Systems monitoring and data analytics tools are commonplace in manufacturing factories today. These tools are used not only to facilitate remote work, but also to help management teams get precise data on production yields and operational efficiencies.
With data tracking turning into a routine practice for factories, artificial intelligence (AI) is quickly becoming a reality in the future of factories.
Data is at the foundation of all AI solutions. An AI programme can learn about a machine’s processes through the data that it receives. It then generates an algorithm to reach an outcome specified by the user. To do so, AI solutions need not just data, but big data – extremely large data sets that can reveal patterns, trends, and associations.
The factory floor is getting increasingly connected. Previously offline machinery can now be easily connected to the enterprise network through a monitoring device. Over time, more complex data sets can be developed to build a better understanding of operating processes and improve manufacturing outcomes to prepare for a fast-evolving economy.
As we move steadfastly into the future of work, here are 3 ways you can deploy AI solutions to your manufacturing environment!
1. Improve quality control
AI solutions can synthesise huge data sets to identify inconsistencies in the production process. This can help manufacturers rectify problems quicker and reduce unnecessary cost due to product issues. Human error from manual quality control processes can also be eliminated if an AI solution is deployed. It ultimately frees up manpower to do more meaningful tasks within the factory floor.
2. Reduce unplanned downtime in the factory
Unplanned downtime can cause severe disruptions to the rest of the supply chain, which relies on each element in the chain to function like clockwork all the time. However, as the term suggests, it can be difficult to predict or pre-empt when unplanned downtime will strike within a factory. Using AI solutions, factory owners can utilise the predictive features of AI to spot errors or issues in the system before they blow up, and allow operators to rectify issues, or prevent them altogether.
3. Predictive analysis on demand and supply
During the pandemic, factory operators felt first-hand what it was like to deal with an unprecedented event that disrupted the demand for products and the flow of goods in the global supply chain. As such, many operators are looking into ways to cushion the effects of a future disruptive event. One way of doing so is by using AI solutions to predict the needs of the market. By analysing data from sales, the industry, and the factory, operators can get a better sense of the demand in the market, and adjust their outputs accordingly to save cost and reduce waste.
Contact us if you’d like to learn more about AI solutions in the factory!