Robotics has become a staple of the manufacturing sector, essential for maximizing productivity, ensuring quality, and reducing labor costs. As valuable as robotics are, many solutions fall short of the time-to-impact metric that manufacturers seek. Enter Artificial Intelligence (AI)-based, closed-loop automation.
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Industrial machinery suppliers are faced with the tall task of pushing the innovation envelope, while keeping production costs at bay. Customers require machines that unlock new use cases, but at the same time don’t necessitate significant training time for employees. To strike this balance, suppliers should strongly consider the adoption of immersive engineering solutions powered by Extended Reality (XR) hardware. As ABI Research already pointed in a recent blog post, cloud-based XR platforms foster greater collaboration between engineering and design teams, reduce error rates, and accelerate the design review process.
Immersive engineering is a game-changer for industrial machinery suppliers as they aim to enhance quality and productivity, while reducing costs and their carbon footprint. Their customers, who cite machine performance improvements as a top priority, have increasingly required new tools and products as they tackle recent headwinds such as COVID-19, worker strikes, and safety recalls.
Nearly 45,000 people and 900 exhibitors signed up for Automate, the largest robotics and automation trade show in North America, held in Chicago May 6-9, 2024. As a show, Automate is more focused than Hannover Messe or IMTS and, consequently, there were many automation and tooling suppliers, including ABB, Atlas Copco, and FANUC that chose this event over its larger peers.
Generative Artificial Intelligence (AI) is one of the booming technology topics of our time. ABI Research has multiple research products and articles covering how generative AI will transform the modern enterprise. The manufacturing sector is one industry that gains tremendous benefits from using generative AI. Whether it’s product design or inventory management, there are many use cases for generative AI in manufacturing. In this article, I’ll identify five examples of how generative AI can be applied to the manufacturing industry.
Despite volatile economic conditions, the manufacturing industry is continuing its push for the “smart” digital factory. Some of the pressures spurring growth in digitalization include labor shortages, sustainability goals, and increased demand for products. In our manufacturing industry outlook, we highlight 6 significant trends that manufacturers and technology suppliers should think about as it relates to a 2023 game plan.
In chemical manufacturing, potential failure can happen in many operational areas. This is because of the complex nature of chemical production and the large number of assets deployed in a chemical plant. To reduce the frequency of manufacturing inefficiencies, the chemical industry should invest in digital transformation. Beyond operational efficiency, digital transformation in the chemical industry helps companies meet other agendas, such as workplace safety, sustainability goals, and tackling labor shortages.
Digital twin companies are in a prime position for robust growth. In 2021, ABI Research forecasts US$3.5 billion in revenue coming from digital twin software. But by 2030, we anticipate that number to soar to roughly US$34 billion as digital twin solutions are embraced across all verticals (manufacturing, industry, smart cities, etc.). This post will provide an in-depth profile of five of the top companies providing innovative software within the digital twin market.
Forecasting where exactly the Electric Vehicle (EV) supply chain is going is a nearly impossible endeavor, with a wide range of unpredictable factors to consider, such as fuel prices, attitudes toward green energy, government policies, availability of charging stations, vehicle range, and vehicle affordability. One thing that can be concluded is that Original Equipment Manufacturers (OEMs) are going to focus on providing flexibility to consumers in order to gain market share. But the rapid development of so many new car models will place a tremendous amount of pressure on ecosystem partners that can’t meet demand in such a short time span, resulting in inevitable issues with the EV supply chain.
