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The manufacturing model developed in the third industrial revolution is going through a disruption process that will permanently change the way goods will be designed, manufactured and delivered to consumers. The fourth industrial revolution or Industry 4.0 rises from two main factors: (i) the demands of a rising portion of consumers who are highly connected, whose hyper customized and immediate consumption patterns tend to favor services despite products, and (ii) the breakthrough of digital technologies that permeate various segments of the modern society. For this new industrial paradigm, the purpose is to merge physical and virtual worlds, building environments where data and information will become the great assets of business models and human intervention in the manufacturing process will be even lesser than what's envisioned for the third industrial revolution. However, bringing this concept into reality is not trivial and there is a need for extensive planning of the physical, technological, and organizational transformations that will be needed to achieve its goals. In this work, two aspects of the manufacturing industry's digitalization process will be exploited: its technical requirements and the demanded strategic competencies. In the technical sphere, there is a range of technologies generally considered by the literature as the backbone of Industry 4.0. Through exploratory research, these technologies will be evaluated, and their characteristics analyzed to identify how they interact with one another and if there are dependencies among them, determining an implementation roadmap that is technically coherent. Within the strategic purview, the competencies enabled by these technologies will be associated with the competencies elected by the German Academy of Science and Engineering on its Industry 4.0 Maturity Index (SCHUH, GÜNTHER et al., 2020) as necessary to reach this new model's strategic goals. Once determining the technical and strategic interactions between the selected technologies, this work proposes a systemic roadmap for the implementation of Industry 4.0 enabling technologies that defines a path for the digitization process of the manufacturing industry. [ABSTRACT FROM AUTHOR]

Pneumatic conveying of powders is an engineering process used for conveying dry granulate or powder material. The aim of this paper is to present a modeling methodology to optimize energy efficiency of pneumatic conveying systems, considering the specific bulk characteristics of the product being conveyed. This work is based on engineering optimization of a workflow with data from an industrial operation commanded by a Programmable Logic Controller (PLC) with a control algorithm, performing logical, sequential, and timed tasks for plant control. The PLC communicates with a Human-Machine Interface and a Supervision and Control System, which are the means of interaction through a graphical environment interface with the process operator. By applying mathematics to introduce a systematic method to select the gas (air) pressure and flow necessary to operate a pneumatic conveying system in dense phase, it has been shown, on an industrial scale, the feasibility of controlling a conveying system by manipulating only two input parameters. This allows operation at pre-determined conveying rates with lower power requirements, resulting in a reduction of OPEX. Thus, this research focuses on optimizing energy efficiency to reduce Operational Expenditure (OPEX) through a systematic modeling approach. Because pneumatic conveyance is highly empirical, general models are difficult to establish. Due to these limitations, evaluating energy efficiency is usually limited to a specific experimental range of conditions. This methodology can be adapted to enhance the energy efficiency of other types of pneumatic conveying systems. [ABSTRACT FROM AUTHOR]

Dry granulate or powder material is transported using the pneumatic conveying of particles engineering method. Adriano's doctoral dissertation's goal is to propose a modeling framework for optimizing pneumatic conveying systems' energy efficiency while taking into account the unique bulk properties of the product being transported. The foundation of this study is the technical optimisation of a workflow using information from an industrial operation that is controlled by a Programmable Logic Controller (PLC) that executes logical, sequential, and timed activities for plant control. In order to connect with the process operator through a graphical environment interface, the PLC interfaces with a Human-Machine Interface and a Supervision and Control System. It has been demonstrated on an industrial scale that it is possible to control a conveying system using only two input parameters by using mathematics to develop a systematic technique to choose the gas (air) pressure and flow required to operate a pneumatic conveying system in dense phase. As a result, OPEX is decreased while still operating at predetermined conveying rates with less electricity used. This study applies a methodical modeling technique to optimize energy efficiency in order to lower operational expenditure (OPEX). Since pneumatic conveyance relies heavily on actual data, general models are challenging to develop. These restrictions mean that measuring energy efficiency is typically restricted to a particular experimental set of circumstances. This approach can be modified to increase the energy effectiveness of other kinds of systems for pneumatic conveying. [ABSTRACT FROM AUTHOR]