An Effective Lean Supply Inventory ManagementModel using VMI HubGuide Words: Supply chain, lean, supply inventoryAbstract: This paper describes an effective lean supply inventory management model using VMIhub for electronics industry. For a complex supply chain system, it is desired a lean supply inventorymanagement approach with simplicity and efficiency. The key elements of such a system areidentified as suppliers, VMI hubs, and factories. This paper firstly compares the two supply inventorymodels and explains the benefits of the model with VMI hub. Then the two key processes of the leansupply inventory model with VMI hub are further discussed, i.e. the kit-to-line process between aVMI hub and factories and the JIT suppliers pull process between suppliers and the VMI hub. Finallythe pilot run results are shown to suggest significant performance improvements in terms inventorysavingsand cycletimereductions.L.INTRODUCTIONWhile every supply chain struggles with demand and supply uncertainties, some electronicssectors like computers and mobile devices are particularly vulnerable. Those with very short productlifecycles have the greatest risk of losing the market share and obsolescence write offs. The recurringeconomic cycles further challenge these sectors which have to deal with components shortages in peakdemand periods and inventory write offs when market downturns coincide with the product's end oflife.After years of chasing surging demand and maneuvering to secure scarce supply, OEMs foundthemselves left with over excess inventory as the market suddenly turn down. Because of the longlead times for certain components on allocation and supply chains did not scale down as readily ashoped,manufacturers werenot ableto reactquicklyenough to plummeted levels of demand.In recent years, both academicians and practitioners have shown an increasing level of interest infinding ways of matching supply with demand while maintaining minimum levels of inventoriesthroughout the entire supply chain. Several researchers have examined many theoretical, as well aspractical issues involving buyer-supplier coordination, as a means of attaining successfulimplementationof Just-In-Time(JIT)baseddecisionsystems,focusingonmaterialflows,inaneffortto minimize the supply chain costs or maximize the entire chain's profitability.A JIT supply chain should produce and deliver goods just in time to be sold, subassembly just intime to be assembled, fabricate parts just in time to go into subassemblies, and purchase materials just
An Effective Lean Supply Inventory Management Model using VMI Hub Guide Words：Supply chain, lean, supply inventory Abstract：This paper describes an effective lean supply inventory management model using VMI hub for electronics industry. For a complex supply chain system, it is desired a lean supply inventory management approach with simplicity and efficiency. The key elements of such a system are identified as suppliers, VMI hubs, and factories. This paper firstly compares the two supply inventory models and explains the benefits of the model with VMI hub. Then the two key processes of the lean supply inventory model with VMI hub are further discussed, i.e. the kit-to-line process between a VMI hub and factories and the JIT suppliers pull process between suppliers and the VMI hub. Finally the pilot run results are shown to suggest significant performance improvements in terms inventory savings and cycle time reductions. I. INTRODUCTION While every supply chain struggles with demand and supply uncertainties, some electronics sectors like computers and mobile devices are particularly vulnerable. Those with very short product lifecycles have the greatest risk of losing the market share and obsolescence write offs. The recurring economic cycles further challenge these sectors which have to deal with components shortages in peak demand periods and inventory write offs when market downturns coincide with the product’s end of life. After years of chasing surging demand and maneuvering to secure scarce supply, OEMs found themselves left with over excess inventory as the market suddenly turn down. Because of the long lead times for certain components on allocation and supply chains did not scale down as readily as hoped, manufacturers were not able to react quickly enough to plummeted levels of demand. In recent years, both academicians and practitioners have shown an increasing level of interest in finding ways of matching supply with demand while maintaining minimum levels of inventories throughout the entire supply chain. Several researchers have examined many theoretical, as well as practical issues involving buyer–supplier coordination, as a means of attaining successful implementation of Just-In-Time (JIT) based decision systems, focusing on material flows, in an effort to minimize the supply chain costs or maximize the entire chain’s profitability. A JIT supply chain should produce and deliver goods just in time to be sold, subassembly just in time to be assembled, fabricate parts just in time to go into subassemblies, and purchase materials just
in time to be transformed into fabricated parts. The JIT approach provides the right materials, in therightquantitiesandquality,justintimeforproduction.Fawcett and Birou predicted that “"future manufacturing strategies will place significant emphasison the control of purchased inventory, increasing the value of a JIT procurement system"Today'semphasis on lean manufacturing further supports the need for efficient JIT supply chains. Therefore, itis critical that JIT suppliers identify and address performance issues as effectively as possible.TheJITpurchasingmethod isanimportanttechniqueoftheJITphilosophy,whichisregardedasoneof the most important productivity enhancement management innovations.JIT purchasingadvocates smaller sized andmorefrequent orders.ThisapproachwasoriginallyexploredbyKanzleras a method for reducing inventory levels at the Fordson Tractor Plant in the 1920s [3].Early studies conducted through the 1980s, including Goyal's pioneering work, focused only onjointlot sizing and buyer-supplier coordination for a single buyer and a single supplier based on alot-for-lot approach [4]. Subsequent researchers who followed this path had advanced the notion ofintegrationthrougheithernovel lotsplitting techniques or by examining more complex structures involving multiple buyers and/orsuppliers.A major gap in the existing literature, much of which focuses on direct, two-echelonbuyer-supplier coordination, is the issue concerning procurement of materials from suppliers by themanufacturing stage, integrated with the coordinated decisions of production and distribution toretailers. In view of this gap, this paper addressed the issue in the context of a real case for electronicsindustry. It is assumed that the factory is building to orders, therefore the production schedule islinked to the product distribution and delivery plan.Againstthisbackground,theaimofthispaperistointroduceaneffectiveleansupplyinventorymanagement approach and its implementation for electronics industry.The rest of this paper will firstdescribe two supply inventory management models and explain the advantages of having a VMI hubin the system. Following the comparison of the two models, Section Ill will discuss theimplementation issues of the supply inventory model with VMI hub. Then, the pilot run results aredemonstrated and discussed.A summary of the paper and lessons learnt conclude this paper.II.COMPARISONOFTWOSUPPLYINVENTORYMODELSThe electronics supply chain under study is just like those of many multi-national companies.There are a number of factories to support the global market. Some factories are self-owned facilitiesand some are ODMs. This study is focusing on the factories cluster in Asia, which provide majority ofthe products to worldwide market. The two options of the supply inventory models are discussed inthis section, i.e. either allowing the factories to manage their own supply inventories, or consolidatingthe suppliers shipments through a VMI hub. The advantages and disadvantages of the two models arecompared, with more emphasize on the impacts on the inventory level and the delivery cycle time
in time to be transformed into fabricated parts. The JIT approach provides the right materials, in the right quantities and quality, just in time for production. Fawcett and Birou predicted that “future manufacturing strategies will place significant emphasis on the control of purchased inventory, increasing the value of a JIT procurement system”. Today’s emphasis on lean manufacturing further supports the need for efficient JIT supply chains. Therefore, it is critical that JIT suppliers identify and address performance issues as effectively as possible. The JIT purchasing method is an important technique of the JIT philosophy, which is regarded as one of the most important productivity enhancement management innovations. JIT purchasing advocates smaller sized and more frequent orders. This approach was originally explored by Kanzler as a method for reducing inventory levels at the Fordson Tractor Plant in the 1920s [3]. Early studies conducted through the 1980s, including Goyal’s pioneering work, focused only on jointlot sizing and buyer–supplier coordination for a single buyer and a single supplier based on a lot-for-lot approach [4]. Subsequent researchers who followed this path had advanced the notion of integration through either novel lot splitting techniques or by examining more complex structures involving multiple buyers and/or suppliers. A major gap in the existing literature, much of which focuses on direct, two-echelon, buyer–supplier coordination, is the issue concerning procurement of materials from suppliers by the manufacturing stage, integrated with the coordinated decisions of production and distribution to retailers. In view of this gap, this paper addressed the issue in the context of a real case for electronics industry. It is assumed that the factory is building to orders; therefore the production schedule is linked to the product distribution and delivery plan. Against this background, the aim of this paper is to introduce an effective lean supply inventory management approach and its implementation for electronics industry. The rest of this paper will first describe two supply inventory management models and explain the advantages of having a VMI hub in the system. Following the comparison of the two models, Section III will discuss the implementation issues of the supply inventory model with VMI hub. Then, the pilot run results are demonstrated and discussed. A summary of the paper and lessons learnt conclude this paper. II. COMPARISON OF TWO SUPPLY INVENTORY MODELS The electronics supply chain under study is just like those of many multi-national companies. There are a number of factories to support the global market. Some factories are self-owned facilities and some are ODMs. This study is focusing on the factories cluster in Asia, which provide majority of the products to worldwide market. The two options of the supply inventory models are discussed in this section, i.e. either allowing the factories to manage their own supply inventories, or consolidating the suppliers shipments through a VMI hub. The advantages and disadvantages of the two models are compared, with more emphasize on the impacts on the inventory level and the delivery cycle time
A.Allow a Factory to Manage its Own Supply InventoryFig.I shows a scenario of allowing an individual factory to manage its own supply inventorieswithout linkingwith otherfactories.The individualfactorywill receiveordersfromdedicated marketand react by JIT pulling of components directly from its suppliers.SupplierFactorySupplierCustomer2SuppliermPullFig.1.Afactoryto manage its own supply inventoryIn this model, the inventories of all components will be stored at the factory store room, and thefactory prefers directly pulling from suppliers based on customer orders, so that the inventory costwould be minimized. For illustration purpose, an important component is selected to study the pullingeffect between the factory and one of the suppliers.The component is one of the major components offinal products, supplied by a particular supplier.Currently,the factory places orders to suppliers in batches to offset fixed ordering costs incurredevery time an order is placed when inventory levels drop. Because suppliers and the factorybuyer-planners react to changes in conditions as they occur, they used a continuous-time approach andthe corresponding optimal policy, a (Q, R) policy, to manage the component inventories.In a (Q, R) policy, as shown in Fig.2, R denotes the reorder point and Q is the size of the orderAn order with a lot size Q is placed whenever system inventory drops to R. The reorder point R isclosely related to safety stock ss, which is catering for both the uncertainty of customer demandduring the lead time and the uncertainty of lead time itself. Assume the demand during the lead time isDL and the standard deviation of demand during the lead time is o. Specifically, safety stock is thedifferencebetweenthe reorder point and the average requirements during replenishment lead time, i.e. R = ss + DL.Further assume the demand for the component per period is normally distributed with a mean ofD and standard deviation of o,; the lead time for replenishment follows normal distribution N(L,sL)In order to evaluate the Cycle Service Level (CSL) given a lot size Q, it needs to calculate theprobability of stock-out of the component if demand during the lead time exceeds the R. A stock-outmay occur in a cycle if the demand during the lead time is more than the reorder point R. The safety
A. Allow a Factory to Manage its Own Supply Inventory Fig.1 shows a scenario of allowing an individual factory to manage its own supply inventories without linking with other factories. The individual factory will receive orders from dedicated market and react by JIT pulling of components directly from its suppliers. Fig.1. A factory to manage its own supply inventory In this model, the inventories of all components will be stored at the factory store room, and the factory prefers directly pulling from suppliers based on customer orders, so that the inventory cost would be minimized. For illustration purpose, an important component is selected to study the pulling effect between the factory and one of the suppliers. The component is one of the major components of final products, supplied by a particular supplier. Currently, the factory places orders to suppliers in batches to offset fixed ordering costs incurred every time an order is placed when inventory levels drop. Because suppliers and the factory buyer-planners react to changes in conditions as they occur, they used a continuous-time approach and the corresponding optimal policy, a (Q, R) policy, to manage the component inventories. In a (Q, R) policy, as shown in Fig.2, R denotes the reorder point and Q is the size of the order. An order with a lot size Q is placed whenever system inventory drops to R. The reorder point R is closely related to safety stock ss, which is catering for both the uncertainty of customer demand during the lead time and the uncertainty of lead time itself. Assume the demand during the lead time is DL and the standard deviation of demand during the lead time is . Specifically, safety stock is the difference between the reorder point and the average requirements during replenishment lead time, i.e. R = ss + DL. Further assume the demand for the component per period is normally distributed with a mean of D and standard deviation of ; the lead time for replenishment follows normal distribution N(L,sL). In order to evaluate the Cycle Service Level (CSL) given a lot size Q, it needs to calculate the probability of stock-out of the component if demand during the lead time exceeds the R. A stock-out may occur in a cycle if the demand during the lead time is more than the reorder point R. The safety
inventory, ss,can be calculated such that the following is true:(1)CSL=F (ss + DL,DL, o,)whereDL=LXD,0,=Lo + D?0(2)Given the distribution of the demand during the lead time L, it is able to obtain the CSL for thecomponentunderdiscussionOn the other hand, with a desired level of CSL, e.g.95%, it is possible to determine the safetyinventoryfrom thebelow equation:SS = F-1(CSL)X (3) InventoryQSafetyDInventoryRun Out PointLeadTimeReorderPointUncertaindemandUncertainleadtimeFig.2.Safety inventory cateringfor demand and supplyuncertaintyFrom above (1), (2) and (3), it can be concluded that the safety inventory is determined by thestandard deviation of the demand during the lead time given desired cycle service level. The safetyinventory can be relativelyhigh when the lead time and the standard deviation of the lead time arebothlarge.Thisisparticularlytruewhenthesuppliersarefardistanceawayfromthefactoriesandtherefore the variances of the transportation lead time are also large.B. VMI Hub to Manage Supply Inventories for FactoriesAnother model of managing supply inventories is illustrated in Fig.3, where a VMI(Vendor-Managed Inventory) hub is adopted to consolidate all the suppliers' shipments for multiplefactories. The VMI hub consists of two segregated inventories, SOI and FOL. SOI refers to SuppliersOwned Inventory, which means the materials are under suppliers' books until they reach the agreedownership transferring dates or receive the request to be transferred. SOI becomes Factory OwnedInventory (FOl)once they aretransferred.Factories could pull FOIwith a fast turnaround time
inventory, ss, can be calculated such that the following is true: CSL = F (ss + DL,DL, ) (1) where DL=L D, (2) Given the distribution of the demand during the lead time L, it is able to obtain the CSL for the component under discussion. On the other hand, with a desired level of CSL, e.g.95%, it is possible to determine the safety inventory from the below equation: (3) Fig.2. Safety inventory catering for demand and supply uncertainty. From above (1), (2) and (3), it can be concluded that the safety inventory is determined by the standard deviation of the demand during the lead time given desired cycle service level. The safety inventory can be relatively high when the lead time and the standard deviation of the lead time are both large. This is particularly true when the suppliers are far distance away from the factories and therefore the variances of the transportation lead time are also large. B. VMI Hub to Manage Supply Inventories for Factories Another model of managing supply inventories is illustrated in Fig.3, where a VMI (Vendor-Managed Inventory) hub is adopted to consolidate all the suppliers’ shipments for multiple factories. The VMI hub consists of two segregated inventories, SOI and FOI. SOI refers to Suppliers Owned Inventory, which means the materials are under suppliers’ books until they reach the agreed ownership transferring dates or receive the request to be transferred. SOI becomes Factory Owned Inventory (FOI) once they are transferred. Factories could pull FOI with a fast turnaround time
normally within one day.SupplieVMIHubSupplierCustomerFactoryCustomeraCTOSuppliePushPullFig.3.Supply inventorymanagement withVMI hubUnder VMI arrangement, suppliers decide how much inventory to ship and when to ship whilefactories just set target inventory levels and record suppliers'deviations from the targets.Factorieswithdraw inventories from FOI only when needed. In addition, factories do not own the inventory inSOI, which is owned by suppliers instead and charged to factories indirectly through componentpricing. The cost of maintaining inventory in SOI is, however, eventually included in the final pricesof thefinal products.Therefore, any reduction in inventorybenefits factories'customers directly byreducingproductprices.In Fig.3, the VMI hub is normally a decoupling point, where pull processes triggered bycustomer demands, and push processes are initiatedby the information sharing between thefactoriesand suppliers. However, this paper will introduce a Suppliers Pull (JSP) process, which is to establisha JIT pulling system between suppliers and the VMI hub.To understand the impact of VMI hub on supply inventories, it is necessary to find out thedistribution of the aggregate demand across all the product models of multiple factories for thecommon components, Assume the aggregate demand of the same component discussed previously isnormally distributed with a mean of Rc, standard deviation of o, and the demands across all theproduct models are independent, that means all correlation coefficients and thus covariance is zero.In our context, because different product models are manufactured by different factories andserve for different market segments, it is acceptable to assume that the demands of the commoncomponent across product models are independent. Therefore, it concludes that the aggregate demandhas a much lower standard deviation than that of the sum of individual demands across productmodelsofmultiplefactories.Since the required safety inventory is proportional to the standard deviation of the demand duringthe replenishment lead time, it is thus likely to conclude that aggregating demands will reduce theamountofsafetyinventoryrequiredwithouthurtingthecomponentavailability.Similarly, the impact of aggregate demand on safety inventory can be evaluated by desired cycle
normally within one day. Fig.3. Supply inventory management with VMI hub Under VMI arrangement, suppliers decide how much inventory to ship and when to ship while factories just set target inventory levels and record suppliers’ deviations from the targets. Factories withdraw inventories from FOI only when needed. In addition, factories do not own the inventory in SOI, which is owned by suppliers instead and charged to factories indirectly through component pricing. The cost of maintaining inventory in SOI is, however, eventually included in the final prices of the final products. Therefore, any reduction in inventory benefits factories’ customers directly by reducing product prices. In Fig.3, the VMI hub is normally a decoupling point, where pull processes triggered by customer demands, and push processes are initiated by the information sharing between the factories and suppliers. However, this paper will introduce a Suppliers Pull (JSP) process, which is to establish a JIT pulling system between suppliers and the VMI hub. To understand the impact of VMI hub on supply inventories, it is necessary to find out the distribution of the aggregate demand across all the product models of multiple factories for the common components. Assume the aggregate demand of the same component discussed previously is normally distributed with a mean of Rc, standard deviation of , and the demands across all the product models are independent, that means all correlation coefficients and thus covariance is zero. In our context, because different product models are manufactured by different factories and serve for different market segments, it is acceptable to assume that the demands of the common component across product models are independent. Therefore, it concludes that the aggregate demand has a much lower standard deviation than that of the sum of individual demands across product models of multiple factories. Since the required safety inventory is proportional to the standard deviation of the demand during the replenishment lead time, it is thus likely to conclude that aggregating demands will reduce the amount of safety inventory required without hurting the component availability. Similarly, the impact of aggregate demand on safety inventory can be evaluated by desired cycle