Maintaining military aircraft in a high state of readiness requires a non-stop flow of spare parts. These replacement parts can either be new parts from procurement or repaired parts coming from overhaul. The cost of these replacement parts is a major component of total lifecycle operating and sustainment costs. Improvements in reliability can potentially reduce removals and these on-going costs. The overall cost reduction depends upon the interaction over time of any increase in the cost of the new improved part, the increase in reliability, changing demand levels and the role of overhaul. Three overhaul scenarios are examined for cases of improved reliability: (i) old parts improved in overhaul; (ii) old parts not improved in overhaul; and (iii) no overhaul. A system dynamics supply chain model including financial performance metrics is developed to investigate these scenarios through simulation. It is shown that all three scenarios reduce total lifecycle costs and that these reductions can be very significant. The first overhaul scenario is shown to have the greatest returns but the third scenario is only slightly lower. All scenarios are shown to have diminishing investment returns and share a common level of investment that maximizes the percentage reduction in lifecycle costs.
Doing more with less has become a long-running and recurring theme across the globe. Affordability is now a key metric for operations and sustainability, and reliability is now seen as a key driver of these lifecycle costs. A system dynamics model has been developed of an aviation supply chain that enables evaluation of alternative cases in which investments are made to improve reliability, lower total demands, and reduce spending on new procurement and overhaul over the lifecycle. It is shown that the payback potential of an investment depends upon annual demand for the part, cost of the part, percent improvement in reliability achieved, and any increase in cost of the part due to the re-design. The analysis show that returns can be high and payback periods can be fast, particularly for investments to improve reliability of items with high demand and high cost. The research also indicates that close coordination is needed between program management, procurement planning and acquisition in order to fully realize savings. Ongoing research is developing reliability investment strategies and estimates for lifecycle costs under differing demand, manufacturing and overhaul scenarios.
The near meltdown of the world financial system led in almost all OECD countries to a sharp economic downswing. Even though there are signs for a recovery the political leaders have to cope with another problem: the steep increase in national debt. The increase is due to the automatic stabilizers (decline in tax revenues increase in transfers) but also to discretionary spending in order to stimulate the economy. Public, politicians and media talk of a debt crisis because they have doubts that an upswing will lead to a symmetric decrease in national debt. This paper analyzes the dynamics of government debt and demonstrates that economic shocks may have, in fact, long lasting effects with respect to the debt process.
A system dynamics model is proposed to analyze the impacts of transportation infrastructure investment on the tourism development of Xidi and Hongcun World Heritage Villages in southern Anhui province, China. It is shown that both the short and long term impacts of transportation infrastructure investment on tourism development could be well predicted by the model. To achieve maximum tourism revenue, both villages attempt to take an aggressive strategy to continuously increase transportation infrastructure investment and exploit all available land. According to the scenarios results from the simulation, several other development strategies are proposed as well as the prediction of the perspective of the two villages 20 years later: with all available land being exploited, the sites are still full of tourists that are comprised mainly of mass tourists.
Recent periodical boom and burst of house price have made mortgage lending issues become the main public interest in Korean real estate market. However, because mortgage-lending issues had not been discussed until then, housing market forecasting associated with mortgage lending has been difficult while using an empirical approach. Thus, comprehensive and systematic approach is required as well as validity of mortgage lending policies should be evaluated. In this regard, this research conducts a sensitivity analysis to validate the proposed policies and estimates the effects of current policies on LTV and DTI ratios with a comparison of another policies scenario. A causal loop and sensitivity analysis using system dynamics confirmed that LTV and DTI regulation is strong clout to housing market. However, to prevent transfer of potential mortgage borrowers to nonmonetary institutions, regulations in loans of nonmonetary institutions should be practiced in accompaniment with regulations of primary lending agencies.
The behavioural method is an important technique for identifying the dominant feedback loops for a variable of interest. The core mechanism of this approach is that deactivating different loops influences the behaviour of the selected variable to various degrees. Through assessing the variance of the behaviour between the reference model and the modified model for all feedback loops, we are able to identify the loops which exert the most significant influence on the variable, i.e., the dominant loops. An important step in the behavioural method is to deactivate a loop by fixing its control variable or a unique edge. However, a drawback is where neither the control variable nor the unique edge is identified. This paper presents another loop deactivation method which is applicable when such circumstance happens. The new method deactivates a loop by modifying its unique consecutive two edges which are able to distinguish this loop from other loops. The long wave model is used to demonstrate the loop deactivation approach and compare the analysis result with other dominant loop identification methods.
Formal analysis plays an important role in understanding how feedback structures drive dynamical behaviour. As we know the state behaviour is determined by a linear combination of behaviour modes (associated with eigenvalues). The weight of each mode is a product of a coefficient and a right eigenvector component. An emerging technique in eigen-based analysis focuses on the behaviour mode weight, together with the behaviour mode (eigenvalue), to identify the dominant feedback structure. The purpose of incorporating the weight analysis is to conduct an overall assessment of how feedback structure influences on the state behaviour. This paper revises the conventional eigensolution to the state trajectory by alternating the behaviour mode coefficient to be a product of the normalized left eigenvector, and the system initial conditions. Therefore, the overall behaviour changes due to the changes in a system element (a link or a pathway) can be fully assessed by calculating the eigenvalue, right and left eigenvector sensitivities. Through studying the eigenvector sensitivity, we observe that the right and left eigenvector sensitivities associated with the same mode cannot be evaluated separately. We present an analytical approach to the eigenvector-related sensitivity computation, i.e., a linear combination of the right and left eigenvector sensitivity.