The residual vibration when a robot manipulator is operated at high speed needs to be suppressed. These vibrations are generated by the resonance of a flexible object being moved by the robot, and research on control algorithms and motion profiles is ongoing to reduce them. In this paper, we propose a method to reduce the residual vibration of an object moved by a robot manipulator by optimizing the acceleration/deceleration time calculated using the object’s natural frequency. The relationship between acceleration/deceleration time and the residual vibration in a trapezoidal velocity profile is considered by analyzing the scenario when the jerking motion characteristic of such vibrations occurs. The results of experiments using a commercial robot show that residual vibrations can be reduced by the proposed method without the need for an additional feedback control algorithm while transferring a flexible object over small and large distances.

This paper presents a decision-making system for semiconductor wafer fabrication facilities, or wafer fabs, with hard interoperation temporal constraints. The decision-making system is developed based on a multiagent architecture that is composed of scheduling agents, workcell agents, machine agents, and product agents. The decision-making problem is to allocate lots into each workcell to satisfy both logical and temporal constraints. A dynamic planning-based approach is adopted for the decision-making mechanism so that the dynamic behaviors of the wafer fab such as aperiodic lot arrivals and reconfiguration can be taken into consideration. The scheduling agents compute quasi-optimal schedules through a bidding mechanism with the workcell agents. The proposed decision-making mechanism uses a concept of temporal constraint sets to obtain a feasible schedule in polynomial steps. The computational complexity of the decision-making mechanism is proven to be, where is the number of operations of a lot and is the cardinality of the temporal constraint set.

As computing power increases, many researchers have addressed online discrete event simulation approaches for real-time decision making in manufacturing shop floors. They typically use real data received from monitoring systems in a shop floor to support real-time decision making, and then the results are transmitted to the shop floor through an execution system. The online discrete event simulation is used to evaluate various 'what-if' scenarios and to predict the behaviours of the shop floor. This paper presents a state-of-the-art review of the researches and developments on real-time decision making based on online discrete event simulations. To provide a comprehensive review, the various approaches proposed and developed in the literature are classified into four categories: general approaches, artificial intelligence-based approaches, distributed systems approaches and virtual manufacturing and/or virtual factory approaches. Finally, future research challenges and opportunities are identified.