Technological evolution in the field of robotics is emerging with major breakthroughs in recent years. This was especially fostered by revolutionary new software applications leading to humanoid robots. Humanoids are being envisioned for manufacturing applications to form human-robot teams. But their implication in manufacturing practices especially for industrial safety standards and lean manufacturing practices have been minimally addressed. Humanoids will also be competing with conventional robotic arms and effective methods to assess their return on investment are needed. To study the next generation of industrial automation, we used the case context of the Tesla humanoid robot. The company has recently unveiled its project on an intelligent humanoid robot named Optimus to achieve an increased level of manufacturing automation. This article proposes a framework to integrate humanoids for manufacturing automation and also presents the significance of safety standards of human-robot collaboration. A case of lean assembly cell for the manufacturing of an open-source medical ventilator was used for human-humanoid automation. Simulation results indicate that humanoids can increase the level of manufacturing automation. Managerial and research implications are presented.

Festo Didactic and SICK have partnered to create a Safety Awareness Bundle that combines curriculum and hardware. The curriculum content focuses on robot risk assessments as well as the implementation of the system approach vs automation à la carte. The hardware includes a Festo Didactic manufacturing production system (MPS), a simulated Cyber-Physical Smart Factory with six-axis robot, SICK area scanners, safety PLC and safety relay. "With such a demand for smart manufacturing methods to be demystified, students who have been exposed to this sort of implementation have a real advantage when it comes to applying to jobs compared to students not provided the same experiential learning and job training," said Ted Rozier, director of engineering at Festo Didactic North America. The curriculum is designed to help students understand the importance of risk assessment.

Doosan Robotics recently appointed William (Junghoon) Ryu as its new chief executive officer. Ryu joined the Doosan Robotics board of directors on July 1, 2021 leaving his previous role as vice-president of corporate strategy at Doosan Group. "I am honoured to take on the leadership role at Doosan Robotics and join forces with the incredible team, aiming to drive innovation and growth of the company to become number one in the robotics industry," said Ryu. "Doosan Robotics is a young and uprising organization. I am excited for more agile practices to accelerate servicing our products to customers in the market with breakneck speed of changes." In his new role, Ryu is expected to enhance technological collaboration with the parent company's new business areas.

One of the great benefits of Industry 5.0 is that it provides the means for robots to help humans work better and faster than ever before. The introduction of collaborative robots (or "cobots" for short) dramatically lowered the bar for automating manual processes by making robotic technology much more accessible and easier to implement alongside existing workers and processes. With the return on investment being easier to justify, manufacturers are looking for ways to automate more tasks. The inherent capabilities of cobots allow them to be assigned to multiple applications and be moved around the facility for different jobs at various times of the day. What's more, the cobots themselves are further galvanizing the transition to Industry 5.0.

In the manufacturing sector, companies are facing pressure on multiple fronts. On the one hand, manufacturers must continuously find ways to drive down costs and increase profit margins. On the other hand, businesses have to maintain worker safety without compromising productivity. Workers are at risk when performing exhausting and dangerous tasks such as moving heavy machinery. Humans also tend to get bored with repetitive work, causing a lack of attention that can lead to making mistakes or becoming less sensitive to them.

Microsoft CTO Kevin Scott believes understanding AI in the future will help people become better citizens. "I think to be a well-informed citizen in the 21st century, you need to know a little bit about this stuff [AI] because you want to be able to participate in the debates. You don't want to be someone to whom AI is sort of this thing that happens to you. You want to be an active agent in the whole ecosystem," he said. In an interview with VentureBeat in San Francisco this week, Scott shared his thoughts on the future of AI, including facial recognition software and manufacturing automation.

Microsoft CTO Kevin Scott believes understanding AI in the future will help people be better citizens. "I think to be a well-informed citizen in the 21st century, you need to know a little bit about this stuff [AI] because you want to be able to participate in the debates. You don't want to be someone to whom AI is sort of this thing that happens to you. You want to be an active agent in the whole ecosystem," he said. In an interview with VentureBeat in San Francisco this week, Scott shared his thoughts on the future of AI, including facial recognition software and manufacturing automation.

Since the early 70s, advancements in technology have widely influenced the manufacturing sector with the aid of robotics, big data, machine learning, artificial intelligence, and the internet of things. Autonomous platforms have become the need of the hour with greater efficiency and higher productivity being some of the quintessential requirements of the current day and age. It is also not surprising to see large-scale manufacturing plants majorly--if not completely--run by robots and autonomous machines. Cobots, also known as collaborative robots are also playing a vital role in mass production industries. Owing to such trends, Robotics-as-a-service (RaaS) has become one of the widely sought out platforms with service providers offering rental and temporary acquisition of robotic hardware for industrial purposes.

Computationally analyzing Big Data is not a passing trend. As volumes of data continue to grow, so will the improvements in analyzing big data. When it comes to applications of Predictive Analytics, we have only seen the tip of the iceberg. It has already helped organizations (i.e. All of these different types of Artificial Intelligence are tied together in a way that has profoundly changed the way we perform everyday tasks, and more is yet to come.

Amazon, Google, Facebook, and IBM are set to lead the way in Artificial Intelligence. As larger companies, they have the right resources to collect data, and therefore, have more data to work with. Google is most likely in the forefront in terms of deploying machine learning for applications and product development and services. Not only were they the first company to start AI research, but with over 70,000 employees, Google is quite a large company. Moreover, with Google Brain, a deep learning AI research project, Google has an entire team with its own research agenda covering areas that include machine learning, natural language understanding, machine learning algorithms and techniques, and robotics.