Industry 4.0 has revolutionised the sector with automation, machines and smart factories that help produce goods more efficiently and productively within the value chain. But is this the reality for industrial companies or is there still a long way to go?
In this article we will tell you about the 5 challenges that remain to be met in order to consolidate themselves in the 4.0 stage.
Collaborative robotics, also known as cobots, have landed in Industry 4.0 to offer more efficient, automated, safe and accessible environments, designed to interact with the human team, understanding their use as a collaboration and not as a replacement of the human team. Its high investment and the need for an environment in line with its implementation means that many of the companies in the industrial fabric still do not value its immediate incorporation.
The most common functions are the manipulation of elements and repetitive tasks. They base their work on artificial intelligence to provide the most efficient solutions for each environment. The software that accompanies the cobots is simple and intuitive with a large sensory network and easily calibrated for rapid incorporation into the production chain.
3D printing and additive manufacturing
Advances in manufacturing techniques are a reality and the latest step is additive manufacturing. It allows the production of three-dimensional objects from virtual models in different materials and sizes.
At the industrial level, the challenges are innumerable, the first difficulty being the manufacture of certain materials, which, due to their composition, weight or arrangement, are very complicated to produce, in addition to their slow manufacturing process and high energy consumption.
The most advanced companies in this technique are those dedicated to the use of moulds and dies or aeronautics and the automotive industry, due to the need to make made-to-measure parts with specific characteristics.
The management of information and the use of data is also a cornerstone of Industry 4.0. The use of cryptography allows for greater protection and optimisation of the value of data.
Within the industrial landscape, if information can be immediately stored, shared and fully transparent within the entire capital goods pool, added value and optimisation of resources within the value chain is achieved. However, as with the previous points, implementation costs are a handicap when it comes to installation, and private keys (excessive security) and storage (as users and transactions grow, more space is needed) can be a disadvantage in the long term.
Any digital transformation must start with IoT as a basis, i.e. the connection to the internet of different equipment operating in a production plant, where smart sensors, automation mechanisms and devices allow to improve the efficiency of industrial processes. If you want to know where to start with all this, we tell you in our article 5 keys to industrial IoT.
Simulation and digital twins
Digital twins and simulation allow us to create virtual copies of what the final version of the product will be, ensuring its future and predicting possible problems in advance.
But this simulation goes further, it collects data in real time and allows us to have them as a basis for future projects, even working autonomously by being able to analyse a situation, propose optimised solutions and implement them. This is what is known as Machine Learning.
One of its main drawbacks is the need for qualified personnel to apply these digital twins, as it requires a strict integration and industrial automation architecture.
Each of these points underpins the foundations of a powerful Industry 4.0. Some companies have already gone through all these steps completely, others are still in the process. Industry will need to invest in qualified personnel, innovation and digital transformation in order to continue to be a driving force for employment and economic growth.