Abstract Industry 4.0 foresees benefits to companies and is supported by technologies such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Internet of Services (IoS), among others. CPS, one of Industry 4.0's key technologies, can be applied in many areas including health, mobility, production and logistics. The partial or total incorporation of CPS technologies into internal logistics equipment can present such advantages to businesses as reductions in logistics operational costs and in production cycle times. Although this application is still under development, several manufacturers already offer to the market internal logistics equipment incorporating CPS technologies, presenting them as fully capable of operating in the Industry 4.0 environment. However, it is observed that there is no effective method of assessing whether these devices effectively integrate such technologies and at what level this integration occurs. This manuscript adopted the design science research methodology to propose a method for assessing the adherence of internal logistics equipment to the CPS concept for Industry 4.0. The method is based on a guide for collecting data with questions that identify information about the CPS technologies embedded in the internal logistics equipment, associated with a tool for processing this information. The tool is supported by a properly trained artificial neural network that measures the equipment's adherence to the CPS concept. The method has proved to be adequate because in its application it assessed fifteen equipment, from worldwide-renowned manufacturers, with an error of less than 2%.

中文翻译：

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评估内部物流设备对工业4.0 CPS概念的遵守情况的方法

摘要 工业 4.0 预见了企业的利益，并得到网络物理系统 (CPS)、物联网 (IoT)、服务互联网 (IoS) 等技术的支持。CPS是工业4.0的关键技术之一，可应用于健康、移动、生产、物流等诸多领域。将 CPS 技术部分或全部纳入内部物流设备可为企业带来诸如降低物流运营成本和生产周期时间等优势。尽管此应用程序仍在开发中，但一些制造商已经向市场提供采用 CPS 技术的内部物流设备，使其完全能够在工业 4.0 环境中运行。然而，据观察，没有有效的方法来评估这些设备是否有效地集成了这些技术以及这种集成发生在什么级别。本手稿采用设计科学研究方法，提出了一种评估内部物流设备是否符合工业 4.0 的 CPS 概念的方法。该方法基于收集数据的指南，其中包含识别有关嵌入内部物流设备的 CPS 技术信息的问题，并与处理此信息的工具相关联。该工具由经过适当训练的人工神经网络提供支持，该网络可测量设备对 CPS 概念的遵守情况。该方法已被证明是足够的，因为在其应用中它评估了来自世界知名制造商的 15 台设备，