Companies understand the potential of current technologies to deal with not only safety issues but also their ability to make the work processes more efficient.
FREMONT, CA: Construction has always been a risk-prone industry. The heavy machinery, uneven terrain, non-stop application, and human errors are the primary threat instigators. Despite extreme security measures, preparations, and technological incorporations, fatalities are still difficult to avoid. So how can current technologies such as artificial intelligence (AI) have a say here?
Companies understand the potential of current technologies to deal with not only safety issues in construction but also their ability to make the work processes more efficient. AI, in particular, is well-suited to construction. A practical example to demonstrate the increasing reliance of the companies on the modern technology is the tie-up between U.S. based NVIDIA and Japan’s Komatsu, one of the largest manufacturers of mining and construction equipment in the world. Komatsu will design 3D images of sites, while NVIDIA’s smart cameras will interact with drones and cameras on the job site and act as a visualization and analysis AI platform.
AI for Original Equipment Manufacturers (OEM)
OEMs are developing new operating capabilities in critical areas of the value chain to leverage AI. Here are some of the good practices that can lead the manufacturers closer to their desired goals:
• Procurement and Talent
OEM supplier strategies must be more technology-centric that enlists onboard software, the aid of telematics, analytics provider, and wireless connectivity. Apart from production engineers, more data engineers and digital specialists will be required.
• Manufacturing and Design
The core machine and deep learning algorithms will considerably impact the design and manufacturing processes. The designs often involve the requirement of complex prototypes. AI-enabled products can fetch the relevant data for research and development processes and provide continuous feedback for the betterment of processes.
• Risk Management in Manufacturing
Advancements in AI have enabled the businesses to automate complex tasks and gain actionable signals from data that were earlier incomprehensible. Moreover, AI can significantly reduce human errors by helping them with redundant tasks and thereby will save money as well as time.
• Areas for Improvement
Natural language processing and text analytics allow the manufacturers to connect service comments, customer sentiment, and other written records to production variables and quality. It enables them to dig into the areas for improvement.
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