The manufacturing industry is known for its appetite for technology. As a traditional early adopter, the industry was the first to benefit from big data analytics, cutting edge sensors and robotics, and digital solutions that reduce human intervention and increase productivity and sharpen competitive edge.
The Internet of Things is not a buzzword, as PwC research shows 71% of industrial makers are building IoT-related solutions in both active and in-development projects. It might not feel as one, but smart manufacturing is in full effect - the 'fourth industrial revolution' taking place - every day behind companies’ walls. IoT is about networks, devices and data sensors on product lines that can increase efficiency. The "gather data, analyze it and create action" has propelled productional Darwinism with IoT solutions, smarter and cleaner processes leading to decisive competitive advantages in the complete manufacturing chain: operations like supply chain, stock management, quality control, optimized production, maintenance, and location tracking as a minimal grasp of the dozens of activities that are being reinvented.
IoT is struggling with growing pains as the proliferation of standards is giving some serious compatibility headaches and the rise of security challenges is demanding new soft- and hardware investments. To make things more interesting, 5G is waiting around the corner with tailored end-to-end networks, finally meeting technical requirements of specific machine-to-machine or mobile solutions. 5G will accelerate data heavy domains such as virtualizations and IoT cloud interworking. The startup and business potential is clearly enormous with complete new approaches in terms of network configuration, sensor upgrades and new elements being built into the devices and software architecture.
Closely interrelated to IoT, is the machine learning shift making robotics and mechanized solutions smarter than ever. ML is helping production teams analyze big data sets and use the insights to replace inventory, reduce operational costs and offer seamless quality control over the entire process. Deep learning has already surpassed the human senses with e.g. improvements of up to 90% in defect detection as compared to human inspection. A new generation of neural networks allows production systems to detect surface scratches, cracks, leaks and missing tags. ML is also good news for the environment with temperature, lighting usage, use of resources, energy consumption being forecasted with astonishing preciseness.
It’s clear that the manufacturing space is flooded with innovative solutions that can bring success in different operations. With IoT and ML magic provided via a tsunami of cloud solutions, the main challenge has become making the right choices to create a future proof production architecture that solves existing problems, sees upcoming issues, and not imaginary ones for the mere sake of technology itself.