Smart Industries
The emergence of various smart devices, such as smart TVs and smartphones, is gradually transforming our society, affecting labour relations, and creating new social habits. Likewise, along with the advancement of data-driven services provided by industrial smart devices, such as sensors and controllers, industry is experiencing worldwide the beginning of a new era of innovation and change. The new generation of industrial smart devices are autonomous and self-adaptive, are capable of interoperability and to take independent decisions. The synergy of these physical and computational elements, embedded with Machine Intelligence and Data-driven behaviour, forms the base for a profound transformation of the global industry, that has been characterized as Smart Industry.
The progressive miniaturization of electronic devices and the drastic decline of their production costs have led to a foundation for a new industrial revolution that quietly enters in our daily lives with increasing importance. The emergence of various smart devices, such as smart TVs and smartphones, is gradually transforming our society, affecting labor relations, and creating new social habits. This physical equipment continuously incorporates functions that go far beyond their basic functions. Provided with several sensors, such as cameras, GPS, accelerometer, and networking capabilities, these devices are steadily assuming functions that are useful for the individual as well as for the surrounding community.
Along with the advancement of services based on data collected by smart devices, the industry is experiencing worldwide the beginning of a new era of innovation and change. Analogous to the sharp increase of the complexity of embedded devices in our daily life, industrial components such as sensors, actuators, and supervision and control elements are increasingly endowed with autonomy, flexibility, communication, and interoperability. The new generation of devices is capable of data collection; local storage and processing have been gradually incorporated into several levels of the industrial production chain. Consequently, the current supervision and control model based on sensors and actuators that are strongly coupled to a centralized control unit has been questioned. In contrast, a novel paradigm gradually enters the industry. This new paradigm is based on the cooperation among distributed industrial devices, sensors, controllers, actuators, and low cost microcontrollers that are networked together. The synergy of these physical and computational elements forms the base for a profound transformation of the global industry. Its perspective is a dramatic increase of productivity and reliability, higher energy efficiency, reduction of plant downtime, and increase of asset utilization in various industries and significant benefits for the society.
Joint efforts between academia and industry in several countries have recently been conducted to create conditions to handle these changes. For instance, in Germany, this transformation has been called “Industry 4.0” while in the United States the term “Industrial Internet” is used. Great Britain will start the Big Data for Engineering Futures Initiative in September 2014 with the purpose to join academia and industry in preparing the British industry for this new technological circumstance. Certainly Brazil will also be affected by this new scenario and must evaluate the new technological era to account for its impact on the national industry today and in the future. Thus, it is crucial that the local academia and industry is prepared from scientific, technological, and engineering point of view, considering all levels of the production chain. Motivated by this observation and in agreement with similar initiatives recently started in the industrialized countries, Smart Industry aims at integration of academia and industry to ensure that advantage is taken from smart communication, control, computation, and new data-driven technology that may bring strong increase in production efficiency, innovation, competitiveness, and economic growth.
Example of a question that can be posted by industry partners:
“A data-driven process in our industry requires that complex decisions are taken within short time periods, what demands uncertainties to be handled according to real time data. The process, however, is difficult to model, since it involves a very large number of variables. Which are the present machine intelligence models and techniques that are capable to deal with such a high dimensional real time temporal data?”