A Flexible and Adaptive Control Architecture for the Efficient Supply Chain Management (SCM)

摘要

The supply chain consists of various subsystems such as manufacturing systems, delivery systems, distribution systems, and transport systems. In particular, the manufacturing system plays an essential role but it is so complex that it is hard to predict and optimize the global supply chain. To optimize and execute the manufacturing system, the shop floor control system (SFCS) has been developed and various control architectures have been proposed. In spite of their benefits, it is difficult to cope with the changing demands of process plans and parts in the supply chain, due to the lack of self-adjustment to the manufacturing environment and guarantee global optimization. The objective of the paper is to propose the conceptual framework of a democratic control architecture that overcomes the defects of the previous control architectures for the efficient supply chain management. The solution to the new control architecture can be found in political systems. Modern nations develop a political system so as to mediate conflicts among people, and to accommodate nation's global benefits. Similarly, a SFCS should also resolve conflicts among controllers and maximize shop floor's overall benefits. To reflect the nature of democracy, the democratic control architecture has two essential characteristics: evaluation of controllers and respective independence of the three powers -administration, legislation, and judicature. First, each controller should be evaluated in terms of its performance and achievement, which initiates countermeasures against the low-performed controllers. Second, the roles of all the controllers should be grouped into the three independent powers so as not to abuse their power and to achieve the balance of power. With the support of proposed framework high-performance and adaptability to the dynamic change of shop environments can be simultaneously achieved in shop floor control to cope with the ceaseless fluctuations in the supply chain.