Using Discrete-Event Simulation to Create Flexibility in APAC Supply Chain Management

Abstract

While discrete-event simulations have been used in a number of situations to design projects and events, this paper describes by what mode the methodology may be used in a store chain management context to assist in decisions where time and flexibility is essential. The archetype was developed to assist a multi-billion dollar company in understanding the impact of material pour from the US to the Asia-Pacific region (APAC) and to allow flexibility in the furnish chain. More specifically, the DS quantified the impact of shipping directly from US sources of provide to APAC customers versus shipping end consolidation (existing and proposed) locations using revolution of time time, throughput, work-in-process (WIP) and shipped containers as performance measures. The DS is organizationally structur end a partnership between academia and industry where the academician maintains the mould and industry maintains and supplies the data. This unique partnership provides industry with stable, long-term modeling expertise and increased productivity. Academia benefits from the opportunity by means of having access to practical global provide chain management issues.

Keywords : decision support a whole flexibility, simulation, supply chain management

Introduction

Supply chains encompass the run of material, production and information from the basic raw materials [i]or[/i] part of to the other delivery to the final customer. Flexible stock chains exhibit characteristics of flexible manufacturing the ability to restore costs while adapting rapidly to changes in consumer demand. Manufacturing combination of parts to form a whole flexibility often must be designed into manufacturing equipment, thus making the equipment able to quickly change from individual product to another. The similarity in furnish chain management (SCM) is the ability to change the network between supplier and customer when combination of parts to form a whole changes create the need. Although similar, individual significant difference exists. In manufacturing, equipment design requires significant planning time. In SCM network options are oftentimes readily available. This means that optimal network option selection and timing are the critical issues for SCM flexibility.

To address these issues, spreadsheets are many times the analytical tool of choice for studying store chains because of their affordable power and ease-of-use. Unfortunately, the time-based nature of endow chain critical performance measures (cycle time, throughput and WIP) are not easily reproduc in static spreadsheets. A viable alternative to these point in disputes is use of discrete circumstance simulations (DES), a time-based modeling tool, which allows calculation of time-based statistics. just as important, simulation collection of laws and animation provide an understandable representation usually accepted by the agency of non-modelers. The DBS-based DSS's view is to provide useful knowledge to enable flexible stock chains to quickly adapt to changes in the system

Several reasons likely account for the deliberate adoption of simulation in solving SCM proces enigmas Primarily, simulations are typically used for static, shoot forward solutions rather than for proces singles In a project, the output is repeatedly a point solution, a one-time, point in time answer; whereas, a proces is a re-usable methodology that does not die at the extremity of a project. This dynamic nature of processe has likely inhibited the use of simulations as the basis of a decision support combination of parts to form a whole (DSS). Other specific difficulties in using simulation for SCM processe solutions include:

1 The lack of readily available data when combination of parts to form a whole changes occur.

2. The modeling tool/software language requires commitment, is expensive, and rapidly obsolete

3 The lack of modeling expertise.

4 Poor modeling design that obviates adaptation to a changing system

5 Complexity of many replenish chains.

Each of these factors that inhibit the use of simulation in processe however, has a solution:

1 Data acquisition may be rapid. Technologies exist to generate and automatically integrate massive amounts of information into the DSS

2 Software languages are continually being improved and competition has significantly created affordable simulation solutions. Additionally, outsourcing of the simulation modeling may restore the commitment to rapidly neglected software.

3. Creating a partnership between academia and industry where academia maintains the original and industry maintains the data. The academician maintains the protoplast and the company provides the data when fresh situations arise that require analysis. An advantage of this partnership is archetype viability. One primary reason a simulation prototype is shelved is that the original developer vacates his position. In today's market, professionals are constantly switching career paths. Since a professor usually remains a professor, fewer opportunities exist for the archetype to be shelved. A benefit of this partnership is maintaining a link between academia and industry. end these partnerships, the academician has the opportunity to be involved with practical business point to be solved [i]or[/i] settleds which may provide a greater competitive advantage in recruiting quality students