11 apr, 2022

Data & Artificial Intelligence: Advantages, solutions, and the future of automated systems

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The phenomenon of Data & Artificial Intelligence applications in industries around the world is revolutionizing production processes, making them more efficient, intelligent, and productive.


With great analytical and data-crossing capabilities, Data & Artificial Intelligence solutions gain strength by turning decision-making into a much more agile and informed process.

 

Thus, we can speak about “smart manufacturing”, which represents the reinvention of how a business operates, whether it's a factory or a retail organization.

 

 

What are the main advantages of applying Data & Artificial Intelligence?

 

  • Operational cost reduction: through intelligent tools and segmented data we can use sustainably and accurately the materials involved in production, contributing to an operational improvement, and avoiding waste.
  • Agility and innovation: Interactive dashboards allow employees to have access to a wide range of data and information that can support decision making.
  • Return on investment: The monetary result of this application is remarkable since it puts technology to the service of a more agile industry. Long-term strategies, market and production perspectives, and many other data are exposed in dashboards, which cross-reference information and provide the basis for decisions.

 

Therefore, the goal of investing in Industry 4.0 is simple and clear: to increase the level of production quality through Data & Artificial Intelligence solutions. By doing so, companies can meet the needs of an increasingly fast-paced and demanding world.

 

But where do we start?

First of all, it is crucial to understand the client's reality to understand what kind of solution can best fit their current scenario.

 

The identification of the goals must happen at the beginning of the project, so it is possible to visualize who will be the main beneficiaries within the organization, whether it is the financial department, HR, marketing, or even planning and control teams, to promote discussions to improve the solution. It is also essential to survey the needs of the industry in which it operates, visualizing perspectives and generating a complete matrix according to the organization's needs and goals.

 

It is also essential to map the data sources and evaluate them for the structuring and development of a BI solution. After all the structuring, there must be a follow-up of the operation of the tools, monitoring whether all the processes comply and if there are possibilities of improvement to leverage business results.

 

The whole development of these stages makes it possible to know in depth the reality of each department and then develop projects tailored to the needs of each organization.

 

All projects must go through a consulting phase to allow companies to obtain valuable insights from their own data.

 

And what are the main challenges of the implementation of Data & Artificial Intelligence Solutions for Industry 4.0?

 

  • Data security: When we address the interaction between physical and digital environments, we enable real-time interoperability. With a wide variety of machines and devices connected to single or multiple networks, vulnerability at connection points with the data network can open a breach for potential attacks. That is why there are solutions capable of anticipating these needs and preventing the system from being defrauded.
  • Training and organizational culture: The digitization of processes brings out the need to have teams prepared and up to date. Companies must invest in training and corporate programs so that their employees know how to make the most of the data obtained. Far beyond the technical, this culture is fundamental so that all employees understand that technologies contribute to the fluidity of the business, reducing waste and avoiding operational efficiency failures.
  • Legacy systems integration: The interoperability of systems must be taken into consideration when dealing with legacy systems integration. Thus, the organization that joins this type of operation will need a technology partner capable of working together to implement and act in the development of solutions that highlight modularity, bringing paths for updates over time and integrating diverse information, data, and solutions.

 

What to Expect in the Future of Automated Systems in Industry?

 

Large-scale connectivity is invading companies around the world. This intelligent and technological way of managing resources is usually the standard for the future and that is why organizations should keep an eye on this change, keeping in mind that all the time lost for bringing competitive disadvantages.

 

Automated systems can enable great strides for improvement in process management and the advancement in decarbonization. In addition, agility and qualitative improvement throughout the process allow a delivery that exceeds expectations. It is the data industry in favor of the evolution in the production industry.

 

Today, organizations don't just need to be able to easily mine data from their activity across different departments. They increasingly need advanced analytics components such as Artificial Intelligence, Data Science, and Deep Learning. All these mechanisms help organizations discover new metrics and insights, make better predictions, and generate recommendations.

 

In practice, Data & Artificial Intelligence bring a huge competitive potential for companies, which, based on intelligent systems, will be able to reduce costs and enhance the quality of their delivery, from resource management to customer experience assessment. Large-scale production and more agile management can fit in the palm of your hand!

 

Digital transformation in the industry is here to stay. This is the future for any organization. Find out more about Data & Artificial Intelligence solutions, with me.

 

Milton Nunes

Intelligence & Analytics at ARMIS Information Technology


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