Like humans, Artificial Intelligence system understands, adapts and learns from their experiences, which is called as Artificial General Intelligence (AGI). Based on the vast amount of data they encounter; they adjust and improve their performance over time which we also call as “Strong AI”. narrow AI has limitation to solve general problem, by reasoning, learning and planning which AGI is capable of. In discrete manufacturing space, with the capability of AGI there is huge potential to enhance efficiency, Innovation and productivity in the process.
Application of AGI is vast we will consider few of them:
Predictive Maintenance:
AGI can prevent unplanned downtime, due to its inherent ability to digest huge data, where the data is generated by sensors associated to machinery, by identifying patterns and anomaly. Their real time monitoring ensures that equipment is always maintained at optimum level. This involves skilled professionals to interpret and act in timely manner on the insights generated by the AGI.
Quality Control:
Vision systems powered by AGI can catch the defect accurately which otherwise could be a potential miss by human oversight causing disruption at a later point downstream in the process. Also, AGI can minimize the risk of product recalls and customer dissatisfaction due to its ability of real time inspection.
Intelligent Automation:
Automation powered by AGI can improve productivity there by reducing the labor costs. using predictive analytics, it can optimize on allocation of resource and production schedules there by maximizing the output and minimizing the potential disruptions. It aids autonomous decision making in manufacturing environment by managing inventory levels and adjusting on machine parameters.
Product Development and Design:
Generative design algorithms powered by AGI can generate many options based on specific objectives and constraints, thus enabling the manufacturers to explore wider range of possibilities. They can optimize product performance by helping manufacturers identify potential flaws in the design under various conditions. They help reduce the time taken from design to manufacture handoff by improving collaboration between manufacturing engineers and design teams.
Supply chain optimization:
AGI can optimize the transportation routes, supply chain networks and warehouse operations to improve efficiency and reduce costs. Using predictive analytics, they can predict demand and forecast accurately thereby reducing stockouts and excess inventory. They help manufacturers by identifying alternative suppliers and optimizing the transport modes.
Thus with human like ability to learn, adapt, reason; AGI can automate complex tasks, optimize processes, aid in quick decision making in discrete manufacturing industry. By embracing the AGI, manufacturers can stay ahead of the curve, drive innovation and create a more sustainable future. The potential is immense.
