Supply Chain Inventory Control Research Articles

Implementation of an Enterprise Resource Planning (ERP) System and its Impact on Manufacturing Company Operational Efficiency

This article explores the implementation of an Enterprise Resource Planning (ERP) system and its consequential impact on operational efficiency within manufacturing companies. The research delves into the intricate process of integrating ERP systems, emphasizing their role in streamlining various business functions such as supply chain management, production planning, and inventory control. The study investigates the challenges faced during the ERP implementation phase and elucidates strategies employed to overcome these hurdles. It also examines the role of employee training and change management in ensuring a smooth transition to the new system, emphasizing their pivotal contribution to operational success. Furthermore, the article meticulously analyzes the tangible outcomes of ERP implementation, focusing on key performance indicators (KPIs) that gauge improvements in operational efficiency. This includes reductions in production lead times, enhanced accuracy in demand forecasting, and optimized resource allocation. The research methodology incorporates case studies and empirical data from manufacturing companies that have undergone ERP implementation. Comparative analyses highlight the variations in operational efficiency before and after ERP adoption, providing a comprehensive understanding of the system’s impact. The findings underscore the positive correlation between ERP implementation and operational efficiency, offering insights that contribute to the body of knowledge in both information systems and manufacturing management. Additionally, the article discusses potential challenges that may persist post-implementation and proposes ongoing strategies for continuous improvement. In conclusion, this article contributes valuable insights into the dynamics of implementing ERP systems in manufacturing companies, shedding light on their transformative impact on operational efficiency and providing a foundation for future research in the field.

Beyond Traditional Boundaries: Embracing Digital Transformation for Enhanced Management Efficiency at Micro and Small Business Enterprisess

This research study explores the role of digital transformation in improving management efficiency in micro and small enterprises (MSEs) in West Java. The objectives of this study were to understand the adoption of digital technology among MSEs, assess its impact on management efficiency, and identify perceived benefits and challenges related to digital transformation. Data was collected through interviews and surveys with MSE owners and managers. Findings indicate significant adoption of digital technologies among MSEs, resulting in improved supply chain management, inventory control, decision-making, and customer relationship management. Perceived benefits include increased productivity, cost savings, improved customer satisfaction, and enhanced competitiveness. However, challenges such as limited resources, lack of digital skills, and resistance to change have been identified. These findings highlight the importance of embracing digital transformation to improve management efficiency in MSEs, while recognizing the need for targeted support and resources to address related challenges.

An Improved Approach for Reader Anti-Collision in Industrial Internet of Things

Radio-frequency identification (RFID) technology has been used in numerous applications, e.g., supply chain management and inventory control. This paper focuses on the practically important problem of reader-to-reader collision in large-scale RFID systems. There are many technical challenges during the existing work such as high computational complexity and low identification efficiency. To tackle the above challenges, this paper proposes a novel reader anti-collision protocol optimized by minimal reverse weight (NRA-MRW), which includes two phases. Extensive simulation results show that our proposed NRA-MRW can improve the identification efficiency and system throughput over the existing protocols by 25.2% and 12.3%, respectively.

Impact of Variable Deterioration Rate of Perishable Food Items on Multi-Echelon Distribution Chains

Customer satisfaction is the backbone of any business entity and supply chain optimization plays a vital role in customer satisfaction efforts. Supply chain inventory control is one of the scientific supply chain optimization methods for determining proper inventory levels at different stages or echelons of the supply chain to meet the requirements of the customers. The intention is to supply right type of material at exact time in appropriate quantities and at competitive rates. Supply chain inventory costs consist of costs to store, track and insure materials. Inventories that mishandled create substantial financial problems for a business, whether the mismanagement results in an inventory accumulation or an inventory shortage. Therefore, an examination of the right quantities to be kept in stock to meet the requirements, the strategic location, storage facilities and recordings of the goods or items should be done systematically such that the desired degree of service can be provided at competitive prices or at minimum ultimate cost. Major objective of inventory control in a multi echelon supply chain is to optimize inventory cost elements like transportation cost, carrying cost, holding cost and all other inventory related costs at all supply chain stages with an elevated service level at the end customer point. The supply chain inventory control becomes tough when the handling material is a perishable one as its deterioration rate is variable rather than constant. This article provides the study results of the deterioration rate of a perishable edible inventory at different selected environmental conditions. The focus of this article is to introduce a mathematical equation for the deterioration rate of the selected perishable inventory which is inevitable for the formulation of inventory models for its supply chain echelons.

Research on Supplier Collaboration of Daily Consumer Goods under Uncertainty of Supply and Demand

This paper establishes the decentralized decision-making model of consumer goods, the active collaboration model of consumer goods suppliers, and the decentralized decision-making model of customized consumer goods. Through formula derivation and simulation, the benefit and influence differences of the three modes are compared. This paper studies the influence of supplier’s active collaboration on the supply and demand instability of consumer goods and discusses the ideal value of supply chain inventory control. In China’s modern circular economy, the inventory control of the consumer goods supply chain is unscientific and nonstandard. We discuss a new inventory control method and study the ideal value of supply chain inventory control. It helps reduce the inventory shortage loss caused by the uncertainty of daily consumer goods, improve the efficiency of the supply chain, enhance the liquidity of supply chain inventory to achieve the purpose of increasing economic value. It has reference value for the inventory control of consumer goods in other countries and regions. The results show that under certain conditions, the horizontal collaboration between suppliers can improve the completeness of consumer goods. The collaboration between suppliers can reduce the hidden dangers caused by the uncertainty of supply and demand and significantly reduce the total inventory cost of manufacturers and improve profits.

Reader Scheduling for Tag Population Estimation in Multicategory and Multireader RFID Systems

Radio Frequency Identification (RFID) technology has been used in numerous applications, e.g., supply chain management and inventory control. This paper focuses on the practically important problem of the rapid estimation of the number of tags in large‐scale RFID systems with multiple readers and multicategory RFID tags. RFID readers are often static and have to be deployed strategically after careful planning to cover the entire monitoring area, but reader‐to‐reader collision (R2Rc) remains a problem. R2Rc decreases the reliability of the estimation of the tag population size, because it results in the failure of communication between the reader and tags. In this paper, we propose a coloring graph‐based estimation scheme (CGE), which is the first estimation framework designed for multireader and multicategory RFID systems to determine the distribution of tags in different categories. CGE allows for the use of any estimation protocol to determine the number of tags, prevents R2Rc, and results in higher time efficiency and less power‐consumption than the classic scheduling method DCS.

Supplier Selection for Spare Parts Supply Chain Networks

Spare parts management encompasses all the spare parts decisions; thus, it has a significant impact on the company results. This paper studies the integration of supply chain network design and inventory control decisions into the spare parts management context. The paper presents a modelling structure that integrates supplier selection, warehouse location, consumption point assignments, and inventory control decisions in order to optimize the total system cost while satisfying the company requirements. Additionally, the proposed structure incorporates sourcing strategy selection (i.e. warehousing or cross-docking strategies). A decomposition-based solution strategy is proposed based on the Generalized Benders Decomposition approach. The modelling structure is specified considering an inventory control policy widely used in industrial sites. The proposed integrated approach is focused on supporting the decision-making process yielding a spare parts supply chain system performance improvement.

Sistem Pengendali Inventori Supply Chain Dengan Pendekatan Probabilitas Pada Industri Pakaian

Inventory control systems have an important role in supply chain management to control process of production, inventory and distribution of products in accordance with rapidly changing consumer demand. The research aims to develop inventory control system on supply chain that can manage the number of production and supply of products based on variables of consumer demand and lead time. Supply chain inventory control systems are designed using model of supply chain inventory control within the information system framework. Model of inventory control using variable of demand lead time is designed by probability approach. Input to the system are data of demand and lead time sent by retail. The results of research provide theory of supply chain inventory control system with probability approach, especially on developing the theory of probability distribution for combined variables from two random variables of normal distributed. Inventory control system used to determine safety stock and reorder point as the basis for determining the replenishment stock. Furthermore by the system, supply chain management can manage the estimation of production number, and manage inventory and stock number of products in warehouse, supplier and retail in accordance with the consumer demand.

Inventory Strategy of Dual-Channel Supply Chain from Manufacturer's Perspective

Compared with the traditional retail channel, the online channel has advantages such as wide coverage, low cost and small time limit. Manufacturers with dual channels can increase market share and reduce operating costs. However, the incoordination between channels and the lack of management methods make it difficult to implement the dual-channel supply chain. The supply chain which contains both offline and online sales channels has gradually become an important part of the supply chain research. The inventory management is an important factor influencing enterprise operating cost and supply chain efficiency. As there are many uncertain factors in the supply chain system, inventory management becomes one of the difficulties that manufacturing enterprises face when expanding the online channel. Different from the traditional supply chain inventory control, the dual-channel supply chain inventory management has its own characteristics. From the perspective of manufacturing enterprises, this paper takes the dual-channel supply chain as the research object. The profit models were established under the independent inventory strategy, centralized inventory strategy and a strategy where the online channel is outsourced to a third party. The optimal inventory and maximum profit under different operation modes are solved and compared with each other through numerical simulation analysis. The study provide guidance for inventory management of manufacturing enterprises to reduce operating costs and improve the efficiency of supply chain.

A green supply chain model of vendor and buyer for remanufacturing

Due to environmental protection and limited resource utilization at optimum level, remanufacturing of defective products or reused products is an essential strategy in green supply chain inventory control system. This paper presents a green supply chain inventory model for integrated production of new items and remanufacturing of redeemable returned items under a situation in which the vendor provides the buyer with a permissible delay of payments and supplies the serviceable items to the buyer on lot-for-lot basis. It is assumed that every member of the chain is ready to collaborate for the maximum benefit of the supply chain. A mathematical formulation is developed to derive the optimal number of deliveries and the replenishment cycle time for the integrated vendor-buyer inventory model. Theoretical results show the global optimality of the solution and it is concluded that the collaboration is profitable for the chain and participating members reach the optimal level under co-operative decision making. Numerical analysis is given to illustrate the theoretical results. Finally, a sensitivity analysis is reported to study the effect of various parameters.

The Effects of Supply Chain Visibility, Supply Chain Flexibility, Supplier Development and Inventory Control Toward Supply Chain Effectiveness

Purpose – The purpose of this study is to examine the significance of supply chain strategies – visibility and flexibility supply chain – as well as the supplier development and inventory control towards the supply chain effectiveness. Design/methodology/approach – Applying the strategic – choice theory and the resource – based view of firms to the supply chain, in this study a research model are developed to demonstrate the premise that implementing proper supply chain practices to support and execute supply chain strategy that will enhance the effectiveness of the supply chain. The study utilizes survey data from 100 senior executive and managers in the purchasing and supply chain functions from manufacturing firms in Malaysia. The results are based on regression analysis and equation modelling by using SPSS software. Findings – The study finds that all supply chain strategies, namely, supply chain visibility, supply chain flexibility, supplier development and inventory control have a positive relationship towards the supply chain effectiveness. Practical Implications – For supply chain practitioners, the results indicate that firms benefit greatly if they consider the strategies of their supply chain and that such a matching yield to improve the supply chain effectiveness. Originality/value – The paper theoretically develops logic and empirically shows that all of the supply chain strategies are appropriate practices for mediating the impact on supply chain effectiveness. Considered at a higher level of abstraction, there relationships indicate a contribution to theory that explains how supply chain strategy can result in supply chain effectiveness, through the concurrent deployment of appropriately matched supply chain practices.

Fast and Adaptive Continuous Scanning in Large-Scale RFID Systems

Radio Frequency Identification (RFID) technology plays an important role in supply chain logistics and inventory control. In these applications, a series of scanning operations at different locations are often needed to cover the entire inventory (tags). In such continuous scanning scenario, adjacent scans inevitably read overlapping tags multiple times. Most existing methods suffer from low scanning efficiency when the overlap is small, since they do not distinguish the size of overlap which is an important factor of scanning performance. In this paper, we analytically unveil the fundamental relationship between the performance of continuous scanning and the size of overlap, deriving a critical threshold for the selection of scanning strategy. Further, we design an accurate estimator to approximate the overlap. Combining the estimate and a compact data structure, an adaptive scanning scheme is introduced to achieve low communication time. Through detailed analysis and extensive simulations, we demonstrate that the proposed scheme significantly outperforms previous approach in total scanning time.

Evaluating predictive count data distributions in retail sales forecasting

Massive increases in computing power and new database architectures allow data to be stored and processed at finer and finer granularities, yielding count data time series with lower and lower counts. These series can no longer be dealt with using the approximative methods that are appropriate for continuous probability distributions. In addition, it is not sufficient to calculate point forecasts alone: we need to forecast entire (discrete) predictive distributions, particularly for supply chain forecasting and inventory control, but also for other planning processes. However, tools that are suitable for evaluating the quality of discrete predictive distributions are not commonly used in sales forecasting. We explore classical point forecast accuracy measures, explain why measures such as MAD, MASE and wMAPE are inherently unsuitable for count data, and use the randomized Probability Integral Transform (PIT) and proper scoring rules to compare the performances of multiple causal and noncausal forecasting models on two datasets of daily retail sales.

A Simulation-Based Optimization Method for Solving the Integrated Supply Chain Network Design and Inventory Control Problem under Uncertainty

A Simulation-Based Optimization Method for Solving the Integrated Supply Chain Network Design and Inventory Control Problem under Uncertainty

Cyclic inventory routing in a line-shaped network

The inventory routing problem (IRP) is a very challenging optimization task that couples two of the most important components of supply chain management, i.e., inventory control and transportation. Routes of vehicles are to be determined to repeatedly resupply multiple customers with constant demand rates from a single depot. We alter this basic IRP setting by two aspects: (i) only cyclic tours are allowed, i.e., each vehicle continuously tours its dedicated route, and (ii) all customers are located along a line. Both characteristics occur, for instance, in liner shipping (when feeder ships service inland ports along a stream) and in facility logistics (when tow trains deliver part bins to the stations of an assembly line). We formalize the resulting problem setting, identify NP-hard as well as polynomially solvable cases, and develop suited solution procedures.

BARCODE AND RFID: TWO TECHNOLOGIES USED IN LOGISTICS TO IDENTIFY PHYSICAL PRODUCTS

ABSTRACT Barcodes and RFIDs (Radio Frequency Identification) are similar in that they are both physical products identification technologies, meaning they automate the process of collecting data; but, they also differ in various characteristics. Even though this comparison indicates some advantages of RFID over barcodes, RFID does not completely substitutes barcode technology. Barcodes offer some advantages over RFID, most particularly their low cost; thus, if an enterprise (specifically oriented to supply chain management and/or inventory control) is searching for an optimization of the relationship between cost and time for the process of data collection; then, a combined use of both technologies will be the most appropriate. Some characteristic properties and operational ranges are presented; moreover, an operating ratio (RFID / Barcode) is proposed. Keywords Barcode, RFID, operating ratio (RFID / Barcode), Turkey statistical method for detecting outliers

Grammatical evolution in developing optimal inventory policies for serial and distribution supply chains

Recently, there has been a growing literature on biologically inspired algorithms, particularly genetic algorithms and genetic programming, applied to supply chain modelling and inventory control optimisation. Due to the rigidity of the genetic algorithms approach, it is difficult to change the underlying model logic and add richness to the supply chain. While genetic programming provides a more flexible approach than that provided by genetic algorithms, to date its application has been limited to small supply chain modelling problems in relation to optimal inventory policies. This research applies Grammatical Evolution, a relatively new biologically inspired algorithm, to the field of supply chain optimisation, employing human readable rules called grammars. These grammars provide a single mechanism to describe a variety of complex structures and can incorporate the domain knowledge of the practitioner to bias the algorithm towards regions of the search space containing better solutions. Results are presented showing Grammatical Evolution is at least competitive in cost terms, and superior in flexibility, with these methods applicable to any supply chain of the serial or distribution type. Furthermore, Grammatical Evolution shows an adaptive ability that augurs well for supply chains in dynamic environments, such as disruption.

Probabilistic Optimal Tree Hopping for RFID Identification

Radio frequency identification (RFID) systems are widely used in various applications such as supply chain management, inventory control, and object tracking. Identifying RFID tags in a given tag population is the most fundamental operation in RFID systems. While the Tree Walking (TW) protocol has become the industrial standard for identifying RFID tags, little is known about the mathematical nature of this protocol, and only some ad hoc heuristics exist for optimizing it. In this paper, first we analytically model the TW protocol, and then using that model, propose the Tree Hopping (TH) protocol that optimizes TW both theoretically and practically. The key novelty of TH is to formulate tag identification as an optimization problem and find the optimal solution that ensures the minimal average number of queries or identification time as per the requirement. With this solid theoretical underpinning, for different tag population sizes ranging from 100 to 100 K tags, TH significantly outperforms the best prior tag identification protocols on the metrics of the total number of queries per tag, the total identification time per tag, and the average number of responses per tag by an average of 40%, 59%, and 67%, respectively, when tag IDs are nonuniformly distributed in the ID space, and of 50%, 10%, and 30%, respectively, when tag IDs are uniformly distributed.

Fast and Accurate Estimation of RFID Tags

Radio frequency identification (RFID) systems have been widely deployed for various applications such as object tracking, 3-D positioning, supply chain management, inventory control, and access control. This paper concerns the fundamental problem of estimating RFID tag population size, which is needed in many applications such as tag identification, warehouse monitoring, and privacy-sensitive RFID systems. In this paper, we propose a new scheme for estimating tag population size called Average Run-based Tag estimation (ART). The technique is based on the average run length of ones in the bit string received using the standardized framed slotted Aloha protocol. ART is significantly faster than prior schemes. For example, given a required confidence interval of 0.1% and a required reliability of 99.9%, ART is consistently 7 times faster than the fastest existing schemes (UPE and EZB) for any tag population size. Furthermore, ART's estimation time is provably independent of the tag population sizes. ART works with multiple readers with overlapping regions and can estimate sizes of arbitrarily large tag populations. ART is easy to deploy because it neither requires modification to tags nor to the communication protocol between tags and readers. ART only needs to be implemented on readers as a software module.

Automobile Industry Supply Chain Inventory Modeling and Optimization Based on MPC

To model the automotive supply chain accurate for deep research,the basic model of automobile supply chain inventory management in the method of advanced control theory is established here. Through anglicizing the inventory of each node in the supply chain under stock replenishment strategy, the bullwhip effect in upstream enterprise of automobile industry supply chain inventory is proved. The method of Model Predict Control is taken in the simulation of the optimization model. Simulation results shows that the model predictive control method for each node in the supply chain inventory control has the characteristics of agility and overall and it has the practical value in restraint the bullwhip effect.