Artificial Intelligence (AI) and Machine Learning (ML) will impact almost all areas of manufacturing and supply chain in some manner. Schedule optimization, predictive maintenance, and predictive analytics are already being implemented within manufacturing.
Projects that would benefit from AI and ML implementation are applications that require personnel to review complex data multiple times from various sources to find subtle correlations in the data. Due to the difficulty in processing this type of data, typically gutfeel or tribal knowledge is the basis for decision-making in these projects resulting in variability and lack of consistency across the organization.
Given the potential applications for AI and ML, implementing these technologies will likely accelerate within the food, beverage, and consumer packaged goods industries.
Vision Systems were developed when technology allowed us to use tools to detect nuances within the digital picture, mostly based on pixels. AI and ML are now able to examine still pictures and videos and see correlations based on history with more advanced detection.
As this technology continues to develop, vision systems and other forms of digital picture and video capture will improve to provide insights that were previously not considered.
Currently, startups are using this as an opportunity to develop solutions that can pull critical insights from the picture or video or take advantage of the greater picture resolution to see meaningful nuances. These solutions are used to detect counterfeit products, identify the uniqueness of a specific item (product, case or pallet), and much more.
AI Analysis and Data Potential
Data from all sources can now be efficiently analyzed using AI. We no longer theorize and then test what variables are impacting process or product quality. AI will consolidate and contextualize the data to determine what is impacting process and product quality – and maybe even find correlations that were not previously considered!