Reactive control of overall power consumption in flexible manufacturing systems scheduling: A Potential Fields model. (November 2015) - Pach, C.; Berger, T.; Sallez, Y.; Trentesaux, D.
Abstract: In recent years, designing "energy-aware manufacturing scheduling and control systems" has become more and more complex due to the increasing volatility and unpredictability of energy availability, supply and cost, and thus requires the integration of highly reactive behavior in control laws. The aim of this paper is to propose a Potential Fields-based flexible manufacturing control system that can dynamically allocate and route products to production resources to minimize the total production time. This control system simultaneously optimizes resource energy consumption by limiting energy wastage through the real-time control of resource states, and by dynamically controlling the overall power consumption taking the limited availability of energy into consideration. The Potential Fields-based control model was proposed in two stages. First, a mechanism was proposed to switch resources on/off reactively depending on the situation of the flexible manufacturing system (FMS) to reduce energy wastage. Second, while minimizing wastage, overall power consumption control was introduced in order to remain under a dynamically determined energy threshold. The effectiveness of the control model was studied in simulation with several scenarios for reducing energy wastage and controlling overall consumption. Experiments were then performed in a real FMS to prove the feasibility of the model. The superiority of the proposition is its high reactivity to manage production in real-time despite unexpected restrictions in the amount of energy available. After providing the limitations of the work, the conclusions and prospects are presented. Highlights: A reactive Potential Fields model to schedule a Flexible Manufacturing System is presented. This model considers energy savings and overall energy consumption. It is assumed that there is an unpredictable limited amount of total energy available. The models are applied to a sound case study. Experiments in simulation and hardware-in-the-loop are very encouraging.