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In the past, the construction industry has been slow to adopt new technology. There has been a rapid expansion of technologies, often referred to as Industry 4.0, to aid in the use of automation. One challenge paralleling these new technologies is implementing how a robot interprets design information, specifically information from a Building Information Model (BIM). This paper presents a method for identifying and transforming information from BIM to support robotic material placement on the construction site. This research will include a review of what information can be directly extracted from the model and what must be supplemented to the model for the robot to perform defined tasks within a construction site. The construction sites’ dynamic nature poses multiple challenges that must be addressed for the information extracted from a model to be used by a robot in daily construction operations. This research also identifies barriers and limitations based upon current practice, such as different levels of development or model content as well as needed precision within the information provided for a mobile robot to complete a defined task. 

The adoption of robotics into the construction industry has been much slower than in manufacturing and industrial sectors. Current shortfalls in skilled labor, productivity trends, and ongoing safety challenges point to the need for a drastic shift toward the adoption of robotics as a component of a shift toward industrialized construction. Despite this lag, the interest and development of robotic technology targeting construction has grown in recent years, ranging from the use of drones for tracking to use in offsite fabrication. However, the integration into fundamental site construction requires reconsideration of the information technology infrastructure needed to support detailed task execution information needs in the transition from craft labor to robotic operations. This research presents the identification and mapping of the IT System Architecture required to support BIM to Robotic Construction. Combining elements of the Building Information Modeling architecture and information exchanges with the needed construction task decomposition is required. These elements are mapped to the robotic system elements required for mobile robotic operations. In addition to defining the functions and integration required to support the BIM to Robotic Construction Workflow, shortcomings in existing infrastructure, notably regarding the ability to decompose construction fabrication and assembly means and methods are defined. 

This paper presents an optimization approach based on mixed-integer programming (MIP) to maximize the profit of the Microgrid (MG) while minimizing the risk in profit (RIP) in the presence of demand response program (DRP). RIP is defined as the risk of gaining less profit from the desired profit values. The uncertainties associated with the RESs and loads are modeled using normal, Beta, and Weibull distribution functions. The simulation studies are performed in GAMS and MATLAB for 5 random days of a year. Although DRP increases the total profit of the MG, it can also increase the risk. The simulation results show that RIP is reduced when downside risk constraint (DRC) is considered along with DRP implementation. Considering DRC significantly reduces the percentage of the risk while slightly decreasinz the profit.