Industry 4.0 integrated with robotic and digital fabrication technologies have attracted the attention of manufacturing researchers. Autonomous assembly with supervisory control and data acquisition (SCADA) systems holds the promise of greater scalability, adaptability, and potentially evolved design possibilities helping to maintain efficiency, process data for smarter decisions, and communicate system issues to help mitigate downtime. This paper concerns with developing an intelligent control system based on SCADA in the Internet of Things (IoT) platform to process configuration and reconfiguration of an autonomous assembly system. The implementation study certifies the effectiveness of the proposed IoT-based SCADA control system in autonomous assembly.

Genetically modified cotton varieties have the potential for increasing returns and/or decreasing labor requirements. A nonlinear optimization model is applied to a whole farm analysis for evaluating cotton production technologies. This model maximizes farm utility, composed of expected returns and their variability, at various risk aversion levels in order to evaluate cotton production technologies. Results show that while conventional cotton maximizes utility in a risk-neutral situation, transgenic cotton varieties entered into the optimal solution as higher levels of risk aversion were considered.

Today, in robot applications continuous paths often result from CAD or other planning tools. We present here an approach to the question that has been discussed for a long time, i.e. how to approximate a given path by a second one in such a way that the latter lies in a tube of given radius ε around the first. The approximation should be a (normally cubic) spline with a small number of breakpoints. The strategy is based on algorithms used in “computer aided geometric design” and is applied to examples from industrial and surgical robotics.