Identifying behavioral patterns to increase sales, foreseeing possible problems in order to resolve them before they happen, managing stock in a much more efficient way or redistributing the workload automatically. These are some of the many smart manufacturing possibilities offered by this new concept in the Industry 4.0 era.
In the metal industry, it’s a concept which is still in its design phase. The main requirements and applications are clear, but research is still underway into the limits and exactly how these ideas should be applied to different sectors. Lantek is shaping this future with an extensive R&D effort, through the development of software platforms that make these systems possible and the training of talent with the ability to cope with the frenetic pace of this change in the new industry paradigm.
Subsequently, equipping a plant with intelligence implies the implementation of software that can compile, automatically and in real time, all of the data generated by the processes with the sensorization of machines, processes and systems. This information is stored in the Cloud and analyzed in a descriptive, predictive and prescriptive manner with Big Data, Artificial Intelligence and Machine Learning programs in order to offer responses to different scenarios in an aim to help people to make better decisions. An Advance Manufacturing that helps to improve the productivity, efficiency and competitiveness of companies.
Our value proposal is called MES+ and Lantek Analytics, a family of products that allow the relevant information to be accessed, reliably and in real time, concerning the whole production chain, from the performance of each machine to the efficiency of a line, also involving an analysis of orders. This way, the users of the production intelligence systems can obtain precise information and results whenever they need to, without having to wait for lengthy analysis procedures
The latest research report, Sizing the Prize by PwC, states that the global Gross Domestic Product (GDP) will have increased by up to 14% in 2030 thanks to progress in Artificial Intelligence which will result in productivity gains in automation processes, an increase in the workforce’s production quality and quantity with the implementation of IA technologies and greater consumer demand as a result of the availability of customized products and services.
To integrate this type of intelligence into the metal industry we need to address four aspects:
- Acquisition of operational data from different sources
Before acquiring, processing and analyzing this data, it must be correctly selected and defined from all the existing variables, both internal and external. Cut length, number of entrance and alignment movements or workload. Even environmental variables, which are seemingly not directly related to the production process, such as atmospheric conditions, location, etc.
To obtain the operational data, Lantek puts its trust in the manufacturers of machine-tools to develop the best detection devices possible that we integrate into each machine. This helps us to establish improvements and new features.
- Generation of analytical data
Once the data has been acquired, we need to transform it so that it can be analyzed, both by professional analysts and by production intelligence tools. We have to take into account that it must be interpreted correctly in every context and that there may also be variables that have to be calculated from the existing data. Examples of these are material consumption, the use of scrap, the shapes of commonparts, utilization rates or OEE indicators, which measure productivity in the production process.
The analytical data must be processed correctly in order to generate a robust structure that is ready to be analyzed. Thanks to our experience, we are able to identify the elements that have a greater impact on metal manufacturing operations. What’s more, if we add other variables to this combination, we could discover unexpected patterns that may bring about massive improvements.
- Application of the right logic underlying the analytical data
It’s now possible to send analytical data to procedures that can detect existing patterns in the information, apply artificial intelligence algorithms, link apparently unrelated events and implement advanced processing techniques with them. Also, we must consider the market, the clients, the behaviors and the culture in order to contextualize the analysis.
- Development of employees’ skills
Finally, we must have competent employees at all levels to be able to analyze the result of the production intelligence systems and take the necessary measures in order to carry out operations in the right direction. In this sense, we foresee a new type of professional in the metal factories, one who is able to analyze the indicators shown to them and act accordingly in compliance with the company’s strategies, objectives and priorities. We call them “analyst-transformer”.
By utilizing the potential of data, which is countless in a factory, we innovate within the concept of smart manufacturing to improve the performance of our plants in a 4.0 environment where competing without transforming digitally is simply not possible.