Amit Mittal al. International Journal of Research Aspects of Engineering and Management ISSN: 2348-6627, Vol. 1, Issue 2, June 2014, pp. 26-30 © 2014 IJRAEM All Rights Reserved 26 Approach of BPEL in supply chain activities for managing Bullwhip effect of SCM system Amit Mittal 1 , Kamal Kumar Sharma 2 , Surjeet Dalal 3 1 Student, M. Tech, ESSEAR, Ambala 2 Professor, Dept. of ECE, E-Max group of Institutions, Ambala 3 Assistant Professor, Dept. of CSE, E-Max group of Institutions, Ambala Abstract—Intending to provide quick, efficient and effective sharing of resources across different organizations with the context of Supply Chain Management, Orchestration Engine and various web services are involved. In this research work, the proposed model using Orchestration Engine for Supply Chain Management supports supply chain consists of all parties involved, directly or indirectly, in fulfilling a customer request. Existing technologies and tools such as Electronic Data Interchange (EDI) infrastructures and Enterprise Resource Planning (ERP) systems do not provide a flexible and reusable solution to information sharing and application integration. The concept of Orchestration is truly nothing new fangled, however it's assessment as an enterprise resource is, and it's obviously the driving force following the value of a Service Oriented Architecture. The orchestration is the capability to organize how information flows and services interrelate to form solutions, processes actually, alive between dozens sometimes hundreds of systems, within and between enterprises. The concept of Business Process Engineering Language (BPEL) is being utilized to design the orchestration engine for the SCM. The Eclipse BPEL designer is being used to construct this engine for the supply chain management systems. Leveraging web service and web portal technologies, that have been developed a prototype web service system to facilitate communication, integration and collaboration among project participants in construction supply chains. Keywords— BPEL, Bullwhip effect, Supply chain, cloud computing I. INTRODUCTION Forrester (1961) has been the first to identify the phenomenon of oscillating and amplifying order behavior upstream of supply chains and its effects on inventories, capacity utilization and other operational parameters [1]. While Lee et al. (1997) first introduced the term ―bullwhip effect‖ to explain this phenomenon; it was first described by Forrester (1961) to demonstrate the demand and variance amplification in an industrial system. His idea has been studied further and illustrated through the ‗‗Beer Distribution Game‘‘ -a simulation based teaching tool to explain the economic dynamics of stock management problem (Sterman, 1989). Lee et al. (1997) identified the following four reasons for the bullwhip problem: 1) demand forecast updating, 2) order batching, 3) price fluctuation, and 4) the rationing and shortage game [3]. The first time the bullwhip effect was evident in an industrial company in the supply chain of Procter & Gamble‘s diaper products. Its sales at retail stores were fluctuating, but the variability‘s were certainly not excessive. However, as they examined the distributors' orders, the executives were surprised by the degree of variability. When they looked at P&G's orders of materials to their suppliers, such as 3M, they discovered that the swings were even greater. At first glance, the variability‘s did not make sense. While the consumers, in this case, the babies, consumed diapers at a steady rate, the demand order variability‘s in the supply chain were amplified as they moved up the supply chain. P&G called this phenomenon the "bullwhip" effect. (In some industries, it is known as the "whiplash" or the "whipsaw" effect.) [2]. Figure: 1. Orders Vs Sales II. BULLWHIP EFFECT AND ORDER FLUCTUATIONS The four factors that cause the bullwhip effect are 1) demand forecast updating, 2) order batching, 3) price fluctuation, & 4) the rationing and shortage game. These will be described briefly in the following: a) Demand forecast updating: When performing demand forecasts, companies interpret historical order information and update them regularly. This order information from customers, however, does not directly reflect actual demand. This information is used to determine supply requirements as a function of historical demand information, service level policies, and lead times in order to satisfy future demand and safety stocks. The further upstream in the supply chain forecasts are conducted through the more their variability increases, because longer lead times require higher safety