Multi-agent System for Cloud Manufacturing Process Planning

The fundamental concern of building a distributed Cloud manufacturing (CM) platform is how wide variety of manufacturing services (SaaS, PaaS, HaaS, IaaS) can be integrated under a common cloud platform? More technically, this concern is related to the classical data integration problem, i.e. how to universally map information from heterogeneous data sources. Adoption of CM may become possible if collaborative agents can automatically discover a set of suitable CM services, and invoke them in a particular order to achieve a certain manufacturing task. Cloud computing community suggested semantic web services in order to enable automatic discovery, invocation and orchestration of web services. In this paper, we describe a novel multi-agent framework, where agents are configured based on Belief, Desire, and Intention (BDI) formalism. In this proposed framework, agents are capable of autonomously discovering and orchestrating manufacturing services based on their intrinsic and extrinsic awareness of the manufacturing knowledge at its most contemporary state. The internal structure of agents are constructed by Horn-DL rules, arguing such DL-safe rules will be able to extract and analyze manufacturing knowledge bases, built with OWL DL. This chapter also introduces a novel method of selecting suitable services, from the intrinsic semantic in Horn-DL rule. This integration of Horn-Dl and semantic cloud services is designed based on a logical extension of Horn-DL. (C) 2018 The Authors. Published by Elsevier B.V.