Six essential manufacturing trends to monitor in 2018

Manufacturing is once again in the midst of a massive revolution. With this fourth industrial revolution, identifiable by digital transformation and internet-enabled information sharing, goods, products, services, and entire industries are changing. Here are six of the most innovative trends to monitor in the coming year.

1. The IoT of the Beholder

The internet of things (IoT), one of the largest drivers of Industry 4.0, provides virtual content warehouses and collaboration centers to accommodate physical structures. The power of interconnectivity provided by IoT resources and data generated an expenditure of $178 billion in 2016.

Manufacturing in particular has benefited from how IoT has streamlined processes and simplified complicated work flows. With increased automation comes increased efficiency. This not only improves the capacity to focus on customer needs through better online support and mass customization, but it also provides insight into new revenue sources. Of the $178 billion spent on IoT, American manufacturing operations account for nearly 58 percent of that total.

2. Printing: See It in 3-D!

Many manufacturers are excited about the potential of 3-D printing to improve their output and decrease waste. Where a single part might require a half-dozen pieces to be crafted and assembled, a 3-D printer can create the part in one piece. These printers also recycle their materials, and they greatly reduce time spent waiting for replacement parts. One 3-D printer, for instance, could print a necessary part needed to fix a second 3-D printer.

Nonetheless, additive manufacturing such as 3-D printing may not always be the best solution. Subtractive manufacturing still has its place, and manufacturers would be wise to incorporate a hybrid form that utilizes the strengths of each while diminishing the weaknesses.

3. Ahead in the Clouds

Across a platform, cloud computing can help organizations achieve goals in optimizing work flows and decision-making in supply chains. Specifically, cloud computing enables team members located in various geographic centers to access the same data in real time, facilitating near-instantaneous communication with greater transparency. This feedback is combined with data from the augmented reality troubleshooting or virtual reality tests, as well as customer feedback, to inform research and development teams.

Smart systems complement cloud computing, providing useful tasks such as unit-of-measurement conversions, statistics tracking, and monitoring equipment for safety concerns. Manufacturers have begun to trust cloud computing software as engineers have improved its stability in leaps and bounds over the past decade.

Many organizations blend their cloud-based capabilities with on-site analysis to provide clearer, more holistic viewpoints. As collaboration becomes the tendency instead of the exception, efficiency thrives.

4. A Brave New (Testing) World

Manufacturers increasingly rely on augmented reality systems for remote assistance. Much like cloud computing, augmented reality glasses can allow people in vastly different geographic locales to troubleshoot in real-time with a live view, reducing travel and expediting problem-solving.

Augmented reality scenarios give manufacturers the ability to test a design in the middle of the process without the need to create the designed product first. These simulations cut down on manufacturing time and ensure that the end products resemble, as accurately as possible, the goals of the design team.

5. Rise of the Machines

Robots and machines have long been admired in manufacturing industries for their ability to improve efficiency and reduce harm to human laborers, and more innovation is on the horizon as Industry 4.0 takes hold.

Robotic Labor—The increased capacity for robots has enabled them to take over certain human roles that have long been dangerous or otherwise risky. As robots are better able to mimic dexterous fine motor skills, or show capabilities of “memory,” they can perform tasks unsuitable for human operators and reduce the risk of workplace injury and downtime. Robots have become easier to program, and voice and image recognition improve the accuracy in replicating complicated tasks.

Perhaps most important for digital transformation, these robots can be equipped with sensors, which then provide data for machine learning and IoT-equipped networks. The increased efficiency minimizes delays by identifying mechanical issues quickly—sometimes even before the breakdown can occur.

One consistent question lingers when discussing the increase of robotics, which is expected to become an $188 billion industry by the year 2020: What will become of the human workers displaced by the new robotic labor?

These workers are not disappearing from the manufacturing scene; companies still need humans to manage operations, program and maintain robots, design automation, build hardware and software, and adapt new equipment to existing structures.

Machine Learning—While machines have replaced certain elements of human labor for decades, their overall quality and efficiency have never been better. In part because of reduced waste, material consumption has decreased by 4 percent. At the same time, production capacity has risen as much as 20 percent in some plants. Algorithms more accurately predict customer behavior, which improves postsale service and presale inventory management.

Machine learning provides insight and data for optimizing work flow and value-chain decisions, particularly in companies where IT systems are not cross-functional or otherwise integrated. By determining the internal process and work flows that contribute best to achieving production goals, machine learning also improves service and product quality. These across-the-board boosts are essential for any complex manufacturer looking to scale up.

6. Big Data, Big Rewards

The influx of information provided by the data-rich system of sensors and optimized networks may seem overwhelming now, but by the end of the decade, the digital universe will grow to a storage level of 44 trillion gigabytes. Information regarding inventory, supply, deliveries, customer support, processing, and day-to-day management must all be analyzed, monitored, and updated as necessary.

Though machines can provide much of this information and analyze it to impressive levels, skilled human labor with the ability to interpret this vast trove of data and apply it in ways that keep organizations competitive and thriving will continue to be key to growth.