The Artificial Intelligence Impact on Manufacturing Industry
To thrive in today’s global markets, manufacturers must optimize everything under their control. Manufacturers are redefining their environment with technologies that connect products, smart factories, and supply chains in unprecedented ways. Massive volumes of data and the application of artificial intelligence in the manufacturing environment are fueling this transformation.
By 2025, the market for Artificial Intelligence in manufacturing is expected to increase at a rate of about 50 percent per year, reaching $17.2 billion.
Benefits of AI in Manufacturing
Artificial Intelligence incorporates the functionalities of learning systems that are recognized as intelligent by humans. Artificial intelligence have risen to prominence on the manufacturing priority list, as the manufacturing industry is undergoing massive upheaval as a result of adopting artificial intelligence.
“According to the AspenTech 2020 Industrial AI Research, 83 percent of large industrial organizations believe AI provides better outcomes.”
Also Read: How AI helps in healthcare facilities for a better outcome.
Some of the benefits enabled by AI for the manufacturing industry are:
- Smart production
- Develops predictive and preventative maintenance
- Improves supply chain optimization
- Product development and optimization
- Cost reduction
- Quality assurance
- Green operations
Manufacturing industries are the most common users of AI to improve overall equipment efficiency and yield. AI is also being used to improve efficiency, quality, and consistency in general, allowing manufacturers to forecast more precisely.
Mark Crowne, general manager of systems integrator Nexer Insight UK, says, “In the last five years, there has been a huge reduction in the complexity and cost of applying AI to manufacturing, thanks to the democratization of machine learning by the hyper-scale cloud vendors.”
“More than 80 percent of C-suite executives trust that AI will help them accomplish their growth objectives.”
Use cases of AI in Manufacturing
Let’s take a peek at few of the prevalent AI use cases in manufacturing, as identified by McKinsey & Company in a widely referenced report on AI in the industrial sector.
To predict and avert machine failure, smart manufacturers are integrating AI systems with IoT data. The goal is to employ predictive maintenance to reduce downtime and inconvenience, mitigate risks, and swiftly fix issues.
“According to McKinsey, AI-driven predictive maintenance can boost asset productivity by up to 20 percent while lowering maintenance costs by up to 10 percent.”
Supply Chain Management
Manufacturers can now make use of AI to predict the sophisticated interactions between each production plant and automate requests for labor, materials, equipment, and repairs.
“According to McKinsey, AI-enhanced supply chain management can help businesses minimize forecasting errors by 20 to 50 percent, allowing them to optimize stock replenishment.”
Manufacturers can now utilize AI systems to reduce defective product scrap rates and extract more value from the materials used in the production process.
“According to McKinsey, in the semiconductor industry, lowering scrap rates and testing costs can result in yield detraction of up to 30% of overall production costs.”
Business Support Functions
AI can assist firms in automating essential aspects of labor-intensive support services. According to McKinsey, this automation of support services will result in increased process quality and efficiency.
Research and Development
The application of AI in the R&D sector has lots of potential. Below are some of the benefits.
Assist design and engineering teams in collaborating more effectively
Selecting the optimal materials for a product
Recognizing design flaws that are prone to failure.
The future of AI in the Manufacturing industry is continually evolving. AI is already assisting businesses in staying ahead of the performance of their assets and influencing their bottom line. This trend is likely to persist. AI will continue to be one of the keys to the success of the manufacturing industry in the digitally driven industrial revolution.