Abstract:Many companies have enjoyed a significant success due to the unique ways in which they have organized their supply chains, which are one of the best ways to compete in today's marketplaces. For make-to-stock production systems the production plans and activities are based on demand forecasting. This is one of the key causes of the bullwhip effect. The bullwhip effect (BE) is the inherent increase in demand fluctuation up the supply chain. In the paper we experimented (by simulating) with a special case of a si… Show more
“…In this model, we have considered the safety stock by extending the lead-time by k i [15,18] so that i t S can be reformulated as shown below in eq. (11). This is similar to what we have done with the centreline of the inventory position control chart.…”
Section: supporting
confidence: 60%
“…This trade-off needs robust replenishment systems to balance the inventory and production costs whilst ensuring a customer service level [9]. Exhaustive research has been conducted to study the impact of various ordering policies on bullwhip effect, and to develop replenishment rules that can avoid the bullwhip effect [10][11][12][13][14][15][16][17]. In particular, extensive research has been focusing on developing smoothing ordering polices that are modified from the order-up-to policy with adding proportional controllers to restrict overreaction/underreaction to demand changes [17][18][19][20].…”
Inventory replenishment rules have been recognized as a major cause of the bullwhip effect and inventory instability in multi-echelon supply chains. There is a trade-off between bullwhip effect and inventory stability where mitigating the bullwhip effect through order smoothing might increase inventory instability. Therefore, there is a substantial need for inventory control policies that can cope with supply chains dynamics. This paper attempts to formulate an inventory control system based on a statistical control chart approach to handle the trade-off between order variability amplification and inventory stability. The proposed replenishment system, namely IR-SPC, incorporates individual control charts to control both the inventory position and the placed orders. A simulation study has been conducted to evaluate and compare the IR-SPC with a generalized order-up-to that has order smoothing mechanism. The comparisons showed that the IR-SPC outperforms both the smoothing order-up-to policy and the Min-Max inventory policy in terms of bullwhip effect and inventory performances.
“…In this model, we have considered the safety stock by extending the lead-time by k i [15,18] so that i t S can be reformulated as shown below in eq. (11). This is similar to what we have done with the centreline of the inventory position control chart.…”
Section: supporting
confidence: 60%
“…This trade-off needs robust replenishment systems to balance the inventory and production costs whilst ensuring a customer service level [9]. Exhaustive research has been conducted to study the impact of various ordering policies on bullwhip effect, and to develop replenishment rules that can avoid the bullwhip effect [10][11][12][13][14][15][16][17]. In particular, extensive research has been focusing on developing smoothing ordering polices that are modified from the order-up-to policy with adding proportional controllers to restrict overreaction/underreaction to demand changes [17][18][19][20].…”
Inventory replenishment rules have been recognized as a major cause of the bullwhip effect and inventory instability in multi-echelon supply chains. There is a trade-off between bullwhip effect and inventory stability where mitigating the bullwhip effect through order smoothing might increase inventory instability. Therefore, there is a substantial need for inventory control policies that can cope with supply chains dynamics. This paper attempts to formulate an inventory control system based on a statistical control chart approach to handle the trade-off between order variability amplification and inventory stability. The proposed replenishment system, namely IR-SPC, incorporates individual control charts to control both the inventory position and the placed orders. A simulation study has been conducted to evaluate and compare the IR-SPC with a generalized order-up-to that has order smoothing mechanism. The comparisons showed that the IR-SPC outperforms both the smoothing order-up-to policy and the Min-Max inventory policy in terms of bullwhip effect and inventory performances.
“…If delays in supplies are long, this might result in a significant increase in inventory, which is unwelcome [6]. Therefore, it is advisable to include equation (4) in the model, which adds constraints allowing for the suspension of any replenishment if its level exceeds the required value [12,[18][19].…”
Section: An Equation Of Inventory Balancementioning
confidence: 99%
“…A range of studies on inventory management in retail have been carried out, taking into account different aspects (e.g., see [2][3][4][5]). …”
Inventory represents an essential part of current assets, which are typically characterized by their transience. This paper aims to outline a numerical solution of the inventory balance equation supplemented by an order-upto replenishment policy for a case in which the problem is described by a differential equation with delayed argument. The results are demonstrated on a specific example and the behaviour of the model is presented using a computer simulation. The results are graphically shown in the Maple system. The solution makes use of the theory of functional differential equations, especially the part dealing with differential equations with delayed arguments.
“…The linking of the different data and systems allows highly personalised, flexible and individually composed production processes. Thus, a small company can become part of a virtual factory and a flexible cooperative network [18][19][20][21][22].…”
Section: The Comvantage Concept As a Solution For The Textile Market mentioning
EU textile industry with its inability to compete with mass-produced and less expensive imported items, mono-perspective business processes, no solutions for trustful interorganisational collaboration and hardly integration of end-customer in design and production processes conflict trends of technological developments, the rise of individual customer requirements and the success of innovative, flexible and heterarchical environments. Offering a web-based product-centric collaboration space for dynamic and flexible information exchange between multiple companies including the end-customer can provide a new dimension of efficiency. For the establishment and effective functioning of such environment referred as virtual factory, intense communication and spontaneous sociability are clearly required and are affected by the connecting element that in modern social sciences -in the context of economic efficiency -is referred to as social capital. With this paper the virtual factory simulation shows the possible development of mobile applications for supply chain management, while promoting and using social capital in a decentralised production process oriented to innovative, custom-made products for the textile industry in Slovenia.
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