Integration of a discrete event simulation with a configurable software application

Abstract

In general terms, the invention can be described as a computer system for enhancing the performance of underlying policies and execution-rules of real-world activities. The computer system includes a demand input section for providing demand information to drive the system. A real-time software application has a series of discrete steps for implementing the underlying policies and execution-rules of the activities and converts the demand information into instructions. A simulation-time operations-simulation model implements the underlying policies and execution-rules of the activities and receivers, the instructions. A control section includes a synchronization clock which synchronizes the discrete steps of the software application with the operations-simulation model by delaying the execution of some of the discrete steps and which communicates the instructions from the software application to the operations-simulation model. An output section outputs data to enhance the performance of the underlying policies and the execution-rules of the activities.

Description

[0001] The present invention relates to a method and apparatus for modeling, simulating, and enhancing planning and operations. In particular the invention relates to the integration of discrete event simulation with a framework-based software application for enhancing the performance of underlying policies and execution-rules.[0002] 1. Background of the Invention[0003] Enterprise Resource Planning (ERP) packages are business management systems that integrate all facets of a business, including planning, manufacturing, sales, and marketing. One of the major shortcomings of traditional ERP packages is that they are very inflexible and unable to handle very complex business processes. Such business applications are initially created using specific business model templates. These templates are customized by manually changing settings and parameters in the software package. Changes in the business processes are always constrained by such templates in these packages.[0004] These shortcom...

AI Technical Summary

Benefits of technology

[0019] The present invention allows framework-based applications to perform discrete event simulations and to combine these applications with discrete event simulation model components. In this way it is possible to "kill two birds with one stone", i.e., to address the shortcomings when applying framework-based business applications or discrete event simulation systems individually.

[0020] Simulation models and business application software are both representations of the actual operations of an enterprise. The present invention is a unified, and optionally distributed, simulation and implementation technology where the entire performance process can be represented along a supply chain in a unified business model. It improves the performance of business; operations with discrete event simulation technology, and then generates and implements the corresponding business application software from the same unified business model, based on a framework-based implementation technology which, unlike conventional applications such as ERP systems, allows the adaptation of operations to permanently changing business environments with the required flexibility and minimal human effort. This allows a company to optimize both operational and business processes through simulation of the entire performance, process along the value-added chain (including planning and customer order management) rather than just the manufacturing process. By using framework-based business application software, optimized business rules / policies can then be implemented into real life systems with minimal effort and time.

[0021] In general terms, the invention can be described as a computer system for enhancing the performance of underlying policies and execution-rules of real-world activities. The computer system includes a demand input section for providing demand information to drive the system. A real-time software application has a series of discrete steps for implementing the underlying policies and execution-rules of the activities and converts the demand information into instructions. A simulation-time operations-simulation model implements the underlying policies and execution-rules of the activities and receives the instructions. A control section includes a synchronization clock which synchronizes the discrete steps of the software application with the operations-simulation model by delaying the execution of some of the discrete steps and which communicates the instructions from the software application to the operations-simulation model. An output section outputs data to enhance the performance of the underlying policies and the execution-rules of the activities.

Problems solved by technology

One of the major shortcomings of traditional ERP packages is that they are very inflexible and unable to handle very complex business processes.

This kind of rapid experience acquisition is normally infeasible with the real system because experimentation with real system is often disruptive, seldom cost-effective and sometimes impossible.

However, improvements in operations and business are often discarded at the design table today as their implementation involves too much work and the advantage is lost by the time the changes are made.

However, this kind of simulation--which is not discrete event simulation (DES)--is not sufficiently able to provide direct and obvious information on the impact of changes in the business model upon the operational and business performance.

But implementation / realization of these changes in the corresponding business applications remains cumbersome and in some cases impossible.

1) Even with advanced framework-based applications the performance of business operations can only be addressed based on the real history of the system. Here the real history of the system is when a real event has occurred and been reported (e.g. the production profile of a month once the month is over).

2) Operational models that are optimized using conventional discrete event simulation technology are difficult to implement.

3) The scope of traditional simulation models does not sufficiently take into account the fact that the underlying business is typically customer-demand driven rather than input-release driven.

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