Most manufacturers still operate under Ford’s philosophy: “Any customer can have a car painted any color he wants so long as it is black.”
It doesn’t work, though.
In the past, it wasn’t a big deal for industry leaders to avoid personalization. Today, however, consumers are getting more vocal with their demands for custom goods and ultra-personalized services. And when a company fails to deliver that, it automatically loses in the battle with a competitor that offers a more tailored customer experience.
Modern smart factories are data-driven, populated with sensors and industrial IoT systems, have augmented teams of humans and robots on the floor, or even function autonomously with the lights out.
As Industry 4.0 failed to accept the increasing demand for personalization, Industry 5.0 aims to amend this.
In this whitepaper, Intellias explores how cutting-edge technologies such as machine learning (ML), artificial intelligence (AI), computer vision, and cognitive systems can be fine-tuned to support mass personalization and add a much-needed human touch to production (and beyond).
In our in-depth research, based on our experience and fully-packed with real-life cases, you’ll learn:
In industry 5.0, technology performs the mundane, repetitive, error-prone tasks and humans set the strategy, provide oversight, and add creative input. This new division of labor will help businesses not only save money but also tap into new value streams generated by the human touch.
Industry 5.0 aims to transform the way humans and technology cooperate. We will show you new vectors of human-technology collaboration at production facilities and beyond that, resulting in robots, cobots, IoT devices, and other cognitive systems.
We have created a baseline technological blueprint for Industry 5.0 initiatives that will help you accomplish the transition to cost-effective mass personalization.
Most customer data required for hyper-personalization is either trapped in silos or cannot be effectively delivered to a centralized repository for real-time analysis.
Create a unified data management platform that can collect and process all customer insights/inputs, transforming them into actionable insights.
Mass customization increases the complexity of the manufacturing process. Predicting the effectiveness and performance of modified products can be tough without prototypes.
Creating a digital twin for complex processes, products, or services can be a viable alternative to prototyping.
The fully autonomous production lines envisioned by Industry 4.0 require greater technical skills from the agents overseeing the operations.
More advanced AI systems, powered by deep and reinforcement learning, are required to run autonomous manufacturing of custom parts.
You will find even more models and initiatives in the Intellias whitepaper.
Delivering advanced technologies services with a vast AI and ML skill sets within Intellias expertise, we are helping manufacturing companies become leaders in the connectivity space. Our experts apply best machine learning, data science, and big data practices to shift from established routines and accelerate their solution and business capabilities.
Make sure you’ll find everything you need to ace in the era of Industry 5.0 with this quick whitepaper preview.