No abstract

No abstract

Within the context of supply chain simulation, this paper introduces the generic runtime infrastructure for distributed simulation as a novel infrastructure for distributed supply chain simulation that promotes user transparency and extensible service provision. These are discussed with regard to a distributed simulation of a supply chain model (federation) GRIDS-SCF and a case study on supply chain simulation from the automotive industry. The main aim of this work is to provide industry with a business benefit from distributed simulation by making it possible to connect and reuse previously developed models in a supply chain while minimizing technological intervention (additional technological skills required) with the end user simulationist. It is suggested that this approach may pave the way for distributed supply chain simulation that emphasizes simulation methodology rather than technology.

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent the decision-making. By linking the VIS and AI representation it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

ABSTRACT:The process of manufacturing system design frequently includes modelling and, usually,