Artificial intelligence is widely used in services from online businesses to consumers such as Amazon, Netflix, and social media.
The foundation of today’s most devastating tech was laid more than half a century ago, but even early adopter tech giants had not brought AI into production until the end of the last decade.
The most important element of AI is a powerful database of training models. So it’s not surprising that the IT business, which is by definition a data collector, was the first technology.
Private user data is relatively cheap, but data collection in other industries is more complex. So it’s no wonder that the manufacturing and trading sectors took years to create the right databases that were established overnight in technology.
Compared to IT and technology companies, the adoption of data-driven technologies such as machine learning and artificial intelligence has changed by about 6 to 10 years in many industries (especially manufacturing).
Today, manufacturing industry pioneers are stepping into developing prototypes that can draw value from this new technology.
As the industry progressed through the data collection process, companies were able to unlock value by using this data for business intelligence. BI and visualization tools provide valuable information to professionals working in warehouses and workshops.
However, companies rely heavily on industry experts to evaluate information, make decisions about various factors, and monitor processes. It’s time to take it to the next level with tools that not only provide insights but also assist directors and decision-makers in using AI in manufacturing and warehousing.
Need for Artificial Intelligence in Manufacturing
After many years of successful delivery to the industry, it’s clear that a solution tailored to your business needs is the best way to do it, rather than adapting internal processes to existing artificial intelligence tools.
The solution turns out to be accurate in each industry and application area. Most solutions are also unique, as there is data available to train the algorithm.
A major technology company worked with Voestalpine to solve certain business problems in warehousing optimization for the steel industry.
There are no smart storage tools on the market for this particular issue. In addition, this tool must be adapted to your specific infrastructure and data acquisition process.
The Pioneers
Warehouse optimization for consumer goods is a fairly common problem, but the storage of heavy and sometimes large parts for commercial customers in the steel industry is a niche application.
The development of an artificial intelligence solution that assists decision-makers with complex forecasting and recommendation tools for optimizing inventory in multiple warehouses is major breakthrough within the manufacturing sector.
This tool may be the foundation on which you can build more artificial intelligence applications within your enterprise. Therefore, companies can have the ideal equipment for further automating warehouses and optimizing inventories in a profitable way.
A major AI center in Vienna has participated in the development of tools to optimize multiple inventories in parallel for customers. Close collaboration has been the key to developing successful solutions that meet user requirements and has also been claimed to have provided excellent results from a technical and professional perspective.
A team of data scientists, data engineers, and consultants at the Center of Excellence has worked closely with the industry and IT professionals to develop products.
How does the Future Look Like
In the future, we will see that AI will play an important role in manufacturing and storage. Imagine a robot loading and unloading pallets, transporting items to a warehouse, and searching for in-stock items.
Optimized production planning and decision-making using machine learning and the entire production facility connected by IoT solutions. Fleet optimization, routes and travel times, demand forecasting, and more.
The list is probably endless, as the need for new solutions arises for all the needs provided by sophisticated solutions. For some players like Amazon and Alibaba, this is already partly a reality.
Most business AI journeys begin with very specific uses until they reach the goal of working in a fully automated way, or at least some confidence in reorganizing the entire competent process.
As Microsoft’s world’s largest partner in artificial intelligence and machine learning and one of the first to offer machine learning on AWS in Europe can help you determine specific use cases to embark on your AI journey today.
