Earthquakes have the capacity for widespread damage to infrastructure and significant loss of life. In the United States, The aftermath of the 1994 Northridge earthquake is reported to have cost the U.S. $20 billion in direct losses. 

The National Earthquake Hazards Reduction Program (NEHPD) was enacted in 1977 to improve techniques in predicting, forecasting, and reducing seismic vulnerabilities of facilities and systems. Risk and reliability engineers adopted appropriate seismic building codes for new structures to protect critical lifelines including electrical power, communication systems, gas and liquid fuel pipelines, transportation systems and water and sewage systems.

The attacks of September 11, 2001 changed the way structures were constructed regarding risk mitigation. Moving forward, engineers implemented regulations to protect the occupants, property, and functions of their facilities in the event of a manmade attack.

The Department of Justice outlined a risk assessment and management plan for engineers to implement in response to the terrorist attacks. The process includes the following six steps:

1. Critical infrastructure and key asset inventory
2. Criticality assessment
3. Threat assessment
4. Vulnerability assessment
5. Risk calculation
6. Countermeasure Identification

Machinery that produces essential items and conducts functions necessary for daily life such as power plants, oil refineries, and factories are susceptible to risks such as deterioration, malfunction and natural disasters. 

Risk and reliability engineering accounts for these events and adjusts the planning and maintenance of equipment properly. Engineers often conduct what is called predictive maintenance. Predictive maintenance uses historical data and ongoing measurements of the equipment to predict future failures or malfunctions and corrects or adjusts them before their occurrence.

These types of proactive measures help companies prevent loss of business, protect employees and bystanders from injury, and ward off property damage.

Risk management is essential to the protection of various technologies, specifically IT systems. In our ever-digitizing world, it is imperative that essential institutions, like the U.S. government, have a risk management plan in place to protect itself from cyber attacks. 

Risk management engineers determine the extent of a threat or risk associated with a given IT system and formulate a plan to mitigate these risks. It not only is important that these systems are protected from breach, but also that in the event of an adverse effect, they can achieve gains in mission capability. 

The National Institute of Standards and Technology’s Risk Management Guide for Information Technology Systems provides a risk assessment methodology for IT services that outlines nine essential steps.

Machine learning has come into focus as an effective means to implement risk management in recent years. Machine learning models study a dataset and use the knowledge gained to make predictions for other data points. Its algorithms have aided risk management engineering from predicting defects in reinforced concrete to predicting natural disasters. 

Machine learning in risk engineering has exciting potential, as it is breaking the mold for traditional risk assessment techniques, and configuring a way to perform real-time risk assessment. Currently, the majority of risk assessments are scheduled in specific time increments, i.e., every six months or once a year. These set assessment times often do not consider any dynamic changes that occur during the time frame between the next mandatory analysis.

Uncertainty analysis is the process of estimating the uncertainty in a prediction, based on uncertainties in various quantities, models, and measurements. Through this estimation, engineers can make concrete contributions to decision-making through the analysis of uncertainties in the relevant variables. 

Uncertainty analysis can also provide the framework for a comprehensive examination of a project and identify potential sources of errors. Furthermore, uncertainty analysis can identify areas in need of improvement to optimize the project outcome.

Digital twins are an astounding innovation that provides digital representations of real-world products. The digital representations demonstrate a product’s form, analyze its functions, simulate product behavior and can even test it before a prototype is built. Digital twins continuously evolve and improve in accuracy by incorporating the constant flow of data and regular user experience input. Furthermore, they can compare the sensor measurement of a physical quantity in real time against the prediction of the same quantity. 

Digital twins enable engineers to utilize virtual tools to manage assets and regularly improve performance. This allows professionals to detect anomalies and schedule inspections and repairs, anticipating problems and preventing their occurrence before they begin.

Reliability is the ability of a product or system to operate under specific operating conditions for a specific period of time or number of cycles. Risk in engineering is defined as the combination of likelihood of an occurrence and the severity of consequences that may arise from it. 

The two metrics combined in risk and reliability analysis are used as a tool for informed decision-making and hazard mitigation.

Risk and reliability engineers assess the reliability of operations and work to reduce risks that could adversely affect operations. They regularly evaluate current processes, assess the reliability and maintainability of equipment and identify failures or issues.

Risk management engineers identify, assess, and prioritize risks and apply resources to control the probability of adverse events occurring. All risks can never be fully mitigated, therefore risk management engineers follow a prioritization process in which the greatest risks with the greatest loss capacity are handled first.

Property field risk engineers create and implement strategic service plans to reduce loss and improve operations. They manage the account risk portfolio and ensure that all underwriting requirements are being met.

Reliability engineers assess and identify potential issues and develop a plan to avoid or mitigate losses. Through in-depth analysis, reliability engineers help inform businesses on how to best maintain their assets by identifying potential hazards and preventing as many as possible.

Site risk management engineers provide technical consulting while also overseeing and monitoring daily site operations. They often work closely in scheduling regular maintenance activities to mitigate risk, update configurations of risk management software and are on-site to respond to emergency risk management activities. 

Quality engineers oversee and ensure that manufactured products meet high-quality standards. They implement quality processes, testing procedures and integrate systems ensuring that all products and processes comply with safety regulations and client requirements.

Security engineers build and maintain the systems used to protect computer systems and networks. Security engineers are responsible for ensuring these systems can withstand adverse events such as natural disasters. They analyze networks, certify they are running securely and proactively think about security issues that could arise in the future.

Equipment breakdown risk engineers perform regular inspections on equipment and report findings to the customer or business. They thoroughly inspect equipment to identify the source of risk, loss, and costs. Equipment breakdown risk engineers also conduct risk evaluations, evaluate exposures and controls, develop loss estimates, and then communicate their findings to the business.