Technology innovation is critical to meeting the increasingly tricky challenge of workplace safety writes Shawn Chandler, IEEE Senior Member and director of IT at PacifiCorp
As improvements to workplace safety continue to gain attention – especially with the new guidance published to help employers to get workplaces operating safely amid the global pandemic – the provisioning of best practices for evolving safety programmes has been rapidly pushed to the top of the agenda. However, there are some industries where safety comes with the territory – including factories, construction sites, distribution centres and, at the moment, even supermarkets and hospitals – and technology innovation is critical to keeping those workplaces safe.
Technology innovation in communications technology, distributed sensing and advanced computing have drawn attention from stakeholders in recent times. Advances in the area of safety are of significant interest, where machine learning, data modelling, and system simulation have allowed for new commercially available solutions which enhance safety stakeholder’s capabilities to detect and prevent accidents. These capabilities can be characterised in three primary areas, including intelligent infrastructure, secure system monitoring and automated assessments.
Adopting intelligent infrastructure
The Internet of Things (IoT) is a vast network of intelligent infrastructure and devices, often capable of communicating in near-real time to gather data. Also referred to as “Big Data”, the information gathered allows for new capabilities in detecting patterns and using machine learning to understand a system’s behaviour. The devices are called “intelligent” because they have ability to systematically assign meaning and orderly groupings to observations to serve a higher purpose supported by identification.
This kind of intelligent classification may be used in equipment at the “edge” to compare characteristics of data observed in real-time to previously gathered data. This can result in very fast assessment of safety issues and can trigger a response in real-time without the aid of an operator. For example, intelligent devices can alert a control system that a condition in one machine may lead to an unsafe condition in another process. Many such devices and systems are available today, ready to prevent hazards and contribute to safe operation in many industries.
Ensuring secure monitoring
Another use of IoT in safety regards security and monitoring for risk. With the advent of all these electronically connected systems, monitoring related to cyber-security is more important than ever before. Intelligently monitoring systems and creating networks of security devices that share the monitoring data helps prevent intrusions, deter in real-time, and keep facilities, electronics, and data safe from ill intentions.
Machine learning is used to understand and document cyber-attack patterns and identify potential issues on the internet or network as they evolve, rather than after they occur. Advanced firewall and intrusion prevention devices are an important component of IoT, and key to evolving issues around data privacy. Indeed, the collected data from IoT itself needs strict control and protection measures to prevent its use for unintended purposes.
Improving safety and technique
Monitoring devices can also be used to improve safety within very dynamic systems, such as a manufacturing floor, in a distribution yard, or even within a large-scale logistics and transportation network. With enough data demonstrating safe operation in a system, machine learning can be used to define unsafe behaviour.
With training, sensors can then identify adverse conditions to safe operation and signal to stop a process or alert a human when safety is at risk – for example, warning a new employee that a machine in their immediate vicinity is about to start and hearing protection is recommended. Examples are not limited to notification – consider a long-shift employee and capturing data demonstrating their performance over time, in order to help them and their supervisor understand their maximum recommended safe time-on-shift. Wearable monitoring devices can also help to identify proper lifting and handling motions as they occur, document performance, and notify the employee when their safety may be at risk.
The same intelligent device technology may be used to identify maintenance needs for machines and equipment before a safety issue arises, highlighting equipment issues, such as parts nearing the end of their component life, and signalling for replacement or inspection. Automated assessment is perhaps the most important safety-related capability enabled from intelligent device infrastructure, and used effectively, will help industries everywhere achieve their goals to improve safety in operations.