An agent-oriented approach to resolve the production planning complexities for a modern steel manufacturing system
The development of strategies for sequencing slabs through the reheat furnace and rolling mill of a modern steel manufacturing system is complicated by multiple and often conflicting objectives. For example, optimal energy efficiency through the reheat furnace may lead to inefficient rolling sequences or a less than desirable product delivery schedule. Thus, not only the model formulation is complicated, but also the combinatorial nature of the problem precludes an optimal solution. To address these complexities, an agent-oriented approach that has originated from distributed artificial intelligence (DAI) is proposed here. It is found that the implementation of agent technology in the steel manufacturing system makes the operations more flexible, economical and energy efficient.
steel manufacturing system agent-oriented technology production planning and control job sequencing