The mission of this chapter is to review and investigate the requirements and applications of using cloud-based internet of things (CIoT) for shifting the legacy robotic manufacturing towards Industry 4.0. Sensing and communications are two requirements of Industry 4.0. In the chapter, the legacy robotic manufacturing equipment collaborate with the environment, where it supports sustainable manufacturing. An implementation example of the proposed scenario will be discussed in this chapter.
TopIntroduction
The advancement in information and communication technology (ICT) and Internet of things (IoT) and their rapid influence in industrial applications has been the foundation for a new revolution in industry (Li, 2017; Santos, et al., 2017). The fourth industrial revolution (industry 4.0) started around 2011, after the third industrial revolution with the presence of industrial computers and information technology in manufacturing sites (Atkeson & Kehoe, 2001). With the assistance of ICT and IoT, industry 4.0 can meet its objectives, such as improvement in production efficiency in manufacturing sites, production speed enhancement, production reliability and quality improvement for better customer experience, reliable production automation, and integration of manufacturing and supply-chain management, with minimum human intervention (Tay, et.al, 2018; Qin, et.al. 2016). In an industry 4.0 ecosystem, the machine-to-machine (M2M) communication and machine-to-environment (M2E) communication improves the reliability, productivity and safety. In this ecosystem, IoT (Alasti, 2021), or in a more generalized concept, network of things (NoT) (Voas, 2016) provides the requirements of M2M and M2E.
Cloud computing with its continuously increasing importance in ICT and IoT services has an essential role in implementation of industry 4.0 services and development of its successor generations. The specific industrial ecosystem of the manufacturing sites, demands computing machinery with rugged attributes, where it may not be necessarily possible. Using cloud computing allows to shift the computing power over the cloud, where it drastically saves in the required special space and expenses. It is important to mention that cloud security is a major concern yet. As a solution to this issue, dynamical security enhancement has been proposed in literatures to overcome the tentative security breaches (Hamilton & Alasti, 2017; Li, et. al 2019; Sanislav, 2017; Tian & Jing, 2019). Some of these solutions are proprietary and need special permission over the data and service domain of cloud or the cloud broker service provider premises (Hamilton & Alasti, 2017).
Regardless of its security concern, cloud environment is one of the popular instances for data storage and processing, that can be used in implementation of ICT and IoT services. The collected data from the robotic and production machinery is transferred over the cloud for storage, online data visualization, data processing and filtering for better next step “on-site decisioning”, and sending notification e-mail or text messages to the relevant identities such as the working machines, or technical and managing personnel, once it is required. Transmission of massive volume of the collected data from variety of the sensor observations for storage over the cloud can be considered as a big data problem. The advantages and weakness of using cloud-based IoT (CIoT) service for industry 4.0 application is discussed in the body of this chapter, in brief.
Collaboration with the other machines and the environment is one essential requirement in industry 4.0 (Alasti, 2021), and for this purpose the industry 4.0 machinery need to have a correct sense of their work environment to track changes. Thus, embedding different types of sensors in machinery and in the environment is of prime importance. Collection of the sensor observations over the cloud happens via communication that is usually wireless. Variety of wireless communication technologies, such as WiFi, cellular technologies, narrow-band IoT wireless communication categories, etc. can be used for collection of the sensor data to the CIoT site. One of the important requirements of the communication technologies that are used for industrial applications is short delay. However, communication is not the only reason for delay in industrial IoT (IIoT) and the other latencies due to coding nature, hardware interfaces, CIoT site bandwidth, etc. needs to be considered in a well-developed CIoT application.
Even though the penetration of industry 4.0 in manufacturing is increasing, however there are a considerable number of factories that have a large number of working legacy robotic machinery and replacement of them with expensive industry 4.0 machinery is not affordable in short term. This chapter proposes a transitional model for shifting towards industry 4.0 requirements by employing CIoT and embedding wireless sensors in the environment.