Pooling of spare components between airlines

To remain competitive, manufacturers must seek transportation strategies that both reduce costs and maintain high levels of service. One approach is to consolidate inbound freight at transshipment points. This provides economies of scale and promotes capacity efficient mixes of high and low density items. When service level considerations are included via inventory holding costs, the approach yields a nonlinear network model with multiattribute multicommodity flows. The model is difficult to solve for global optimality in that the objective function is neither convex nor concave; therefore, a composite algorithm is proposed. The algorithm alternates between a linearization technique to find local optima and a heuristic search based on “adjacent concave flows” to provide local improvements. Computational results demonstrate the ability of the multiattribute approach to identify savings in overall transportation and inventory costs when compared to a single attribute approach.

Supply Chain Design Considering Economies of Scale and Transport Frequencies

Balancing learning and economies of scale for adaptive clinical trials

The use of additive manufacturing has increased significantly in previous years. Additive manufacturing is used by multiple industry subsectors, including motor vehicles, aerospace, machinery, electronics, and medical products. Currently, however, additive manufactured products represent less than one percent of all manufactured products in the U.S. As the costs of additive manufacturing systems decrease, this technology may change the way that consumers interact with producers. Additive manufacturing technology opens up new opportunities for the economy and society. It can facilitate the customized production of strong light-weight products and it allows designs that were not possible with previous manufacturing techniques. Various challenges, however, can impede and slow the adoption of this technology. In many instances, the cost of producing a product using additive manufacturing processes exceeds that of traditional methods. This report examines literature on the costs of additive manufacturing and seeks to identify those instances where additive manufacturing might be cost effective and also identify potential means for reducing costs when using this technology. Current research on additive manufacturing costs reveals that this technology is cost effective for manufacturing small batches with continued centralized manufacturing; however, with increased automation distributed production may become cost effective. Due to the complexities of measuring additive manufacturing costs, current studies are limited in their scope. Many of the current studies examine the production of single parts. Those that examine assemblies tend not to examine supply chain effects such as inventory and transportation costs along with decreased risk to supply disruption. Currently, research also reveals that material costs constitute a major proportion of the cost of a product produced using additive manufacturing. However, technologies can often be complementary, where two technologies are adopted alongside each other and the benefits are greater than if they were adopted individually. Increasing adoption of additive manufacturing may lead to a reduction in raw material cost through economies of scale. The reduced cost in raw material might then propagate further adoption of additive manufacturing. There may also be economies of scale in raw material costs if particular materials become more common rather than a plethora of different materials. The additive manufacturing system is also a significant cost factor; however, this cost has continually decreased. Between 2001 and 2011 the average price decreased 51 % after adjusting for inflation.

Ultra large ships have the advantage of scale economies, but whether they successfully getting into service depend on cargo flow, shipping distance, port efficiency and constraints, etc. The study constructs a two-objective model to determine the optimal ship size and sailings frequency and analyze the shipping economies of ultra large ships by minimizing shipping costs and inventory costs. The results show the Pareto optimal solutions of the two-objective model and optimal ship size and sailings frequency with respect to each level of inventory costs and shipping costs. The sensitivity analysis shows the optimal ship tends to be large as route flow increases. Furthermore, the economies and possibility of using ultra large ships tend to increase, as port efficiency improves, shipping distance increases, the ports of call decreases, or the relative costs of large ships decrease.

PT. MMU is an industry engaged in processing marine fish. The aim of this research is to minimize the cost of snapper supplies so that the production process becomes more efficient. The analysis begins with data on demand for red snapper in 2023. The movement of recorded demand shows fairly stable fluctuations, although there are some significant declines in certain months, data on ordering costs and storage costs, including raw material prices, ordering frequency, costs forklift, and ice cube costs, have been obtained to account for the total cost of raw material inventory. Data on fish demand, ordering costs, storage costs, and inventory factors were analyzed, resulting in an optimal order quantity of 298.98 kg per order with an order frequency of 6 times a year. Cost analysis shows potential savings of Rp. 3,078,677.43, safety stock of 127 kg and re order point of 42 kg. This research provides insight into the efficiency of inventory management at PT. MMU and its important implications for stock control in the fishing industry

Import companies operating in the globalized market and in a multi-item context are frequently faced with the need of aggregating their orders to benefit from scale economies associated to the use of containers for freight shipping. We introduce the problem of optimal replenishment order placement, namely the problem of scheduling and aggregating a fixed number of replenishment orders, along a given planning horizon, with the aim of minimizing the total inventory and backorder costs. For this problem, a continuous optimization formulation is provided, which is characterized by a nonconvex piecewise affine objective function. We introduce an ad hoc algorithm, based on the coordinate search approach, for the approximate numerical solution of the continuous model, and present the numerical results obtained on a set of randomly generated instances. In order to evaluate the quality of solutions returned by the algorithm, a discrete formulation of the problem is also provided, which falls into the well-known class of uncapacitated location models of the p-median type, whose exact solution on the same instance set can be obtained by means of an integer programming commercial solver.

(ProQuest: ... denotes formulae omitted.)1. IntroductionMonk (1987) defined inventory as idle resources that possess economic value. In a broad sense, everyone keeps inventory such as food, clothes, domestic items, paper, pens and many other goods. Inventory applies to all types of work systems. Some types of inventory are raw materials inventory, in-process inventory, finished goods inventory, spare parts inventory, and so on.There are three basic reasons for keeping an inventory:a. Time - The time lags present in the supply chain, from supplier to user at every stage, requires that you maintain certain amounts of inventory to use during the lead time.b. Uncertainty - Inventories are maintained as buffers to address the problems of uncertainties in demand, supply and movements of goods.c. Economies of scale - Ideal condition of one unit at a time at a place where a user needs it, when he needs principle tends to incur lots of costs in terms of logistics. So bulk buying, movement and storing brings in economies of scale, thus inventory (Wikipedia, 2010).The total cost of inventory is calculated as the sum of the purchasing cost, setup cost, holding cost, and shortage cost (Taha, 2007).Economic order quantity is the level of inventory that minimizes the total inventory holding costs and ordering costs.Several models exist depending on the assumptions taken in efforts to describe real life situations. Some considerations used are:a. Demand: the classical inventory model assumed demand to be known with certainty (deterministic). Chaudhuri (2003) considered a scenario where the demand varies with time, while Teng et. al. (2005) considered demand as deterministic but as an exponential function. Kar et. al. (2001) also considered demand as stochastic and price-dependent.b. Shortages: The classical model assumes that shortages are not allowed. Many works have been carried out under this assumption in times past and even recent times (e.g. Covert & Phillip (1973), Teng. et. al. (2005)). However, some works have also been done in which shortage-costs component is added to the inventory model (e.g. Kar et. Al,.2001; Mirzazadeh, 2010).c. Ordering pattern: Sharma (1987) identified five ordering policies namely:i. (s ,Q) policy: Place order for a fixed quantity, Q whenever the inventory position drops to a given level s or below.ii. (s ,S) Policy: Place order for a quantity that would bring the inventory to a given maximum stock level, S whenever the inventory position drops to a given level s or below.iii. (T, S) Policy: Place order for a quantity that would bring the inventory to a given maximum stock level, S at regular interval of time T, spaced at time intervals of equal length.iv. (T, s, S) Policy: Place order for a quantity that would bring the inventory to a given maximum stock level, S at regular interval of time T, spaced at time intervals of equal length if the inventory level is at level s or below.v. (T, Q) Policy: Place order for quantity Q at every ordering interval, T.Researchers (Sivakumar, 2009; Kalpakam & Sapna, 1995; Kalpakam & Sapna, 1994) have considered ordering policy in their studies.d. Inflation: Inflation can simply be defined as an increase in the supply of currency or credit relative to the availability of goods and services, resulting in higher prices and a decrease in the purchasing power of money. Buzacott (1975) stated that while classical EOQ formula assumes all costs are constant, it would be unreasonable to use the EOQ formula without investigating how it is modified when inflation causes cost to increase with time. The Buzacott model (1975) led to the consideration of inflation as an important factor in the determination of economic order quantity by many researchers and thus led to the development of many other models with inflation considerations (Mirzazadeh, 2010; Mirzazadeh et al. …

Joint optimization of condition-based maintenance and inventory control for a k-out-of-n:F system of multi-state degrading components

A bi-objective multi-period series-parallel inventory-redundancy allocation problem with time value of money and inflation considerations

We study a component inventory planning problem in an assemble‐to‐order environment faced by many contract manufacturers in which both quick delivery and efficient management of component inventory are crucial for the manufacturers to achieve profitability in a highly competitive market. Extending a recent study in a similar problem setting by the same authors, we analyze an optimization model for determining the optimal component stocking decision for a contract manufacturer facing an uncertain future demand, where product price depends on the delivery times. In contrast to our earlier work, this paper considers the situation where the contract manufacturer needs to deliver the full order quantity in one single shipment. This delivery requirement is appropriate for many industries, such as the garment and toy industries, where the economies of scale in transportation is essential. We develop efficient solution procedures for solving this optimization problem. We use our model results to illustrate how the different model parameters affect the optimal solution. We also compare the results under this full‐shipment model with those from our earlier work that allows for multiple partial shipments. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007

A recent paper in Journal of Public Health Medicine (O'Neill et al., 2000; 22(1): 108-115) used regression modelling to determine the average costs of neonatal care services for a sample of 49 units in the United Kingdom in 1990-1991, and concluded that economies of scale were present in the sample as a whole. Although this form of modelling is useful, analysis of the efficiency of production for individual units is also important. Data envelopment analysis (DEA) was used to analyse the data set published by O'Neil et al., to determine technical efficiency of neonatal units, measuring efficiency compared with a benchmark efficient frontier, and estimating economies of scale for each unit. Potential cost savings if units were to operate efficiently are estimated. There is evidence of substantial levels of technical inefficiency. Economies of scale varied between units, with increasing returns in the 36 inefficient units, and mainly constant returns in the 13 efficient units. This suggests that the presence of technical inefficiency was as important as scale inefficiencies. Total cost savings, if all units were operating efficiently, are estimated at ł10.4 million, equivalent to 10 extra units producing 57,000 additional days of care. DEA is a technique of great potential value in analysing the efficiency of health care production. As well as inefficiencies in the production of neonatal care in the United Kingdom due to differences in the scale of production, there appears to have been considerable technical inefficiency, which was not due to differences in case mix. The potential cost savings from efficiency gains are large.

BackgroundTo improve the efficient use of scarce resources, low- and middle-income countries and development partners are increasingly encouraged to deliver multiple vaccines and other interventions in a single integrated campaign. However, little is known regarding the cost of delivering vaccines through integrated campaigns, and the extent to which efficiencies are achieved. To fill this evidence gap, we estimated the cost of integrated immunization campaigns in Nigeria and Sierra Leone, and the potential savings from integration.MethodsWe conducted a retrospective ingredients-based costing study from a payer perspective of a campaign held in 2019 in Sierra Leone with measles-rubella vaccine and oral polio vaccine, during which nutrition supplements were also offered in part of the country, and yellow fever campaigns held in three states in Nigeria in 2019 and 2020, where in one state (Anambra) meningococcal A vaccines were co-delivered. We collected data from 108 health facilities, all relevant administrative levels, and implementing partners. We estimated the full financial and economic cost of each campaign, the average unit cost of delivery, as well as the cost by activity and resource type. We also estimated the cost savings from integration in Anambra state by modelling out the cost of the alternative of two standalone campaigns.ResultsThe average financial delivery cost was $0.34 per dose in Sierra Leone, and the economic cost was $0.73 per dose. In Nigeria, the financial cost per dose was $0.29–$0.35 across the three states, and the economic cost per dose was $0.62–$0.85. Facilities and wards delivering more doses achieved a lower financial and economic unit cost of delivery, demonstrating evidence of economies of scale. We estimated that Anambra may have saved at least $1,204,133 in financial resources by integrating yellow fever and meningitis A vaccine delivery, amounting to $0.17 per dose delivered. When including opportunity costs, the economic cost saving was estimated at $0.34 per dose delivered.ConclusionsThe study offers evidence on what it costs to deliver integrated campaigns, and shows that integrated delivery is likely to result in significant cost savings. Where high delivery volumes can be achieved, integrated campaigns can benefit from economies of scale. The findings can be used to inform planning and budgeting for immunization campaigns in low- and middle-income countries.

Drivers of cost reduction in solar photovoltaics

For a long time, an important discussion in economics has focused on the welfare effects of horizontal mergers and on policies associated with such mergers. Most researchers seem to agree on a general tradeoff according to which potential cost savings from a merger have to be set against the price-raising effects which frequently result from the corresponding increase in concentration. An influential view suggests that the effect of cost savings can be expected to dominate because cost reduction applies to all inframarginal output. Williamson's (1968) senminal contribution provided reasons for the cost reduction effect to dominate. Hjalmarsson (1976) argued that this conclusion might be particularly plausible for small countries such as those in Scandinavia. However, this traditional approach takes the source and magnitude of cost reductions as exogenous. The main contribution of the present paper is to model endogenously the size of potential cost reductions from a merger. In this respect, it is shown that mergers typically imply cost reductions, but that this effect is outweighed by the adverse decrease in output. Consequently, this paper provides a plausible counter-example to the view that cost savings outweigh output reduction in welfare terms. In general, the structure of cost savings from mergers might differ from case to case and the actual savings might be difficult to observe. Such cost savings can be of a static nature, based on economies of scale or scope, or they can be of a dynamic nature, based on learning or innovative activity. Here, we concentrate on cost savings based on the fact that merger expectations might change fixed cost expenditures on R & D activity, which will affect the level of marginal costs. Proponents of mergers often refer to mergers as necessary to support sufficiently extensive R&D investment