Inventory Management Research Research Articles

Investigation about Inventory Management Model for Raw Materials in Steel Industry

With the continuous development of the economy, the steel industry, as one of the important components of the national economy faces lots of challenges. Effective inventory management for firms can not only achieve the optimal state of inventory cost benefit but also improve the efficiency of capital use, which can also improve the efficiency of the firm’s operational management. It is of great significance to enhance the market competitiveness of enterprises. This article examines raw material inventory management in steel companies. As the world's second-largest steel producer, Japan's high dependence on imported raw materials makes it a typical example of how Japanese steel companies manage their inventory levels. This paper focuses on Kosuke Kawakami's model of a non-flush gamma process for Nippon Steel Corporation, which has been effective in reducing inventory levels in practice. The paper then suggests ways of optimizing the model in light of new research in inventory management in recent years.

Estimating the reorder point for a fill-rate target under a continuous review policy in the presence of non-standard lead-time demand distributions

Skewed and multimodal lead-time demand (LTD) distributions can be present in supply chains. Under these conditions, logistics managers find that conventional approaches, which assume standard LTD distribution shapes, yield unreliable estimates of a single item’s reorder point (ROP) in relation to meeting fill-rate targets under a continuous review inventory policy. Furthermore, logistics managers have limited data available from which to determine the true shape of the underlying LTD distribution. In this study, I present a non-parametric bootstrap approach to set a least-biased estimate of the ROP. In addition, to deriving bootstrap expressions for non-standard LTD shapes, I derive expressions for standard distribution shapes to estimate the ROP across a range of fill rates. Thus, eliminating the double counting of stockouts with conventional fill-rate measures. Using Monte Carlo simulation experiments, I show that in comparison to the conventional state-of-the-art approaches the non-parametric bootstrap approach yields the least-biased ROP estimates robust to both the shape of the LTD distribution and the sample size. This research offers more accurate ROP estimators, which can serve as a basis for expanding the scope of future inventory management research and enabling logistics managers to reduce inventory while maintaining and even improving fill rates.

Analysis of Inventory Level Optimization Using PSONN Model and Fuzzy Logic Approach

Raw materials, intermediate goods and finished goods are termed as inventories while considering it as portion of business’s assets which can be considered as prepared or are prepared for sale. One of the suitable solutions is to design optimal inventory model. Major concern of industry is to design suitable inventory model. Some of the existing inventory management research work are discussed in literature. But this field is still a big area of interest. Many research works used artificial intelligence models for inventory management. One amongst the area for inventory management is worker behavior in a company. So, employees are taken into account to be as an inventory that contributes in growth of an organization. Employee attrition may be a big issue for the organizations specially once trained, technical and key staff leave for a far better chance from the organization. This results in financial loss to replace a trained employee. Therefore, this paper uses the current and past employees’ data to analyze attrition behavior of employees and to provide bonus/promotion to employees having non attrition behavior by using PSONN and fuzzy rules. The result shows that the efficiency of model is improved with respect to existing methods by approximately 2%.

Lateral transshipment with partial request and random switching

A large body of inventory management research has been devoted to lateral transshipment. Most of the existent models assume that the unmet local demand will automatically request transshipment, and that the unmet local demand does not seek inventory at other locations within the same echelon. In contrast, we investigate a two-store retailer’s inventory replenishment and transshipment decisions when those two assumptions do not hold. Specifically, we use a fixed request rate to model partial demand for transshipment at the shortage store and a random switch rate to model the arrival of the unmet demand at the surplus store. We characterize the optimal transshipment and inventory replenishment policies. We find that it is not always in the best interest of the retailer to satisfy as much as possible the transshipment demand. In light of the switched demand flowing to the surplus store, the retailer may benefit from saving the leftover inventory at the surplus store for the switched demand. The optimal transshipment policy follows a double-threshold structure when the prospect of the switched demand is not large enough; and a transshipment quantity of zero becomes optimal otherwise. Through an extensive numerical analysis, we examine the impact of the request rate and the switch rate, together with other parameters. We also evaluate a few simple-to-use transshipment heuristics, including one that we devise based on the structure of the optimal transshipment policy. The consistent, near-optimal performance of the devised heuristic is a confirmation of the importance of our theoretical work on the optimal policy.

Employees Attrition Detection using PSONN

Raw materials, intermediate goods and finished goods are termed as inventories while considering it as portion of business’s assets which can be considered as prepared or are prepared for sale. One of the suitable solutions is to design optimal inventory model. Major concern of industry is to design suitable inventory model. Some of the existing inventory management research works are discussed in literature. But this field is still a big area of interest. Many research works uses artificial intelligence models for inventory management. One amongst the area for inventory management is worker behavior in a company. So, employees are taken into account to be as an inventory that contributes in growth of an organization. Employee Attrition may be a big issue for the organizations specially once trained, technical and key staff leave for a far better chance from the organization. This leads to loss to interchange a trained worker. Therefore, we use the present and past worker data to analyze attrition behavior of employees.

A bibliometric analysis of inventory management research based on knowledge mapping

Purpose The research mainly aims at the hotspot of inventory management by knowledge mapping and provides a visualization reference in this research field. Design/methodology/approach First, inventory management journals during 1986 to 2017 were selected as the research object and text formatting in the Web of Science (WOS) database is exported. Then inventory management knowledge mapping is done and clustering keywords are extracted by using CiteSpace and VOSviewer software. Based on co-word analysis, the three special clusters are exported: inventory optimization strategy, inventory pricing and inventory technology. Besides, the clustering structure and time evolution are analysed. Finally, bibliographic item co-occurrence matrix builder (BICOMB) was used to extract the “journal” and “researchers” keywords in the inventory management research fields. Setting three parameters such as the cited half-life, centrality, frequency and keywords for data mining, it can infer the trend keywords of future research. Findings Results showed that inventory management research has been abundant in literature over the past 30 years and has experienced a change from focusing on inventory optimization strategy to inventory pricing and inventory technology in process. It shows that inventory management research focused on the classic topics and includes economic order quantity, dynamic pricing, design and technology, and the new topics include channel coordination, hierarchical price and simulation. Research limitations/implications Based on knowledge mapping, this study is still relatively macro and cannot cover all areas of inventory management. This study only investigated the state of correlational research in WOS and Google Trends and not additional databases. Originality/value The current research mainly builds on knowledge mapping for the research hotspot of inventory management and provides visual references for future research in this field.

Process mining is an underutilized clinical research tool in transfusion medicine.

To understand inventory performance, transfusion services commonly use key performance indicators (KPIs) as summary descriptors of inventory efficiency that are graphed, trended, and used to benchmark institutions. Here, we summarize current limitations in KPI-based evaluation of blood bank inventory efficiency and propose process mining as an ideal methodology for application to inventory management research to improve inventory flows and performance. The transit of a blood product from inventory receipt to final disposition is complex and relates to many internal and external influences, and KPIs may be inadequate to fully understand the complexity of the blood supply chain and how units interact with its processes. Process mining lends itself well to analysis of blood bank inventories, and modern laboratory information systems can track nearly all of the complex processes that occur in the blood bank. Process mining is an analytical tool already used in other industries and can be applied to blood bank inventory management and research through laboratory information systems data using commercial applications. Although the current understanding of real blood bank inventories is value-centric through KPIs, it potentially can be understood from a process-centric lens using process mining.

Inventory management of supply chain with robust control theory: literature review

Supply chain management (SCM) has become a vital tool for organisations, which desire to improve performance and resilience. More and more attention in SCM has been dedicated to inventory. The great potential of control theory to handle inventory problems was evidenced since the early 1950s. In particular, the robust control which is devoted to dealing with uncertainties and minimising the worst case value of disturbances represents a useful tool to help research in inventory management. This paper aims to provide a review of 37 articles covering the application of robust control in modelling and control of inventory problems according to the considered uncertainties mainly in demand and delay time.

Inventory management of supply chain with robust control theory: literature review

Supply chain management (SCM) has become a vital tool for organisations, which desire to improve performance and resilience. More and more attention in SCM has been dedicated to inventory. The great potential of control theory to handle inventory problems was evidenced since the early 1950s. In particular, the robust control which is devoted to dealing with uncertainties and minimising the worst case value of disturbances represents a useful tool to help research in inventory management. This paper aims to provide a review of 37 articles covering the application of robust control in modelling and control of inventory problems according to the considered uncertainties mainly in demand and delay time.

Inventory management research for the fashion industry

Fashion products have a short-life-cycle with highly volatile demand uncertainty. This uncertainty leads to challenges in managing inventory, as matching supply and demand is always difficult in the fashion industry. In this paper, we review the recent literature on fashion industry inventory management. We classify the extant literature by four widely-used research methodologies, including analytical, empirical, case study and simulation approaches. We identify that inventory ownership, information technology, and incentive schemes for increasing inventory efficiency are the key factors to enhance inventory management in the fashion industry. We propose that inventory management of luxury fashion, sustainability in inventory, and empirical and case study approaches are the most important directions for future research.

Inventory management research for the fashion industry

Inventory management research for the fashion industry

A Review on Deteriorating Inventory Study

To provide a comprehensive introduction about the deteriorating items inventory management research status, this paper reviews the recent studies in relevant fields. Compared with the extant reviews (Raafat 1991; S.K.Goyal 2001), this paper reviews the recent studies from a different perspective. First, this paper proposes some key factors which should be considered in the deteriorating inventory studies; then, from the perspective of study scope, the current literatures are distinguished into two categories: the studies based on an enterprise and those based on supply chain. Literatures in each category are reviewed according to the key factors mentioned above. The literature review framework in this paper provides a clear overview of the deteriorating inventory study field, which can be used as a starting point for further study.

Dynamic planned safety stocks in supply networks

Safety stocks are commonly used in inventory management for tactically planning against uncertainty in demand and/or supply. The usual approach is to plan a single safety stock value for the entire planning horizon. More advanced methods allow for dynamically updating this value. We introduce a new line of research in inventory management: the notion of planning time-phased safety stocks. We assert that planning a time-phased set of safety stocks over a planning horizon makes sense because larger safety stocks are appropriate in times of greater uncertainty while lower safety stocks are more appropriate when demand and/or supply are more predictable. Projecting a vector of safety stock values is necessary to assure upstream members in the supply network have advanced warning of changes. We perform an empirical study of U.S. industry, which demonstrates that significant savings can be achieved by employing dynamic planned safety stocks, confirming recent case study reports. We provide a simple optimisation model for the problem of minimising inventory given a vector of safety stock targets. We propose a computationally efficient solution procedure and demonstrate its implementation in an MRP/ERP system. We then illustrate an MRP/ERP planning system feature, which employs a dynamic planned safety stock module that supports a production planner by showing the inventory implications of safety stock plans.

Replenishment policy for single item inventory model with money inflation

Finding out the replenishment policy is a hot topic of research in inventory management. In this article, we propose an optimal replenishment policy by considering stock dependent consumption rate for non instantaneous deteriorating items with money inflation and time discounting. In this model shortages are allowed and backlogging is partial. Solution procedure is given and explained with examples. The impact of various parameters of the system on the optimal solution is analyzed by carrying out sensitivity analysis with perturbations in various parameters.

A review of inventory management research in major logistics journals

PurposeThe purpose of this paper is to provide a review of inventory management articles published in major logistics outlets, identify themes from the literature and provide future direction for inventory management research to be published in logistics journals.Design/methodology/approachArticles published in major logistics articles, beginning in 1976, which contribute to the inventory management literature are reviewed and cataloged. The articles are segmented based on major themes extracted from the literature as well as key assumptions made by the particular inventory management model.FindingsTwo major themes are found to emerge from logistics research focused on inventory management. First, logistics researchers have focused considerable attention on integrating traditional logistics decisions, such as transportation and warehousing, with inventory management decisions, using traditional inventory control models. Second, logistics researchers have more recently focused on examining inventory management through collaborative models.Originality/valueThis paper catalogs the inventory management articles published in the major logistics journals, facilitates the awareness and appreciation of such work, and stands to guide future inventory management research by highlighting gaps and unexplored topics in the extant literature.

Resolving uncertainty in manufacturing systems

AbstractThis paper examines the effectiveness of three commonly practiced methods used to resolve uncertainty in multi‐stage manufacturing systems: safety stock under regenerative material requirements planning (MRP) updates, safety capacity under regenerative MRP updates, and net change MRP updates, i.e., continuous rather than regenerative (periodic) updates. The use of safety stock reflects a decision to permanently store materials and labor capacity in the form of inventory. When unexpected shortages arise between regenerative MRP updates, safety stock may be depleted but it will be replenished in subsequent periods. The second method, safety capacity, overstates the MRP capacity requirements at the individual work centers by a prescribed amount of direct labor. Safety capacity either will be allocated to unanticipated requirements which arise between MRP regenerations or will be spent as idle time. The third method, net change, offers a means of dealing with uncertainty by rescheduling instead of buffering, provided there is sufficient lead time to execute the changes in the material and capacity plans.Much of the inventory management research has addressed the use of safety stock as a buffer against uncertainty for a single product and manufacturing stage. However, there has been no work which evaluates the performance of safety stock relative to other resolution methods such as safety capacity or more frequent planning revisions. In this paper, a simulation model of a multi‐stage (fabrication and assembly) process is used to characterize the behavior of the three resolution methods when errors are present in the demand and time standard estimates. Four end products are completed at an assembly center and altogether, the end products require the fabrication of twelve component parts in a job shop which contains eight work centers. In addition to the examination of the three methods under different sources and levels of uncertainty, different levels of bill of material commonality, MRP planned lead times, MRP lot sizes, equipment set‐up times and priority dispatching rules are considered in the experimental design.The simulation results indicate that the choice among methods depends upon the source of uncertainty, and costs related to regular time employment, employment changes, equipment set ups and materials investment. For example, the choice between safety stock and safety capacity represents a compromise between materials investment and regular time employment costs. The net change method is not designed to deal effectively with time standard errors, although its use may be preferred over the two buffering alternatives when errors are present in the demand forecasts and when the costs of employment changes and equipment set ups are low. The simulation results also indicate that regardless of the method used, efforts to improve forecasts of demands or processing times may be justified by corresponding improvements in manufacturing performance.

Operations Research in Inventory Management: A Review and Critique

The objectives of inventory management, including the relevant related costs, are examined in this paper. A brief review of standard problems, that have been effectively solved, is presented. However, we point out that a serious gap exists between theory and practice in many organizations. Suggestions are made for bridging this gap. Finally, a list is provided of a number of research problems whose implementable solution would have a major beneficial impact on the practice of inventory management.