利用 DEMATEL 法和 LINGUISTIC q-ROF 信息评估智能制造服务中智能供应链的风险因素

Tingjun Xu, Haolun Wang, Liangqing Feng, Yanping Zhu
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摘要

随着科技信息化的快速发展,企业间的竞争逐渐从 "以生产为中心 "过渡到 "以客户为中心",服务型企业变得越来越重要。除此之外,随着全球制造业在智能制造(IM)进程中的不断推进,制造业与服务业的融合也日益受到关注,这引起了智能制造服务(IMS)领域众多专家学者的兴趣。本文将智能制造企业、智能服务节点和消费者结合起来。以智能制造服务为背景,收集了智能供应链(SSC)中连接不同服务节点的风险因素。专家们利用所提出的语言q-rung正交模糊加权平均(Lq-ROFWA)算子,结合决策试验与评估实验室(DEMATEL)方法对这些因素进行了评估,并进行了汇总操作。最后,我们得出结论:影响其他风险因素的最大影响因素是客户核心需求识别不足;面向智能制造服务的智能供应链最重要的风险因素是客户信息泄露。在对相关数据进行分析后,我们将为智能制造企业提供一些理论和管理启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Risk Factors Assessment of Smart Supply Chain in Intelligent Manufacturing Services Using DEMATEL Method With LINGUISTIC q-ROF Information
With the rapid development of technological informatization, competition among enterprises is gradually transitioning from being "production-centered" to being "customer-centric," making service-oriented enterprises increasingly important. In addition to this, as global manufacturing advances in the process of intelligent manufacturing (IM), there is growing attention on the integration of manufacturing and the service industry, which has garnered the interest of numerous experts and scholars in the field of intelligent manufacturing services (IMS). This article combines intelligent manufacturing enterprises, intelligent service nodes, and consumers. Based on the background of intelligent manufacturing services, it collected risk factors within the smart supply chain (SSC) that connect different service nodes. These factors were evaluated by experts using a proposed linguistic q-rung orthopair fuzzy weighted averaging (Lq-ROFWA) operator in combination with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method for aggregation operations. Finally, we obtain the conclusions that the most influential factor affecting other risk factors is the inadequate identification of core customer needs; and the most important risk factor for smart supply chains oriented to intelligent manufacturing services is the leakage of customer information. After analyzing the relevant data, we will provide some theoretical and managerial implications for IM enterprises.
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