Risk assessment is a safety measured process that has the main goal to identify potential risks that are present in the workplace. These are identifyed according to non-confmity situations, processes, or equipment that may cause a particular harm to workers.
Essential tool when work involves risks, which is the case of industrial. Risk Analysis is a process that helps you identify and manage potential problems that could undermine key business initiatives or projects.
The process starts by identifying possible risks and hazards, and estimate how these threats can be materialized in the workplace. This includes the elaboration of project plans, financial data, security protocols, forecasts and others. Accordingly, risks are distincted from hazards, hence: (1) risk is the chance of the hazard happening, and (2) and hazard is the point that may cause harm, such as dangerous liquids,electricity, and others. Therefore, the Risk Assessment process includes 6 mandatory steps that specialists should follow to guarantee a proper execution:
Digital platforms enables process digitalization and organizes workflows. With the correct support information, workers can execute their tasks correctly. Finally, automatic reports are extracted from processes which present a valuable output for continuous improvement.
Our product also augments workers capabilities and safety with AR. With visual guidance and contextual information, workers are able to execute any process by themselves, independently of its complexity.
Information is extracted from both process digitalization, execution and the Internet of Things (IoT), and centralized into one plaform that help both field workers through execution, and managers for decision-making. The data centralization in a digital platforms guarantees an improved visibility and control, risk can be detected earlier , execution is ensured elevating productivity patterns.
Additionally to our data centralization platform in which processes are digitized, different inputs are centralized and automated reports are extracted from quality control execution. Data can be collected in real-time in the form of digital checklists that workers must complete. Therefore, workers are not biased while analyzing the quality of the products. Visual evidence can also be provided by field workers, which makes the quality managers analysis more accurate and efficient.