Blog: Manufacturing in 2024 Means Embracing AI
Blog: Manufacturing in 2024 Means Embracing AI
The ability of manufacturers to gather, understand, and implement change, remains key to profitability and growth moving into the new year. And AI is at the heart of it all.
Amid an incredibly challenging job market and supply chain issues that persist into 2024, manufacturers are searching for solutions. They are confronting an alarming slowdown in some key sectors despite a hot economy and this has caused the lowest level of optimism among manufacturers since Q2 2020.
The one bright spot that continues to shine amid the often bleak manufacturing news is artificial intelligence and machine learning (AI/ML), in all its forms, including generative AI (GenAI). Data, it seems, and manufacturers’ ability to gather, understand, and implement change, remains key to profitability and growth moving into the new year. In fact, AI in all its forms will be the most important area of technology for manufacturers according to a new global survey, “The Impact of Technology in 2024 and Beyond.”
The idea of data driving the strategy of manufacturers has been around for a long time. The potential for AI in manufacturing has long been touted as an eventual key to unlocking significant value in the form of efficiency and reduced operational costs. According to McKinsey, using AI/ML, manufacturers can reduce downtime by up to 50 percent and reduce the costs that come with quality-related issues by up to 20 percent.
Become a Member: How to Join ASME
But despite what proponents such as the World Economic Forum predict about AI, the uptick in usage has continued to be slow as well as uneven. Yet, most manufacturers report that turning to AI/ML is inevitable. According to the “Manufacturing in 2030 Survey,” 84 percent of manufacturers report that they expect the pace of digital transformation to accelerate over the next decade.
Most manufacturers understand AI/ML fueled by sensors are able to monitor everything from temperature to system flow. With an unprecedented amount of data (both internal and external sources) they have come to understand that data allows them to better understand processes and systems and make better decisions.
Yet the technology exemplified by ChatGPT, may have more immediate results in 2024. In "The State of Manufacturing and Generative AI Adoption in Manufacturing Organizations," manufacturers report that they are turning to GenAI to improve production product development and design. One key obstacle to AI in general is the dependence on large, labeled datasets for training AI systems.
More for You: Podcast: How AI Could Impact Manufacturing
Collating these datasets can be resource-intensive, especially because images of component defects, for example, can be difficult to obtain. GenAI addresses this shortcoming. By leveraging the technology, AI practitioners are able to create synthetic data to train AI, enabling it to detect defects through visual quality inspection (VQI) systems, including surface mount technology (SMT) and through-hole technology (THT) anomalies.
Beyond production companies are looking to put GenAI to work with supply chain optimization, workforce augmentation and empowerment, and sales and customer service. But AI/ML remains a long-term strategy for most companies. Not a quick fix to get instant results or put a band-aid on broader challenges, but many are looking at the future of manufacturing see AI/LM at the heart of it.
Cathy Cecere is membership content program manager.
The one bright spot that continues to shine amid the often bleak manufacturing news is artificial intelligence and machine learning (AI/ML), in all its forms, including generative AI (GenAI). Data, it seems, and manufacturers’ ability to gather, understand, and implement change, remains key to profitability and growth moving into the new year. In fact, AI in all its forms will be the most important area of technology for manufacturers according to a new global survey, “The Impact of Technology in 2024 and Beyond.”
The idea of data driving the strategy of manufacturers has been around for a long time. The potential for AI in manufacturing has long been touted as an eventual key to unlocking significant value in the form of efficiency and reduced operational costs. According to McKinsey, using AI/ML, manufacturers can reduce downtime by up to 50 percent and reduce the costs that come with quality-related issues by up to 20 percent.
Become a Member: How to Join ASME
But despite what proponents such as the World Economic Forum predict about AI, the uptick in usage has continued to be slow as well as uneven. Yet, most manufacturers report that turning to AI/ML is inevitable. According to the “Manufacturing in 2030 Survey,” 84 percent of manufacturers report that they expect the pace of digital transformation to accelerate over the next decade.
Most manufacturers understand AI/ML fueled by sensors are able to monitor everything from temperature to system flow. With an unprecedented amount of data (both internal and external sources) they have come to understand that data allows them to better understand processes and systems and make better decisions.
Yet the technology exemplified by ChatGPT, may have more immediate results in 2024. In "The State of Manufacturing and Generative AI Adoption in Manufacturing Organizations," manufacturers report that they are turning to GenAI to improve production product development and design. One key obstacle to AI in general is the dependence on large, labeled datasets for training AI systems.
More for You: Podcast: How AI Could Impact Manufacturing
Collating these datasets can be resource-intensive, especially because images of component defects, for example, can be difficult to obtain. GenAI addresses this shortcoming. By leveraging the technology, AI practitioners are able to create synthetic data to train AI, enabling it to detect defects through visual quality inspection (VQI) systems, including surface mount technology (SMT) and through-hole technology (THT) anomalies.
Beyond production companies are looking to put GenAI to work with supply chain optimization, workforce augmentation and empowerment, and sales and customer service. But AI/ML remains a long-term strategy for most companies. Not a quick fix to get instant results or put a band-aid on broader challenges, but many are looking at the future of manufacturing see AI/LM at the heart of it.
Cathy Cecere is membership content program manager.
Related Content
Manufacturing Blog: Workforce Skill Gaps Makes 4IR Inevitable
Nov 20, 2024
Manufacturers finally incorporate Industry 4.0 technology to maintain production amid the challenges of evolving trends and worker technical skills shortfalls.
Podcast: Don't Neglect the Caster
Nov 18, 2024
Manufacturing companies are tackling a myriad of challenges, from growing automation to talent shortages, that are requiring new strategies and solutions.
Low-Temperature Production Could Lead to More Uses for Ammonia
Oct 14, 2024
Rare-earth metals capture nitrogen without high temperatures or pressures.
Researchers to Create a Digital Library for Aircraft Parts
Sep 30, 2024
Some airframes are many decades old. Scanning and digitizing components could enable small manufacturers to produce replacement parts.