ERP, APS and Simulation Systems Integration to Support Production Planning and Scheduling

Abstract

The paper presents a method of the integration of ERP and advanced planning and scheduling (APS) systems extended with automatic generators of simulation models. The approach allows the use of simulation and visualization for rapid verification of production plans. Both integration module and model generator use data exchange and data transformation methods. The concept of data-driven modeling also allows to verify the obtained solution in terms of quality of production flow with full visualization of the processes occurring in the system. A practical example of simulation verification of a solution achieved in the APS system, using the method of automatic generation of simulation models has been shown. During the verification phase of the implemented methodology, the IFS Application -ERP system, Production Order Verification System (SWZ) for multi-assortment, concurrent production planning and Enterprise Dynamics simulation system integration have been used.

Production planning and scheduling with material handling using modelling and simulation

“…The integration of scheduling and simulation systems is performed using the method of automating the process of creating simulation models based on the concept of Data-driven simulation model generation, which are now the largest group among the developed concepts [5,6,7,8,9] The simulation model is created automatically simultaneously with its parameterization based on specific data instances obtained automatically from the planning and scheduling system. Generating (creating) the models could therefore be performed by users without knowledge of how to build the simulation model.…”

“…The process of data transformation representing the computer implementation of the previously described integration methods was realized in the RapidSim software [8,11]. The data transformation documents (XSLT) can be developed independently, so the software can be used for any scheduling and simulation systems.…”

A declarative decision support framework for supply chain problems

“…Indices, and decision variables for the illustrative example have been reported in Table II. The set of reference constraints (1).. (22) for the illustrative example was created and its mathematical/formal notation is included in Appendix A. Brief description of reference set of constraints has been provided below.…”

“…In general, these may be any linear functions. The remaining constraints (13).. (22) arise from the nature of the decision variables. …”

Ant colony optimisation for scheduling of flexible job shop with multi-resources requirements

“…More attractive in practical applications are approximate algorithms and methods using heuristics, metaheuristics [1] and fuzzy logic [2,3] and simulation tools [4,5]. Abandoning the determination of optimal solutions for sufficient solutions provides an acceptable time for determination of a satisfactory solution and the ability to analyze more complex models [6,7].…”