Industrial Safety deals with the physical integrity of humans, machines and the environment when they interact during production scenarios. Industrial Safety is subject to a rigorous certification process that leads to inflexible settings, in which all changes are forbidden. With the progressing introduction of smart robotics and smart machinery to the factory floor, combined with an increasing shortage of skilled workers, it becomes imperative that safety scenarios incorporate a flexible handling of the boundary between humans, machines and the environment. In order to increase the well-being of workers, reduce accidents, and compensate for different skill sets, the configuration of machines and the factory floor should be dynamically adapted, while still enforcing functional safety requirements. The contribution of this paper is as follows: (1) We present a set of three scenarios, and discuss how industrial safety mechanisms could be augmented through dynamic changes to the work environment in order to decrease potential accidents, and thus increase productivity. (2) We introduce the concept of a Cognition Aware Safety System (CASS) and its architecture. The idea behind CASS is to integrate AI based reasoning about human load, stress, and attention with AI based selection of actions to avoid the triggering of safety stops. (3) And finally, we will describe the required performance measurement dimensions for a quantitative performance measurement model to enable a comprehensive (triple bottom line) impact assessment of CASS. Additionally we introduce a detailed guideline for expert interviews to explore the feasibility of the approach for given scenarios.
翻译:工业安全涉及在生产情景中相互作用的人类、机器和环境的物理完整性。工业安全必须经过严格的认证程序,这种认证程序导致不灵活的环境,禁止所有变化。随着智能机器人和智能机械逐步引入工厂楼层,加上熟练工人日益短缺,安全方案必须包含灵活处理人类、机器和环境之间界限的概念。为了提高工人的福利,减少事故,补偿不同的技能组,机器和工厂楼层的配置应当动态调整,同时仍然执行功能安全要求。本文件的贡献如下:(1) 我们提出一套三种设想,讨论通过动态改变工作环境来扩大工业安全机制,以减少潜在事故,从而提高生产力。(2) 我们提出认识安全系统及其结构的概念。CASS的理念是将基于AI的关于人类负荷、压力和注意力的推理与基于AI的行动的选择结合起来,以避免触发安全停止模式。(3) 最后,我们将提出一个全面的绩效评估标准,以便进行实地评估。