购买还是免费?
试用了下,提几点建议:
1、零件区的数据需要可从excel直接粘贴,现在粘贴只能第一行。另外表头也不应该写原料;
2、原料长度建议可设置多种,现在只能一种;
3、优化完成后,建议有导出成word的功能,最次也要有导出excel的功能,便于打印;



这个表格版的暂时秒杀你现有功能

ㄘ丶转裑ㄧ灬 发表于 2025-7-27 20:57:35

~~我就编写回复的几分钟,你就发新的了~~已经改了前一条半,点赞!

czb203 发表于 2025-7-27 22:34:19

ㄘ丶转裑ㄧ灬 发表于 2025-7-27 20:56
试用30天,注册需要付费购买还是免费?
试用了下,提几点建议:
1、零件区的数据需要可从excel直接粘贴, ...

大佬的你的excel运行会错误哦,看看啥问题

橡皮 发表于 2025-7-27 23:55:53

本帖最后由 橡皮 于 2025-7-28 09:28 编辑

橡皮 发表于 2025-7-27 20:49
嘿嘿,上传一个支持多原料的演示

测试案例用的是文件夹里边


这个应该是最优了吧



mahuan1279 发表于 2025-7-28 09:16:52

橡皮 发表于 2025-7-27 23:55
这个最优应该是这个了吧

用的啥算法?
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