基于感性工学增强的GPT模型在分布式定制化制造方案中的研究

    A GPT Model Enhanced by Kansei Engineering in Distributed Customized Manufacturing Solutions

    • 摘要: 针对消费者个性化需求得不到满足,传统制造业对用户自然语言表达分析不到位,以及商家不能准确把握反馈的产业环境等问题,提出一种基于感性工学增强的GPT模型(简称“感性工学GPT”),并基于感性工学GPT进一步提出分布式定制化制造方案。该方案通过研究、微调、训练GPT语言模型,并结合基于感性工学的文字情感挖掘方法,探讨感性词汇的情感量化,根据用户的个性化需求生成定制产品。同时将个性化产品数字原型上传至区块链,通过区块链技术保护用户知识产权和敏感信息。针对分布式制造环境中缺少透明管理机制、设备差异大、用户需求多等问题,提出一种基于多属性逆拍卖和区块链的任务分配及定价机制。最后建立基于感性工学GPT的区块链分布式3D制造管理平台,通过与其他分配方法对比,验证提出的任务分配策略在分布式制造环境中的可行性,证明了基于感性工学GPT驱动的分布式定制化制造方案能有效地在分布式环境中实现用户的个性化需求。

       

      Abstract: To address issues such as the inability to meet consumer personalized demands, the insufficient analysis of user natural language expressions in traditional manufacturing, and the lack of accurate feedback interpretation by businesses, this paper introduces an enhanced GPT model based on Kansei engineering, referred to as "Kansei engineering GPT". Further, a distributed customized manufacturing solution based on it is proposed. The solution fine-tunes and trains the GPT language model while integrating a sentiment mining approach based on Kansei engineering to quantify the emotional attributes of Kansei vocabulary and generate products that meet user personalization. Additionally, digital prototypes are blockchain-uploaded to protect user intellectual property and sensitive information. To address challenges in distributed manufacturing environment such as the lack of transparent management mechanisms, significant equipment differences, and diverse user demands, we introduce a task allocation and pricing mechanism using multi-attribute reverse auctions and blockchain technology. Finally, a blockchain-based distributed 3D manufacturing management platform driven by Kansei engineering GPT is developed. By comparing it with other task allocation methods, the feasibility of the task allocation strategy proposed in the paper in a distributed manufacturing environment is verified. Results demonstrate that the distributed customized manufacturing solution driven by Kansei engineering GPT can effectively realize the user personalized needs in a distributed environment.

       

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