Integrated Enterprise Risk Management and Industrial Artificial Intelligence in Railway

Traditionally, solutions for Industrial Artificial Intelligence (IAI) in railways focus on productivity improvements and single-loop learning. This is mainly achieved by the implementation of IAI in the technical rail system and its operation, traffic management, maintenance, and modification. These productivity improvements are limited to doing things the right way or better according to existing regulations. However, to support the implementation of these solutions and keep pace with the fast technological development (e.g., by reducing the pacing problem), IAI should also be used to manage effectiveness improvements and double-loop learning. Hence, IAI should be used in the management of regulations (e.g., based on technical specifications for interoperability, TSI) according to process-related regulations for dependability and safety (e.g., EN 50126/28/29 and Common Safety Methods, CSM). Thereby, IAI can change the traditional evolutionary management of railway regulations, where it tends to expand gradually based on experienced risks, incidents, and accidents. In addition, IAI can also support management in how to decide upon what the right things to do are by triple-loop learning. This might be achieved by using relevant theories in managing risks related to internal control, i.e., effectiveness, productivity, compliance, and reporting. This paper presents an integrated enterprise risk management framework and approach for the future railway, including the use of four different levels of IAI for continuous improvement and organizational learning. The applied approach is deductively based on a literature review in databases for regulations, standards, and scientific publications. The work is inductively supported by empirical examples, mainly from the Reality lab digital railway at Trafikverket (the Swedish transport administration). The result is an integrated enterprise risk management framework that should be applied to support the management of requirements related to risk in the railway when working with continuous improvement supported by IAI.