Artificial intelligence, or AI, technology is transforming many aspects of our lives and this includes manufacturing. Used correctly, it can help streamline processes, resulting in improved efficiency and reduced costs.
Generative design
AI is being used at all stages of the manufacturing process. Generative AI design tools are already in use. These can explore design options based on parameters such as materials and manufacturing constraints, allowing designs to be quickly evaluated. It should be emphasised that these are tools, used by human designers to help accelerate the process.
Cobots
Cobots are collaborative robots that can work alongside human workers, handling physically demanding and repetitive tasks. This can help improve safety in the workplace and free up human workers for more creative and less repetitive tasks. This represents a significant advance in automation, something that is nothing new in manufacturing. For example, Roscamat electric tapping machines are a form of automation that has long been in use. Today’s factories will see a mixture of humans, traditional automated devices like Roscamat electric tapping machines and cobots.
Management
AI can be used in a variety of management roles. For example, it can keep track of inventory and analyse data to predict demand, automating supply processes. It can also monitor the use of energy in real time, checking for energy saving measures to help save money and reduce an organisation’s environmental impact. It can even manage employees, analysing data to advise where employees are best deployed and create optimal shifts to improve production.
Digital twin
Digital twin technology allows AI to create a virtual replica of aspects of the manufacturing process such as production lines or supply chains. These can be used for simulations or to analyse data and production in real time.
Custom manufacturing
Traditionally, customised products would take longer and would require extra expense. But AI can easily integrate customisation into the process without slowing down production. It can also use customer feedback and data in real time to quickly adapt to customer preferences, resulting in a higher level of customer satisfaction.
