This paper introduces an effective Model, which is the combination of the methods of S.D. – I/O/O (input-occupancy – output) in studying the improvement of regional industrial structure and the problems in economic development.
This article expounds the necessity of improving reliability of the S.D. model and based on the concepts of “Big System”, “Strictness” and “Parameter Accuracy” when developing a model puts forward some tentative methods to improve reliability of the S.D. model.
Changing and improving manufacturing operations in such a way that optimum flexibility is achieved is a standard task nowadays.Enhanced by the availability of CIM concepts and techniques the pervading paradigm how to solve the problem tends to be based on the structure of the data processing systems.Since management of data systems and inventory are often handled as different functional entities the complex relations of the effects of goods flows and data flows that make up the dynamic behavior of the operations as a whole often evade appropriate treatment.CIM related practice, doing the easy things first, is to follow a hands-on bottom-up approach in optimizing first individual process steps using preferably discrete simulations and then trying to add those optimized islands to a system.If we follow the original ideas of J. Forrester and his group a quite different approach is proposed. In a combination of top-down analysis and bottom-up implementation we would first apply S.D.A. with continuous simulation to understand the operations in their context as is. After optimization we would implement the upgraded system bottom-up.The approach used two levels of imaging the real system to a model. Top level simulation with a continuous model is used to analyze and define dynamic behavior, feed back loops and embedding of operations in the context of sales and supply.Bottom level simulation thereafter serves to check detailed implementation of single tasks within the dynamic specifications arrived at by the continuous overlay model.The procedure allows to exploit the strong points of both continuous and discrete simulation, namely analysis of the dynamic behavior of complex and intertwined systems of flows of goods and data on the one hand and detailed analysis of process steps involving clearly defined operations with work pieces handled.A few examples serve as illustration how this first step of a top-down optimizing with the aid of S.D.A. worked in defining manufacturing systems as a whole before starting bottom-up implementation.As the S.D.A. model is a lumped together model of the real system, its use for on-line prognosis can be a welcome byproduct.
There is growing application of simulation to practical training in management of business on strategic and operational level. In use are simple models where a business is immersed in a much bigger market which sets the context, and others where the context is set dynamically by the actions of the competitors (3), (4).The simulation exercises reported are centered on the question of how to appreciate the impact of a reactive context in managing a business (1). The Implementation of Simulation with continuous simulation (Dynamo, etc.) gives easy appreciation of the impact of operational dynamics in a reactive strategic context.
This study introduces the concept of linking together the Urban Transportation Planning (UTP) and urban Dynamic (UD) models by means of some key indices, such as transportation accessibility, population and economic development (i.e. Gross Provincial Project, GPP). It is found that, by repeating the procedure several times, a certain level of socio-economic development can be achieved which will reflect future transportation conditions in the city. In addition, this study also found some new MOE’s (Measures of Effectiveness) concerned with socio-economic development which can be used to measure and evaluate the effectiveness of transportation investment policies on urban growth.
Corporate planning process uses tools that are inadequate for present day environment of complexity and rapid change. Managements must supplement their intuition and experience with planning using corporate planning models. The key to assist managements to plan effectively lies in better and greater use of computerized corporate planning models. System Dynamics is one of the latest modeling innovations that provide a flexible framework in which to view the interdependent operations of a system in a coherent and orderly manner. With this in view, a modular approach using System Dynamics principles has been adopted to model an integrated steel plant. The model so developed has been applied to conduct simulation experiments in the area of corporate planning. For the purpose of modular construction the corporate model has been considered to be constituted of three modules of marketing production and finance. The production system has been taken for detailed investigation in this model. The physical flow of men, materials and machines in various capacity centers of the steel plant have been separately modeled and then integrated. The financial consequences of these flows have also been considered to simulate indicators of corporate performance such as profit and return on investment. The model has been applied to study the behavior of a large number of variables of interest in response to controllable as well as uncontrollable variables. The model has also been used to conduct “what if” type simulation experiments. It also has been used to identify debottlenecking priorities and evaluate modernization, expansion and debottlenecking projects.
In the near future the organization of home care in the Netherlands will be reorganized. In order to show some of the dynamic consequences of these changes, a preliminary model was developed. In this paper we will discuss the use of the preliminary model to elicit the ideas from policy makers about future changes in the organization of home care. This is done by conducting a Delphi study to keep the time investment of the policy makers as limited as possible.
In order to examine different strategies in the search for more resistant bacterial cultures, we have simulated a variety of growth, mutation, competition and selection processes that may arise in interacting populations of bacteria and phages. Our model considers a culture containing several variants of the same bacterium, each sensitive to attacks from a specific phage. The culture is growing in a chemostat with a continuous supply of nutrients. Surplus bacteria and vira are removed through dilution. Depending on the rate of dilution, the model exhibits a stable equilibrium, self-sustained oscillations, quasi-periodic behavior, deterministic chaos, or extinction of certain species. The model can also be used to describe evolutionary changes in the composition of the microbiological system.
In the Netherlands, ammonia emissions from agriculture contribute significantly to the acidification of soil and water. A 50-70 % reduction of these emissions within the next ten years is one of the great challenges for agricultural practice. This paper presents an outline of a combined system dynamics-optimization model of this problem, which will be used to study the effect of three different abatement scenarios.A concise analysis of the acidification problem is given. The main causes of the current environmental problems of the agricultural system are described.Next the choice of modeling techniques is discussed. System dynamics was applied because of the many (non-linear) interactions and delayed feedback relations in the agricultural system. The flexible responses to policy measures shown by the system’s actors in the past, urged including economic optimization procedures in the model.Some remarks are made on technical problems, using Professional DYNAMO linked with a FORTRAN optimization module.The model contains an integrated description of the ecological problem in its economic context, with links to the related policy field of eutrophication. Interaction with reference groups consisting of experts and governmental officials, and interviews with representatives of interest groups have greatly contributed to the development of the model.Only tentative conclusions can be presented at this stage, as results are still being worked on. However, a better understanding of the acidification problem had been reached, by the reference groups and the researchers. An interesting aspect is the link between emission reduction policy scenarios and possible shifts in land-related agricultural activities.
Today’s investment decisions in the production industry require - as this industry becomes more and more integrated by information systems - a careful long-range planning. Investment projects have to be seen within the network of their environment, and their interdependent impacts can be assessed in a systematic investigation, as part of a Technology Strategy. Furthermore a Systems approach helps to clarify the complex process of Technology Innovations.