本文選題：工藝規(guī)劃 + 智能車間�。� 參考：《浙江大學(xué)學(xué)報(bào)(工學(xué)版)》2016年10期

【摘要】：為了實(shí)現(xiàn)制造智能化環(huán)境下工藝規(guī)劃決策目標(biāo),優(yōu)化制造資源配置,提出面向智能車間的工藝規(guī)劃輔助決策方法.以零件加工特征為基礎(chǔ),將含有加工工序和設(shè)備信息的歷史工藝規(guī)劃方案視為云服務(wù)資源,通過制定語義匹配策略,初步匹配出待選工藝規(guī)劃方案集.把工件的加工時(shí)間、加工成本、在工序間的轉(zhuǎn)運(yùn)距離與設(shè)備實(shí)時(shí)狀態(tài)效用作為優(yōu)化目標(biāo),引入罰函數(shù)建立適應(yīng)度函數(shù)模型,運(yùn)用改進(jìn)群領(lǐng)導(dǎo)優(yōu)化算法在待選規(guī)劃方案集中優(yōu)選出最佳方案.通過實(shí)例驗(yàn)證了該方法的有效性.
[Abstract]:In order to achieve the goal of process planning decision in intelligent manufacturing environment and optimize the allocation of manufacturing resources, a process planning assistant decision method for intelligent workshop is proposed. Based on the feature of parts processing, the historical process planning scheme which contains the information of processing process and equipment is regarded as cloud service resource. By making the semantic matching strategy, the set of process planning schemes to be selected is preliminarily matched. Taking the processing time, the processing cost, the transfer distance between the processes and the real-time utility of the equipment as the optimization objectives, the penalty function is introduced to establish the fitness function model. The improved group leadership optimization algorithm is used to select the best scheme in the selection plan. The effectiveness of the method is verified by an example.
【作者單位】： 重慶大學(xué)機(jī)械工程學(xué)院;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(71501020;71401018) 重慶市科技攻關(guān)計(jì)劃資助項(xiàng)目(cstc2012gg-yyjs0319)
【分類號(hào)】：TB497

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