The manufacturing industry was always at the forefront of developing and adopting new technologies to increase production and efficiency. As such, they are also pioneers in using artificial intelligence in manufacturing. As a result, the steel industry is among the first to adopt AI and IoT technologies that show incredible results.
Steel companies use data to streamline production, increase product quality, reduce waste, and redefine production processes. The right AI solution can help steel manufacturers save a lot of money during production, so let’s take a closer look at how AI strengthens steel production.
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Challenges of Adopting AI in Steel Manufacturing
AI-powered manufacturing solutions provide a long list of benefits, but adopting them doesn’t come with certain challenges. The integration process must be done according to the best practices to get the most out of the technology. Here are some of the challenges you have to face down the road.
Operational Data Organization
AI has the power to help streamline production, increase manufacturing efficiency, and improve overall product quality. However, to do so, it needs access to operational data. The first and most important step when adopting this technology is to ensure that the central AI platform has access to high-quality operational data. After IoT sensors are placed all over the facility, they generate operational data and send it to the AI that learns how everything works.
Once it analyzes large amounts of data, the AI can find areas that need improvement to help increase production and efficiency. Generating so much data requires a significant amount of storage space and careful optimization of data pipelines. You’ll need a few experienced data scientists to set things up and ensure that your data is stored and used safely.
Finding The Right People
As you can imagine, adopting new technologies requires people with the right skills. For example, artificial intelligence in the steel industry takes the world by storm. As more and more manufacturers enter the digital transformation process, finding data scientists is more complex than ever before.
If you’re struggling to find the right talent, you will have to invest in employee training programs to prepare your staff for the future. Apart from understanding how AI works, your team members will have to master a few management software solutions and other essential tools in the process.
Defining the Process
Even with everything in place, introducing artificial intelligence in steel industry is long and demanding. Most solutions require at least 18 months of learning before they can help improve manufacturing processes. During this time, incoming data will surely change multiple times due to unforeseen circumstances, leading to a drop in data quality and output. Therefore, it would help if you found a way to close the gap between different data sets to ensure that the model is trained using accurate data.
Many factors can harm AI training, including the environment, raw materials, the type of coal used during smelting, etc. These factors can affect the final output, and if you’re not careful, the model might become irrelevant before its deployment. That’s why you have to be extra cautious during data preparation and find ways to correct existing errors before training the model.
Of course, the use of artificial intelligence in steel industry includes the adoption and integration of new technologies. However, the process isn’t as hard to handle as previous challenges, as there are plenty of public libraries and tools your data scientists can use to make the process more manageable.
Changes in Company Culture
Some steel mills have been operating for over a century. They’ve established a strong company core and company culture that follows it. However, the implementation of artificial intelligence in steel industry will also require a change in company culture. Your employees will have to evolve from traditional methods to modern techniques based on data. However, the benefits of adopting AI solutions will quickly become evident to everyone involved so that they won’t have a problem with the evolving work environment.
Tata Steel Use Case
Tata Steel is a successful steel manufacturer based in India. They have adopted artificial intelligence already, showing some incredible results. The company uses data to improve processes, and the process consists of three stages, simplify, synergy, and scale.
Their data scientists have found a way to provide training in simple terms. Instead of using complicated terms, their data scientists communicate all ideas and responsibilities. Once the rest of the employees understand how a process works, the data scientists connect incoming data from various pipelines and operations into one easily scalable system
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Moreover, they use other processes such as predictive modeling, neural networks, machine learning regression, and others to gain insights that can help improve production and efficiency. Every workstation has its model, which all tie together to achieve its goals. The models are designed to learn from past mistakes allowing them to perfect the manufacturing process over time.
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However, so many variants and independent processes make it harder for the AI to find correlations and calculate outcomes and their impact on the operation. So instead of giving up, the company reached out to industry experts and academics to find better AI applications in manufacturing. They are doing a great job so far, as the company keeps expanding to new markets and evolving into an industry leader.
The Future Of AI in the Steel Industry
The future is looking bright for artificial intelligence in steel industry, as more and more companies develop and adapt their solutions as they enter the digital transformation. Besides providing insights using operational data, AI also improves manufacturing through automation and unsupervised processes.
AI can improve production and increase product quality to satisfy customers as it becomes more accurate. There is no doubt that AI is the future of steel manufacturing and many other industries, and the sooner you adopt it, the more success you will have over your competition.
Travis Dillard is a business consultant and an organizational psychologist based in Arlington, Texas. Passionate about marketing, social networks, and business in general. In his spare time, he writes a lot about new business strategies and digital marketing for FindDigitalAgency.