Quality control is very important aspect in Building Information Modelling (BIM) workflows. Whatever stage of the lifecycle it is important to get and to follow building indicators. The BIM it is very data consuming field and analysis of these data require advance numerical tools from image processing to big data analysis. Artificial intelligent (AI) and machine learning (ML) had proven their efficiency to deal with automate processes and extract useful sources of data in different industries. In addition to the indicators tracking, AI and ML can make a good prediction about when and where to provide maintenance and/or quality control. In this article, a review of the AI and ML application in BIM will be presented. Further suggestions and challenges will be also discussed. The aim is to provide knowledge on the needs nowadays into building and landscaping domain, and to give a wide understanding on how those technics would impact industries and future studies.

In milling process, surface topography is a significant factor that affects directly the surface integrity and constitutes a supplement to the form error associated with the workpiece deformation. Based on the tool machining paths and the trajectory equation of the cutting edge relative to the workpiece, a new and general iterative algorithm is developed here for the numerical simulation of the machined surface topography in multiaxis ball-end milling. The influences of machining parameters such as the milling modes, cutter runout, cutter inclination direction, and inclination angle upon the topography and surface roughness values are studied in detail. Compared with existing methods, the basic advantages and novelties of the proposed method can be resumed below. First, it is unnecessary to discretize the cutting edge and tool feed motion and rotation motion. Second, influences of cutting modes and cutter inclinations are studied systematically and explicitly for the first time. The generality of the algorithm makes it possible to calculate the pointwise topography value on any sculptured surface of the workpiece. Besides, the proposed method is proved to be more efficient in saving computing time than the time step method that is commonly used. Finally, some examples are presented and simulation results are compared with experimental ones.