The autonomous industrial plant – future of process engineering, operations and maintenance. (April 2020) - Gamer, Thomas; Hoernicke, Mario; Kloepper, Benjamin; Bauer, Reinhard; Isaksson, Alf J.
Highlights: This paper discusses the use of the notion of Autonomous Systems for the process industry. A taxonomy of 6 autonomy levels is proposed – ranging from 0 no Autonomy to 5 Full Autonomy. The taxonomy is inspired by the SAE standard for autonomous driving and is here illustrated by industrial examples from Marine and Mining, as well as process examples. It is argued that, while self-driving cars are mainly about replacing the driver, there are many potential benefits of industrial systems autonomy which relate to yield, product quality, cost of material and energy as well as safety. It is further argued that process automation has several lifecycles such as Plant Engineering and Operations that may all be at different levels of Autonomy. Even within one lifecycle phase, for example, Operations there are different tasks such as Control Room Operation, Field Operation and Maintenance and Production Planning and Scheduling that may need further refinement on Autonomy levels. Abstract: Almost every day we read about new advances in self-driving cars and artificial intelligence. For autonomous driving, there already exist established standards with six levels describing the steps from driving without assistance to fully automated, i.e., autonomous driving. While many people and industries – in particular the automotive industry – believe that self-driving cars are feasible in the near future, one may ask how feasible full autonomy is in the process industry? Is it realistic to aim towards a fully autonomous chemical plant, and what does full autonomy even mean for the process industries? This paper introduces a definition of autonomy and corresponding levels of autonomy for the process industry. It starts from an abstract definition of six autonomy levels that are applicable to various industrial domains, also illustrated by recent examples from different industrial applications such as mining and marine. It also discusses how to achieve an autonomous system in general, based on cognitive capabilities and AI technologies potentially implementing them. Then, it discusses the applicability of this definition for process industry in a first step. Finally, the taxonomy is further refined by studying some key autonomous features of two process lifecycle phases: operations and engineering, and examples for the meaning of each autonomy level per feature are given.