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8 4.0 Collaborative Robotics In manufacturing, stand-alone robots have been traditionally used to replace humans for repetitive operations or in hazardous environments. However, the convergence of technologies is paving the way for a new generation of robots, called "collaborative robots" or "cobots." Instead of replacing humans, these robots collaborate with humans in a shared workspace on tasks that require greater process control, flexibility, scalability, and agility. Cobots are affordable, highly adaptable, and almost plug-and-play capable. Thus small- and medium-sized companies can cost-effectively increase productivity and labor utilization by using cobots for lower-speed, lower-volume production runs. Some everyday use cases for cobots include machine tending, packaging, palletizing, and augmenting human abilities during manufacturing and assembly operations. For example, in an automobile assembly operation, different vehicle styles might require varying amounts and forms of doors for installation, which may not be a suitable situation for a completely automated process. However, a cobot can be useful in this situation to lift the heavy parts. It could then carry out "instructions" from the human operator by positioning the piece on the desired location of the unfinished assembly. Special measures need to be in place to enhance worker safety to enable cobots to work together with the human workforce, Digital Twins According to Gartner, within three to five years, digital twinning, also referred to as device shadows or device twins, will represent billions of devices. Digital twins are physics-based, dynamic digital replicas of a physical asset or a system. Advances in digital simulation and sensor technology, AI, and the availability of massive volumes of IoT data are the critical enablers for digital twins. Data scientists and product designers can gain insights on an asset and analyze its behavior under various real-world conditions without accessing it physically. Digital twinning is thus becoming a top trend to design and develop product improvements, predict failures, and avoid downtime. Since the digital twin exists in a simulated environment, it is controllable in very exact ways that are not easy to duplicate in the real world (e.g., speeding up time so that years of use may get simulated in a fraction of a second). Since digital twins act as proxies for the combination of the domain experts (e.g., technicians) and the physical assets (e.g., pressure gauges), their proliferation may call for a shift in workplace culture. The resultant trend would demand a tighter collaboration between the technicians, who carry in- depth domain knowledge of managing and maintaining the physical assets, and the scientists and IT professionals. Digital twins are quickly becoming a feasible reality for many companies looking to make better products and more informed business decisions. Rooted in modeling and simulation, with rapid advancements in companion technologies, digital thread, and machine learning, digital twinning is on the verge of shifting the landscape of engineering design. Drones An industrial inspection can be a high-risk and expensive business, as it often involves physical access to hazardous environments. Inspectors may need to scale to the tops of flare stacks, ascend a 200m high wind- turbine tower, or dive to the depths of underwater pipelines. Many companies spend millions of dollars on the inspections of their industrial assets.