Delivery Lead Time Research Articles

A model measurement system for collaborative supply chain partners

The purpose of this paper is to understand business performance in the context of an electronic component company. This paper developed a system dynamics model that describes supply chain process structure and examines scenarios, as well. Thus, this study adopted the signal-to-noise (SN) ratio defined by the Taguchi method to evaluate the robustness of a specific supply chain behavior. Resulting in poor inventory cost performance with uncertainty demand, this paper shows how the factor delivery time and lead time of an order can improve performance. Finally, this paper serves as a guideline for decisions that require different inventory strategies.

A strategic analysis of dual-channel supply chain design with price and delivery lead time considerations

Abstract This paper extends the work of Chiang et al. (2003) by investigating how price and delivery lead time decisions affect channel configuration strategy under either the manufacturer-owned or the decentralized mode. We show the choice of channel structure depends on customer acceptance of the online channel and the cost parameters, following a threshold policy in both forms of ownership. We prove that the strategic use of direct marketing to mitigate the double marginalization – the major finding in Chiang et al. (2003) – still holds even in this general situation; moreover, Pareto zone exists where both manufacturer and retailer outperform their counterparts in the traditional indirect channel-only case, thus indicating that mitigating double marginalization may bring mutual benefits. We also compare pricing and delivery lead time decisions between different forms of ownership or between different channel structures under the same form of ownership. The manufacturer adopts a “slow down deliver later” approach and speeds up delivery to serve customers with a higher sensitivity to delivery lead time when he owns the whole indirect channel, but chooses to “stay fast and brag about better services” and surprisingly slows down the speed of service when customers are more sensitive to delivery lead time due to the internal competition between two channels in the decentralized mode.

Managing an Available-to-Promise Assembly System with Dynamic Short-Term Pseudo-Order Forecast

We study an order promising problem in a multiclass, available-to-promise (ATP) assembly system in the presence of pseudo orders. A pseudo order refers to a tentative customer order whose attributes, such as the likelihood of an actual order, order quantity, and confirmation timing, can change dynamically over time. A unit demand from any class is assembled from one manufactured unit and one inventory unit, where the manufactured unit takes one unit of capacity and needs a single period to produce. An accepted order must be filled before a positive delivery lead time. The underlying order acceptance decisions involve trade-offs between committing resources (production capacity and component inventory) to low-reward firm orders and reserving resources for high-reward orders. We develop a Markov chain model that captures the key characteristics of pseudo orders, including demand lumpiness, nonstationarity, and volatility. We then formulate a stochastic dynamic program for the ATP assembly system that embeds the Markov chain model as a short-term forecast for pseudo orders. We show that the optimal order acceptance policy is characterized by class prioritization, resource-imbalance-based rationing, and capacity-inventory-demand matching. In particular, the rationing level for each class is determined by a critical value that depends on the resource imbalance level, defined as the net difference between the production capacity and component inventory levels. Extensive numerical tests underscore the importance of the key properties of the optimal policy and provide operational and managerial insights on the value of the short-term demand forecast and the robustness of the optimal policy. This paper was accepted by Martin Lariviere, operations management.

An Application of Master Schedule Smoothing and Planned Lead Time Control

Make‐to‐order (MTO) manufacturers must ensure concurrent availability of all parts required for production, as any unavailability may cause a delay in completion time. A major challenge for MTO manufacturers operating under high demand variability is to produce customized parts in time to meet internal production schedules. We present a case study of a producer of MTO offshore oil rigs that highlights the key aspects of the problem. The producer was faced with an increase in both demand and demand variability. Consequently, it had to rely heavily on subcontracting to handle production requirements that were in excess of its capacity. We focused on the manufacture of customized steel panels, which represent the main sub‐assemblies for building an oil rig. We considered two key tactical parameters: the planning window of the master production schedule and the planned lead time of each workstation. Under the constraint of a fixed internal delivery lead time, we determined the optimal planning parameters. This improvement effort reduced the subcontracting cost by implementing several actions: the creation of a master schedule for each sub‐assembly family of the steel panels, the smoothing of the master schedule over its planning window, and the controlling of production at each workstation by its planned lead time. We report our experience in applying the analytical model, the managerial insights gained, and how the application benefits the oil‐rig producer.

Justification of coordinated supply chain in small and medium enterprises using analytic hierarchy process

Small and medium enterprises (SMEs) play a critical role in the success of supply chains because in most of the situations they work as suppliers for bigger organisations. SMEs need a coordinated supply chain to face dynamic market requirements in terms of short product life cycle, less delivery lead time and continuous cost reduction. This paper tries to justify a coordinated supply chain in SMEs on the basis of major benefits of coordinated supply chain over a non-coordinated supply chain. The author has used analytic hierarchy process (AHP) for this purpose. Major benefits of coordinated supply chain are lead time reduction, agility in supply chain, delivery on time, inventory reduction, service reliability, cost reduction and accurate forecasting of data. By using AHP, global desirability index of coordinated and non-coordinated supply chain are calculated and compared.

Single-Period Inventory Models with multiple ordering opportunities: a review

Single-Period Inventory Models (SPIMs) or else referred as newsboy model are used to acquire optimal ordering decisions of short life-cycle products facing uncertain demand. Due to longer production and delivery lead-time, SPIM have single-ordering opportunity. To reduce the higher demand variability, the concept of SPIM with multiple ordering opportunities has been adopted in the recent literatures and has proved that the supply chain performance is better than SPIM. This paper broadly studies the literature discussing the SPIM with multiple ordering opportunities under three major classifications such as This paper identifies several research gaps from the existing literatures and proposes a conceptual model based on those gaps. This study also suggests some potential scope for research.

Time Overruns as Opportunistic Behavior in Public Procurement

This paper considers the supplier’s strategic delivery lead time in a public procurement setting as the result of the firm’s opportunistic behavior on the optimal investment timing. In the presence of uncertainty on construction costs, we model the supplier’s option to defer the contract’s execution as a Put Option. We include in the model both the discretion of the court of law in enforcing contractual clauses (i.e. a penalty for delays) and the 'quality' of the judicial system. Then, we calibrate the model using parameters that mimic the Italian procurement for public works and calculate the maximum amount that a firm is 'willing to pay' (per day) to postpone the delivery date and infringe the contract provisions. Our results show that the incentive to delay is greater the higher the construction costs and their volatility, and the weaker the penalty enforcement by the courts of law.

Single machine scheduling problems with subcontracting options

In this paper, we study a scheduling model as follows: there are n jobs which can be processed in house on a single machine or subcontracted to a subcontractor. If a job is subcontracted, its processing cost is different from the in-house cost and its delivery lead time is a stepwise function of the total processing time of outsourced jobs. Two objective functions are studied (1) to minimize the weighted sum of the maximal completion time and the total processing cost and (2) to minimize the weighted sum of the number of tardy jobs and the total processing cost. For the first problem, we prove that it is NP-hard and get a pseudo-polynomial time algorithm. For the second problem, we prove that it is NP-hard and get a pseudo-polynomial time algorithm for a special case.

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Applying selected quality management techniques to diagnose delivery time variability

PurposeThis research seeks to identify and apply techniques that can be used in a supply chain context to diagnose the causes of variability in delivery lead time.Design/methodology/approachA literature review was conducted and a number of quality management (QM), techniques were selected as candidates for diagnosing delivery time variability. A case study of the application of these techniques is provided on the UK‐based defence supply chain that supported UK operations in the Iraq war of 2003.FindingsCandidate QM techniques for diagnosing delivery time variability were identified, namely: Process Chart; Histogram; Failure Mode and Effect Analysis; and Cause and Effect Analysis. These techniques were successful in enabling the diagnosis of the causes of delivery time variability in the context of the case study investigated.Practical implicationsThe work illustrates how QM techniques can be employed to address issues with supply chains, not least with regard to the important problem of variability in delivery leadtime. In practice, this highlights benefits that result to practitioners in order to improve the performance of operations in a dynamic setting, such as the defence supply chain studied here.Originality/valueThis work has value in presenting the findings of an in‐depth case study on the application of QM techniques in a multi‐echelon supply chain setting. It is also original in employing the FMEA technique together with an end‐customer perspective to assess the effect of failure modes in operations across a supply chain. FMEA also provided the means to examine supply chain risk, thus providing a research instrument for deploying risk as a lens. The application of QM techniques in this novel setting provides support for their application beyond the conventional setting of internal operations.

Analyzing the Lead Time and Shipping Lot-Size in a Chaotic Supply Network

Supply network issues recently have attracted a lot of attention from industrial practitioners and academics worldwide. Supply networks are highly complex systems. The oscillations in demand and inventory as orders pass through the system have been widely studied in literature. Studies have shown that supply networks can display some of the key characteristics of chaotic systems. Chaos theory is the study of complex, nonlinear, dynamic systems; therefore it can be useful for studying the dynamics of supply networks. In this paper the authors implemented a system dynamic approach and simulated a chaotic multi-level supply network. The authors analyzed the effects of decision parameters, delivery lead time and shipping lot-size on chaotic behavior of the whole supply network. The simulation revealed that an increment in lead times or shipping lot-size has a similar impact on chaotic behavior of the system and reduces the chance of chaotic behavior occurrence.

Ant Colony Algorithm for Just-in-Time Job Shop Scheduling with Transportation Times and Multirobots

Handling rapidly evolving technology and almost daily changes in demand and customer satisfaction, while maintaining competitiveness in a highly competitive environment, requires good coordination and planning of both production and logistics activities on the shop floor, namely: machines and tools. The goal is to optimize costs and reduce delivery lead times in order to provide the customer just in time; we focus on the job shop scheduling problem (JSSP), which is one of the most complex problems encountered in real shop floor. In this paper, we study a generalized (JSSP) including transportation times and a set of additional constraints on the number of transporter vehicles and their multiple transfer capabilities and also on the limited capacity of input/output of machines. The objective is to minimize in one hand tardiness and earliness penalties on delays and advances compared to the lead-time delivery of finished jobs and on the other hand the number of empty moves of transporter vehicles.

Myopic optimal policy for a multi-period, two-delivery-lead-times, stochastic inventory problem with minimum cumulative commitment and capacity

This paper studies a single-product, multi-period, stochastic inventory problem that imposes the lower and upper bounds on the cumulative order quantity during a planning horizon and allows two delivery lead times. This model includes three features. The first one is that a buyer purchases a fixed capacity from a supplier at the beginning of a planning horizon and the buyer’s total cumulative order quantity during the planning horizon is constrained with the capacity. The second one is that the buyer agrees to purchase the product at least a certain percentage of the purchased capacity during the planning horizon. The third one is that the supplier allows the buyer to order the product with two-delivery-lead-times. We identify conditions under which a myopic ordering policy is optimal. We also develop an algorithm to calculate the optimal capacity when the minimum cumulative order quantity commitment is a certain percentage of the capacity. We then use the algorithm to evaluate the effect of the various parameters on the buyer’s minimum expected total cost during the planning horizon. Our computation shows that the buyer would benefit from the commitments and two-delivery-lead-times.

Setting planned lead times for a make-to-order production system with master schedule smoothing

This article considers a make-to-order manufacturing environment with fixed guaranteed delivery lead times and multiple product families, each with a stochastic demand process. The primary challenge in this environment is how to meet the quoted delivery times subject to fluctuating workload and capacity limits. The tactical planning parameters are considered, namely, the planning windows and planned lead times. The planning process that is modeled is the one in which the demand represents a dynamic input into the master production schedule. A planning window for each product family controls how the schedule of each product family is translated into a job release. It can be thought of as the slack that exists when the fixed quoted delivery lead time is longer than the total planned production lead time. Furthermore, the planned lead time of each station regulates the workflow within a multi-station shop. The model has underlying discrete time periods to allow the modeling of the planning process that is typically defined in time buckets; within each time period, the intra-period workflow that permits multiple job movements within the time period is modeled. The presented model characterizes key performance measures for the shop as functions of the planning windows and planned lead times. An optimization model is formulated that is able to determine the values of these planning parameters that minimize the relevant production-related costs. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for additional results of the simulation study in Section 6 of this manuscript.]

An international supplier selection model with inventory and transportation management decisions

In this paper, we develop a mixed integer programming model for a supplier selection problem in an international context. The main features that characterize the international supplier selection are first identified. We show that when operating in an international context, the supplier selection process should consider the following issues: several buyers’ sites; inventory decisions, in particular the safety stocks that are held by buyers to cope with the delivery lead time uncertainty; inventory capacity constraints in buyers’ sites; selection of transportation modes, each having a specific delivery frequency and a transportation capacity; and multiple products and multiple time periods. Then, we propose a supplier selection model that takes into account such characteristics and that is suited for the international context. Finally, we solve the model with the commercial optimization software Cplex and we perform computational experiments based on a realistic case study from the automotive industry in order to prove the solvability and the usefulness of the model. Sensitivity analyzes are also performed for a number of model parameters.

Soil simulant sourcing for the ExoMars rover testbed

ExoMars is the European Space Agency (ESA) mission to Mars planned for launch in 2018, focusing on exobiology with the primary objective of searching for any traces of extant or extinct carbon-based micro-organisms. The on-surface mission is performed by a near-autonomous mobile robotic vehicle (also referred to as the rover) with a mission design life of 180 sols (Patel et al., 2010). In order to obtain useful data on the tractive performance of the ExoMars rover before flight, it is necessary to perform mobility tests on representative soil simulant materials producing a Martian terrain analogue under terrestrial laboratory conditions. Three individual types of regolith shown to be found extensively on the Martian surface were identified for replication using commercially available terrestrial materials, sourced from UK sites in order to ensure easy supply and reduce lead times for delivery. These materials (also referred to as the Engineering Soil (ES-x) simulants) are: a fine dust analogue (ES-1); a fine aeolian sand analogue (ES-2); and a coarse sand analogue (ES-3). Following a detailed analysis, three fine sand regolith types were identified from commercially available products. Each material was used in its off-the-shelf state, except for ES-2, where further processing methods were used to reduce the particle size range. These materials were tested to determine their physical characteristics, including the particle size distribution, particle density, particle shape (including angularity/sphericity) and moisture content. The results are analysed to allow comparative analysis with existing soil simulants and the published results regarding in situ analysis of Martian soil on previous NASA (National Aeronautics and Space Administration) missions. The findings have shown that in some cases material properties vary significantly from the specifications provided by material suppliers. This has confirmed the need for laboratory testing to determine the actual parameters to prove that standard geotechnical processes are indeed suitable. The outcomes have allowed the confirmation of each simulant material as suitable for replicating their respective regolith types.

Developing a reconfigurability index using multi-attribute utility theory

Reconfigurable manufacturing systems (RMSs) have been acknowledged as a promising means of providing manufacturing companies with the required production capacities and capabilities. This is accomplished through reconfiguring the system elements over the time for a diverse set of individualised products often required in small quantities and with short delivery lead time. This necessitates the requirement of mapping the manufacturing system capabilities and other characteristics by developing a suitable index. In this paper an index has been developed to measure the reconfigurability of RMSs keeping in mind their various core characteristics such as modularity, scalability, convertibility and diagnosability. These characteristics have been mapped together using multi-attribute utility theory. One could easily use this index to find the reconfigurability of a system possessing different characteristics. An illustrative example is provided to reveal the application of the proposed methodology on a given system. Insight gained would be of much interest to the decision makers managing the complexity of a manufacturing system for diversified products.

Performance measurements in supply chains within Swedish industry

A critical issue for a company to gain a competitive position is to improve its supply chain performance. This study investigates with interviews how 30 Swedish companies in ten different sectors define an excellent supply chain and work with Supply Chain Management, performance measurements and Supply Chain Costs. It shows that the companies define excellence more by a performance focus than a cost focus. Delivery precision, inventory turnovers (days of inventory) and lead time are the most common performance measurements. The costs of the supply chain are measured in many different ways and with different accuracy.

Coordinating a supply chain with a quality assurance policy via a revenue-sharing contract

This paper explores coordination of a (global) supply chain consisting of one manufacturer and one retailer via a revenue-sharing contract, where a product quality assurance policy is provided and the utility of consumer is sensitive to product (physical) quality, service quality (i.e., reciprocal of delivery lead-time) and retail price. We assume that the supply chain operates in a make-to-order (MTO) environment and a defective product is returned to the manufacturer for remanufacturing free. We give the optimal service quality and pricing decisions of the decentralised supply chain, its coordination mechanism and the Pareto condition of coordination mechanism. In the decentralised setting, although a higher defective rate of the final product implies a higher cost for the manufacturer, the optimal service quality first decreases and then increases and the optimal retail price decreases as the defective rate increases, which differs from the effects of the unit remanufacturing cost due to the service reliability constraint and the effects of the defective rate on the market scale and lead-time sensitivity; when the supply chain is coordinated, comparing to the traditional models without considering service quality, the manufacturer charges the retailer a higher unit wholesale price. The effect of the defective rate on the Pareto range of coordination mechanism is inconsistent with that of the unit production cost because the defective rate directly influences the demand rate.

Component Commonality and Order Matching Rules in Make-to-Forecast Production

Make-to-forecast production is a way to realize high customization and fast responsiveness. This study firstly investigates the effect of introducing a common component in a make-to-forecast production environment. The common component can eliminate a modification step, which is a major cost component in make-to-forecast production. It is illustrated, however, that introducing a versatile component that merely covers several variants is unattractive, and thus adding values to the common component is inevitable in this environment. Secondly, an order-matching rule under the condition that two partially overlapped delivery lead time intervals exist is proposed. The rule considers the effect of matching orders to units that can cover both intervals. An alternative re-matching rule is also developed and examined. Numerical experiments clarify that the proposed rule generally realizes higher contribution ratio and lower percentages of orphans and rejected orders. The proposed re-matching rule increases the average contribution ratio at the expense of increased orphans and order rejections.