Inventory Control Strategy Research Articles

Inventory Control Using ABC Classification and Min-Max Stock Method in The Manufacture of Armored Vehicle Body Hull at PT XYZ

Research and development efforts are currently underway to enhance inventory control systems. However, fluctuations in demand often pose challenges to achieving optimal inventory management. To address this issue, it is crucial to establish efficient control measures that maintain an optimal inventory level. This study focuses on finding an effective approach for PT XYZ to manage stockpiles of raw materials for armored vehicle body hulls, aiming to prevent shortages or excessive stockpiling. The research uses the ABC categorization system and the min-max stock approach as its material inventory control strategies. Inventory classification, inventory turnover, the amount of safety stock, minimum stock, maximum stock, and order quantity are all determined using this procedure. By conducting a case study on PT XYZ's material inventory control for Panzer body hulls, it was identified that 3 materials fell under the important category (A), 3 materials in the moderate category (B), and 20 materials in the less critical category (C). The findings of this research are that the ABC method and min-max stock can be used as a reliable foundation for establishing inventory control parameters. Companies are advised to evaluate and consider the rules for each material, such as material costs, rare or not material types, and a history of delays from suppliers. These factors play a significant role in determining appropriate inventory control measures.

BIM Based Inventory Management in Construction of Residential Highrise Building in India

According to a study, construction materials account for more than 65 percent of a project's entire cost. Material Planning efficiency is critical to completing a project on scheduled time and on budget. This research paper focuses primarily on inventory control and materials planning using BIM process as this are the important pillars of material management. The S-curve analysis is used to determine how much the estimated materials cost differs from the market materials cost. Engineers and contractors are interviewed to determine the main reasons for this. Inventory management techniques such as ABC classification and economic order quantity (EOQ) analysis are performed. In most cases, S-curve analysis shows that actual material costs are greater than estimated material costs. BIM-based ABC and EOQ analyses are used to continuously maintain sufficient inventory, protect inventory materials from damage, reduce inventory costs, solve inventory problems, and maintain optimal inventory levels. A sensitivity check is applied to the results of the EOQ analysis. “The use of ABC classification and EOQ analysis can help to alleviate the stock-out of A class and B class materials that occur on building sites. Following the implementation of these easy inventory control strategies, the total inventory expenditure is reduced”.

Dynamic performance for discharging process of pumped thermal electricity storage with reversible Brayton cycle

Pumped thermal electricity storage (PTES) is suitable for large-scale energy storage applications because of its low cost and no geographical constraints. In this study, the performance of PTES system for adjusting the net power output of the heat engine cycle to meet the load demand variation, is investigated. Based on the off-design condition models of turbomachinery and heat exchangers, the heat engine cycle dynamic model of a 5 MW PTES system is established. The disturbance simulation of the user-side load is carried out, and the dynamic response results are obtained. The inventory control strategy of working fluid is proposed to control the net power output to follow the variations of the load demand. The traditional PI controller is used in the two control processes of 50% ramp-down in load demand and a typical day load demand in Zhangbei District of north China. The results indicate that the net power output of the heat engine cycle can follow the variation of load demand in time. With the inventory control strategy, the heat engine cycle mode of PTES system can adjust the net power output to meet changes in load demand.

Multi-Period Spare Parts Supply Chain Network Optimization under (T, s, S) Inventory Control Policy with Improved Dynamic Particle Swarm Optimization

Spare parts are the critical operation asset for ensuring a production line keeps going, which significantly improves the performance of manufacturing enterprises. This article pays attention to the joint optimization of spare part management and spare part supply chain network optimization in multiple supply periods. An extended (T, s, S) inventory control strategy is utilized to manage spare parts in customer nodes which can determine supply time, consumption and demand. In this spare part supply chain, the supply environment is different in different periods, so the mathematical model and solution method should be able to respond to and detect the environment change quickly. Hence, a dynamic nonlinear programming model is developed for optimizing inventory control decisions and spare part supply decisions so as to minimize the total cost. Furthermore, an improved self-adaptive dynamic migrating particle swarm optimization algorithm is proposed to solve the optimization problem. In this algorithm, a novel environment change detection and response strategy is applied to deal with the dynamic period in the spare part supply chain network. The results obtained show that the improved algorithm improves the computation time by eight percent and has better computational efficiency compared with the traditional algorithm.

Research on empty container transportation based on (D, U) control strategy under random demand

In order to effectively reduce the cost of empty container dispatching and transportation, an integer programming model for empty container dispatching and transportation with multiple periods and multiple ports was established, and the empty container dispatching and transportation scheme was optimized under the (D, U) inventory control strategy considering the service level. The results show that compared with no inventory control strategy, the (D, U) strategy can effectively reduce the total operating cost of liner companies. Select the service level for sensitivity analysis, and verify that (D, U) control strategy can effectively reduce the dependence of liner companies on container chartering.

Dynamic characteristics and control strategy of pumped thermal electricity storage with reversible Brayton cycle

The pumped thermal electricity storage (PTES) based on reversible Brayton cycle can effectively absorb the instability and periodic fluctuations of renewable energy. The dynamic model of heat pump cycle in 5 MW PTES system is established and the disturbance characteristics of the electric power input are obtained. The results indicate that the thermal energy storage temperature drops by 16.52K and the specific exergy loss of molten salt is 6.67% when the electric power input ramps down by 7%. Affected by thermal inertia, the variation trend of thermal energy storage temperature is obviously lagging behind the disturbance signal of electric power input. Inventory control strategy is employed to maintain the thermal energy storage temperature of the heat pump cycle, thereby maintaining energy quality of the thermal energy storage. During the 50% ramp-down progress of electric power input, the variation range of thermal energy storage temperature is within 1.87K and the specific exergy loss of molten salt is within 0.71% by the PI controller to adjust the total amount of working fluid inventory in the cycle. As the daily output of wind power plant is used as the electric power input of system, the variation range of thermal energy storage temperature is within 1.71K and the specific exergy loss of molten salt is within 0.65%, which further verifies the feasibility of the control strategy.

Application of ABC-VED analysis for inventory control in drug store of a tertiary care hospital of North Maharashtra

Abstract Introduction: The hospital's pharmacy is one of the most heavily used therapeutic services and one of the few places where a significant amount of money is spent on recurrent purchases. This underlines the need of strategically planning, creating, and arranging the pharmacy to ensure effective clinical and administrative services. Materials and Methods:Inventory control techniques like ABC, VED and ABC-VED matrix analysis were used to evaluate the annual drug expenditure at drug store of Government Medical College & Hospital Jalgaon for the financial year 2019-20. Results:Total number of drugs in inventory in Government Medical College & Hospital Jalgaon in the year 2019-20 were 334 and the annual drug expenditure was 54040462/-. Category A comprised of 49 drugs (14.7%) for which annual drug expenditure was 37286500/- i.e. 69%. 87 drugs (26%) accounting to 11324859/- (20.96%) were classified as category B drugs. Category C drugs included 198 drugs comprising 59.3% of total inventory and consumed 5429103/- i.e. 10.05% of total annual drug expenditure. 39 drugs (11.7%) were classified into vital/V category which accounted for 15257089/- i.e. 28.23% of annual drug expenditure, while essential/E category included 127 (38%) drugs for which 30161684/- (55.81%) was incurred for their procurement. 168 (50.3%) drugs accounting to 8621689/- (15.95% of total annual drug expenditure). Conclusion:The application of inventory control strategies such as ABC, VED, and the ABC-VED Matrix will help in significant improvements in patient care.

Two-stage supply chain inventory management based on system dynamics model for reducing bullwhip effect of sulfur product.

Bullwhip effect is prevalent in supply chains, creating supply and inventory risks that affect marketing, supply and production. However, there are limited researches on the optimization of chemical supply chain inventory management. In order to solve the above problem, this paper took the sulfur product supply chain of a sulfur plant as an example, combined with the idea of system dynamics, and systematically studied the inventory control strategy in the distributor-retailer two-level inventory system constituted by the supply chain. Firstly, the causal loop diagram was drawn according to the system relationship between variables in the two-level supply chain, and then the system dynamics model of sulfur product supply chain was formed. Finally, problems existing in the supply chain were explored through simulation, and optimization suggestions were submitted. It can be concluded from the simulation results that there was bullwhip effect in the sulfur product supply chain, and the delay of transportation time and the change of inventory adjustment time would have an impact on the inventory level of each node enterprise in the supply chain. Therefore, the method of building an information sharing platform, implementing visual information management, and adopting logistics transportation service outsourcing could enhance the information exchange among node enterprises, so as to improve the operational efficiency of the entire product supply chain.

Optimization on the multi-period empty container repositioning problem in regional port cluster based upon inventory control strategies

Within the area of regional port clusters, this paper establishes a multi-period mixed integer programming model to optimize the empty container repositioning between public hinterlands and ports, comprehensively considering the quantitative and periodic inventory control strategy. At the same time, this paper dynamically and heuristically determines the empty container inventory threshold (D, U) under quantitative strategy and S under periodical strategy at each port within the regional port clusters. On this basis, the empty container repositioning schemes between public hinterlands and ports are optimized by using Markov decision process combined with dynamic programming method. In addition, Liaoning coastal regional port cluster and its northeast hinterland are selected as the objects to solve this model and the results show that the total cost of shipping company can be saved by 14.16% and 11.92%, respectively, by the quantitative and periodical inventory control strategy. Selecting the quantity of public hinterland terminals, the empty container demand of public hinterland terminals and ports, the inventory threshold of empty containers and other factors, this paper carries on the sensitivity analysis. This paper validates inventory control strategy can weaken the shipping company in the influence of the external environment changes. And the quantitative inventory control strategy can reduce the total cost value to a greater extent and more effective in cost control than periodical strategy.

Research on Process Control Strategy of Asphalt Tank Inventory Based on Dynamic Programming Algorithm in Post Epidemic Era

Abstract Based on the background of post epidemic era, starting with the traditional industrial inventory process control, this paper discusses the dynamic inventory process control strategy under the asphalt tank inventory mode, and analyzes the intelligent inventory mode under the trend of intelligent logistics through the dynamic programming method, so as to provide reference for the development direction of intelligent inventory of unconventional storage materials such as chemical industry and energy. At the same time, with the recurrence of short-term epidemic and the dilemma of low return to work and production rate, through the integration and interconnection of mobile communication, intelligent analysis, digital management and other technologies with all links, the strategies of inventory dynamic control, inventory risk control, improving inventory efficiency and optimizing inventory cost are put forward.

Optimal pricing and inventory control strategy for a continuous-review system with product return

We consider joint pricing and inventory control strategies for a stochastic inventory system with product return. Customer's demand and product return follow independent point processes with demand rate being price-dependent. Using a general verification theorem, we prove that an (s⁎,S⁎,p⁎) policy is optimal, where the optimal price p⁎(x) is a quasi-concave function of inventory level with a nonpositive changeover point. Furthermore, we propose an algorithm to search for the optimal policy parameters and numerically study the effect of product return.

Inventory management of vertically differentiated perishable products with stock-out based substitution

The need for optimal inventory control strategies for perishable items is of the utmost importance to reduce the large share of food products that expire before consumption and to achieve responsible food stocking policies. Our study allows for a multi-item setting with substitution between similar goods, deterministic deterioration, delivery lead times and seasonality. Namely, we model demand by a linear discrete choice model to represent a vertical differentiation between products. The verticality assumption is further applied in a novel way within product categories. Specifically, the same product typology is vertically decomposed according to the age of the single stock-keeping unit in a quality-based manner. We compare two different policies to select the daily size of the orders for each product. On the one hand, we apply one of the most classical approaches in inventory management, relying on the Order-Up-To policy, modified to deal with the seasonality. On the other hand, we operate a state-of-the-art actor-critic technique: Soft Actor-Critic (SAC). Although similar in terms of performance, the two policies show diverse replenishment patterns, handling products differently.

Cross-Border Internet of Things E-Commerce Warehouse Control System Based on TRIZ Theory

Cross-border e-commerce of the Internet of Things is affected by international situations and political factors. Supply chain interruption and returns will cause violent fluctuations in commodity inventory, making the inventory control of cross-border e-commerce very difficult. The TRIZ principle is utilized to solve the problem of the difficulty to evaluate the suppliers comprehensively in e-commerce warehouse management. The Markov algorithm is used to describe the change of inventory level. The cyclic expected time and cost function are constructed by the horizontal crossing method, updating the process and Martingale theory. The effect of the correlation between the demand and supply interruption on the optimal inventory control strategy is studied by simulation. The change of the optimal control strategy under the different interrupt and return types is analyzed, and the validity of the management system is verified.

Leveraging customer engagement to improve the operational efficiency of social commerce start-ups

Despite the surge of literature on customer engagement (CE) in social media, few studies shed light on how to leverage CE to improve firms’ operational efficiency. This research proposes a fresh framework using social media data to improve demand forecasting accuracy, resulting in a cost-efficient inventory control strategy. Drawing upon the resource mobilization perspective in particular, this research quantifies the construct of CE from the view of input–output efficiency evaluation using the Data Envelopment Analysis (DEA) model, and then leverages CE to forecast consumer online demand and reconfigure inventory management strategy. Using a 71-week data set from a social commerce start-up in China, this research shows that this new framework dramatically increases demand forecasting accuracy and reduces operational costs in inventory management. This study contributes to the literature by demonstrating the value of social media data in improving operational efficiency, particularly regarding inventory management.

Solving a warehouse inventory control problem by Benders decomposition and the Lagrangian relaxation

In modern businesses, organizations hold large numbers of inventory items, but cannot find their inventory system economical to make policies for the management of individual inventory items. In this paper, a mathematical model is presented to classify inventory items, taking into account significant profit and cost reduction indices. The model has an objective function to maximize the net profit of items in stock. Limitations such as budget even inventory shortages are taken into account too. The mathematical model is solved by the Benders decomposition and the Lagrange relaxation algorithms. Then, the results of the two solutions are compared. The TOPSIS technique and statistical tests are used to evaluate and compare the proposed solutions with one another and to choose the best one. The results show that the Lagrange algorithm is more efficient for solving the model in terms of both computational time and quality. Subsequently, several sensitivity analyses are performed on the model, which helps inventory control managers determine the effect of inventory management costs on optimal decision making and item grouping. Finally, according to the results of evaluating the efficiency of the proposed model and the solution method, a real-world case study is conducted on the ceramic tile industry. Based on the proposed approach, several managerial perspectives are gained on optimal inventory grouping and item control strategies

Designing a new mathematical model based on ABC analysis for inventory control problem: A real case study

In modern business today, organizations that hold large numbers of inventory items, do not find it economical to make policies for the management of individual inventory items. Managers, thus, need to classify these items according to their importance and fit each item to a certain asset class. The method of grouping and inventory control available in traditional ABC has several disadvantages. These shortcomings have led to the development of an optimization model in the present study to improve the grouping and inventory control decisions in ABC. Moreover, it simultaneously optimizes the existing business relationships among revenue, investment in inventory and customer satisfaction (through service levels) as well as a company’s budget for inventory costs. In this paper, a mathematical model is presented to classify inventory items, taking into account significant profit and cost reduction indices. The model has an objective function to maximize the net profit of items in stock. Limitations such as budget even inventory shortages are taken into account too. The mathematical model is solved by the Benders decomposition and the Lagrange relaxation algorithms. Then, the results of the two solutions are compared. The TOPSIS technique and statistical tests are used to evaluate and compare the proposed solutions with one another and to choose the best one. Subsequently, several sensitivity analyses are performed on the model, which helps inventory control managers determine the effect of inventory management costs on optimal decision making and item grouping. Finally, according to the results of evaluating the efficiency of the proposed model and the solution method, a real-world case study is conducted on the ceramic tile industry. Based on the proposed approach, several managerial perspectives are gained on optimal inventory grouping and item control strategies.

Research on Multi-Echelon Inventory Optimization for Fresh Products in Supply Chains

Fresh products are perishable and fragile, which easily leads to higher inventory costs and requires reasonable planning of inventory management. Therefore, it is very important for fresh product supply chain systems to have multi-echelon inventory control. However, in past studies, few control models of the multi-echelon inventory considered the deterioration rate of perishable products as the variable factor. In this paper, on the basis of considering the perishable characteristics of fresh products, combining the deterioration rate with the inventory control model, a multi-echelon inventory control model for fresh products is designed and optimized, and the optimal solution from the whole supply chain is obtained through the optimal fitness function by genetic algorithm. Finally, Flexsim is used to simulate the two inventory strategies before and after optimization. After simulation comparison and analysis, it is verified that the optimized inventory control strategy has lower costs. The research results can help supply chain managers of fresh products to make inventory management decisions and save costs, which is of practical significance.

Integrated Optimization of the Location–Inventory Problem of Maintenance Component Distribution for High-Speed Railway Operations

Sustainable distribution network design for the maintenance components of electric multiple units (EMUs) is critical to reduce the problem of unreasonable resource allocation and capital occupation of high-speed railway (HSR) operations. Motivated by the above analysis, this study investigates the integrated optimization of the location and inventory of EMU maintenance component distributions. Aiming to improve the sustainable operation for high-speed railway, we proposed a corresponding nonlinear mixed-integer programming model to determine the location of the distribution center (DC) for EMU maintenance component delivery, inventory control strategy, and corresponding service level. The above optimization model is solved by an adaptive improved genetic algorithm. The proposed model and algorithm are applied to a real-world case study on China’s EMU maintenance components. The findings show that a higher service level is not better to achieve the lower total cost in the maintenance component distribution network. The ratios of transportation modes are significant to balance the service level and total cost of the EMU distribution network. Furthermore, the unit out-of-stock cost and the service level both show great impacts on the total costs of the EMU distribution system. Finally, there exists an optimal ratio of different transport modes, which ensures the least total cost of the EMU distribution system.

Efficient food service chain management considering substitute products

PurposeThis study investigates the pricing and inventory control decisions of a company that owns a coffeehouse chain providing drip coffee and a coffee manufacturing factory producing ready-to-drink (RTD) coffee. To determine a way to maximize profit, optimal pricing and inventory control strategies are studied for both the RTD coffee as well as the coffeehouse chain network.Design/methodology/approachIt is assumed that the company sells only drip coffee through its coffeehouse chain and would like to launch RTD coffee via other channels such as convenience stores, supermarkets and so on to maximize its total profit. A mathematical model–based optimization is adopted to address the decision-making for the given problem situation, where the demand for both drip and RTD coffee are dependent on the values of decision variables. To solve the proposed mathematical model, particle swarm optimization (PSO) is applied due to nonlinearity of the developed model.FindingsIt is confirmed that a company can earn more profit by launching RTD coffee, even though the profit from drip coffee would reduce. In addition, the scenario analysis shows that by launching RTD coffee under various conditions, the total profits would also improve.Originality/valueThe value of this study is the proposed basic framework for the industry. In addition to the modeling framework and cost structure, realistic cost figures and technical details can be considered when applying the model to a practical setting.

Parametric study and optimization of closed Brayton power cycle considering the charge amount of working fluid

With the advent of various heat sources for electric power, the interest in closed Brayton cycles (CBCs) is increasing. For an open Brayton cycle like gas turbine plants, numerous options exist to adjust cycle operation through flow control or speed modulation of turbomachines. For a CBC, however, the amount of ‘closed’ working fluid inside the cycle is constrained and the control schemes for cycle operation are limited. Thus, the performance of the CBC is analyzed considering the fact that the density of working fluid is related to the charge amount in this study. With a concept of the charge amount as a constraint, an alternative approach to reflect CBC characteristics is introduced to set the turbine inlet conditions unconstrained. As a result, the influence of the charge amount on the cycle performances is analyzed, and the optimum charge amount for the given operating conditions is obtained. Using the results of this study, the charge amount can be considered as a design and control parameter of the CBC. Furthermore, the performance of the CBC can be improved by implementing a proper inventory control strategy during off-design operation based on the calculated optimum charge amount in this study.