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Home›3D printing start ups›Key Areas of AI Adoption in Manufacturing

Key Areas of AI Adoption in Manufacturing

By Shirley Allen
July 4, 2021
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The latest revolution in the industry is the better integration of the factory stack and the creation of a synergistic ecosystem to enable MaaS (Manufacturing as a service). Likewise, software-defined manufacturing is rapidly evolving to bring the next level of automation.

Everyone is talking about AI and its global impact on the different facets of the industrial life cycle. Having a clear idea of ​​where AI can be applied to gain efficiency, profitability and better customer service will help entrepreneurs adopt it quickly.

Tests and quality control: It is a critical task in the manufacturing process at every stage of the operation. Whether you are assembling a product or producing it from raw materials, you will need to check if the result is as expected. For this, AI combined with various industry sensors plays a very effective role. It can include temperature sensors, camera sensors, pressure sensors, vacuum sensors, vibration sensors, motion sensors, torque sensors, etc. Depending on the product you are dealing with, you will get appropriate triggers and data values ​​that will give you enough information about the quality of the product. Based on this, you can accept or reject the result and take appropriate action.

Preventive maintenance: Currently, industries spend billions of dollars to maintain, replace and upgrade their equipment to ensure continuity and efficiency. It is important that spare parts and equipment receive the proper attention before they begin to affect performance or damage the entire machine. To prevent loss and unwanted defect in their products, many start-ups have developed innovative solutions whereby every smallest spare part in the plant can be monitored 24/7 and triggers can be generated whenever a specific part needs to be inspected or replaced. This results in considerable savings for the company and continuous operation of the factories. Companies also use drones and robots for maintenance when the field of operation is large, for example power lines, gas pipelines, oil pipelines, water networks and fiber optic cables.

Digital twins: Automation becomes part of complex tasks and products are becoming more and more sophisticated. Thus, it is necessary to have a complete simulation / shadow / copy of the underlying digital plan of any factory. As many of these factories can involve millions of lines of software code and other artifacts, it will be crucial to deploy the digital twin from the original factory to another factory, so that the quality and specifications of the product remain. the same. Digital twins technology helps companies reproduce processes seamlessly and save a lot of costs. Imagine the complexity of producing self-driving cars with all the AI ​​models associated with them; the complexity of producing space rockets, robots, jet fighters or even submarines. Digital twins technology will certainly be a boon for all these sectors. Even if you are producing genetic material, pharmaceutical compound, chemical dye, artistic design, etc., it contains so much detail at the micro / nano level that digital twin technology will be crucial for the reproduction of the systems. Digital twins are now also used in the design of oil rigs, Giga factories, chip manufacturing, mobile production, 3D printing, etc.

Other areas of focus include the deployment of RPA (Robotic Process Automation) to automate routine tasks such as invoicing, invoicing or accounting. AI can also be used to better forecast demand for different products over the coming quarters or to help maintain a balanced supply of plant inventory by supporting complex scenarios. With the advancement of NLP, AI can now also take care of the production of reports, compliance documents, periodic target scans, etc. On the customer side, chatbots, customer service assistants in the form of chatbots can contribute to better customer satisfaction. Smart robots can also help with warehouse operations, packaging and storage.

There is no doubt that AI is becoming crucial for the manufacturing industry to remain competitive in the market – and it will soon become a must-have accessory for many companies.

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The opinions expressed above are those of the author.



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