Ijtra130523

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 1, Issue 3 (july-August 2013), PP. 68-75

IMPROVEMENT OF SUPPLY CHAIN MANAGEMENT BY MODEL ANALYSIS R.K.VERMA, K.M.MOEED, K.G.SINHA Department of Mechanical Engineering Integral University, Lucknow, India

Abstract—This paper analyses the case of any production system by making a model for the existing or a new industry we can analyze the different aspects of manufacturing and then by using various techniques we can minimize the flow from one end to another end so that the lead time decreases and productivity increases. Index Terms—supply chain management, productivity, model analysis. (key words)

I. INTRODUCTION Simulation models are used in evaluating supply chain configuration decisions because of their ability to represent the problem realistically and to capture a wide range of factors. They can also be applied to select the most appropriate configuration Trends of supply chain management have increasingly influenced independent companies or autonomous divisions along the supply chain to move away from adversarial towards cooperative arrangements. These trends stem from several driving forces on both the demand and supply sides of the chain. There are two key driving forces on the demand side, namely globalisation and mass customisation. Globalisation provides plentiful opportunities to multinational firms to capitalise on economies of scale and scope in research, product development, and manufacturing. Further, they can expand their operations to capture increasingly similar demands of end users for global products. To tap these potential opportunities, they must deal with logistics problems such as long delivery lead times, outsourcing vendors who are located on a different side of the globe, complex transportation costs, high buffer stock, and complex transaction costs including tax and foreign exchange. II. LITERATURE REVIEW Simulation models are used in evaluating supply chain configuration decisions because of their ability to represent the problem realistically and to capture a wide range of factors. They can also be applied to select the most appropriate configuration from a limited set of alternative configurations. Existing models representing configuration, related issues are grouped according to the simulation-modelling approach used namely, process-oriented simulation, object-oriented

simulation, and agent-oriented simulation. We discuss these below. A. Process-Oriented Models A simulation model is described by a sequence of processes initiated by events occurring in the system. This approach is attractive from the model- integration point of view. Supply chain process models can be transformed into simulation models. Bowersox (1972) presents an early study on application of simulation for long-term distribution planning. The model consists of standardized nodes representing manufacturing plants with adjacent warehouses, distribution centres, consolidated shipping points, and demand units. In the case studies reported, simulation is used to evaluate several preconfigured supply chain design alternatives. Decisions to be made include capacity expansion and location of new facilities. The author indicates that data availability and complex model building are major obstacles for widespread use of simulation in supply chain management. The business process orientation is adopted by Van der Vorst et al. (2000). The supply chain is defined as consisting of multiple business processes governed by design variables, defined as configuration level and operational level. Thus, a simulation model is used for decision-making in both strategic and operational decisions. The business process modelling formalism used is Petri-nets, which are often considered over other process and network modelling methods because they are based on sound theoretical principles and enable some analytical evaluation. Strategic and operational supply chain design decisions to be made are identified following the principle that supply chain performance can be improved by reducing the impact of various sources of uncertainty. Configuration-related decisions are implementation of real-time inventory management information systems and reallocation of some of the supply chain management functions. The supply chain performance is evaluated for numerous scenarios, where each scenario is characterized by a set of design variables with specified values. It is reported that the adoption of decisions made on the basis of simulation modelling has resulted in major performance improvements. Petri-nets also have been used for simulation of the manufacturing supply chain by Dong and Chen (2001).Ganeshan et al. (2001) simulate the performance of a retailing supply chain. The simulation model takes the supply

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