Impact of AI & ML in Manufacturing Industry – Overview
- It’s an eternal manufacturing goal: to produce more and better-quality products at the lowest cost.
- Artificial intelligence (AI) plays many roles in manufacturing. It is inseparable from the Industrial Internet of Things (IIOT), driving Industry 4.0 forward.
- It is without a doubt that AI technology is used by more than 60% of manufacturing companies. AI in manufacturing reduces downtime while also ensuring high-quality end products.
- The “smart Mobile app for manufacturing” revolution has enabled manufacturers to achieve this more successfully than ever before – and one of the core technologies driving this new wave of innovation is industrial artificial intelligence.
- Data has become an extremely valuable resource, and it is cheaper than ever to collect and store it. Today, thanks to artificial intelligence – especially machine learning – more and more manufacturers are using this data to dramatically improve their profits.
- According to Forbes, one of the major problems is the data infrastructure. Data infrastructure struggles to keep up with the massive flow of data generated daily as products travel from field to floor or from factory to destination.
- Many manufacturers are still trying to run their business with outdated systems.
- However, the need for more information sharing, collaboration, and connectivity is clear as a bell.
- Indeed, manufacturers working in silos struggle to innovate and are even more vulnerable to disruption than those on their digital transformation journey.
- And while digital technologies like AI/ML help build sustainability and overcome barriers, adoption is often slow.
How can AI/ML help in process plants?
Process plants depend on AI to integrate information, analyze it, and manufacture the deep insights and predictions that facilitate drive higher decision-making across the board. mil is the form of AI that crunches immense datasets to identify patterns and trends, then uses them to create models that predict what is available in the long run.
ML enables plants to forecast fluctuations in demand and provide, estimate the simplest intervals for maintenance schedules, and spot early signs of anomalies. With the assistance of AI and ML, manufacturing plants can:
- To save money, look at alternative cost savings and minimize waste.
- Recognize market trends and changes
- Comply with regulations and industry standards, improve safety, and minimize the environmental impact
- Identify and eliminate bottlenecks in the manufacturing process.
- Enhance visibility into the supply chain and distribution networks
- Detect early signs of malfunction or discrepancies to aim at reducing downtime and speed up repairs.
- Assist in promoting more accurate root cause analysis
How does Optisol help one of the leading manufacturers to streamline a portion of their process using AI/ ML technology?
- Streamwise reports for each individual processing plant along with the main manufacturing plants.
- Module for updating targets KPIs against each stream and plants
- Stream-wise and plant-wise daily entry of actual KPI based on group and equipment.
- Dashboard to view the performance of the plant levels on a monthly, weekly, and date range basis and for Manufacturer’s levels based on each stream like Fuel, Power, manpower, etc
- Modules to view best-performing plants, groups and shift with top three performers highlight and display ranks for each plant and subgroups.
- Ability to set WIP adjustments against targets and actual to increase the efficiency of the processing plants.
How big is AI & ML in the Manufacturing sector?
According to Precedence Research, the artificial intelligence (AI) market size is projected to surpass around US$ 1,597.1 billion by 2030 and is expanding growth at a CAGR of 38.1% from 2022 to 2030.