Facilitating the analysis of a UK national blood service supply chain using distributed simulation

In an attempt to investigate blood unit ordering policies, researchers have created a discrete-event model of the UK National Blood Service (NBS) supply chain in the Southampton area of the UK. The model has been created using Simul8, a commercial-off-the-shelf discrete-event simulation package (CSP). However, as more hospitals were added to the model, it was discovered that the length of time needed to perform a single simulation severely increased. It has been claimed that distributed simulation, a technique that uses the resources of many computers to execute a simulation model, can reduce simulation runtime. Further, an emerging standardized approach exists that supports distributed simulation with CSPs. These CSP Interoperability (CSPI) standards are compatible with the IEEE 1516 standard The High Level Architecture, the defacto interoperability standard for distributed simulation. To investigate if distributed simulation can reduce the execution time of NBS supply chain simulation, this paper presents experiences of creating a distributed version of the CSP Simul8 according to the CSPI/HLA standards. It shows that the distributed version of the simulation does indeed run faster when the model reaches a certain size. Further, we argue that understanding the relationship of model features is key to performance. This is illustrated by experimentation with two different protocols implementations (using Time Advance Request (TAR) and Next Event Request (NER)). Our contribution is therefore the demonstration that distributed simulation is a useful technique in the timely execution of supply chains of this type and that careful analysis of model features can further increase performance

Commercial-off-the-shelf simulation package interoperability: Issues and futures

Commercial-Off-The-Shelf Simulation Packages (CSPs) are widely used in industry to simulate discrete-event models. Interoperability of CSPs requires the use of distributed simulation techniques. Literature presents us with many examples of achieving CSP interoperability using bespoke solutions. However, for the wider adoption of CSP-based distributed simulation it is essential that, first and foremost, a standard for CSP interoperability be created, and secondly, these standards are adhered to by the CSP vendors. This advanced tutorial is on an emerging standard relating to CSP interoperability. It gives an overview of this standard and presents case studies that implement some of the proposed standards. Furthermore, interoperability is discussed in relation to large and complex models developed using CSPs that require large amount of computing resources. It is hoped that this tutorial will inform the simulation community of the issues associated with CSP interoperability, the importance of these standards and its future

Bridging the gap: a standards-based approach to OR/MS distributed simulation

Pre-print version. Final version published in ACM Transactions on Modeling and Computer Simulation (TOMACS); available online at http://tomacs.acm.org/In Operations Research and Management Science (OR/MS), Discrete Event Simulation (DES) models are typically created using commercial simulation packages such as Simul8™ and SLX™. A DES model represents the processes associated with a system of interest; but, in cases where the underlying system is large and/or logically divided, the system may be conceptualized as several sub-systems. These sub-systems may belong to multiple stakeholders, and creating an all-encompassing DES model may be difficult for reasons such as, concerns among the intra- and inter-organizational stakeholders with regard to data/information sharing (e.g., security and privacy). Furthermore, issues such as model composability, data transfer/access problems and execution speed may also make a single model approach problematic. A potential solution could be to create/reuse well-defined DES models, each modeling the processes associated with one sub-system, and using distributed simulation technique to execute the models as a unified whole. Although this approach holds great promise, there are technical barriers. One such barrier is the lack of common ground between distributed simulation developers and simulation practitioners. In an attempt to bridge this gap, this paper reports on the outcome of an international standardization effort, the SISO-STD-006-2010 Standard for Commercial-Off-The-Shelf Simulation Package Interoperability References Models (IRMs). This facilitates the capture of interoperability requirements at a modeling level rather than a technical level and enables simulation practitioners and vendors to properly specify the interoperability requirements of a distributed simulation in their terms. Two distributed simulation examples are given to illustrate the use of IRMs

Interoperability and Standards: The Way for Innovative Design in Networked Working Environments

Organised by: Cranfield UniversityIn today’s networked economy, strategic business partnerships and outsourcing has become the dominant paradigm where companies focus on core competencies and skills, as creative design, manufacturing, or selling. However, achieving seamless interoperability is an ongoing challenge these networks are facing, due to their distributed and heterogeneous nature. Part of the solution relies on adoption of standards for design and product data representation, but for sectors predominantly characterized by SMEs, such as the furniture sector, implementations need to be tailored to reduce costs. This paper recommends a set of best practices for the fast adoption of the ISO funStep standard modules and presents a framework that enables the usage of visualization data as a way to reduce costs in manufacturing and electronic catalogue design.Mori Seiki – The Machine Tool Compan

A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches

A distributed simulation methodological framework for OR/MS applications

Distributed Simulation (DS) allows existing models to be composed together to form sim- ulations of large-scale systems, or large models to be divided into models that execute on separate computers. Among its claimed benefits are model reuse, speedup, data pri- vacy and data consistency. DS is arguably widely used in the defence sector. However, it is rarely used in Operations Research and Management Science (OR/MS) applications in areas such as manufacturing and healthcare, despite its potential advantages. The main barriers to use DS in OR/MS are the technical complexity in implementation and a gap between the world views of DS and OR/MS communities. In this paper, we propose a new method that attempts to link together the methodological practices of OR/MS and DS. Using a rep- resentative case study, we show that our methodological framework simplifies significantly DS implementation.This research was funded by the Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH), an Innova- tive Manufacturing Research Centre (IMRC) funded by the Engineering and Physical Sciences Research Council (EPSRC) (Ref: EP/F063822/1 )