Development of a dynamic simulation model for inventory level optimization through supply chain

System dynamic is an approach to understanding the behavior of complex systems over time. Current research on system dynamics modeling in supply chain management focuses on inventory decision and policy development, time compression, demand amplification, supply chain design and integration, and international supply chain management. Less attention has been devoted on the inventory level improvement with fuzzy demand controller in dynamic simulation model. This study is aimed to consider customer demand fluctuation to improve the finished goods inventory level of Electronic Company by using dynamic simulation model. Dynamic and changes in demand and corresponding excess during time through the product life is considered as serious problems in supply chain. Data collection and analysis have been considered to find the current problems of the company. Dynamic model has been constructed by ITHINK software to represent the inventory level of company. The stock and flow diagrams are become visible to represent the structure of a system with more detailed information. Three different variables have been applied in Fuzzy controller to give the better level of inventory by MATLAB SIMULINK. Generated results have been compared by current company inventory level in ITHINK software and the best alternative was selected to suggest the company management

Sexismo en "digimon": Quince años de inmovilismo

Este artículo científico tiene como objetivo realizar un análisis descriptivo sobre el sexismo que mantiene una popular serie japonesa de dibujos animados, “Digimon”. Este programa fue emitido por primera vez en España en el año 2000 y en la actualidad sigue transmitiendo la imagen tradicionalista de los roles sexuales a todos los niños que siguen ese programa. Para poder afirmar lo dicho, se han comparado las principales características personales que la serie otorga a cada uno de sus protagonistas en función de su sexo y las metas que han logrado en las dos primeras temporadas de esta longeva serie, con el nuevo material audiovisual que se ha presentado en el año 2015; junto a un análisis denotativo de los adjetivos calificativos que los protagonistas humanos de la serie usan en cuatro capítulos escogidos al azar de la primera temporada y de los primeros cuatro capítulos de su última temporada. Las conclusiones son claras; tanto en el nuevo como en el viejo material, los protagonistas varones y sus acompañantes representan los estereotipos sexuales masculinos típicos: fuerte liderazgo e importancia de la valentía y fortaleza; mientras que las mujeres, representan los roles sexuales femeninos clásicos: actitud sumisa respecto el líder grupal, gran capacidad de autosacrificio o demostrar afecto por los demás

Development of dynamic simulation model for inventory level optimization through supply chain

System dynamic is an approach to understanding the behavior of complex systems over time. Current research on system dynamics modeling in supply chain management focuses on inventory decision and policy development, time compression, demand amplification, supply chain design and integration, and international supply chain management. Less attention has been devoted on the inventory level improvement with fuzzy demand controller in dynamic simulation model. This study is aimed to consider customer demand fluctuation to improve the finished goods inventory level of Electronic Company by using dynamic simulation model. Dynamic and changes in demand and corresponding excess during time through the product life is considered as serious problems in supply chain. Data collection and analysis have been considered to find the current problems of the company. Dynamic model has been constructed by ITHINK software to represent the inventory level of company. The stock and flow diagrams are become visible to represent the structure of a system with more detailed information. Three different variables have been applied in Fuzzy controller to give the better level of inventory by MATLAB SIMULINK. Generated results have been compared by current company inventory level in ITHINK software and the best alternative was selected to suggest the company management

System dynamics-based modelling and analysis of greening the construction industry supply chain

Increasing concern on global warming and corporate social responsibility have made environmental issues an area of importance to address for governments and businesses across the world. Among the Middle East countries, the United Arab Emirates (UAE) tops the list in terms of per capita energy spending and per capita carbon footprints. The construction industry is the major contributor to environmental pollution due to its size and nature of activity. The rapid growth of construction sector has a significant environmental impact with increase in carbon footprints. This paper analyses the environmental implications of the rapidly growing construction industry in UAE using system dynamics approach. Quantitative modelling of the construction industry supply chain helps to measure the dynamic interaction between its various factors under multiple realistic scenarios. The potential carbon savings and the impact of each factor are calculated using scenario development analysis. The paper has addressed in detail the various drivers and inhibitors of carbon emission in the construction industry supply chain and ways to evaluate the carbon savings. The paper provides an analytical decision framework to assess emissions of all stages applicable to the construction industry supply chain

The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain

We investigate a three-echelon manufacturing and remanufacturing closed-loop supply chain (CLSC) constituting of a retailer, a manufacturer and a supplier. Each echelon, apart from its usual operations in the forward SC (FSC), has its own reverse logistics (RL) operations. We assume that RL information is transparent to the FSC, and the same replenishment policies are used throughout the supply chain. We focus on the impact on dynamic performance of uncertainties in the return yield, RL lead time and the product consumption lead time. Two outcomes are studied: order rate and serviceable inventory. The results suggest that higher return yield improves dynamic performance in terms of overshoot and risk of stock-out with a unit step response as input. However, when the return yield reaches a certain level, the classic bullwhip propagation normally associated with the FSC does not always hold. The longer remanufacturing and product consumption lead times result in a higher overshoot and a longer time to recover inventory, as well as more oscillation in the step response at the upstream echelons. We also study bullwhip and inventory variance when demand is a random variable. Our analysis suggests that higher return yield contributes to reduced bullwhip and inventory variance at the echelon level but for the CLSC as a whole the level of bullwhip may decrease as well as increase as it propagates along the supply chain. The reason for such behaviour is due to the interaction of the various model parameters and should be the subject of further analytical research. Furthermore, by studying the three-echelon CLSC, we produce a general equation for eliminating inventory offsets in an n-echelon CLSC. This is helpful to managers who wish to maintain inventory service levels in multi-echelon CLSCs

COMBINING SUSTAINABLE VALUE STREAM MAPPING AND SIMULATION TO ASSESS MANUFACTURING SUPPLY CHAIN NETWORK PERFORMANCE

Sustainable Value Stream Mapping (Sus-VSM) builds upon traditional VSM to capture additional sustainability aspects of the product flow, such as environmental and societal aspects. This work presents research to expand the utility of Sus-VSM to supply chain networks, develop a general approach towards improving supply chain sustainability, and examine the benefits of implementing simulation and a design of experiments (DOE) style analysis. Metrics are identified to assess economic, environmental, and societal sustainability for supply chain networks and visual symbols are developed for the Supply Chain Sus-VSM (SC Sus-VSM) to allow users to easily identify locations where sustainability can be improved. A discrete event simulation (DES) model is developed to simulate the supply chain, allowing easier creation of future state maps, which are used to identify locations for sustainability improvement. A scoring methodology and DOE-style analysis are developed to collect more information from the supply chain. Results from the case study show that the SC Sus-VSM meets the goals desired, and that the DES model aids the goals of the map. It is also indicated that interventions in the supply chain should first focus on economic improvements, followed by societal and then environmental improvements to achieve the greatest supply chain sustainability

The application of discrete event simulation and system dynamics in the logistics and supply chain context

Discrete event simulation (DES) and system dynamics (SD) are two modelling approaches widely used as decision support tools in logistics and supply chain management (LSCM). A widely held belief exists that SD is mostly used to model problems at a strategic level, whereas DES is used at an operational/tactical level. This paper explores the application of DES and SD as decision support systems (DSS) for LSCM by looking at the nature and level of issues modelled. Peer reviewed journal papers that use these modelling approaches to study supply chains, published between 1996 and 2006 are reviewed. A total of 127 journal articles are analysed to identify the frequency with which the two simulation approaches are used as modelling tools for DSS in LSCM. Our findings suggest that DES has been used more frequently to model supply chains, with the exception of the bullwhip effect, which is mostly modelled using SD. Based on the most commonly used modelling approach, issues in LSCM are categorised into four groups: the DES domain, the SD domain, the common domain and the less common domain. The study furthermore suggests that in terms of the level of decision making involved, strategic or operational/tactical, there is no difference in the use of either DES or SD. The results of this study inform the existing literature about the use of DES and SD as DSS tools in LSCM