Ontology-Based Task Allocation for Heterogeneous Resources in Line-Less Mobile Assembly Systems

Abstract

AbstractVolatile markets and production request for assembly systems adaptable to changes of product types, production capacity, and product order. Computer-aided decision support systems facilitate scheduling, planning, and controlling adaptive and flexible assembly systems. Formal description models of resources and their capabilities, assembly tasks and their requirements are necessary for automated decision-making. This paper contributes a conceptual CAPabILity-based resource AllocatioN Ontology (CAPILANO). The ontology is tailored as a uniform description of heterogeneous assembly resources and their (combined) capabilities, connected to a capability-based task allocation approach. The intended application of the resulting framework is the identification of suitable assembly resources in Line-less Mobile Assembly Systems (LMAS) and their allocation to assembly tasks, based on a unified and formal description. To date, ontologies in assembly have been limited to querying resources and their capabilities; here, subsequent task allocation is presented as an integral component of a tailored framework. The resulting framework consists of a model of heterogeneous resources and their capabilities in an ontology created in Protégé in OWL, SPARQL-based querying, and a consecutive and availability-aware task allocation in Python. The development of the ontology-based task allocation framework, including ontology taxonomy, querying and task allocation, is discussed. Its applicability in LMAS is demonstrated through linear scalability of task allocation and future advances are discussed.