Holistic Framework for Spatial-Temporal Analysis of Production Schedules

Spatial-temporal ( 4D) modeling is a promising technology for production planning with many positive impacts not reachable through the usage of traditional methods. Its benefits are better visualization of planned works, better communication among project stakeholders, and better coordination. 4D modeling assists planners in detecting potential problems prior to production phase and thereby reducing reworks, waste and delays peculiar to complex industrial projects. By simulating activities in spatial dimensions and across time, the planners can detect conflicts and avoid possible production problems. 4D modeling tools currently available provide very basic functions to detect collisions among product elements. However, these tools are unable to detect more sophisticated conflicts caused by the absence of supporting or fastening elements nearby, the inability to deliver elements being installed to their eventual positions, the congestion of required workspaces. A complementary set of clash, join, path and workspace conflicts was introduced and discussed in our previous papers from an applied point of view. In this paper a holistic framework for spatial-temporal analysis of production schedules is presented. The framework is a family of mathematical models and computational algorithms intended to identify these conflicts. A particular attention in the paper is paid to the implementation of these algorithms using spatial-temporal indexing and collision detection techniques. Conducted computational experiments with large-scale industrial data confirm the efficiency of the framework that stipulate its introduction into emerging 4D modeling tools. Such tools are expected to improve the spatial-temporal coherence, reliability and trustworthiness of production schedules.