The key application of Artificial Intelligence in heavy equipment and machinery industry is a dynamic shift in how heavy equipment operator uses artificial intelligence as a safety and enhanced productivity measure in today’s time.
Companies like Komatsu partnered with NVIDIA to develop construction AI solutions for the job-site by deploying intelligent cameras. It helps them in addressing the safety risks and inefficiencies in construction.
An example of artificial intelligence in heavy equipment industry is that with the help of them experts can guide machine operators through complex operations from a remote location. Machine learning and AI can be used to detect a design flaw for specific machinery missed by the operator and the manufacturer. This in turn can cause considerable damages. This is where machine intelligence helps in predicting faults way ahead of time. Thus, the cost of failure that could amount to millions can be prevented.
According to Skanska, Norway spends $11.15bn (NOK 100 billion) a year on road construction, with about 70% of that expenditure linked to fuel, personnel and the operation of machinery. It teamed up with Volvo Construction equipment, a research organization and a software company in January 2020 to use artificial intelligence to better coordinate the movement of heavy machinery on construction sites
As per an article published by Forbes, many construction sites are also using AI to run what-if scenarios and contingency planning. The similar pattern detection software that works with scheduling can be deployed to look for common trends in the project. Drones are used for surveying and taking overhead images of construction sites allowing a complete view of the site through various stages of the construction project. Robots are being used to help with various tasks such as bricklaying, pouring concrete, or installing drywall. AI-enabled surveillance systems are helping enterprises in protecting expensive equipment and machinery at the site.
Futuristic warehouses are using driver-less robotic equipment to assist in picking and moving operations. Most frequently used systems are Global Positioning System (GPS), lasers, and radio-frequency identification(RFID). Companies like Cyient help heavy equipment customers embrace digitization and maximize value across the product life cycle, from concept initiation to aftermarket services along with value add analytics, IIoT, smart embedded systems, and power electronics design.
The various aspects where material handling can leverage AI are
- Conveyors, wherein AI can be used to place or move products horizontally, vertically, around corners etc.
- Self-Driving Vehicles (SDVs), where the machine is designed in a manner that it can sense and eliminate physical obstacles on the configured travel path
- AI-enhanced racks that can count the stock and report data to supervisors via a system message
Additionally, each time when a robot picks a product or places a product in a location, a message is sent to the warehouse control system confirming the same.
The study commissioned by Forrester Consulting on behalf of SAP showed that manufacturers preferring digital priorities were important for their business. Interestingly, those manufacturers that considered themselves innovative had a much higher focus on digital priorities than other companies.
Accenture research suggests AI will add approximately $3.7 trillion to the manufacturing sector by 2035.
One of the major challenges for companies that want to heavily invest in AI will be to achieve interoperability. This means creating flawless integration between AI and the company’s IT infrastructure, best worker-machine and partner ecosystem collaboration.
As per Capgemini, the various technologies that help in establishing flexible and optimized value chain for heavy machinery industries are
- Construction Management Software
- Digital Twin
- Automated Construction Forecast
- Robotics & Drones
- Connected Services
- Intelligent Automation
- Market Places
- Functions on demand
- Connected Machines
The current applications of AI in heavy equipment industry is paving a way for smart manufacturing in future that will not only enhance machine performances, but will also ensure minimal risk attached with operator’s and worker’s lives. Going digital, is no more an option rather it’s a necessity to thrive in the upcoming global scenarios and staying ahead of competition.
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