Advanced manufacturing - Safety and productivity

Resilient products and stable operations in IIoT

Resilient products and stable operations in IIoT

UNLOCK THE FULL POTENTIAL oF NEW MANUFACTURING TECHNOLOGIES

As developments in flexible automation pave the way for innovative business models and higher productivity, machine builders, integrators and operators find themselves transitioning to more advanced production and manufacturing environments.

Solutions for Industry 4.0, IIoT and skill-based production significantly improve efficiency-levels and flexibility, enabling the manufacturing industry to capitalise on smart factory concepts - provided that the operations run as planned. In these environments, smart safety concepts evolve from a tool for compliance to a driver of productivity. 

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The transition to an increasingly skill-based production is a stepwise process, where each maturity level comes with benefits and requirements. The path will differ across companies, depending on their objectives, starting points and roadmaps. Nevertheless, it's possible to identify typical use-cases and their characteristics, as shown in the infographic below. 

The use-cases illustrate how the manufacturing environment evolves from a set of stand-alone machinery, via connectivity to flexible configurations and autonomous optimisations. For each step, the objective is to gain a competitive edge by increasing flexibility and overall productivity. 

 

TRUSTWORTHINESS ENSURES STABLE OPERATIONS


If the commissioning of an upgraded production line is followed by issues such as increased downtimes, retrofitting of configurations or emerging liabilities, profitability goals might be delayed or even reduced. Irrespective of the use-case, minimized downtimes and stable operations must always be ensured.

The trustworthiness of the system describes parameters that need to be fulfilled to ensure stable operations. For an alone-standing component, the product quality is reflected in properties related to safety and reliability. Looking at the connected systems, the trustworthiness requirements expand to include security and privacy. Dynamic systems will need to ensure the resilience of its assets, whereas use-cases operating in a smart system must also include functions that ensure resilience for the system.   

 For trustworthiness to be achieved, a paradigm shift in risk management and safety validation is required.  

 

HOLISTIC AND DIGITAL RISK MANAGEMENT CAPABILITIES

While the introduction of connected, dynamic and smart configurations can vastly improve facilities’ performance and efficiency levels, the new solutions also increase the complexity of the risk landscape. With the overall aim to ensure trustworthiness over the lifecycle, risk management must be extended to include new capabilities.

 

1. Capture, assess and manage interdependencies

For stand-alone machinery, the system limits and risk-mitigation capabilities are well-defined. But as the machine starts connecting and interacting with other parts of the configuration, interdependencies emerge throughout the system. 

The new risk assessment process must be designed to recognise and evaluate all interdependencies. This requires holistic assessments on system-level, supported by digital solutions to fully capture, analyse and manage the complexity of the setup.  

 

2. Enable runtime safety statements

In a flexible manufacturing system, changes occur rapidly in line with the adaptive configurations. As each change could introduce a hazard (or threat), a risk assessment needs to be performed for every new setup.

Well-established risk assessment practices could still be applied, provided all interdependencies can be captured and understood. However, frequent system changes, combined with classic risk assessment based on worst-case scenarios, would result in numerous downtimes. Further reductions in productivity could be caused by implementation of measures that might be unnecessarily restrictive in the given situation.

In order to provide safety statements in runtime, smart safety concepts must be designed to include decision capabilities for dynamic environments that can only provide incomplete data. The decision capabilities are enabled by equipping digital twins with safety and security profiles, combined with the use of safety agents for high-probability statements. In other words, the system recognises and reacts to events as they happen during the lifecycle and provides suitable measures for the actual situation.

 

SAFETY VALIDATION BASED ON REFERENCE ARCHITECTURE

Given the fast pace of advances in technology, the regulatory safety standards have a hard time keeping up with industry developments. For advanced manufacturing factories, a standardised catalogue of safety requirements and well-established risk management practices might not be applicable, or even available, at the time of system implementation. To ensure safety compliance, resilience and optimised productivity as described above, each domain-specific use case needs a customised safety architecture.

The safety architecture can consist of a variety of building blocks, depending on the complexity and maturity of the system. Elements include safety standards and frameworks, analytics, information protocols, simulation & modelling (digital twins) and AI. They might also include a reference architecture from a similar setup. 

The transition to smart manufacturing is a step-by-step journey, where a successful use case is followed by an extension of the initial case, or a novel concept for another use case. Safety needs to be an integral part of the process to evolve with the production setup. This way, the initial safety architecture will not only ensure continuous safety for the first use case but can also be of high value in subsequent steps. By passing on concepts and learnings, the initial safety reference architecture becomes a blueprint for proven safety concepts, thereby enabling the navigation of uncharted waters ahead.

This knowledge transfer translates into shorter planning cycles, optimised configurations and reliable production planning. Brick by brick, a solid foundation for operational excellence in smart manufacturing is established.

 

LIFECYCLE RISK MANAGEMENT SPANS THE MANUFACTURING VALUE CHAIN

Trustworthiness requirements for advanced manufacturing concepts are relevant across the value chain, from the safety of industrial components designed for a lifetime of connectivity, to the secure integration of interoperable machinery and the resilient operation of the smart factory. To ensure seamless exchange of unambiguous data and achieve operational excellence, collaboration across the supply chain is vital.

Manufacturing value chain

 

TÜV SÜD ENABLES SAFE AND STABLE OPERATIONS

A leading provider of industrial safety services, TÜV SÜD has worked to ensure safe and stable operations since the steam engine and has continued to do so throughout all development stages of industrial manufacturing. As we approach new levels of advanced manufacturing, our objective remains the same: facilitate innovation and increase profitability for our customers by providing effective safety risk assessment services. Based on technology developments across IIoT, skill-based production and Industry 4.0, our safety experts proactively develop new risk management solutions so that we are always ahead of the evolving risk landscape. Projects include the active participation in multiple innovative collaboration platforms, such as the Digital Twin Consortium, SmartFactoryKL and SmartFactory OWL.

 

HOW CAN WE HELP YOU?

With our worldwide network of safety and security experts, TÜV SÜD delivers machinery safety and risk management services to machinery builders, suppliers, integrators and operators across all markets. Irrespective of how far along you are on the smart manufacturing journey, TÜV SÜD ensures effective risk management, thereby enabling improved performance and a competitive edge for your business.

 

Our portfolio supports all industrial manufacturing use cases



Safety compliance validation

AVM Component safetyHOLISTIC SAFETY - Do your components fulfil the regulatory requirements of their target markets? Is the equipment designed for secure operations in a connected environment? Which product safety features are vital to potential customers who are planning flexible production lines?

Our testing, inspection and certification portfolio for industrial equipment, products and machinery validates compliance to safety regulations in international markets. Based on an individual project scope derived from your specific use-case, all relevant safety aspects are captured, assessed, and validated.


Digital safety compliance management

AVM connected safetyCONTINUOUS SAFETY - How can hazards and risks across production sites and product lifecycles be managed effectively and continuously? Which interdependencies exist between connected manufacturing components and their production environment? If the production site was to experience a cyberattack, which consequences might it have for the safety of workers, equipment and the environment?

By combining the in-depth risk management expertise of TÜV SÜD with our cloud-based machinery safety compliance tool which offers collaboration features, data repository (single point of truth), analytics and online resources, we deliver continuous digital safety compliance management to the manufacturing industry over the asset lifecycle.


Smart safety

AVM smart safetySYSTEM RESILIENCE - How can asset and system resilience be strengthened to reduce downtimes and ensure stable operations in a smart factory? Who answers to the risk and liabilities on system level when everything is connected? How can interdependencies be captured and managed in runtime, e.g. between connected components, AI and wireless solutions?

Going beyond the physical world, our risk management concepts for smart assets, systems and factories provide runtime safety statements. By extending digital twins to feature safety and security profiles, the safety-agents deliver the required decision capabilities with high probability.

 





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