Towards an Affordance-Based Ad-Hoc Suitability Network for Indoor Manufacturing Transportation Processes

Abstract

Abstract:In manufacturing companies, productivity and efficiency are the main priorities, besides an emphasis on quality issues. The outcome of this research contributes to increasing production quality and efficiency in manufacturing. The article deals with indoor manufacturing environments and the transportation processes of production assets-referred to as smart transportation. The authors modelled the objects present in the indoor manufacturing environment with ontologies including their affordances and spatial suitability. To support flexible production and dynamic transportation processes have to be tailored towards the 'needs' of the production asset. Hence, the authors propose an approach utilizing an ad-hoc suitability network to support the "optimal" path computation for transportation processes. The objective is to generate a graph for routing purposes for each individual production asset, with respect to the affordances of the indoor space for each production asset, and measurements of a sensor network. The generation of the graph follows an ad-hoc strategy, in two ways. First, the indoor navigation graph is created exactly when a path needs to be found-when a production asset shall be transported to the next manufacturing step. Secondly, the transportation necessities of each production asset, as well as any disturbances present in the environment, are taken into account at the time of the path calculation. The novelty of this approach is that the development of the navigation graph-including the weights-is done with affordances, which are based on an ontology. To realize the approach, the authors developed a linked data approach based on manufacturing data and on an application ontology, linking the indoor manufacturing environment and a graph-based network. The linked data approach is finally implemented as a spatial graph database containing walkable corridors, production equipment, assets and a sensor network. The results show the optimal path for transportation processes with respect to affordances of the indoor manufacturing environments. An evaluation of the computational complexity shows that the affordance-based ad-hoc graphs are thinner and thus reduce the computational complexity of shortest path calculations. Hence, we conclude that an affordance-based approach can help to decrease computational efforts for calculating "optimal" paths for transportation purposes.

Cross-Domain Building Models—A Step towards Interoperability

“…In particular, refs. [36,44,45] use a graph-based representation to track objects present in the indoor space. Most of these models rely on the dual graph approach ( [46,47]) that uses a node-relation structure.…”

Mapping Parallels between Outdoor Urban Environments and Indoor Manufacturing Environments

“…The latter could be analyzed by an approach following geo-visual analytics or geostatistical methods, whereas a detailed performance analysis would require an analysis of the underlying algorithm in a mathematical manner and in-situ testing-see [15] for details. In the indoor environment under review, humans carry out transportation tasks, which leads to the necessity of communicating the recommendations of the system in a user-centered manner, utilizing theory and methods from the Human Computer Interaction.…”

“…They apply this general approach in the context of manufacturing environments, coupled with an affordance-based routing approach to support transportation processes in indoor spaces. The authors do not intend to elaborate on the navigation algorithm, as this will be outlined in a forthcoming paper [15]. Here, the authors present the idea of applying the solution strategy of decomposition for solving tasks in outdoor spaces to an indoor manufacturing environment.…”

3d Geospatial Indoor Navigation for Disaster Risk Reduction and Response in Urban Environment

“…Indoor navigation for evacuees requires a guidance system which could be based on navigation algorithm devised using information on hazardous areas, emergency spreading, congestion areas (Weeraddana et al, 2013). Another specific application of indoor navigation research is for routing purposes to fulfil the transportation necessities of each production asset (Scholz et al, 2017). Similarly, a user can be a normal person with no problems with eyesight while another user could be a visually impaired person or a person in an environment with bad visibility (e.g.…”

“…An optimization technique considering time-space-based risk is proposed taking into account the spatial location of evacuees within a building to minimize the risk (Han et al, 2007). One interesting approach used is of navigation graphs with weights, done with affordances based on ontology (Scholz et al, 2017).…”