Managing Electricity Peak Loads in Make‐To‐Stock Manufacturing Lines

In this article, we study the control of stochastic make‐to‐stock manufacturing lines in the presence of electricity costs. Electricity costs are difficult to manage because unit costs increase with the total load, that is, the amount of electricity needed by the manufacturing line at a certain point in time. We demonstrate that standard methods for controlling manufacturing lines cannot be used and that standard analytic results for stochastic manufacturing lines do not hold in the presence of electricity costs. We develop a control policy that balances electricity costs with inventory holding and backorder costs. We derive closed‐form expressions and analytic properties of the expected total cost for manufacturing lines with two workstations and demonstrate the accuracy and robustness of the policy for manufacturing lines with more than two workstations. The results indicate that avoiding electricity peak loads requires additional investment in manufacturing capacity and higher inventory and backorder costs. Our approach also applies to companies which aim at reducing their carbon emissions in addition to their operating costs.     

Synchronization of material flow to aid production planning in a job shop

This paper discusses how synchronizing finish times for correspondingly numbered process operations of mating component parts (batches) can help a job shop take advantage of some aspects of the just-in-time philosophy.This paper proposes that the synchronization of process operations of mating parts (batches) can be an effective production planning tool that may actually decrease total throughput time where manufacturers are attempting to decrease in-process inventory. An example problem is included to demonstrate the situation.A production planner must keep in perspective all production orders when trying to decrease in-process inventory. The throughput times of all orders may be increased, while too much effort is concentrated on reducing in-process inventory costs of individual orders.     

Centralized inventory in a farming community

A centralized inventory problem is a situation in which several agents face individual inventory problems and make an agreement to coordinate their orders with the objective of reducing costs. In this paper we identify a centralized inventory problem arising in a farming community in northwestern Spain, model the problem using two alternative approaches, find the optimal inventory policies for both models, and propose allocation rules for sharing the optimal costs in this context.     

Multi-item single-source ordering with detailed consideration of transportation capacities

We consider multi-item single-source ordering with detailed consideration of transportation capacities. Such problems are characteristic for companies which operate direct links as part of their supply chain to transport loads with heterogeneous physical dimensions and fluctuating demands. Given knowledge on transportation demands, companies can eliminate future transports by shifting the load to fill the inflexible capacity of prior transports. While reducing transportation costs, doing so will ceteris paribus imply inventory. The problem is to coordinate orders across multiple items such that transport costs are minimized at minimal increase in inventory. The approach is distinct from prior works in that it considers detailed loading restrictions. We therefore interpret the problem as a multi-period version of the container loading problem. A wall building approach is used and incorporated into a heuristic rolling horizon procedure. We test the proposed procedure on some random problems which resemble a real inbound case from the automotive industry. As compared to period-by-period planning and two benchmarks with aggregated capacity models from the literature and practice, cost savings are possible under a wide range of operating conditions and mostly independent of the shipping volume. The largest potential exists for mid- to long-distance transports. There is a relevant potential to improve short-distance transports as well, however, only if inventory cost rates are moderate.     

独立定价还是共同定价:新支付工具的定价策略

基于新支付工具发展初期市场特征构建双边市场定价模型，分析共同定价和独立定价策略下企业利润和社会福利最大化新支付工具定价。研究显示：政府较企业对新支付工具制定更低价格水平促使用户支付选择转移，特别是在共同定价策略下会有效提升市场效率，达到社会福利最大；但若政府无法做到共同定价，特别在新支付工具成本优势不明显时，会使支付工具间存在过度补贴而降低社会福利，这时企业利润最大化定价为次优选择。     

Inventory management with variable lead-time dependent procurement cost

A reduction in the inventory replenishment lead-time allows reducing safety stock requirements and improving customer service. However, it might be accompanied by increased procurement costs because of premium charges imposed by suppliers, or higher transportation costs. This paper studies a single-stage variable lead-time inventory system with lead-time dependent procurement cost. Selection of the lead-time value represents finding the trade-off between benefits of lead-time reduction and increase in the procurement cost. A model for joint optimization of inventory and procurement costs is developed. Numerical studies are conducted to identify conditions under which lead-time reduction is favorable compared to procuring at the lowest cost.     

Decentralised bilevel model for shared inventory management

In this study, we consider the case of a large corporation that owns a warehouse and two concurrent chains. The company opted for shared inventory policy. The warehouse is looking into minimising its inventory cost and at the same time reducing the fluctuation of the personnel. The chains, independently, are trying to minimise their inventory costs. The warehouse plays the role of a leader in optimising its objectives and, as followers, the two chains try to satisfy their objectives. The problem is formulated into a decentralised nonlinear bilevel programming problem. We also consider the fuzziness of some parameters due to the imprecise available information. We propose the mathematical model and we solve it for our specific case.     

The Impact of Modular Assembly on Supply Chain Efficiency

This article studies the impact of modular assembly on supply chain efficiency. In the modular assembly approach, a manufacturer acquires pre‐assembled modules from its suppliers, rather than the individual components, as in the traditional assembly approach. We analyze the competitive behavior of a two‐stage modular assembly system consisting of a manufacturer, and a supplier who pre‐assembles two components into a module. The firms can choose their own inventory policies and we show the existence of Nash equilibrium in the inventory game. Moving from the traditional to the modular approach has a twofold effect on the supply chain. First, we investigate the effect of centralizing the component suppliers. It can be shown that when there is no production time shift, the module supplier always holds more component inventories than suppliers do in the traditional approach, which yields a lower cost for the manufacturer. However, the suppliers, and therefore the supply chain may incur a higher cost in the modular approach. Second, we study the effect of a shift in production time from the manufacturing stage to the supplier stage. From numerical studies, it has been found that such a lead time shift always benefits a centralized supply chain, but not necessarily so for a decentralized system. Combining the two effects, we find that the modular approach generally reduces the cost to the manufacturer and the supply chain, which explains the prevalence of modular assembly from the perspective of inventory management. These results also provide some insight into how firms can improve supply chain efficiency by choosing the right decision structure and lead time configuration.     

A Comparative Analysis of Master Production Scheduling Techniques for Assemble-To-Order Products

This paper studies the master production scheduling (MPS) activity of manufacturing firms that produce assemble-to-order (ATO) products. It describes four techniques for master scheduling ATO products: end-product bills, modular bills, super bills, and percentage bills. These procedures are compared in terms of the percentage of customer orders delivered late, the mean tardiness of customer order deliveries, and the total cost of inventory using simulation analysis. The results indicate that the performance of an MPS technique is affected by the level of uncertainty of the end products' demands and the degree of component commonality in the product structure. In particular, modular bills produce the highest customer service level and super bills produce the lowest total inventory cost under most operating conditions. The conclusions also suggest that the choice of a particular MPS technique is often a compromise between the benefits of improved MPS performance and the costs of implementing and executing the MPS system.     

Measuring Modularity‐Based Manufacturing Practices and Their Impact on Mass Customization Capability: A Customer‐Driven Perspective

As uncertainty in markets and technology intensifies, more companies are adopting modular product and process architectures to cope with increasing demands for individually customized products. Modularity‐based manufacturing is the application of unit standardization or substitution principles to create modular components and processes that can be configured into a wide range of end products to meet specific customer needs. This study defines modularity‐based manufacturing practices (MBMP), develops a valid and reliable instrument to measure MBMP, builds a framework that relates customer closeness, MBMP, and mass customization capability, and tests structural relationships within this framework using LISREL. Based on 303 responses from members of the Society of Manufacturing Engineers, statistically significant and positive relationships were found among customer closeness, modularity‐based manufacturing practices, and mass customization capability. Managerial implications of the empirical findings of this study and future research directions are also discussed.     

MODELS FOR OPTIMAL LEAD TIME REDUCTION

Most inventory and production planning models in the academic literature treat lead times either as constants or random variables with known distributions outside of management control. However, a number of recent articles in the popular press have argued that reducing lead times is a dominant issue in manufacturing strategy. The benefits of reducing customer lead times that are frequently cited include increased customer demand, improved quality, reduced unit cost, lower carrying cost, shorter forecast horizon, less safety stock inventory, and better market position. Although the costs of reducing lead times in the long term may be relatively insignificant compared with the benefits, in the short term these costs can have a significant impact on the profitability of a firm. This article develops a conceptual framework within which the costs and benefits of lead time reduction can be compared. Mathematical models for optimal lead time reduction are developed within this framework. The solutions to these models provide methods for calculating optimal lead times, which can be applied in practice. Sensitivity analysis of the optimal solutions provides insight into the structure of these solutions.     

Simulation Analysis of a Manufacturing Supply Chain*

A supply chain is a series of manufacturing plants that transform raw material into finished product. A pipeline within a supply chain refers to the stream of information, material, components, and assemblies that are associated with a particular product. It is typical for manufacturing plants to put considerable effort to optimize the performance of a horizontal slice of a supply chain (such as coordination among parts that share a common resource). The need to optimize the performance of the vertical slice (the supply chain connecting raw material to finished product) by controlling the transmission of schedule instability and the resulting inventory fluctuation is often overlooked. A schedule is stable if actual production requirements for a given period do not change from the forecast production requirements. Stable production schedules are important when managing supply chains as they help control inventory fluctuation and inventory accumulation. Failure to control schedule instability results in high average inventory levels in the system. In this paper a simulation analysis of supply chain instability and inventory is conducted, and it is shown how supply chains can be analyzed for continuous improvement opportunities using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors (GM). It is shown that the techniques used in this paper are a useful tool for supply chain analysis.     

Emerging Market Penetration,Inventory Supply,and Financial Performance

Realizing potential benefits from emerging market penetration requires firms to address inherent supply chain challenges. A major challenge is for firms to manage costly inventories to address demand and supply risks in emerging markets. However, emerging market penetration may offer opportunities for firms to lower inventory levels, reduce costs, and improve operating performance. Using data for 482 manufacturing firms over the 5‐year period, 2003–2007, obtained from the COMPUSTAT Industrial and Segment Databases, this article examines the relationships between emerging market penetration, inventory supply, and financial performance. Our results show that a multinational firm's sales penetration into emerging markets is associated with fewer days of inventory supply and improved financial performance. As emerging market penetration may allow firms to operate with lower inventory supply, the positive effect from emerging market penetration, such as labor cost reductions, may be enhanced due to inventory cost savings.     

Analysis and Management of Periodic Review,Order‐Up‐To Level Inventory Systems with Order Crossover

In this article, we investigate the (R, S) periodic review, order‐up‐to level inventory control system with stochastic demand and variable leadtimes. Variable leadtimes can lead to order crossover, in which some orders arrive out of sequence. Most theoretical studies of order‐up‐to inventory systems under variable leadtimes assume that crossovers do not occur and, in so doing, overestimate the standard deviation of the realized leadtime distribution and prescribe policies that can inflate inventory costs. We develop a new analytic model of the expected costs associated with this system, making use of a novel approximation of the realized (reduced) leadtime standard deviation resulting from order crossovers. Extensive experimentation through simulation shows that our model closely approximates the true expected cost and can be used to find values of R and S that provide an expected cost close to the minimum cost. Taking account of, as opposed to ignoring, crossovers leads, on average, to substantial improvements in accuracy and significant cost reductions. Our results are particularly useful for managers seeking to reduce inventory costs in supply chains with variable leadtimes.     

Coordinated Replenishments from a Common Supplier

Coordinated replenishment strategies may be implemented by jointly ordering multiple items from a common supplier. A major benefit of coordinated replenishment is that it increases the size of shipments, permitting the buyer to enjoy transportation economies without a major increase in average inventory levels. The coordinated replenishment problem is complex because side constraints govern the attainment of transportation rate breaks. The problem is further complicated by the presence of purchase quantity discount opportunities. Thus, the buyer must decide which items to order independently, which items to include in a group order, and the order quantities of each item, governed by the frequency of independent or group orders. We present a mathematical model and a heuristic solution procedure that provide analytical support to the buyer seeking to minimize total costs of replenishing multiple items from a common supplier. The relevant costs are purchase prices, ordering costs, holding costs, and transportation costs. Coordinated replenishment provides nearly a 30 percent reduction in controllable costs relative to independent control. Experimentation with the heuristic has yielded optimal solutions over 88 percent of the time. When optimality was not obtained, the mean penalty was much less than one percent. The average heuristic search was more than two orders of magnitude faster than branch and bound, even for small problems, and possessed a much tighter distribution around the mean search time.     

Lean-healthcare approach to reduce costs in a sterilization plant based on surgical tray rationalization

Abstract

Sterilization plants process all reusable materials used in hospitals during different stages of healthcare provision. Most items sterilized come from the surgical theater in the form of individual instruments, linen and surgical trays. Reducing the number of instruments in trays impacts on the performance of the sterilization process. Here, we propose a three-phase method, based on lean healthcare principles, cluster analysis and kaizen groups of experts to rationalize surgical trays, reducing sterilization processing costs. We innovate by proposing a strategy to approach tray rationalization prioritizing surgical specialties that are both complex and frequent, and by using group technology to cluster surgical trays expediting expert analyses carried out by kaizen groups. Our propositions were tested in a high complexity, tertiary care hospital, covering 12 surgical specialties, reducing the number of instruments by average 9.75%, and the time-to-assemble trays by average 9.68%, obtaining annual savings of US$285.756,00 in sterilization processing costs.     

Production planning and inventory control in a company manufacturing PC parts: A case study

In this paper, we present a case study on the production planning and inventory system in a company manufacturing personal computer (PC) parts. In the case study, the targets are specified for developing a system for production planning and inventory control. The current state of the company is analysed for clarifying the points necessary to achieve the targets. Also, a system based on the analysis is proposed and its effects are estimated.     

Contracting in a Supply Chain with Stochastic Demand and Substitute Products

Retailers often stock competing products from multiple manufacturers. When the retailer stocks out of a particular item, customers who prefer the item are likely, with some probability, to switch to a substitute product from another manufacturer at the same store. In such an event, a “lost sale” for the manufacturer is not a “lost sale” for the retailer. This exacerbates differences in manufacturer's and retailer's stockout costs for the item. Such differences in stockout cost influence the optimal contract between the manufacturer and the retailer and also impose agency costs on the channel. Such contracts, in turn, determine equilibrium inventory levels and fill rates. We study these issues in a single‐period supply chain, consisting of a manufacturer and a retailer, under three different scenarios (when the two firms are integrated into a single entity, when the retailer makes stocking decisions, and when the manufacturer makes stocking decisions). We compare, and present a methodology for comparing, stocking quantities, manufacturer efforts, and supply chain profits across different scenarios. We find that VMI performs better when manufacturer effort is a substantial driver of consumer demand and when consumers are unlikely to substitute to another brand in case of a stockout. On the other hand, if non‐contractible manufacturer effort is unimportant, or when substitution is significant, VMI can exacerbate, rather than mitigate, channel inefficiencies, and can perform worse than traditional Retailer Managed Inventory.     

Willingness to Pay for Shifting Inventory Risk: The Role of Contractual Form

In order to reduce their inventory risk, firms can attempt to contract with their suppliers for shorter supply lead‐times, with their buyers for longer demand lead‐times, or both. We designed a controlled laboratory experiment to study contracts that shift a focal firm's inventory risk to its supply chain partners and address two questions. First, is it more effective if the cost of shifting inventory risk is framed as a fixed fee or in per‐unit cost terms? We find that, generally, our participants are willing to pay more to avoid supply–demand mismatches than the expected costs from such mismatches. This tendency to overpay is mitigated under fixed fee schemes. Second, does it matter whether the option to reduce inventory risk is the outcome of either increased responsiveness from the upstream supplier or advanced demand information from the downstream buyer? Our results suggest that this difference, when only a matter of framing, has no significant effect on willingness‐to‐pay.     

Multiple In‐Cycle Transshipments with Positive Delivery Times

We study a centralized inventory sharing system of two retailers that are replenished periodically. Between two replenishments, a unit can be transshipped to a stocked‐out retailer from the other. It arrives a transshipment time later, during which the stocked‐out retailer incurs backorder cost. Without transshipment, backorder cost is incurred until the next replenishment. Since the transshipment time is shorter than the time between two replenishments, transshipments can reduce the backorder cost at the stocked‐out retailer and the holding costs at the other retailer. The system is directed by a centralized inventory manager, who minimizes the long‐run average cost consisting of replenishment, holding, backorder, and transshipment costs. The transshipment policy is characterized by hold‐back inventory levels, which are nonincreasing in the remaining time until the next replenishment. The transshipment policy differs from those in the literature because we allow for multiple transshipments between replenishments, positive transshipment times, and backorder costs. We also discuss the challenges associated with positive replenishment time and develop upper and lower bounds of average cost in this case. Bounds are numerically shown to have an average gap of 1.1%. A heuristic solution is based on the upper bound and differs from the optimal cost by at most this gap.