Starting the road to metal 3D printing is not as difficult as you think

Metal 3D Printing-opportunities and challenges coexist At present, metal 3D printing is rapidly evolving from design verification to mass production of terminal parts. Metal 3D printing can now be applied to many industries such as aerospace, medical care, molds, automobiles, energy and power, rail transit, electronics, etc., and it is also penetrating into more industries, and the overall market capacity is rapidly increasing. 

Metal 3D printing is rapidly evolving from design verification to mass production of terminal parts in many industries. However, huge opportunities are often accompanied by severe challenges. Metal 3D printing has a high threshold. Under the traditional model, for novices to enter this field, they first need to spend several months or even a year on theoretical learning and establish an understanding of design, technology, materials, equipment operation, post-processing and other aspects. In the subsequent practical links, we will also face a large number of printing failures, as well as the high cost of equipment, materials and time invested during this period. In this mode, many people cannot cross this steep learning curve, or cannot afford such a high price, and are eventually blocked from the gate of metal 3D printing, thus missing such a huge business opportunity. This is undoubtedly a challenge. People regret it. So, is there a better model that can make the road to metal 3D printing simple and efficient?

Artificial intelligence escorts the road to metal 3D printing. Many people have the experience of learning to swim as a child. No matter how much time was spent on the shore to learn the theory before, the real mastery of this technology starts from the moment of jumping into the water. But the reason why he can summon the courage to jump into the water is largely because of the sense of security the coach brings to him. On the one hand, the coach can give guidance, but the more important role is to ensure that no accidents happen. The process of learning metal 3D printing is the same. Novices who rely on theoretical learning can only stay on paper. The key to speeding up the learning process is to enter the actual combat link as soon as possible. However, in this process, most people gave up halfway because they couldn’t bear the huge frustration. Imagine if there is a “coach” who can provide guidance throughout the process and help avoid various risks that may lead to failure, the process of learning metal 3D printing will surely be twice the result with half the effort. At Oqton, we believe that artificial intelligence can play this “coach” role. The unique advantage of artificial intelligence is that it can form knowledge through the study of massive data and use this knowledge to make decisions. Therefore, since the inception of Oqton, artificial intelligence has been the mainstay of the production platform we built. Under the escort of the “coach” of artificial intelligence, users can step by step, accumulate confidence from bit by bit of success, and with the improvement of technology and the growth of experience, they will more and more enjoy the fun and sense of accomplishment brought by exploration, and finally arrive The other side of success. 

How the Oqton platform solves the placement problem A major problem in metal 3D printing is how to find the best placement angle for the parts, which has a decisive impact on the quality and efficiency of printing. The ideal placement angle can reduce the amount of support material used, improve the surface quality of the parts, and greatly shorten the time and complexity of the post-processing process. However, mastering this skill requires long-term accumulated experience. Novices are often at a loss when faced with such open-ended problems. In order to solve this problem, the Oqton platform uses a placement algorithm based on artificial intelligence. This algorithm has been trained on a large number of parts and has been verified by many customers to ensure that it has sufficient reliability even when the user is just getting started. The Oqton platform can automatically identify the type of parts, and can also determine the placement angle according to the important surface of the feature recognition part, thereby ensuring the surface quality of the part. While providing recommended placement, the platform will also give reasons for choosing this placement method. For novices, this method is not only convenient and fast, but also a good tool for learning the principles of placement.

The Oqton platform recommends the ideal placement method through artificial intelligence, and gives the reasons behind it. With the growth of experience, users may express different opinions on the placement method given by the Oqton platform. The platform will learn according to the user’s preferences to adapt to the user’s habits and grow together with the user. The Oqton platform always starts with one or more recommended placement methods for users to choose. If the user wants to change the placement method, he only needs to make manual adjustments, and the platform will recommend this new placement method for similar parts in the future. This approach not only helps to improve efficiency, but also achieves the perfect combination of personalization and automation.