Increasing Efficiency With Industry 4.0

Industry 4.0, sometimes called IIoT or smarter manufacturing, combines traditional physical manufacturing with smart digital technologies, machine learning, and large-scale distributed workforce to build a more integrated and holistic ecosystem for businesses that concentrate on manufacturing and distribution. Industry 4.0 is poised to change the way people do business, just like the changes in other industries. But just like any disruptive innovation, industry 4.0 can cause problems. That’s why some companies are already transitioning into industry 4.0 while others have yet to make the transition. Below are five industries we will see disruptive innovation impacting in the next five years.

Industry 40

Healthcare is one of the first sectors to capitalize on the benefits of industry 4.0 with a number of health-related applications, such as clinical diagnostics and drug design, which require a high degree of accuracy and precision. Machine vision is also becoming an important factor in the manufacturing process. Analytic technology will be playing an important role in the production process as well as in customer care.

In the manufacturing sector, integrated systems are being applied to new technologies to improve productivity, quality, and efficiency. Machine vision is playing an increasingly important role as technologies are designed to enable manufacturing processes with greater visibility and more information about all the products being made. This will allow companies to quickly identify problems before they hamper production.

Automotive manufacturers are already implementing advanced driver assistance technologies that integrate with LCD displays and electronic displays to improve driver safety. New safety ratings for vehicles are likely to require vehicles to have daytime running lights (LED’s) as part of the standard model. Automotive manufacturers are already using this technology in the car and truck fleet and it is expected to become the norm in new vehicles. Industry 4.0 technologies are being applied to many aspects of manufacturing. Other manufacturing processes, such as packaging and inventory will also see improvements in the coming years. Truckload and pallet load shipping are two transportation processes that have seen advancements due to the adoption of RFID technology.

In the trucking and transportation industries, the adoption of fleet management software to track vehicle costs has boosted productivity. The Epicor system, invented by Delphi, allows truckers to view the status of their trucks in real-time. Delphi’s Epicor system allows for real-time inventory management, maintenance scheduling, vehicle availability reporting, and more. These real-time capabilities allow the transport industry to make faster decisions about inventory and reduce logistics costs. The Epicor software will help manufacturers to reap the benefits of lower costs and increased profitability.

Machine vision is another technology being applied to the manufacturing industry. Many different applications are being developed for manufacturing to enable computer generated control for many different manufacturing processes. Some examples of potential applications include machine vision for eliminating waste, automated inventory management, improved quality control, production scheduling, and many different operational processes. Machine vision will also benefit the customer by providing faster customer service and a safer manufacturing environment.

German companies are making steady advances in machine vision technology. Recently, a group of IBM Researchers in Germany were awarded a seven-year, $2.75 million contract by Mercedes Benz to improve the on-board diagnostics of the company’s fleets. This new system will allow fleet managers to diagnose a problem virtually anywhere, at any time. The goal is to enable fleet managers to determine the root cause of a problem, analyze the problem, and then take action to improve it. By applying real-time analytics, this program will enable the company to not only locate common problems but to also pinpoint individual manufacturing errors or failures.

In Germany, Krones is another example of how companies are leveraging image processing in their industrial robots. Krones has been developing mobile vision systems to help manufacturing facilities to increase their efficiency and reduce their total cost of ownership. These devices currently capture and streamline large quantities of data that has been collected during the course of a manufacturing process. The captured data is then fed into a computer system that makes decisions about what should be done based on the analyzed data. This is a critical component of enabling the company to improve its efficiency and to reduce the costs associated with bad manufacturing practices. Ultimately, this technology will lead to better work flow and increased productivity.

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