Supply chain simulation tools and techniques. International Journal of Simulation and Process Modelling. In order to have good supply chain design there is a need to understand how the available tools can be used for modelling and simulating any alternative designs and strategies in supply chain systems. This unit introduces. In this paper we present an application dedicated to modelling and simulating Supply Chain systems. The simulator application, with its various tools for automatically. For Supply Chain Modelling and Simulation. Optimizing Your Supply Chain: A Model Approach. By Leslie Hansen Harps. No tags available. A wide array of technological tools are just the do- it- yourself kit companies can use to model, then optimize, their supply chains. Applying the information you get by using the right supply chain modeling tool can help squeeze cost and inventory out of your supply chain while improving service to customers. Yet, while some companies do an excellent job of modeling their supply chains, others have barely tapped the potential for improvement. Similarly, companies in process industries, such as paper and beer manufacturing, . But they're getting increased attention because of their lower cost and greater capability, coupled with companies' quests for improved supply chain performance. A variety of modeling tools are available today. Deciding which type is right for you begins with understanding the environment in which you work and how often you need to change your supply chain, Lapide says. Dynamic environments—which may experience numerous new product introductions, have products with short life cycles, or use segmented customer fulfillment with multiple service levels, lead times, and fulfillment methods—require more frequent supply chain reconfiguring. Companies that model their supply chains once every three years or so may want to tap a third party's modeling technology and expertise. Saturn Service Parts Operations (SPO) has gotten excellent results leveraging third party modeling capabilities. The company turned to Wharton Business School several years ago to model its supply chain, taking into account variables such as inventory, facility, labor, and transportation costs. Saturn manages inventory for its 4. But the high cost of outbound transportation did not. So Saturn turned to Schneider Logistics, its third- party logistics provider, for modeling help. Saturn also looked at integrating its traffic with that of General Motors Service and Parts Operations (GMSPO), which also uses Schneider Logistics. GMSPO and Saturn have customers in many of the same cities, and in some cases were running duplicate routes. Today, Saturn is nearly two- thirds of the way to converting its transportation to the dedicated delivery system it shares with GMSPO. Close to 8. 7 percent of Saturn's parts volume is shipped through the dedicated delivery system. Saturn retailers receive replacement orders from the Spring Hill DC twice a week. Orders for a group of retailers are shipped as a line haul to the carrier's regional interline facility (located next to the 1. The second objective is to provide a decision making tool for supply chain management. A STUDY ON REORDER POLICIES FOR PERISHABLE FOOD PRODUCTS Marta Rinaldi(a). Supply chains and logisticsView Other. It’s difficult to maintain efficiency in managing your supply chain without new. There's no doubt the right simulation and modelling tool was selected for the majority of. The objective with the SCOR template is to create an easy to use, graphical interface for simulation modelling, and analysis of supply chains. Using graphics, easy drag and drop functionality and a set of predefined generic. What is supply chain simulation? Simulation enables an organization to analyze and experiment with its existing supply chain process in a virtual. FlexSim also gives decision makers the tools to confirm their. SELECTION OF SIMULATION TOOLS FOR IMPROVING SUPPLY CHAIN PERFORMANCE. Supply chain modelling approaches typically fall. GM parts distribution centers). Then they're broken down by route, shipped to the GM parts distribution centers, loaded with the GM freight, and delivered to the retailer. The shared delivery model has improved service to retailers—especially those in remote locations—and enhanced tote pickups and returns. Modeling 1. 01 Models—which may take the form of a mathematical program or simulation—can be used at the strategic, tactical, or executional level, looking at such factors as demand, distribution networks, transportation routing, or warehouse operations. Gue, associate professor of logistics, Graduate School of Business and Public Policy, Naval Postgraduate School, Monterey, Calif. They don't have a lot of good technology support, so they end up building buffers of inventory. Optimization tools can be used . The cost of these may run into the hundreds of thousands of dollars. Simulation tools using what- if concepts are more tactical, simulating plant or warehouse operations, for example. These are less expensive. PC- based simulation tools may cost in the tens of thousands. A new type of tool is the inventory optimizer, which focuses on . These tools are gaining popularity as companies look for new ways to minimize inventory. As with inventory optimization, logisticians often use competing objectives, such as maximizing service levels while minimizing cost. These situations call for optimization tools that can incorporate a multi- criteria decision- making structure, Gue says. By considering the relative importance you've specified for service and cost, for example, the system identifies the answer that best satisfies the objectives, based on the tradeoffs. A model may . The solution has to be feasible, and respect the constraints of your supply chain. Deterministic vs. Stochastic Models can be deterministic or stochastic, depending upon whether uncertainty is built into the model. So the actual demand has some sort of distribution underlying the average of 4. Incorporating probabilities such as these into models can be . Heuristic approaches are common in everyday life. Imagine assembling a jigsaw puzzle. We often shortcut the puzzle- building process by finding all the edge pieces first to build a frame for our solution. This is a heuristic solution. Unlike heuristic programs, mathematical programs are not iterative. This advanced planning system, a key component in the company's customer- centered supply chain program, enables Agere to improve its performance significantly, reports Andy Micallef, vice president of supply chain management for the Allentown, Pa.- based company. Despite a down market, inventory turns have increased from six to eight a year. Shipping performance—against original acknowledgement date—has jumped from mid- 6. Micallef says. That's just the beginning, as Agere begins to leverage visibility and real- time data to implement a breakthrough supply chain model. Agere's move to daily planning was driven by its desire to provide customers with better service and the ability to carry less inventory. This can slash the order cycle by as much as one week. Two information systems enable the change to daily planning: 1) Agere's proprietary enterprise system solution, Total Order Management, which ties into the company's factory schedule system and Oracle ERP, and. Access database with Excel spreadsheet tools, co- developed by Agere and Lehigh University's Department of Industrial and Systems Engineering. It also looks at the forecast. Take the customer whose demand is shown in Figure 1. Even though demand looks tightly distributed, . The weighted average change is 1. Agere currently performs this analysis quarterly for its top strategic customers, then builds to demand and buffer on a daily basis. Agere's staff of supply chain planners in Allentown, Pa., begin their mornings reviewing system- generated daily move plans for individual products and specific technologies. Changes might be caused by such factors as data integrity issues, capacity constraints, or new products. Planners have several hours to make changes in the move plan, then all the data is gathered into an integrated execution plan for Agere's wafer fab facilities and packaging/test factories in Asia. The supply chain staff reviews each day's actions. All partners in the supply chain will work toward the same set of intentions simultaneously. Instead of each supply chain partner maintaining an inventory buffer, the buffer will be statistically sized and located. The new model will thus minimize volatility, lead time, and inventory, enabling Agere to deliver improved service while lowering costs. Agere is just beginning to implement this new breakthrough supply chain model. Accenture's Kiron Shastry thinks so.
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