An efficient pursuit towards analytics

The size of the global market for big data in the manufacturing sector was estimated at $576.47 billion in 2021. It is expected to increase from $731.13 billion to $4617.78 billion from 2022 to 2030 at a 26.7% CAGR. This article explores how Big Data, and the AI that helps categorise it, will be applicable in the manufacturing industry for years to come.

The use of Industrial Internet of Things (IIoT) and smart factories generates enormous amounts of data every day that needs to be monitored, analysed and classified. Thus, Artificial Intelligence (AI) and Big Data analytics have various potential applications in manufacturing. Manufacturers are increasingly using AI solutions like deep learning neural networks and Machine Learning (ML) to better evaluate data and make decisions.

Applications of AI and Big Data in manufacturing:

• Predictive Maintenance

• Preventing breakdowns: AI and Big Data are revolutionising maintenance strategies in manufacturing by enabling predictive maintenance.

• ML algorithms: ML algorithms process this data to identify patterns that precede equipment failures.

• Optimising machinery: Manufacturers can then schedule maintenance activities proactively, which reduces downtime and minimises production disruptions.

• Quality control:

• Enhancing product quality: AI and Big Data play a vital role in quality control by ensuring that products meet stringent quality standards.

• Real-time monitoring: AI algorithms process this data in real-time, identifying defects, irregularities or deviations from quality benchmarks.

• Reducing defects: By identifying and removing subpar products early in the manufacturing process, manufacturers can significantly reduce the number of defects that reach the final product stage.

• Supply chain optimsation: