If we look back in time, we will see that the machines of the future will follow the same paradigm as previous industrial revolutions, producing more at a lower cost.
Danobat Laser Cutting Machine
However, in this Fourth Revolution, the revolution of Industry 4.0, we are faced with machines that are interconnected through the Internet of Things to cloud platforms, so that data is processed, analysed, and stored. One where enablers such as artificial intelligence, big data, and machine learning will analyse this data, offering up responses to the different levels of production, helping people make better decisions.
For this to work, it is crucial for machines to mutually understand each other and communicate. There are a number of protocols, but in the sheet metal industry an agreement has not yet been made to establish a standard, and at times we have to work unit by unit so that machines can mutually understand each other. In any case, the evolution of the world of engineering is allowing communications services to be built between different systems that make the technology behind them more transparent.
Nevertheless, the crucial aspect is not going to be the communications protocol, understood as the basis on which the machine publishes information, but rather the publication of the services offered by the machine. The idea is for the machine to offer data that responds to specific questions and to resolve any issues the system may have. The approach will differ if machine programming software (CAM) is talking to the machine, if a manufacturing execution system (MES) is communicating, or if a maintenance management system is the one talking.
To meet these challenges, the MES must be verticalized to understand the services offered by the machine and how best to leverage them so that it is able to organize the plant’s manufacturing with big picture vision. With regards to CAM, the challenge will be knowing what the new architectures will be like. Their base architecture has not evolved over the last 40 years: relying on the machine’s parametrization, CAD importers, mechanized instructional design, and finally generation of a numerical control program for industrial control. This structure and everything entailed by it is currently being reassessed, and therefore it remains to be seen whether we will be able to resolve issues more efficiently from the machine’s perspective and in a manner that is transparent and automated for the systems, allowing more specialized solutions to be built. Ultimately, programming software must focus on determining what the customer needs with regard to cost, timeline, quality, and other aspects involved in manufacturing, i.e., focus on the function of the MES. In the end, the direction of the trend is toward building systems that offer full general interoperability where specific integration is not necessary.
The machines of the future must be fully autonomous, can never have downtime, and must work efficiently. In this way, the location of the data and the systems that allow responses to be given for decision-making or which calculate instructions for the machine must be hosted wherever the premise above can be ensured. Thus, as stated at the beginning of this article, in order to be able to use the technological problem-solving capabilities available through Industry 4.0, we have to move some of the processes to the cloud in order to make the most of its capacity. Initiatives are already underway examining the question of the portion of the data that should be on the machine, the data that should be on local or private networks, and the portion that should be on the cloud. This hybrid architecture is the one that guarantees better productivity and, at the same time, a greater capacity to solve problems more effectively.
Ultimately, the machines of the future will be smart, thanks to Industry 4.0 enablers that move processes to the cloud, driving efficiency and productivity which will result in reduced costs for smart factories.