Hybrid jobs are the future of manufacturing, especially those that implement robotics. Misconceptions portray robotics as the demise of manufacturing jobs. But, it’s quite the opposite. Robots don’t eliminate the need for skilled laborers—human involvement is needed to accomplish robotic tasks.
Collaborative robots, otherwise known as cobots, have wowed the robotics industry with their unique capabilities representing some of the most exciting advancements in robotic technology today. With the flexibility of cobots, companies can automate even the simplest of tasks. Regardless of the scale of output, cobots can be deployed for processes that are repetitive, manual, or potentially strenuous for workers – such as pick and place, packaging and palletizing, screw driving, gluing, dispensing, and welding.
Digital manufacturing is rapidly changing the fundamentals of how products are developed, scaled and manufactured. By digitizing traditional manufacturing methods, including injection molding and CNC machining, and leveraging newer technologies, like 3-D printing, the industrial internet of things (IIoT) and artificial intelligence (AI), companies are optimizing their supply chains, reducing development cycles, increasing efficiencies, and driving down costs.
Despite enthusiasm for digital manufacturing, few companies have realized its potential at scale, according to a new survey by McKinsey. While there is significant importance placed on the topic and many pilots have been launched across a range of use cases, less than a third of respondents cite having moved critical use cases—such as digital performance management—into large-scale rollout. At the same time, more than 90 percent of surveyed companies believe that they are either at the forefront of digital manufacturing in their industry or, at least, on par with the competition.
IIoT is transforming the way manufacturers identify problems on the plant floor as the latest wireless solutions address integration challenges. IIoT eliminates data silos, so device-level data is accessible to the entire operations team. It provides valuable insights into machine performance, process inefficiencies and other potential risks. In this smart environment, wireless sensors enable real-time remote monitoring of machine performance. Manufacturers can use the information to increase overall equipment effectiveness (OEE), which is a calculation of manufacturing process efficiency.
In their new book, Human + Machine: Reimagining Work in the Age of AI, Paul Daugherty and James Wilson make a compelling case for pairing this particular technology with human capital. In their research, they found that companies that focus on human and machine collaboration create outcomes that are two to more than six times better than those that focus on machine or human alone. For instance, BMW has found that robot/human teams were about 85% more productive than the old assembly line process, where you had industrial robots over on one side of the factory and people working on an old automated assembly line.
Capgemini found that the successful manufacturers have mastered the use of data from smart, connected products to build actionable insights. 93% of digitally successful manufacturers have mastered the ability to use data from smart, connected products to gain insights into how they can improve product designs and manufacturing techniques.
Press Release from New York City Economic Development Corporation (NYCEDC):
Futureworks NYC will create over 2,000 advanced manufacturing jobs over next five years...