【Author】
Manimuthu, Arunmozhi; Venkatesh, V. G.; Shi, Yangyan; Sreedharan, V. Raja; Koh, S. C. Lenny
【Source】INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
【Abstract】With smart sensors and embedded drivers, today's automotive industry has taken a giant leap in emerging technologies like Machine learning, Artificial intelligence, and the Internet of things and started to build data-driven decision-making strategies to compete in global smart manufacturing. This paper proposes a novel design framework that uses Federated learning-Artificial intelligence (FAI) for decision-making and Smart Contract (SC) policies for process execution and control in a completely automated smart automobile manufacturing industry. The proposed design introduces a novel element called Trust Threshold Limit (TTL) that helps moderate the excess usage of embedded equipment, tools, energy, and cost functions, limiting wastages in the manufacturing processes. This research highlights the use cases of AI in decentralised Blockchain with smart contracts, the company's trading policies, and its advantages for effectively handling market risk assessments during socio-economic crisis. The developed model supported by real-time cases incorporated cost functions, delivery time and energy evaluations. Results spotlight the use of FAI in decision accuracy for the developed smart contract-based Automobile Assembly Model (AAM), thereby qualitatively limiting the threshold level of cost, energy and other control functions in procurement assembly and manufacturing. Customisation and graphical user interface with cloud integration are some challenges of this model.
【Keywords】Artificial intelligence; blockchain; federated machine learning; original equipment manufacturer; smart contract
【标题】使用具有智能合约的联邦人工智能设计和开发汽车装配模型
【摘要】借助智能传感器和嵌入式驱动器，当今的汽车行业在机器学习、人工智能和物联网等新兴技术方面取得了巨大飞跃，并开始构建数据驱动的决策战略，以在全球智能制造中竞争。本文提出了一种新颖的设计框架，该框架使用联邦学习-人工智能 (FAI) 进行决策，并使用智能合约 (SC) 策略进行完全自动化的智能汽车制造行业的流程执行和控制。提议的设计引入了一种称为信任阈值限制 (TTL) 的新元素，有助于缓解嵌入式设备、工具、能源和成本函数的过度使用，限制制造过程中的浪费。本研究重点介绍了人工智能在分散式区块链中的智能合约用例、公司的交易政策及其在社会经济危机期间有效处理市场风险评估的优势。由实时案例支持的开发模型结合了成本函数、交付时间和能源评估。结果突出了 FAI 在开发的基于智能合约的汽车装配模型 (AAM) 的决策准确性中的使用，从而在质量上限制了采购装配和制造中成本、能源和其他控制功能的阈值水平。具有云集成的定制和图形用户界面是该模型的一些挑战。
【关键词】人工智能;区块链；联合机器学习；原始设备制造商；智能合约
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