Design Considerations for Building an IoT Enabled Digital Twin Machine Tool Sub-System

The Internet of Things (IoT) and digital twins (DT) are both key advancements in the fourth industrial revolution. IoT can enable the connection of various devices which collect data that can be utilized to create a DT which can provide various services such as condition monitoring, predictive maintenance, modeling, and other useful functionality. Machine tools are key components in modern manufacturing forming the backbone of most modern factories. Modern machine tools are very complex and expensive machines, often costing hundreds of thousands to millions of dollars. It is desirable to ensure they are in good working condition. Given their complexity it may be desirable to begin IoT enabled DT development with one of its various subsystems such as the feed drives, tool changer, or spindle. This work covers considerations when building an IoT-enabled subsystem DT including: which data streams can be utilized, what should be considered when selecting a DT platform, and how data will be transmitted and analyzed in the system. A case study of a linear feed drive IoT-enabled feed drive is examined under this framework of development. This work should aid others with beginning the development process for an IoT enabled DT sub-system of their own

IIoDT: Industrial Internet of Digital Twins for Hierarchical Asset Management in Manufacturing

The Internet of Things (IoT) and digital twins (DT) are emerging technologies in the industry 4.0 landscape. Both technologies offer the capabilities of collecting and analyzing large quantities of data and utilizing this data for intelligent decision-making. These technologies together form the Industrial Internet of Digital Twins (IIoDT). Currently most works on DTs in literature focus on a single level of the manufacturing hierarchy without considering the interactions among levels. It is important to understand how these different scales of DTs can interact together in order to create a scalable system. The various assets in a manufacturing environment exist in a hierarchy with information flowing up from the lowest level to the highest. Additionally, information flows from various levels to a central database and data processing center. DTs connected in an IoT network can provide various services for asset management in manufacturing such as condition monitoring, health assessment, simulation, forecasting, and visualization. It is important to understand the various capabilities and interactions between the various DTs. This work examined DTs at multiple levels along the manufacturing hierarchy, what value they can provide, examples in the literature of DTs at each level, and how they can interact with other DTs along the hierarchy. This IIoDT system can be used to analyze both vertically along the hierarchy and horizontally across assets of the same level. This framework can help bridge link the various levels of DTs that exist to better integrate them in a manufacturing system