This article presents the results of ongoing research on resilience in production systems. It refers to the term resilience as a way of dealing with uncertainty and disturbances. The proposed resilience analysis method, based on dynamic models, supports analysis of the production system in order to determine which structures and processes should be improved or reduced, and what resources preserved, in order to manage resilience. The application of the method is presented using results of the research project in Bombardier Transportation manufacturing plant in Poland. For the purpose of the analysis highly detailed discrete-event model and System Dynamics model were built. Both area of interest of both models complemented one another. In this paper the main focus is given to the System Dynamics model. In the course of the research project the System Dynamics approach proofed to be very useful for examining the impacts of various disturbances and possible solution policies. As a tool for the resilience analysis results dissemination, the dynamic model based simulator, was prepared.
Abstract.
This paper critically examines the challenges associated with demand for immunization, including the interplay of political, social, economic and technology forces that influence the level of immunization coverage. In an earlier paper by the same authors, system dynamics modeling and case study research methods are used to capture the complex and dynamic nature of the immunization process. This paper suggests a framework to capture the complex and dynamic nature of the immunization process and tests its effectiveness using a case study on Uganda healthcare provision. The results indicate in cases of developing nations, immunization demand outstrips immunization coverage. The paper suggests that the model and results could be used for theory building in immunization policy evaluation in developing countries.
Modeling and Analysis of Production System of A Steel Plant- A System Dynamics Approach
K.R.Divakar Roy
Department of Mechanical Engineering, A.U.College of Engineering (Autonomous)
Visakapatnam-530 003
Mail Id: divakarroy@rediff.com, krdroy@hotmail.com
Abstract
In the fast changing economic scenario world over, the economic strength of any company depends on the managements ability in improving quality, cutting production costs and providing better customer services to compete effectively in the global market. Even though every management aims at improving the productivity, there is a limitation on the part of various production facilities located in any plant as they cannot be stretched beyond a point. However, management can exploit the existing facilities to the maximum extent possible by introducing the latest state of art technology. Against this backdrop, present production scenario of a local integrated steel plant is described. The key variables considered for the simulation of steel plant production activities are: production of hot metal, liquid steel, prime blooms, bar mill products and wire rod products over a period of 20 years from 1994 to2013. The results obtained from the SD modeling are validated. Further, the model is utilized to explore alternative policies, which have been compared for their relative effectiveness.
This paper is about a group model building project at the Ministry of Justice in the Netherlands. The aim of the model is to gain insight into the combined effects of an increase in the case load and investments in different phases of criminal justice administration and contextual developments such as increased complexity of cases. A group of representatives from the police force, public prosecution, courts and sentence execution participated in constructing the model from January to August 2004. In this paper we report on reasons for starting the modeling effort and the process of model construction. We then compare the procedure followed to scripts small parts of modeling process that have been tested out in practice and serve as standard building blocks for a group model building project. Scripts specify a technique, the situations for which it is suited and the expected results, enabling a modeler to choose from the wide variety of available modeling techniques. By describing the process followed in this case and consistently relating it to well-established practices we hope to further clarify the modeling process, by contributing to the existing body of modeling techniques and the dissemination of process insights.
This paper is aimed at formalizing and testing a model for explaining the relations among supply chain design decisions (i.e. sourcing strategies, number of network stages, nodes capacity and localization) and the need for collaboration between the nodes of pull-based supply chain. As a consequence, a causal diagram which depicts such relations is built and its validation is performed by means of simulation techniques and statistical analyses (ANOVA and linear regression). In particular, since the magnitude of the relations is out of the scope of the paper, the validation is done in relative terms. The results obtained by running the simulation model of the supply chain which represents the base case are compared with the outputs of the models which simulates the original logistic network modified according to the above mentioned supply chain design elements. The statistical analyses allow the majority of the relations of the proposed causal diagram to be actually validated.
This paper examines the rising competition between computational and dynamic conceptualizations of complexity in economics. While computable economics views complexity as something rigorously defined based on concepts from probability, information, and computability criteria, dynamic complexity is based on whether a system endogenously and deterministically generates erratically dynamic behavior of certain kinds. One such behavior is the phenomenon of emergence, the appearance of new formes or structures at higher levels of a system from processes occurring at lower levels. While the two concepts can overlap, they represent substantially different perspectives. A competition of sorts between them my become more important as new, computerized market systems emerge and evolve to higher levels of complexity of both kinds.
Tuna ranching is a value-added economic activity along the coast of Baja California in Mexico involving the live capture and transport of migrating juvenile bluefin tuna to pens located near shore, where they are fed for a period of months then harvested and shipped fresh for the high-end sushi market, which is centered in Japan but expanding elsewhere. Ranching is nested within the entire global tuna fishing and processing business. Little is known outside the industry about the functioning of Mexican tuna ranching, which differs in important ways compared to its Australian and Mediterranean counterparts, and does not involve the harvest of reproducing age animals. Our analysis and exploratory modeling exercise identify several factors and issues that merit closer examination. A feedback perspective can shed light on whether Mexican ranching activities have the potential to become sustainable.
This paper describes a recent activity where scholars from two disciplines met to consider possible systemic causes of repeating failure during a three-decade long IT modernization project in the US government. From the system dynamics perspective, the problem appears to be related to a dynamic and repeating management failure with an embedded project management model. We decided to use a simple project model to develop this perspective. Our initial attempt shows some of the anticipated dynamics of project escalation. More important, though, was the discussion of the problem itself that was launched by the use of a formal model. We believe that this approach has provided insight into how to approach a more focused and grounded analysis of the problem domain.
We argue that it is possible to explain much of the history of the worlds shipping markets since 1950 as the interaction of two balancing feedback loops: a capacity adjustment loop which creates a 20-year wave, and a capacity utilization adjustment loop which generates a 4-year cycle. We show how this insight has been used rather successfully since the early 1980s for practical forecasting of turning points in the shipping market 1 - 4 years ahead of time. The basic mechanisms in the shipping system create a strong deterministic backbone which is visible through the exogenous noise, and hence predictable with useful precision. Our experience leads to a number of questions concerning system dynamics best practice, for future research.
The paper argues that current world developments are starting to resemble the "pollution crisis" scenario in The Limits to Growth book from 1972. Ongoing global warming increasingly demonstrate the reality of two major structural assumptions in the Limits to Growth models: namely 1) long reaction delays from pollution levels to corrective action, and 2) self-reinforcing feedback from the pollution level to pollution absorption time, and back to the pollution level. If left unchecked, these mechanisms could generate a climate crisis in the 21st century. The paper seeks to highlight the strength in high level system dynamics conceptualization.