Smart Hybrid Manufacturing Control Using Cloud Computing and the Internet-of-Things

Abstract

Industry 4.0 is expected to deliver significant gains in productivity by assimilating several technological advancements including cloud computing, the Internet-of-Things, and smart devices. However, it is unclear how these technologies should be leveraged together to deliver the promised benefits. We present the architecture design of an information system that integrates these technologies to support hybrid manufacturing processes, i.e., processes in which human and robotic workers collaborate. We show how well-structured architecture design is the basis for a modular, complex cyber-physical system that provides horizontal, cross-functional manufacturing process management and vertical control of heterogenous work cells. The modular nature allows the extensible cloud support enhancing its accessibility to small and medium enterprises. The information system is designed as part of the HORSE Project: a five-year research and innovation project aimed at making recent technological advancements more accessible to small and medium manufacturing enterprises. The project consortium includes 10 factories to represent the typical problems encountered on the factory floor and provide real-world environments to test and evaluate the developed information system. The resulting information system architecture model is proposed as a reference architecture for a manufacturing operations management system for Industry 4.0. As a reference architecture, it serves two purposes: (1) it frames the scientific inquiry and advancement of information systems for Industry 4.0 and (2) it can be used as a template to develop commercial-grade manufacturing applications for Industry 4.0.

Classification of Small- and Medium-Sized Enterprises Based on the Level of Industry 4.0 Implementation

“…As the results showed, technological enterprises have very high value of variables at the first level VPi4. The importance of people is also emphasized by Nickel et al [95], data by Chumnumporn et al [96], cloud by Erasmus et al [97] and analysis by Choy et al [98]. These enterprises have high value of variables as mobile platforms and IT; average value of sensors and M2M at second-level VPi4, which is not yet widely used by SMEs [99].…”

Artificial intelligence and internet of things adoption in operations management: Barriers and benefits

“…According to Zhang et al (2020), AI and IoT technologies in OM help to build and connect platforms and to centralize data. These tools contribute to communication between systems and between people, improving processes, planning, and controls (Fettermann et al, 2018;Kobbacy et al, 2007), thus facilitating command and responses both for devices and teams to perform operations (Erasmus et al, 2018). High operational efficiency and more effective decision-making are observed when a complete sharing of data is present and there is an on-demand use of the generated information (Li, Dai et al, 2020;Lohmer & Lasch, 2020).…”

Barreiras e benefícios na adoção de inteligência artificial e IoT na gestão da operação

“…Segundo Li, Dai et al (2020), além da coleta de dados em tempo real, as ferramentas digitais oferecem maior capacidade de produção ao fornecerem um suporte de dados para avaliação, planejamento e tomada de decisão na GO, tudo de uma maneira ampla, on-line e rápida. contribuem para a comunicação entre os sistemas e entre as pessoas, pois melhoram os processos, o planejamento e os controles (Fettermann et al, 2018;Kobbacy et al, 2007), e facilitam o comando e as respostas tanto para os dispositivos como para que equipes de pessoas executem as operações (Erasmus et al, 2018). Quando há o compartilhamento completo dos dados e o uso sob demanda das informações geradas, uma alta eficiência operacional e tomadas de decisões mais eficazes são observadas (Li, Dai et al, 2020;Lohmer & Lasch, 2020).…”