RDF and property graph models have many similarities, such as using basic graph concepts like nodes and edges. However, such models differ in their modeling approach, expressivity, serialization, and the nature of applications. RDF is the de-facto standard model for knowledge graphs on the Semantic Web and supported by a rich ecosystem for inference and processing. The property graph model, in contrast, provides advantages in scalable graph analytical tasks, such as graph matching, path analysis, and graph traversal. RDF-star extends RDF and allows capturing metadata as a first-class citizen. To tap on the advantages of alternative models, the literature proposes different ways of transforming knowledge graphs between property graphs and RDF. However, most of these approaches cannot provide complete transformations for RDF-star graphs. Hence, this paper provides a step towards transforming RDF-star graphs into property graphs. In particular, we identify different cases to evaluate transformation approaches from RDF-star to property graphs. Specifically, we categorize two classes of transformation approaches and analyze them based on the test cases. The obtained insights will form the foundation for building complete transformation approaches in the future.
In this paper, we describe our development of a fully integrated manufacturing planning assistant (IMPA) system, which is able to: (1) interpret the finished part requirements directly from the designer's CAD systems or solid modelers without user intervention or special feature coding; (2) check the machinability of a designed part; (3) automatically generate a process plan, a tool path and an NC (numerically controlled) code, and (4) support interactive user modification of the resulting plans, tool paths and NC code. A demonstration version of the system was designed to provide automated assistance for the planning of machining processes on three-axes NC machine tools. The underlying architectural concepts and reasoning algorithms can be extended to more complex machines such as four-or-more-axes NC machines. CAD, CAE, and CAM including robotic, FMS (flexible manufacturing system) and NC machines are widely used in industry today. There is increasing interest in automation of factory control software Merchant, (1988); this includes automating the generation of the control programs -that is, in developing systems which will automatically produce the NC code for machining the part, given a model of the part, the shape of the raw material, and the machine specifications. With such systems, there are several difficulties in the manual preparation of an NC program code such as, long and tedious calculations, high risk of error in data preparation, etc., which need to be eliminated. This is a critical step toward the integration of CAD and CAM into a truly concurrent engineering and manufacturing environment.
This paper describes the use of a planning ontology of the domain of Aircraft Maintenance, Repair and Overhaul [MRO] at a USAF depot to produce a discrete event simulation model of the aircraft ramp. The ramp is a very flexible, critical, shared resource for aircraft production. The "found work" variability inherent in the MRO process forces the ramp allocations and routing to be modified frequently. Unplanned aircraft moves are expensive and propagate queuing congestion and more moves. Therefore, it is necessary to develop a Rapid Ramp Reconfiguration Plan (RRRP). Ontology models allow the language of the planner to be harmonized with the language of the simulation analyst to speed model development. Simulation based planning is useful to mitigate the impact of "discovered work" by enabling the evaluation of and best selection from thousands of potential ramp resource allocation scenarios.
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