To gain a competitive advantage, businesses are applying simulation to supply chain management (SCM). The path to the logical combination of SCM and simulation tools can be understood by the strategies employed by businesses over the past 20 years. The following table lists the area of strategic focus and tools used to effect improvement.
| Period | Focus | Tools |
|---|---|---|
| 1980s | Raw material in, Finished goods out | Simulation |
| Early 1990s | Improve shipping of finished goods | Analytical tools |
| Mid 1990s | Flow of material from supplier to end user | SCM tools |
| Currently | Supply Chain | SCM and Simulation |
In the 1980s, businesses looked beyond manufacturing to the beginning and ending processes to improve operations. Applications of simulation involved shortening the raw material delivery time from the supplier to the manufacturer and shipping the final product to the customer. In the early 1990s, increased competition forced businesses to decrease the shipping time of finished goods to the end user. Tools were designed to specifically address the logistics surrounding shipping. By mid 1990, businesses began to look at the flow of material from vendor to manufacturer to customer. To deal with these issues, companies developed SCM packages which incorporated and automated analytical tools such as linear programming and scheduling, algorithms, and processes such as inventory control systems. Now, businesses are realizing that vital information can be gained by employing both simulation and supply chain management. This recent marriage has enabled businesses to evaluate both variability and the interdependency of the components in the supply chain [1, 2].
One of the most difficult aspects of a business to manage is the supply chain. The supply chain consists of a network of suppliers, production and manufacturing processes, warehousing and distribution methods, and customers. In the past, efforts to improve the balance between costs and meeting customer demand have involved the separate analysis of each supply chain component. What has been lacking in this analysis is the relationship between the components and how these relationships contribute to the effects of change. Simulation software that incorporates SCM tools function to determine the interdependency of the system constraints that minimizes costs, maximizes profits, and meets customer demand. Secondly, supply chain simulation allows analysis of the impact of uncertainty, such as the effects of bottlenecks at different points in the supply chain. Thus the main goal of the supply chain simulation model is the formulation of a system capable of withstanding variability and shifts in customer demand. By predicting the reaction of the supply chain to operational disturbances, businesses have increased capability of managing the delivery of finished products to customers [1, 2]. Although in relative infancy, the coupling of simulation and supply chain management poses to become a necessary ingredient in the design suite of any business.
With the ensuing transformation of businesses into e-businesses, the impact of the Internet will dwarf that of other trends such as strategic alliances and globalization. As businesses emphasize supply chain management, the convergence of the supply chain and the Internet produces the e-value chain, where suppliers, manufacturers, shippers, distributors, and customers share real-time information regarding the delivery of product [3]. The Internet increases the number of alternatives in supplying raw materials to production processes to shipping product by connecting networks of suppliers, shippers, and distributors through shared information such as inventory, customer demand, and shipping times. This e-value chain is more dynamic in the sense that the best supply chain is the network of components that responds the quickest and least costly way to changes in customer demand.
The role of simulation in this convergence should be important in terms of the various networks that will form within the supply chain. Simulation will play an important role in investigating the different e-value chains possible. In order to play this role, new methods of analyzing simulation output and multiple alternatives will be necessary. One emerging technique employs simulation-optimization in which the supply chain is modeled using simulation software, and algorithms are applied to the model to find the best alternative among multiple alternatives. The major drawbacks to this new technology are that relatively few businesses have the appropriate resources or personnel to use this tool, and a significant amount of time may be necessary for the software to find the best alternative [4].
The difficulty in modeling human behavior rivals that of modeling the supply chain. Despite this difficult task, another emerging application of simulation involves the ergonomics of the work environment. Software tools are available that determine whether or not the worker will physically fit in the designed work environment, and analysis of the work operations may be broken down into motion and cycle time data [5]. Adding this application to that of modeling the supply chain promises to elevate the importance of simulation in running a competitive business.