Early industrial automation systems, first deployed in the 1970’s, used integrated circuits — or microchips — to power miniature active and passive devices like transistors and capacitors. Today, most manufacturing companies are using automated manufacturing systems that integrate software and machinery, enabling computers to automatically control production. Read on to learn some of the ways that digital transformation is impacting manufacturing. Artificial Intelligence (AI) We hear a lot of scary stories about how AI will replace jobs. The flip side of fear around AI is that the technology should be a collaborative tool for workers to not only complete work more efficiently, but also to focus more on tasks they historically haven't had the time or resources to achieve. As the manufacturing industry seeks ways to automate workflows, increase productivity, and efficiency, companies are looking to AI. Through the adoption of AI machine which are able to perform complex tasks and, through repeated performance, learn better, more efficient practices over time in the field. AI combines a plethora of different methodologies, including deep learning, machine learning, neural networks, natural language processing, and more. Basically, AI is a lean, mean, learning machine, revolutionizing the ways workers engage with their work. Industrial Internet of Things (IIoT) For the better part of the last decade, the IoT — a global network of connected, IP-enabled devices — has been steadily growing and advancing. In the manufacturing sector, there’s the IIoT, which specifically refers to intelligent devices and sensors that collect data from the manufacturing floor for use in AI, machine learning, and predictive analytics systems. To give you a sense of the magnitude of this transformation, the IIoT market is expected to reach $124 billion by 2021. And by 2030, IIoT could add $14.2 trillion to the global economy. Open process automation Until now, the manufacturing industry has been using programmable logic controllers (PLCs) and distributed control systems (DCSs) for process automation. A PLC is a ruggedized digital computer used for controlling processes like assembly lines and robotic devices. DCSs, which typically interface with PLCs, are used to control operations of large plants using GUI screens. The main downside to these systems is that they are usually proprietary and, as a result, are difficult to maintain and update. In search for a better way, the manufacturing industry is starting to migrate to open process automation solutions, which are easier to use and more cost-effective to manage. Additive manufacturing Commonly referred to as 3D printing, additive manufacturing involves using computer-aided design (CAD) and object scanners to layer material and form geometric parts. 3D printing removes many of the costly and time-consuming elements of manufacturing, such as carving and shaping. As a result, companies can design products faster and more affordably than they could in the past. In this day and age, who has time to wait around for a replacement part to be processed and shipped out to your business? Additive manufacturing is putting the power in your hands to print what you need, when you need it. One of the most exciting aspects of additive manufacturing is its potential to transform the space industry. Thanks to additive manufacturing, astronauts can print objects and assemble units in space without having to transport materials from earth. Additive manufacturing is also proving to be helpful for companies that have workers in remote, hard-to-reach areas. What’s more, additive manufacturing can reduce expensive shipping costs, and it can allow construction projects to be completed much faster. Asset management A manufacturing company depends entirely on the quality and availability of its operational resources. In the past, these assets were managed manually using staff members, paper, and spreadsheets — a system that opened the door for error, abuse, safety hazards, and system errors, among other pitfalls. In the spirit of digital transformation, the industry is moving toward asset performance management (APM). According to Gartner, APM “encompasses the capabilities of data capture, integration, visualization, and analytics tied together for the explicit purpose of improving the reliability and availability of physical assets.” In short, APM involves automating asset control, providing a streamlined way to manage and control everything from fleets to assembly lines to forklifts, and everything in between. Edge computing As manufacturing environments become more connected and cloud-based, companies are being forced to find new ways to move data. Transferring large amounts of data over long distances to a centralized server can lead to data bottlenecks, latency, and other problems. To solve these problems, manufacturing environments are moving data towards the “edge” of the network. An edge computing framework leverages distributed, open architectures to process select data locally — vastly improving performance. Through edge computing, manufacturing companies can reduce resource-intensive long-haul data transfers and latency. For example, imagine a sensor recording anomalies on a milk bottle assembly line. Instead of taking photographs of every single milk bottle, a sensor can instead be trained to identify broken or deformed items — transporting less information and reducing data bottlenecks along the way. Connected systems and devices The influx of connected systems and devices in manufacturing has increased the need for fast, scalable, and reliable networks. Many manufacturing facilities are integrating SD-WAN as a way to augment or replace their expiring multiprotocol packet layer switching (MPLS) networks. SD-WAN involves separating the networking hardware from the control plane, enabling multi-site manufacturing facilities to create a centralized virtual network that can be deployed and managed from a single location. In doing so, it’s possible to allocate network resources, control costs, improve security, and reduce downtime across a global private network. Conclusion Manufacturing is an incredibly complicated process that is made harder with out-of-date software. Thankfully, the industry is coming out of the dark and embracing the light. Through digitization, manufacturing is collaborating with artificial intelligence that not only automates processes, but also seeks to continually learn new ways of increasing productivity, efficiency, and safety in the workplace. We’d love to hear how you’re implementing digital solutions to your manufacturing business, and we’re always here to answer any questions you might have. Can’t wait to hear from you.