We present a novel robot programming methodology that is aimed at reducing the level of robotics expert knowledge needed to operate industrial robotic systems by explicitly modeling this knowledge and abstracting it from the user. Most of the current robot programming paradigms are either user-centric and fully-specify the robot’s task to the lowest detail (used mostly in large industrial robot...

In this research we model a job shop that produces a set of discrete parts in a make-to-stock setting. The intent of the research is to develop a planning model to determine the optimal operating tactics that minimize the relevant manufacturing costs subject to workload variability and capacity limits. We model the interplay of three key components in the job shop, namely, the production freque...

This paper uses an economic agent-based model of land use in a hypothetical urban fringe community to examine the effects of large-lot zoning on land conversion, land prices, and the spatial configuration and density of new development. The model incorporates the actions of heterogeneous housing consumers, developers, and farmer/landowners who make economic decisions in land and housing markets...

Additive manufacturing (AM) has attracted a lot of attention in the industry and studies due to ability fabricate parts different sizes shapes along with economic costs. Among three-dimensional (3D) printing methods, stereolithography (SLA) is becoming an important method. The objective this work investigate effect sub-build orientations acrylate-based 3D SLA rapid-prototyping photosensitive re...

Genetic algorithms (GAs) have been used widely for such combinatorial optimization problems as the traveling salesman problem (TSP), the quadratic assignment problem (QAP), and job shop scheduling. In all of these problems there is usually a well defined representation which GA's use to solve the problem. We present a novel approach for solving two related problems-lot sizing and sequencing-con...