【标题】Collaborative Artificial Intelligence in Actuator Development
【参考中译】协作式人工智能在执行器开发中的应用
【类型】 期刊
【作者】 Guillaume Callerant; Mathieu Gerber; Jacques Wicht; Christophe Audouy
【摘要】 Future demands on actuator systems for use in battery electric vehicles require new approaches to development and application. Functions must be optimized in the system network so that the potential of each component is used in the best possible way. In the following, Sonceboz outlines how collaborative artificial intelligence in smart actuators can help improve the functionality of individual domains in electric vehicles. New Battery Electric Vehicle (BEV) platforms and associated applications bring new challenges to the core embedded mechatronic domains, such as vehicle thermal systems. One of the major challenges for domain control and diagnostics and its peripherals is dealing with a wide variety of environmental influences and a multitude of past and new use cases. Analyzing the different elements and domains individually without considering the global integration of the domains would be pointless. There is a multitude of direct and indirect causal relationships between the domains themselves (e. g. heat and heating, ventilation, and air conditioning (HVAC) systems), the domain and its subcomponents such as water pumps and valves, as well as its environment (e. g. air temperature, heat demand of battery packs) [1]. Obviously, the Domain Control Unit (DCU) supports the essential tasks for control, security and diagnostics of the associ-ated domain, but is this architecture truly optimal? Today, development teams try to analyze a system step by step. They draw up lists of all potential use and test cases, taking into account the combination of loads and stresses, determining the most important limiting conditions.
【参考中译】 未来对用于电池电动汽车的致动器系统的需求需要新的开发和应用方法。必须对系统网络中的功能进行优化，以便以尽可能最佳的方式利用每个组件的潜力。在下文中，Sonceboz概述了智能执行器中的协作人工智能如何帮助提高电动汽车各个领域的功能。新的电池电动汽车(BEV)平台及其相关应用给汽车热系统等核心嵌入式机电一体化领域带来了新的挑战。域控制和诊断及其外围设备面临的主要挑战之一是处理各种环境影响以及大量过去和新的用例。单独分析不同的要素和领域，而不考虑领域的全球整合将是毫无意义的。在域本身(例如，热和供暖、通风和空调(HVAC)系统)、域及其子组件(例如水泵和阀门)以及其环境(例如，空气温度、电池组的热需求)之间存在多种直接和间接的因果关系[1]。显然，域控制单元(DCU)支持相关域的控制、安全和诊断的基本任务，但这种架构真的是最优的吗？如今，开发团队试图一步一步地分析系统。他们制定了所有潜在使用和测试用例的列表，考虑了载荷和应力的组合，确定了最重要的限制条件。
【来源】 ATZ Electronics Worldwide 2022, vol.17, no.12
【入库时间】 2023/7/26
【标题】Industrial Internet of Things on integrated preventive maintenance and enterprise-resource-planning systems: A case study of fastener forming manufacturing processes
【参考中译】基于集成预防性维护和企业资源规划系统的工业物联网--以紧固件成形制造过程为例
【关键词】 Industrial internet of things; Fastener forming process; Classification algorithms; Preventive maintenance; Enterprise resource planning; Manufacturing execution system
【参考中译】 工业物联网；紧固件成型工艺；分类算法；预防性维护；企业资源计划；制造执行系统
【作者】 Chih-Wei Hsu; Jui-Han Lu; To-Cheng Wang; Jui-Chan Huang; Ming-Hung Shu
【摘要】 The Industrial Internet of Things (IIoT) has evolved industrial operations to be more efficient and reliable. The fastener forming process (FFP) used to rely on the judgments of in-process inspectors and experienced operators. Since no critical information was transmitted between machines, the machining status during production was unable to reveal. Now, with sensors installed in the machines of FFP, manufacturing data can be collected, analyzed, and responded to the machines. This IIoT-embedded FFP can not only carry out real-time data, pre-processing, and feature engineering but also enable optimally selecting classification algorithms for preventive maintenance. Consequently, the FFP establishes machine-health indicators for the production site and the heading process recognizes the abnormal situations between punches. The operator-delayed response leads to a great amount of loss that can be avoided. Besides, with the integration of enterprise resource planning (ERP) and manufacturing execution system (MES), this IIoT-embedded FFP converts receiving customer orders into work orders and coordinates operations and sales within enterprises. This system integration catches the status of various production indicators and further advances accurate materials preparation and inventory costs control. Overall, this IIoT-embedded FFP system becomes no necessity for increasing inventory and reserving backlog funds to cope with the impact of a vast number of scrap products. Finally, other types of machining processes or systems can adopt this systematic approach in the future.
【参考中译】 工业物联网(IIoT)使工业运营变得更加高效和可靠。紧固件成型工艺(FFP)过去依赖于过程中检查员和有经验的操作员的判断。由于机器之间没有传输关键信息，生产过程中的加工状态无法透露。现在，通过在FFP的机器上安装传感器，可以收集、分析和响应机器的制造数据。这种嵌入IIoT的FFP不仅可以进行实时数据、预处理和特征工程，而且可以为预防性维护选择最佳的分类算法。因此，FFP为生产现场建立机器健康指示器，并且掘进过程识别冲头之间的异常情况。操作员延迟响应会导致大量损失，而这些损失是可以避免的。此外，通过集成企业资源计划(ERP)和制造执行系统(MES)，这个嵌入IIoT的FFP将接收客户订单转换为工单，协调企业内部的运营和销售。通过系统集成，及时掌握各项生产指标的运行状态，进一步推进精准备料和库存成本控制。总体而言，这个嵌入IIoT的FFP系统不再需要增加库存和预留积压资金来应对大量报废产品的影响。最后，其他类型的加工工艺或系统可以在未来采用这种系统化的方法。
【来源】 Proceedings of the Institution of Mechanical Engineers 2023, vol.237, no.6/7
【标题】Digital manufacturing process quickly produces liquid silicone rubber parts
【参考中译】数字化制造流程快速生产液态硅橡胶零件
【作者】 Simon Atkinson
【摘要】 To support manufacturers, Trelleborg Sealing Solutions has developed and is offering a fast and flexible digital manufacturing process for product development and small-batch production of liquid silicone rubber (LSR) parts. This article briefly looks at what is involved.
【参考中译】 为支持制造商，特瑞堡密封系统公司为液体硅橡胶(LSR)部件的产品开发和小批量生产开发了并正在提供快速、灵活的数字化制造流程。本文简要介绍了其中所涉及的内容。
【来源】 Sealing Technology 2022, vol.2022, no.9