Blockchain cloud manufacturing is an emerging service-oriented paradigm that takes many advantages to cloud manufacturing. Previous researchers have studied from eradicating third party trust problem among service providers and customers by decentralized data record and involving smart contract. However, the existing paradigm still suffers from third party trust problem among service-related participants and cloud manufacturing provider since service is solely managed by cloud manufacturing provider without supervision and service related participants cannot know whether composed service provision which indeed is NP-hard problem is optimal. In this paper, the architecture of blockchain cloud manufacturing system is proposed with adoption of several cloud manufacturing providers and vote mechanism to vote for optimal composed service provision on candidate composed service scheme firstly calculated by one cloud manufacturing provider. According to customer satisfaction-based service match and quality control, a system framework of composed service performance evaluation is desifned to incorporate the vote mechanism. Firstly, customer satisfaction dimensions as evaluation dimensions are extracted from customer text reviews based on latent dirichlet allocation (LDA) and sub-dimensions under each customer satisfaction dimension are set up based on professional field knowledge. Secondly, overall customer satisfaction rating of reviews and sentiment of reviews towards customer satisfaction dimensions are analysed by three score scheme, bag of words (BOW) and support vector machine (SVM) classification. Thirdly, the sentiment effect and category of customer satisfaction dimension on overall customer satisfaction are identified with the application of neural network and Kano model. Fourthly, in consideration of category characteristic, overall performance of customer satisfaction dimension is measured as distance and using proposed Logit-SVM method. Service selection standard according to value of customer satisfaction is set up. Finally, one empirical study is presented to verify the feasibility of proposed system framework, and proposed model is further discussed.

区块链云制造是一种新兴的面向服务的范式，具有云制造的诸多优势。以前的研究人员已经研究了通过分散的数据记录和涉及智能合约来消除服务提供商和客户之间的第三方信任问题。然而，现有范式仍然存在服务相关参与者和云制造提供商之间的第三方信任问题，因为服务完全由云制造提供商管理，没有监督，服务相关参与者无法知道确实是 NP-hard 问题的组合服务提供是否是最佳。在本文中，提出了区块链云制造系统的架构，采用多个云制造提供商和投票机制，对首先由一个云制造提供商计算的候选组合服务方案投票选出最优组合服务提供。根据基于客户满意度的服务匹配和质量控制，设计了一个包含投票机制的组合式服务绩效评价系统框架。首先，基于潜在狄利克雷分配（LDA）从客户文本评论中提取客户满意度维度作为评价维度，并基于专业领域知识建立每个客户满意度维度下的子维度。第二，通过三个评分方案、词袋 (BOW) 和支持向量机 (SVM) 分类来分析评论的总体客户满意度评分和评论对客户满意度维度的情绪。第三，应用神经网络和Kano模型，识别了客户满意度维度对整体客户满意度的情感效应和类别。第四，考虑到类别特征，客户满意度维度的整体性能以距离为衡量标准，并使用提出的Logit-SVM方法。建立根据顾客满意值的服务选择标准。最后，通过一项实证研究来验证所提出的系统框架的可行性，并进一步讨论了所提出的模型。词袋 (BOW) 和支持向量机 (SVM) 分类。第三，应用神经网络和Kano模型，识别了客户满意度维度对整体客户满意度的情感效应和类别。第四，考虑到类别特征，客户满意度维度的整体性能以距离为衡量标准，并使用提出的Logit-SVM方法。建立根据顾客满意值的服务选择标准。最后，通过一项实证研究来验证所提出的系统框架的可行性，并进一步讨论所提出的模型。词袋 (BOW) 和支持向量机 (SVM) 分类。第三，应用神经网络和Kano模型，识别了客户满意度维度对整体客户满意度的情感效应和类别。第四，考虑到类别特征，客户满意度维度的整体性能以距离为衡量标准，并使用提出的Logit-SVM方法。建立根据顾客满意值的服务选择标准。最后，通过一项实证研究来验证所提出的系统框架的可行性，并进一步讨论所提出的模型。第四，考虑到类别特征，客户满意度维度的整体性能以距离为衡量标准，并使用提出的Logit-SVM方法。建立根据顾客满意值的服务选择标准。最后，通过一项实证研究来验证所提出的系统框架的可行性，并进一步讨论所提出的模型。第四，考虑到类别特征，客户满意度维度的整体性能以距离为衡量标准，并使用提出的Logit-SVM方法。建立根据顾客满意值的服务选择标准。最后，通过一项实证研究来验证所提出的系统框架的可行性，并进一步讨论了所提出的模型。