Today, the production processes are being automated with AI technology. The core of this machine-learning technology and software for design recognition can be the key to the future transformation of factories. What if computers, like people, started to learn from experience? And this has begun to take shape already.
It is a timeless production objective: to produce high-quality products at a low cost. It is already proven by Factory 4.0, which manufacturers are successfully achieving this goal more than ever and Industrial AI and ML is one of the core technologies that drive this new wave of ultra-automation. Data has become a precious resource and capturing and storing is cheaper than ever. Utilizing AI and, in particular, process-based machine learning, manufacturers can use data to significantly improve production efficiency, product quality, and safety for employees.
For manufacturers that can predict a part, machine or system failure, predictive maintenance has become a must-have solution. Predictive maintenance uses advanced machine learning AI algorithms and artificial neural networks to formulate asset malfunction forecasts. This makes for a drastic reduction in costly unexpected downtimes and the expansion of production machinery's Remaining Useful Life (RUL). In cases of unavoidable maintenance, technicians will be informed in advance about which components are necessary for inspection and what tools and methods they need to use.
Manufacturing companies find it difficult to preserve a high level of quality and comply with quality regulations and standards because of the very short deadlines for marketing and the growing complexity of products today. On the other hand, customers have expected unsuccessful outcomes, driving manufacturers to increase their quality while understanding the damage that a company and its brand can suffer from high defect rates and recall of products.
Tens of thousands of parts can be used in a complex manufacturing process. They must all be obtained, supplied, and stocked. It is essential that this supply chain is highly operational and functional—it is one of the tenants of lean production. The demand forecast for every industry is the sacred grail of supply chain management, but its applications benefit in particular from manufacturing.
For the application of AI, manufacturing fits perfectly. While Industry 4.0 is still in the early stages, there are significant advantages from AI for the world already. AI is aimed at changing the way companies manufacture products and process materials from the design and production floor to the supply chain and administration.