The “production triangle” model in Production Planning and Control

Capability to adapt to the changing requirements of customers presents an increasing importance in the field of industrial production. Increasing demands of quality and reliability can only be met with a high level of readiness for delivery. The up-to-date ERP systems include such Production Planning and Control (PPC) components that are based on theoretically well-established state-equations, production models, data-base transactions and functional supplies. Three macro-parameters: readiness for delivery, stock level and utilization of the available production resources can form such an abstract model - the “production triangle” - on the basis of which a model meeting both the necessary and, at the same time, the satisfactory conditions to realize a good approximation of optimum production planning and control can be created. One of the essential problems of PPC is that the readiness for delivery, stock level and utilization of production resources are such complex state variables (macro-parameters), which cannot be managed independently of each other, especially when disturbances and/or uncertainties occur in production processes, which cannot be planned before executing the processes themselves. The utilizable application systems have to present hierarchical structure along time domain. Long, medium and short term production planning are to be combined with real-time control of manufacturing processes. In this sense, the Manufacturing Execution Systems (MES) may offer new possibilities. Solving of hierarchical production planning and control tasks is fairly difficult, despite of the advantageous achievements in the field of Information and Communication Technology (ICT). The objectives defined for a higher hierarchy level are transformed to the lower levels in form of constraints. In the course of the last few years the authors have got advantageous experience related to utilization of “Production Triangle” based approach, both in - - mathematical modeling of the objectives and constraints, as well as in elaborating the methods and algorithms suitable for constituting the basis of new algorithms and software prototypes.