A tale of automation safety: Lessons learned from automotive to aviation and beyond

Industrial automation is increasing due to the potential to reduce costs, and expectations to increase productivity, efficiency, agility, safety. The latest developments are fueled by technological leaps, such as AI advancements for robotic automation, metaverse, machine vision and “humanlike” machine perception, to name a few. However, the generic narrative has often been that the workers should adapt to the automation.

From an organizational factors perspective, it is critical to design and implement automation solutions in a way that allows the people in organizations – from shop floor workers to top managers - to make sense of the underlying conditions and make decisions that control the potentially unsafe and dynamic conditions to prevent risks from actualizing. Organizational factors, such as decision-making, communication, incentives systems, competence development and training, leadership, management and culture for safety, as well as political, social, economic and regulatory context all play an important role for creating conditions for safe automation. Previous research in the context of offshore drilling automation indicated that organizational factors are influenced by automation systems, and they influence the way in which these systems are applied in a specific organizational setting.

This paper offers a tale of automation safety, bringing in insights, lessons learned and historical accounts from aviation to automotive industry and beyond. It advances the understanding on the role of non-technical, organizational factors and business and operational environment that have contributed to the Boeing 737 MAX crashes and linking them to historical accounts for developing regulatory foundations for automotive safety. Latent deficiencies in these factors have been present decades ago in the Boeing’s case but their cumulative effect on safety have not been timely and effectively addressed. Research method is scoping review of public sources and publications. The value of cross-industry learning is emphasized: although different safety-critical industrial domains have specific standards, requirements and regulatory context, there are similarities, which allow for transferability of lessons learned to support safety oversight and overall safe operations in complex sociotechnical industrial settings.

The paper concludes by emphasizing the value of cross-industry organizational learning and the importance of knowing the past to shape the future of safe automation.