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Parts of the world, especially the manufacturing industry, appear to have gradually overcome the difficulties during the pandemic and the supply chain disruptions of a few years ago. However, manufacturers are expected to face new challenges by 2024, many of which can be solved through wider application of digital technologies.
Recent industry research has focused on the challenges manufacturers face this year and how they plan to respond. A study from the State of Manufacturing Report found that in 2023, the manufacturing industry is facing economic uncertainty and workforce challenges, and there is an urgent need to adopt new technologies to solve these problems.
Deloitte made a similar point in its "2024 Manufacturing Outlook," noting that manufacturing companies will face economic uncertainty, supply chain disruptions, and challenges in recruiting skilled labor. Whatever the case may be, Deloitte believes technology will play a key role in the future. This is also consistent with the conclusions of other studies, emphasizing the importance of technology in the development of manufacturing.
Specifically, technologies including the Internet of Things (IoT), automation, and analytics that support data-driven decision-making can help manufacturers improve operational efficiency, control costs, etc. These technologies are used in production environments to provide real-time insights and end-to-end visibility into processes. These insights and visibility enable manufacturers to identify production bottlenecks, inefficiencies and waste. Once these issues are identified, steps can be taken to help reduce downtime and improve operations.
In the long term, most manufacturers will increase their digital investments by fully adopting Industry 4.0 and smart manufacturing. According to a survey by Deloitte, 83% of manufacturers believe that smart factory solutions will change the way products are manufactured in the next five years. However, in the short term, the introduction and application of IoT, automation and analytics technologies can bring immediate and significant benefits.
Although the manufacturing industry has been severely affected during the epidemic, it has made a remarkable recovery despite the challenges of large-scale supply chain issues . However, there are still some issues that need to be addressed. Many manufacturers are looking to improve supply chain reliability by integrating IoT devices and production line data analytics. They hope to connect factory floor operation technology (OT) data with traditional enterprise IT systems such as ERP, CRM, etc., to better meet challenges. This integration can provide manufacturers with more comprehensive insights, helping them better manage and optimize production processes, thereby increasing efficiency and reducing costs.
Deloitte noted in its outlook report that by adopting digital tools, manufacturers can increase supply chain transparency. how did you do that? By combining OT and IT systems, manufacturers can become proactive in the ordering process. This data, combined with data from suppliers, enables manufacturers to digitize their supply chain processes.
While the manufacturing industry continues to introduce new technologies, the demand for talents is also gradually increasing. However, manufacturers are facing some difficulties finding skilled labor, according to surveys by Deloitte and others.
This challenge is not limited to manufacturing. Fortunately, across industries, many people are looking into generative artificial intelligence (GenAI), automation and other tools to make their work more efficient.
GenAI can be used to assist technical staff and help them become more efficient. For example, GenAI can be used to quickly summarize large device user manuals, find specific settings in device spec sheets, or search for anomalies in device log output.
By offloading these common tasks, GenAI frees up technical staff to accomplish more specialized tasks in a given time. This could reduce the need to hire more skilled workers in a market where skilled talent is hard to find.
Another common use of GenAI is to help people who are less technically competent than experienced employees. For example, an original equipment manufacturer that manufactures production line equipment might place a GenAI front end on its management console. GenAI could allow workers to type or speak requests, such as setting running speed to X, without having to understand cryptic command-line instructions. GenAI converts input or expressed requests into commands that the machine can understand. Here again, the application of this technology reduces the need to hire hard-to-find technical talent.
Similarly, intelligent automation of manufacturing processes based on real-time status data can save employees time. Likewise, by getting rid of rote tasks, employees have more time to spend on matters that matter. For example, instead of having workers routinely walk around the factory floor and assess the health of equipment, automation could be as simple as sending automatic alerts when equipment's health monitoring data exceeds thresholds.
Expanding the use of years-old technologies such as the Internet of Things, enterprise connectivity and analytics is key to solving the key challenges facing manufacturers in 2024.
Other technologies and wider initiatives currently being adopted will certainly play an important role in the future, including the full adoption of Industry 4.0 and the move to smart factories. The underlying technologies that power these efforts are the same technologies that are delivering benefits today.
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