Creating Safe Working Environments: Lessons From Oil & Gas on Managing COVID-19 Risk

    Dr Warrick Cooke


    Automotive Consumer Goods Aerospace and Defense Energy COVID-19 Series

    As manufacturing starts to return to work, employers are grappling with how to reopen whilst keeping employees safe. Government advice for offices is fairly straightforward– sit a certain distance apart, avoid sharing workstations, etc. But starting up, say, an automotive plant is rather more complicated.

    Industries which require people to move around a shop floor, handle tools, or work across different stages of a moving assembly line, involve much more complex interactions. Advice about not touching shared surfaces or keeping two meters apart are harder to follow.

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    These usually low risk environments are having to come to terms with operating in a high-risk world, and complying with new government guidance on safe working – where both risks and guidance are likely to continually evolve. Fortunately, these organisations have a ready-made approach they can draw on to manage these risks.

    The Oil & Gas and process industries have long operated in high risk environments. Working around highly explosive substances carries constant danger. In response, these industries have developed tools to help them cope with, and mitigate, that risk. These have driven down dangerous incidents to near zero. Just as importantly, they allow such industries to operate with confidence.

    Safety processes used in oil and gas, and what can be learned

    A simple safety assessment tool, widely used in these industries, is the bowtie diagram. For each risk, the potential inciting incident, eg a gas leak, is placed in the middle. On the left is preventative action such as regular valve checks, on the right is protective measures for if it does happen, such as leak detection and shielding ignition sources.




    An equivalent in an automotive plant during COVID-19 might have the incident as an infected person coughing. On the left could be regular temperature checks for employees, on the right protective barriers, regular cleaning, and air curtains.

    This is a simple planning tool, which allows you to quickly think through hazards and what measures to take to limit the risk. But the real value to be learned from these industries is how to assess where and when to deploy these preventative and protective measures.

    This draws on more complex modelling which combines information about the nature of risks, with temporal and spatial models of the facility. An example is BP’s OMAR tool for offshore risk management, which Tessella has been working with them on since 2007.

    Such a model starts with a 2D or 3D plan of the facility and pinpoints elements of risk, such as pipelines and gas storage. It would use a list of established possible accidents, such as gas leaks or explosions, to model how these would play out at each risk point, and how the consequences would map onto where employees are at different times.

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    To understand how each incident could play out, modellers work with experts on explosions and fluid dynamics, to build models which truly reflect how such incidents would spread through the facility. They can then put in place effective mitigation measures, and run the model again to see what works best.

    This same approach could be used in manufacturing. Most operators have floor plans and knowledge of where people should be at what times. Onto these, they can overlay risk points to build up a model of how viral particles might spread.

    Just as Oil & Gas works with experts on explosions, factory managers need to work with virologists and aerodynamics experts to develop virus dispersion models. These would help them answer questions such as: how would a short conversation, or a sneeze, disperse viral particles? How does this change if they are wearing a mask? How does airflow affect where and how far it travels? What would be the impact of someone touching a surface that has been sneezed upon? How quickly does the virus break down to a non-infectious level?

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    This can be incorporated into the models to create standardised risks. These are then mapped onto time and location data about where people are, and where they move throughout day.

    This allows the creation of a tools for quantitative assessments of risk to each individual based on their daily movements, very similar to those that are common practice in Oil & Gas.

    Using models to make informed decisions

    These models can be used to assess risks and see how they might propagate. Managers can then decide the best ways to prevent the spread of the virus between employees, such as mandating mask use, staggering arrival times, fitting barriers between stations, cleaning of equipment after use, using UV to kill virus on the assembly line, or airflow management.

    Models can also be run with different parameters. They can test whether interventions will have knock on effects, such as whether protective barriers change airflow that may need further changes. If there is a local outbreak near the facility, the model can be run to assume a higher level of undiagnosed infection in the workforce, and so understand if temporary changes are needed, such as fewer staff on site.

    This process-based approach allows companies to prioritise the highest risks first. It allows them to deploy measures in a way that addresses their specific risks, rather than following blanket rules. It also allows them to present very clear reasoning and evidence for their decisions and engage in constructive discussions with employees and unions.

    Business as usual during COVID-19

    High risk is the new normal for manufacturing. But it has been long been ‘business as usual’ in the Oil & Gas and process industries. Manufacturers can learn from their many years of experience managing risk, and protecting workers from real dangers.

    Risk modelling has driven down dangerous incidents, and allowed companies to take informed decisions in risky environments which keep people safe without compromising their business operations. Such approaches can now be used to allow large manufacturing facilities to safely get back to work.

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