Increasing the use of simulation in business

The nature of Discrete-Event Simulation (DES) and the use of DES in organisations is changing. Two important developments are the use of Visual Interactive Modelling systems and the use of DES in Business Process Management (BPM) projects. Survey research is presented that shows that despite these developments usage of DES remains relatively low due to a lack of knowledge of the benefits of the technique. This paper considers two factors that could lead to a greater achievement and appreciation of the full benefit of DES and thus lead to greater usage. Firstly in relation to using DES to investigate social systems, both in the process of undertaking a simulation project and in the interpretation of the findings a 'soft' approach may generate more knowledge from the DES intervention and thus increase its benefit to businesses. Secondly in order to assess the full range of outcomes of DES the technique could be considered from the perspective of an information processing tool within the organisation. This will allow outcomes to be considered under the three modes of organisational information use of sense making, knowledge creating and decision making which relate to the theoretical areas of knowledge management, organisational learning and decision making respectively. The association of DES with these popular techniques could further increase its usage in business.

Using DEA and simulation in guiding operating units to improved performance

The potential for the use of DEA and simulation in a mutually supporting role in guiding operating units to improved performance is presented. An analysis following a three-stage process is suggested. Stage one involves obtaining the data for the DEA analysis. This can be sourced from historical data, simulated data or a combination of the two. Stage two involves the DEA analysis that identifies benchmark operating units. In the third stage simulation can now be used in order to offer practical guidance to operating units towards improved performance. This can be achieved by the use of sensitivity analysis of the benchmark unit using a simulation model to offer direct support as to the feasibility and efficiency of any variations in operating practices to be tested. Alternatively, the simulation can be used as a mechanism to transmit the practices of the benchmark unit to weaker performing units by building a simulation model of the weaker unit to the process design of the benchmark unit. The model can then compare performance of the current and benchmark process designs. Quantifying improvement in this way provides a useful driver to any process change initiative that is required to bring the performance of weaker units up to the best in class. © 2005 Operational Research Society Ltd. All rights reserved.

Simulation in the supply chain context:matching the simulation tool to the problem

The supply chain can be a source of competitive advantage for the firm. Simulation is an effective tool for investigating supply chain problems. The three main simulation approaches in the supply chain context are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). A sample from the literature suggests that whilst SD and ABM have been used to address strategic and planning problems, DES has mainly been used on planning and operational problems., A review of received wisdom suggests that historically, driven by custom and practice, certain simulation techniques have been focused on certain problem types. A theoretical review of the techniques, however, suggests that the scope of their application should be much wider and that supply chain practitioners could benefit from applying them in this broader way.

Using simulation to assess the introduction of technology in a continuous operations process

Purpose – To investigate the role of simulation in the introduction of technology in a continuous operations process. Design/methodology/approach – A case-based research method was chosen with the aim to provide an exemplar of practice and test the proposition that the use of simulation can improve the implementation and running of conveyor systems in continuous process facilities. Findings – The research determines the optimum rate of re-introduction of inventory to a conveyor system generated during a breakdown event. Research limitations/implications – More case studies are required demonstrating the operational and strategic benefits that can be gained by using simulation to assess technology in organisations. Practical implications – A practical outcome of the study was the implementation of a policy for the manual re-introduction of inventory on a conveyor line after a breakdown event had occurred. Originality/value – The paper presents a novel example of the use of simulation to estimate the re-introduction rate of inventory after a breakdown event on a conveyor line. The paper highlights how by addressing this operational issue, ahead of implementation, the likelihood of the success of the strategic decision to acquire the technology can be improved.

Enabling a simulation capability in the organisation

Enabling a Simulation Capability in the Organisation addresses the application of simulation modelling techniques in order to enable better informed decisions in business and industrial organisations. The book’s unique approach treats simulation not just as a technical tool, but within as a support for organisational decision making, showing the results from a survey of current and potential users of simulation to suggest reasons why the technique is not used as much as it should be and what are the barriers to its further use. By incorporating an evaluation of six detailed case studies of the application of simulation in industry by the author, the book will teach readers: •the role of simulation in decision making; •how to introduce simulation as a tool for decision making; and •how to undertake simulation studies that lead to change in the organisation. Enabling a Simulation Capability in the Organisation provides an introduction to the state of the art in simulation modelling for researchers in business studies and engineering, as well a useful guide to practitioners and managers in business and industry.

The challenges of representing human behaviour in simulation models:some case examples from supply chain, evacuation modelling and rail disruption

As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.

Modelling and improving human decision making with simulation

Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant

The case for the organisational use of simulation

This paper describes the use of simulation in a large manufacturing organisation and analyses how it could have been used more fully. Although the benefits from using simulation were clear, it was seen that the technique could have been deployed more effectively by considering the organisational context of the use. From the analysis of the case study, certain recommendations are made on how to maximise the benefits from simulation within the organisation, thereby extending the benefits from what is often a considerable investment in developing a simulation model. Recent developments in simulation software in terms of improvements in usability and integration with organisational data are seen to increase the feasibility of a wider role for simulation if the organisational barriers discussed can be overcome.