A Dynamic Algorithm for Distributed Feedback Control for Manufacturing Production, Capacity, and Maintenance

作者：Lee Seokgi^*; Prabhu Vittaldas V

来源：IEEE Transactions on Automation Science and Engineering, 2015, 12(2): 628-641.

DOI：10.1109/TASE.2014.2339281

• Distributed feedback control
• just-in-time production and machine maintenance
• machinery capacity control
• maintenance scheduling
• nonlinear and discontinuous differential equation
• production scheduling

We propose a dynamic algorithm for distributed feedback control which unifies the functions of production and maintenance scheduling at the shop floor level, and machinery capacity control at the CNC level, which are usually considered in isolation in practice. A continuous-time control theoretic approach is used to model dynamics of these three functions in a unified manner, considering stochastic machine failures and a corresponding maintenance interval. Theories of nonlinear control and discontinuous differential equations are used to analytically predict the system dynamics including the resulting discontinuous dynamics.
Note to Practitioners-This paper was motivated by the question, "how decisions can be made regarding multiple functions existing in the manufacturing system in a unified manner." Specifically, we focus on three subsystems in the manufacturing system: production scheduling, maintenance scheduling, and machine capacity control, which are usually handled in isolation or partially coupled manner due to high complexity of integrated decision making. Needs of such integrated decision making can be observed in a variety of manufacturing systems such as metal cutting and laser-based free forming production systems in which production efficiency, timeliness, and operating cost are all important. This paper suggests a rigorous mathematical framework for modeling interrelated dynamics of these systems and a dynamic algorithm to determine integrated solution. Computational experiments show that the proposed algorithm is within 10% similar to 20% from the optimum, but has a much faster convergence rate. Simulation results also indicate that increasing flexibility of production and maintenance events improves timely completion of these tasks.

• 出版日期2015-4