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Long-term trend of electric vehicle sales in Thailand

Chinda Thanwadee

Engineering Management in Production and Services

2022

Vol. 14, no. 1

13--25

This research study aims at examining the long-term trend of EV sales in Thailand, utilising the system dynamics (SD) modelling approach. This approach is commonly used to model complex systems with causal relationships among key factors within the system. The developed SD model consists of five key factors affecting electric vehicle (EV) sales, namely, the environment, economy, charging infrastructure, government support, and battery maintenance. The simulation results show the increase in EV sales by ten times in the next 20 years with implementation plans related to the five key factors. The government support factor is the most important in enhancing EV sales in the short term. Several government support plans should be initiated to attract more EV consumers, such as subsidies and tax reductions. The environment and charging infrastructure factors are crucial to increasing EV sales in the long term. The enforcement of the CO2 tax and the provision of charging stations all around the country should be established to achieve a sustainable EV market in the long term. This research study contributes to the Thai government and automotive industry to better understand the complex relationships among key factors affecting EV sales. The related sectors may use the study results to plan for EV campaigns to promote the use of EVs and achieve a sustainable EV market.

System dynamics as a decision support system for machine tool selection

Adane T. F., Nicolescu M.

Journal of Machine Engineering

2016

Vol. 16, No. 3

102--125

The worldwide competitive economy, the increase in sustainable issue and investment of new production line is demanding companies to choose the right machine from the available ones. An improper selection can negatively affect the overall performance of the manufacturing system like productivity, quality, cost and companys responsive manufacturing capabilities. Thus, selecting the right machine is desirable and substantial for the company to sustain competitive in the market. The ultimate objective of this paper is to formulate a framework for machining strategy and also provide methodology for selecting machine tool from two special purpose machine tools in consideration of interaction of attributes. A decision support system for the selection of machine tool is developed. It evaluates the performance of the machining process and enhances the manufacturer (decision maker) to select the machine with respect to the performance and the pre-chosen criteria. Case study was conducted in a manufacturing company. A system dynamics modelling and simulation techniques is demonstrated towards efficient selection of machine tool that satisfy the future requirement of engine-block production.