The AI in the manufacturing market is expected to be valued at USD 1.1 billion in 2020 and is likely to reach USD 16.7 billion by 2026; it is expected to grow at a CAGR of 57.2% during the forecast period. The major drivers for the market are the increasing number of large and complex datasets (often known as big data), evolving Industrial IoT and automation, improving computing power, and increasing venture capital investments.
Table of Content:
- COVID-19 Impact on the Global AI in Manufacturing Market
- What is AI in Manufacturing?
- Why is AI important in the Manufacturing Industry?
- Added Benefits of AI
- Challenges of Implementing AI in Manufacturing
- Is AI the Future of Manufacturing?
COVID-19 Impact on the Global AI in Manufacturing Market
The ongoing COVID-19 pandemic has led to economic disruption. It will eventually lead to distress to the supply chain and eventually push companies and whole industries to rethink and adapt to the global model for the supply chain. Many manufacturing businesses have halted their operations, and the supply chain and industry suffered collateral damage. Industries have started to rebuild their business model for 2020. Many small and medium-sized businesses and large industrial facilities have stopped/postponed new upgrades in their factories to recover from lockdown and economic downturn losses. The growth in the adoption of AI solutions is completely dependent on the growth of manufacturing units.
What is AI in Manufacturing?
Artificial Intelligence (AI) plays many roles in manufacturing. It is inherently linked to IoT (IIoT) and drives industry 4.0. There are hundreds of use cases for AI in manufacturing and various ways that help to increase industrial value. Machine learning (ML) is one of the most common AI subsets. Process manufacturing is a highly competitive industry with swiftly changing markets and complicated systems with many moving parts. Process plants require all the advantages that AI and ML can provide to drive innovation and enhance profits.
Machine learning in manufacturing usually enables predictive analysis, robotics, predictive maintenance, and automated processes that improve efficiency, cost-effectiveness, and safety.
Why is AI important in the Manufacturing Industry?
Using artificial intelligence in manufacturing plants allows companies to change their business operations completely. Let’s have a look at how AI helps the manufacturing industry to accomplish:
- Directed Automation
The use of AI and robotics are particularly observed in industrial manufacturing as they revolutionize mass production. Robots can do recurring tasks, design a production model, raise competence, develop automation solutions, eradicate human mistakes, and deliver higher quality superior levels of quality assurance.
- 24×7 Production
While humans are forced to work in 3 shifts to ensure continuous production, robots can work 24/7 in the production line. Businesses can be seen to increase their production capacity and satisfy customers’ high demand across the world.
- Safer Operational Environment
A step towards AI means that fewer human resources must carry out risky and too laborious jobs because of many mistakes in the manufacturing plant. Work accidents are reduced as robots replace human beings and carry out regular and dangerous jobs.
- Novel Opportunities for Humans
As AI takes over the manufacturing plant and automates boring and normal human jobs, workers focus on creative and challenging tasks. As AI handles unskilled labor, people can drive innovation and route their business to advanced levels.
- Condensed Operating Costs
Although AI would require a large capital investment in the industrial business, the ROI is substantially high. When intelligent machines begin to handle daily operations, businesses can benefit from much lower operational costs.
Added Benefits of AI
In recent years, AI and industrial automation have progressed significantly. Development in machine learning techniques, the advancement of sensors, and the growth of computer power have helped produce a new generation of robots. AI helps machines collect and extract data, recognize patterns, and learn and adapt to new things and environments via machine learning, intelligence, and speech recognition. Using AI, manufacturers will be able to:
- Create rapid and data determined decisions
- Facilitate enhanced production outcomes
- Advance process effectiveness
- Minimize operational costs
- Facilitate superior scalability
- Facilitate product development
Furthermore, AI understands the natural language very well and translates it, making communication with software easier for employees and supervisors.
Challenges of Implementing AI in Manufacturing
Manufacturing is a very well-established industry, although its importance is not sufficient enough. Companies demand employees with certain skills to design, manage and execute AI systems that are complex. These are the challenges faced by AI service providers:
- High revenue volatility
- Need to find cost savings continuously
- Short production times
- Agile and flexible enterprise capabilities and supply chains
- Increased regulation and inspections
- Learning and adaptability on the factory floor
- Manufacturing capacity and supply chain demands
- Increased need for small-batch or customized goods
Is AI the Future of Manufacturing?
The future of the manufacturing industry will be artificial intelligence. The manufacturing industry uses emerging technologies such as AI, ML, and so on, driven by increased product demand. Overall, using AI in manufacturing AI offers process optimization, low-cost overheads, and high productivity. It also enables manufacturers to make rapid and enhanced customer service decisions.
Get more information on Dash Technologies’ AI services and solutions for the manufacturing industry. Let’s see might our AI solutions in manufacturing help your business.
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50% of companies that embrace AI over the next five to seven years have the potential to double their cash flow with manufacturing leading all industries due to its heavy reliance on data, according to McKinsey.
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