{"id":56026,"date":"2022-03-19T10:49:32","date_gmt":"2022-03-19T02:49:32","guid":{"rendered":"https:\/\/www.tm-robot.com\/?p=56026"},"modified":"2023-04-26T15:58:17","modified_gmt":"2023-04-26T07:58:17","slug":"4-ways-to-integrate-ai-in-manufacturing","status":"publish","type":"post","link":"https:\/\/www2.tm-robot.com\/en\/4-ways-to-integrate-ai-in-manufacturing\/","title":{"rendered":"4 Creative Ways to Integrate Artificial Intelligence in Manufacturing"},"content":{"rendered":"
Manufacturing with AI<\/a> continues to find its way into improving the industry. Primarily, in the manufacturing industry, reports show that the global market can expect AI to thrive \u2013 it is expected that by 2027, market value will reach 9.89 billion USD.<\/p>\n Why is this the case? The manufacturers of today are seeing the impact, and are looking to implement AI \u2013 in one form or another \u2013 into their manufacturing plants, factories, and operation facilities. What\u2019s causing the surge?<\/p>\n The benefits of implanting AI in various manufacturing processes is said to improve quality by as much as 50% in the production phase. The question here is how.<\/p>\n Among the creative ways that AI can introduce and improve processes include: defect detection, quality assurance, predictive maintenance, and product assembly.<\/p>\n Manufacturing with AI systems are said to be able to detect defects in machinery and equipment even before they cause real damage. If you think about it, this prevents the downtime of operation facilities. It would also mean reduced wastes, lower costs for maintenance personnel, faster production times, better quality products, and overall improvement of productivity.<\/p>\n This is possible through a technique called machine learning \u2013 a system that learns from different data sets and patterns. Instead of inspecting each manufactured product manually, AI can be used to automate the process.<\/p>\n According to CNBC, AI can detect defects within seconds, saving 25% of energy costs. This has an impact on swifter decision-making based on the findings of the data driven technique. More than that, manufacturers can now focus on quality rather than testing for it \u2013 this increases efficiency and saves up almost 50% in terms of time spent.<\/p>\n What about quality assurance? Reading for this topic, one can learn that AI is able to reduce waste or rejections by as much as 50%. This is achieved through quality data being automatically generated and statistically relevant which improves the whole production process. Production time can be reduced, and more importantly, materials can be sourced properly to reduce costs of material wastage.<\/p>\n In the past, machines required a human operator to check for defects. This created issues in itself then, due to errors that may occur in interpreting data or quantifying it. With AI, companies can now gather more accurate insights into product quality and status of production lines, with just an algorithm at play.<\/p>\n4 Ways AI Can Innovate Manufacturing Processes and Systems<\/strong><\/h2>\n
Defect Detection<\/strong><\/h3>\n
Quality Assurance<\/strong><\/h3>\n