This article describes the results of one of the ten pilot programmes under the Integrated Manufacturing and Service Systems (IMSS) initiative pursued by the Agency for Science, Technology and Research (A*STAR) in Singapore. The objective of this particular programme is to investigate how design, analysis, enhancement and implementation of critical business processes in a manufacturing and service network can be realised using one single simulation/application framework. The overall architecture of the framework outlines how commercial simulation packages and web-service based business process application components would have to be connected through a commercial application framework to achieve maximum leverage and re-usability of the applications involved. In the pilot phase of this programme, research issues were also addressed with regard to mechanisms for interoperation between commercial simulation packages, symbiotic interaction between simulation-based decision support components and physical systems, and simulation speed-up through multiobjective optimal computing budget allocation techniques on a grid infrastructure.

This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing. POSITION STATEMENT OF PETER LENDERMANNThis contribution is specifically looking from the point of view of discrete event simulation as a tool for virtual experimentation to enable design and performance enhancement in manufacturing and logistics. In a world of increasing complexity and customization it will be very important to make sure that the complexity of the systems that simulations are supposed to represent does not develop faster than the capability to model these systems. To achieve this, modeling techniques will have to meet five major requirements as described in the following sections.