FEATURE MACHINE BUILDING, FRAMEWORKS & SAFETY


smart manufacturing AdAptive sAfety


Likewise, in a confined area, with no


human presence allowed, an AGV making its final approach to a machine for docking may pose a collision risk between two industrial assets. This unsafe docking event risk may be mitigated by using two safety measures incorporated in AGV design: 1. Speed control system 2. Parking braking system control. Although there is no risk for humans in a


confined area, the measures are necessary to protect industrial assets from expensive damage. The use of a context-sensitive safety approach could achieve the goal of property protection combined with higher system efficiency. The above scenarios demonstrate the


Paul Taylor, business director for Industrial Services at TÜV SÜD, looks into the importance of safety and security, and examines how Industry 4.0 cyber-physical systems have the potential to significantly enhance industry performance


I


ndustry 4.0 (I4.0) is a major paradigm shift as the convergence of enterprise IT and operational technology enables systems


and devices to exchange and interpret shared data on a global scale. While I4.0 sees reduced risk in several areas,


the range and flexibility of connected interfaces introduce a new set of risk issues. As production facilities become more complex, operators must manage a rapidly evolving system that incorporates multiple interdependencies, while minimising downtime. It is therefore vital to consider the shifting landscape of risk, which is why I4.0 requires a new risk management approach that is customised to each individual actual use case. As the increased flexibility created by these


interdependent and dynamically changing I4.0 systems introduces new complexities and challenges, there is a shift from static risk assessment to one of dynamic risk. Analysing and assessing the underlying physical and cyber risks to humans, property, and the environment is therefore a challenging task.


sAfety meAsures


Addressing safety and security is not just a legal obligation for system designers, integrators, system owners and operators, it also directly impacts their ultimate I4.0 mission to minimise downtime and maximise system availability. However, tackling safety issues by using a conventional static risk assessment approach, including existing tools such as Sistema, would require time-consuming reiterations for every


10 DESIGN SOLUTIONS OCTOBER 2021


changing condition, which could potentially result in operational downtime. However, current standards, such as ISO 12100 – Safety of machinery – General principles for design – Risk assessment and risk reduction, have not been designed around the concept of machine connectivity and interoperability. Safety measures are designed to protect


only human health using a ‘worst-case’ approach, and given the connective complexity of interacting assets, applying worst-case assumptions can have an extremely negative impact on manufacturing productivity. In practice, when a machine operates in


an application-specific context, its limits and applicable hazardous situations may differ significantly from those considered under worst-case and stand-alone scenarios. Additional hazardous situations may also arise from machine-to-machine interaction. To give an example, an automated guided


vehicle (AGV) navigating towards a machine in an operating area with a human presence represents a ‘collision risk’. This risk may be mitigated by using three safety measures incorporated in AGV design (according to ISO 3691-4 - Industrial trucks — Safety requirements and verification — Part 4: Driverless industrial trucks and their systems): 1. Personnel detection system 2. Speed control system 3. Braking system control In current practice, speed limitations due


to a human presence are therefore applied even if there are no humans in the actual AGV operating area.


need for adaptive production systems capable of monitoring and recognising hazardous situations during runtime, to ensure that residual risks are handled within current practices. In addition to the limitations of the conventional (I3.0) worst-case approach, system operators should also be aware of real-world situations where safety installations may be either consciously manipulated or inadvertently modified, as these can cause serious accidents.


AdAptive sAfety


To meet the new needs of I4.0, a new event-triggered, dynamic risk assessment and automated validation of safety measures approach is required. This requires a continuous and holistic risk assessment to ensure stable operations, increased productivity and reduce downtime in a smart manufacturing environment. A digital representation of the physical manufacturing system, using digital twins and asset administration shells, is therefore needed. While digital twins and AAS help


manufacturers optimise performance and accurately predict business obstacles, they are also faced with the challenge of navigating a complex new risk landscape. It is therefore vital that the digital twins have customised safety and security profiles. A safety profile should be modelled to describe asset safety from a general and an application-specific perspective. These profiles should then be processed by an inference engine, against actual application constraints, to define limits and risk-mitigation capabilities in a real-world application, thereby providing automated risk evaluations at runtime. I4.0 cyber-physical systems have the


potential to significantly enhance industry performance and facilitate innovative products, but alongside this a new set of risk issues must also be addressed.


TÜV SÜD www.tuvsud.com/uk


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