When Data is at the service of manufacturing intelligence

                                Contributed by Juan José Colás, Lantek CCO

Situations like the COVID-19 pandemic have made it clear that just having plans isn’t enough, we need action, the industry has to be digital, or it simply won’t survive.

In this leap towards the digital factory, information has reclaimed its leading role, becoming one of the company’s greatest assets. Its correct management will depend on the possibility of making it truly intelligent, marking the difference that allows us to attain competitive advantages within the market.

In Industry, just like in other areas, the information and data processing requirements are growing at such a rate that it’s becoming difficult for conventional IT solutions to cover them. The dilemma faced by organizations is that either they are overwhelmed by the data to be processed or they are unable to identify the value that could be provided by the data they have. Whatever the case may be, more than ever, they need to filter and choose key data carefully in order to make better decisions.

According to a report by IDC, the global value of the Big Data market this year reached 202,000 million dollars. Does any industry really still believe that information isn’t power?

Data for creating better functional analysis

Data has significantly revolutionized the way of finding solutions to traditional problems, basing itself on the practical use of information and its effective real-time analysis.

The industrial sector of today needs an integral understanding of its business ecosystem to give it a 360º overview of all of the parts that intervene therein, from markets to clients, including products, competition, workers, partners, suppliers, legal framework... Subsequently, to maintain its competitiveness, the industry needs to create more value from the structured and unstructured data stored in its systems.

The efficient use of Data will favor immediate decision-making and improve the client’s experience. It will also optimize the procurement of materials by identifying sales trends and will help in maintenance tasks through the analysis of data generated by the machines. Ultimately, the company will have the vision it needs to take action in any scenario.

All of this translates as Manufacturing Intelligence. This concept refers to the streamlined combination of software systems that are used to gather a company’s manufacturing data from different sources in an aim to draw up reports, analysis and visual graphics, as well as to transfer data between systems at the company and the plant.

With the right analytical tools, we can create a new structure or status that will help users to find what they need regardless of where it comes from. The main objective is to turn large quantities of manufacturing data into real knowledge and boost business results based on this knowledge. All of this will help factories to achieve their goals in terms of productivity, efficiency and competitiveness.

But, to make the most of this technology, it requires optimal implementation. The solutions must be deployed as a system that allows structured and unstructured data, from any source, to be entered and stored. This data is saved in file systems and categorized in databases to be interpreted.

On a second level, where analytical tools come into play, the data is studied and organized to obtain results that, equally, allow the business objective to be attained by implementing specific actions.

To attain this objective, companies must face challenges such as the lack of experts qualified in data science, the quality of the data itself, aspects related with cybersecurity and the protection of confidential information, the increasingly stringent legal framework or take into account how the rapid evolution of technology can bring about changes that result in the obsolescence of IT in the short term.

Analytical solutions applied to Data mark a convergence point for other important tools and technologies such as AI, the Cloud and connectivity, subsequently resulting in the accurate identification of each plant’s requirements, along with a suitable composition of solutions, the correct methodology will be key in shaping the path towards the Digital Factory.