Evaluación de amenazas por movimientos en masa e inundación

The term Cyber-Physical Systems (CPS) was coined in the US in 2006 to refer to the increasing importance of the interactions between interconnected computing systems and the physical world (Wang et al., 2015; Leitao et al., 2015). CPS is defined as “automated systems that enable connection of the operations of the physical reality with computing and communication infrastructures” (Jazdi, 2014; p2). CPS technologies such as wireless system integration, wireless controls, machine learning, and sensor-based tools provide a focused capability of sensing, cross-platform-communication and control for manufacturing (Wright, 2014).

From a system components perspective, manufacturing technologies have evolved from embedded systems to CPS (Mosterman & Zander, 2015). Embedded systems refer to the combination of computer systems that are configured for specific functions, residing within a larger functional system, but typically lacking in real- time connectivity capability (Lu, 2017; Hehenberger et al., 2016; Sanislav & Miclea, 2012; Lee, 2008). Whereas, CPS are “open, linked-up systems that operate flexibly, cooperatively (system-system-cooperation) and interactively (human- system-cooperation)” (Mikusz, 2014; p385). In other words, while embedded systems focus on computational elements that are hosted in stand-alone devices, CPS exist in a network of interacting computational and physical devices (Leitao et al., 2015). This characteristic emphasises the integration of computation systems with physical processes, either by machines or humans.

The evolution of embedded systems to CPS is also characterised by the growing presence of heterogeneous data and knowledge integration (Lu, 2017). This is based on the understanding that the entire manufacturing process generate huge amount of data. Some of these data can be analysed and converted into knowledge that can help manufacturers reduce product development costs and timeframe, while enhancing product functionalities (Hehenberger et al., 2016). The system capability that captures, stores, analyse these data is enabled by the availability and affordability of sensors, data acquisition systems and computer networks (Lee, et. al, 2015).

The development of CPS can be described by three different, but interrelated, phases (Hermann et al., 2016). In the first phase, CPS focuses on identification technologies such as RFID37 _{(Radio Frequency IDentification) tags so that an item’s}

status within the manufacturing process can be identified and tracked (Zhou & Piramuthu, 2012). The second phase of CPS development is characterised by machines and tools that are equipped with sensors and actuators, but with limited interoperability as they may operate as standalone units. The third generation of

37 _{RFID provides item-level identification capability, as well as enables local storage and retrieval}

CPS are not only equipped with sensors and actuators, but are able to exchange, store, and analyse data via a secure communication link (Hermann et al., 2016).

Today, a typical setup of CPS consists of a control unit comprising one or more microcontrollers, which regulate the sensors and actuators that require a communication interface to interact with other machines or the human users, as well as process the data obtained (Jazdi, 2014). This setup is prevalent not only on the factory floor but can also be observed in an aircraft, for instance, where sensors and networking systems enable the monitoring of its operation while coordinating with ground stations (Khaitan & McCalley, 2015).

Empirical research on the adoption of CPS in the OM domain is scarce. Key discussion topics are explored by IEEE journals on CPS concepts and scope (Hu et al., 2016; Kim & Kumar, 2012; Sha et al., 2008), CPS characteristics (Monostori et al., 2016; Hehenberger et al., 2016; Mikusz, 2014), as well as, the utility and impact of CPS on manufacturing activities (Babiceanu & Seker, 2016; Herterich et al., 2015; Wang et al., 2015; Dworschak & Zaiser, 2014). One of the most significant aspects of utility and impact of CPS on manufacturing highlighted by these researchers is the accumulation and transformation of massive data into information that assist in organisational decision-making.

The concept of connected systems in CPS enables planning that improves communication among machines. The communication interface in CPS is critical in augmenting the inter-working of embedded controllers, sensor systems, robots, and humans (Brettel et al., 2014). For machine-to-machine interactions, manufacturers have traditionally relied on wired connectivity among manufacturing systems in the form of point-to-point or peer-to-peer connections (Bi et al., 2014).

Fortunately, the prevalence of wireless networks today provides the network ubiquity that enables not only machine-to-machine interactions but also seamless human-to-machine exchanges. The advancements in wireless broadband network connectivity, for instance, allow the capabilities of individual machine tools to be queried, instructions downloaded and executions monitored at real time (Bourne et al., 2011); both by other machines as well as by human operators.

The components that make up a typical CPS as described in the preceding paragraphs are illustrated in Figure 3-10.

(Adapted from Brettel et al. (2014; p38)) Figure 3-10: Typical components of CPS

Development in electronics, wireless communication, internet bandwidth, including the availability of sophisticated computing devices; and the continuous improvements in energy capacity have contributed to the transformation of manufacturing technologies into CPS (Lee, 2008; Rajkumar et al., 2010). With the increased demand for complex products such as an aircraft, the manufacturing activity requires sensor-intensive, computer-controlled production machinery (Wright, 2014). Incidentally, the aerospace industry is recognised as a leading industry in creating the demand for CPS technologies. This is attributed to the industry’s need for safety-critical aircraft components and parts that are produced timely and precisely (Rajkumar et al., 2010).

One of the main aspects of the aerospace manufacturing activity that relies on CPS technologies is design. The design requirements span across the industry which includes aerodynamics, new engines, alternative fuels, as well as flight deck and cabin configurations (Sampigethaya & Poovendran, 2013). The application of CPS

technologies features prominently in each component’s early design process as described earlier in this chapter.

It is apparent that manufacturing technologies have evolved from the standalone production machines, computer systems, and production techniques to the integrated platform of networked and connected computer systems, virtual systems, and physical processes on CPS. This evolution is depicted in Figure 3-11

illustrating the initial convergence of production machinery and equipment, computer control systems, and production techniques and methodologies to form advanced manufacturing technologies (AMT). With the advancements of computing and communication technologies, these manufacturing technologies can be differentiated according to their characteristics of physical, virtual, and communication; which then forms cyber-physical systems (CPS). Monostori et al. (2016) refer to the convergence as the intersection, while Rajkumar et al. (2010) suggest that it is the confluence of the physical and the cyber.

(Adapted from Kotha and Swamidass (2000), Swink and Nair (2007), and Chung and Swink (2009) for AMT; Rajkumar et al. (2010); Wang et al. (2015), Monostori et al. (2016) for CPS)

Figure 3-11: Evolution of manufacturing technologies into CPS