Inventory Control Strategy Research Articles

Performance Modeling and Analysis of a Single-Shaft Closed-Cycle Gas Turbine Using Different Operational Control Strategy

Abstract In the last few years, one considerable factor for the viability and interest in the closed-cycle gas turbine (GT) systems for nuclear or conventional power plant application is its potential to maintain high cycle performance at varying operating conditions. However, for this potential to be realized, more competitive analysis and understanding of its control strategy are importantly required. In this paper, the iterative procedure for three independent control strategies of a 40 MW single-shaft intercooled-recuperated closed-cycle GT incorporated to a generation IV nuclear reactor is been analyzed and their performance at various operating conditions compared. The rationale behind this analysis was to explore different control strategies and to identify potential limitations using each independent control. The inventory control strategy offered a more viable option for high efficiency at changes in ambient and part-load operations, however, operational limitations in terms of size and pressure of inventory tank, rotational speed for which the centrifugal forces acting on the blade tips could become too high, hence would affect the mechanical integrity and compressor performance. The bypass control responds rapidly to load rejection in the event of loss of grid power. And more interestingly, the results showed the need for a mixed or combined control instead of a single independent technique, which is limited in practice due to operational limits.

Optimal Inventory Control Strategies for Deteriorating Items with a General Time-Varying Demand under Carbon Emission Regulations

Climate warming nowadays has caused people to increasingly enhance public awareness about carbon emissions from industries. In the storing industry, inventory management for deteriorating items is crucial in the business competition. To slow down the deterioration and ensure the quality of products, the items are usually stored in certain temperature-controlled environment. However, a lot of carbon emissions of the inventory system are caused by these warehousing activities. In a finite panning period, this paper studies a continuous review inventory system and proposes inventory models to analyze the impacts of carbon emissions on inventory system for deteriorating items with a general time-varying demand, in which shortages are allowed, and the customer demand during shortage period is partially backlogged till the next replenishment. Under carbon emission regulations, the existence and uniqueness of the optimal solution to each model is explored and comparisons of optimality among the proposed models are given. Numerical examples and robust analysis of the models are presented to illustrate the applicability in practice. Some management insights about inventory policies and emission reduction strategies are obtained.

A Review of Multi-Echelon Inventory Control in Supply Chain

Multi-echelon inventory control is the core issue in supply chain. Firstly, we summarize the current research status of multi-echelon inventory control by using Citispace which is the scientific knowledge map visualization analysis software. Second, two strategies of multi-echelon inventory optimization and control are analyzed. Then, multi-echelon inventory control problem is divided into three strategies, namely multi-echelon multi-node inventory control strategy, multi-echelon single-node inventory control strategy, and transshipment-based multi-echelon multi-node inventory control strategy, and comparative analysis. Finally, we point out future development trend.

Comparing Application of R-Model over Conventional ABC Analysis in a Pump Manufacturing Organization

Inventory control technique is widely employed in every manufacturing organization and ABC analysis is traditionally used for selective inventory control in a supply chain, or in the production system. The main purpose of ABC analysis is to classify stock keeping units to control the high value, medium value and low value items. ABC analysis concentrates quantities of inventory items and inventory values only. Different criteria such as lead time and criticality of inventory items may be initiated to manage the inventory items in a better way. Since consideration of those criteria is impossible for ABC inventory control technique, different multi criteria based inventory control techniques are applied to manage stock items. In this article, selective ABC inventory control technique has been applied to manage inventory items of a pump manufacturing organization situated in the Eastern region of India. Procurement lead time for a stock item plays an important role in supply chain as well as production also. So, lead time criterion in different inventory control strategies ensures an appropriate inventory management system. An AHP based Multi Criteria Inventory Control (MCIC) technique has been adapted regarding different criteria, such as quantities of inventory items, inventory values and lead time criteria to manage inventory items of the pump manufacturing organization. This MCIC model is a weighted linear optimization technique, termed as ‘R-model’. To evaluate the performance of conventional ABC analysis and R-model, a comparison is drawn based on the safety stock inventory cost and fill rate of the inventory items. The entire investigation is capable to find out the cost effective inventory control technique.

Inventory Control When Selling to Human Newsvendors

We develop inventory control strategies for a supplier who is selling a product to a group of human newsvendors. Recent research in newsvendor experiments using human subjects revealed significant behavioral tendencies in the decision making processes of human newsvendors. If the supplier would incorporate these behavioral tendencies while managing her inventories, her costs would be significantly reduced. Using data from our own experiments, we estimate the possible reductions in supplier costs and determine the factors that significantly impact it. We observe a significant improvement in the supplier’s inventory decision if she estimates the demand distribution with a model that captures the anchoring tendencies instead of assuming aggregate randomness. As the model selection relies much on the data, it is an important task to determine whether the retailers are mean-anchoring, demand-chasing, both, or neither. In addition, we observe that the information about retailers’ behaviors is more beneficial for the supplier when the end-customer demands are more variable. It is certain that more precise information on the data will lead to a better inventory decision for suppliers. The information includes the retailers’ behavioral tendencies, individual-specific order behaviors, and the variability of end-customer demands.

Supply Chain Management Local Model for Unreliable Suppliers

A supply chain management mathematical model for an isolated warehouse with two suppliers of different reliability is considered. Optimal inventory control strategy synthesis algorithm is constructed. The transfer to stationary strategies is investigated. We developed C++ software package to simulate algorithm for two different probabilistic distributions of demand: discrete Gauss-like and another one, discrete too, close to uniform. These examples are used to investigate the optimal stationary strategy parameters and costs dependency of econometrical attributes (among these–discount factor).

Simulation-Based Optimization on Control Strategies of Three-Echelon Inventory in Hybrid Supply Chain With Order Uncertainty

Multi-echelon inventory control is the main form of the management of supply chain inventory, and it has been paid extensive attention by scholars because of its importance in supply chain management. Process industries, represented by metallurgy, petrochemical and pharmaceutical industry, have typical characteristics such as high investment, high costs, and high resource utilization, they play a key role in industrialization. In this paper, the simulation model of a multiproduct three-echelon inventory control system is established for the hybrid supply chain of the process industry. Based on the idea of control engineering, a feedback control law is designed for inventory control. Several mixed inventory control strategies were applied to the model. The proportional plus integral control algorithm is used to modify the inventory control strategies. Based on this simulation model, a simulation-based optimization method is applied to the three-echelon inventory control system. The results show that the reciprocal of total entropy ratio and customer satisfaction are optimized by the mixed inventory control strategies when the hybrid supply chain is affected by order uncertainty.

Joint pricing and inventory control for a stochastic inventory system with Brownian motion demand

ABSTRACTIn this article, we consider an infinite horizon, continuous-review, stochastic inventory system in which the cumulative customers’ demand is price dependent and is modeled as a Brownian motion. Excess demand is backlogged. The revenue is earned by selling products and the costs are incurred by holding/shortage and ordering; the latter consists of a fixed cost and a proportional cost. Our objective is to simultaneously determine a pricing strategy and an inventory control strategy to maximize the expected long-run average profit. Specifically, the pricing strategy provides the price pt for any time t ⩾ 0 and the inventory control strategy characterizes when and how much we need to order. We show that an (s*, S*, p*) policy is optimal and obtain the equations of optimal policy parameters, where p* = {p*t: t ⩾ 0}. Furthermore, we find that at each time t, the optimal price p*t depends on the current inventory level z, and it is increasing in [s*, z*] and decreasing in [z*, ∞), where z* is a negative level.

A Study of Inventory Control Systems by Jamaican SMEs in Retail and Manufacturing/Distribution Industries

It is widely accepted that firms can achieve effective inventory management with the right strategies. This study analyzed the inventory control strategies of small to medium-sized enterprises (SMEs) in Jamaica. The objectives of the study were to identify whether these companies used the “best practices” in inventory control, the effects of their strategies on business performance, and the factors that affected the development of their strategies. The study employed a methods triangulation approach that included case studies, interviews, questionnaires, and observation with a focus on twelve inventory-intensive SMEs in retail and manufacturing/distribution industries. The SMEs were found to use common inventory control strategies such as stock counts, Enterprise Resource Planning (ERP) systems, forecasting, and inventory classification.The findings of this study support institutional theory and isomorphism because it was discovered that due to external influences, firms studied within the same industry adopted similar strategies, and even in different industries, the ‘best practices’ in inventory control were the same. The drivers of this isomorphic organizational behavior were found to be costs, government regulations, and imitation of successful strategies in other companies. The SMEs surveyed were classified as semi-automated due to limited automation and confirmed success in their inventory management. The study validates the existence of institutionalism among SMEs in the retail as well as manufacturing/distribution industries in Jamaica. A broader scope examining larger firms and other industries would further identify isomorphic organizational behavior across the Jamaican business landscape. For future research, an investigation of financial performance and changes and adoption of new inventory control strategies of Jamaican SMEs is recommended to achieve a broad view of inventory management on the financial performance of Jamaican SMEs.

The Influence of Quality Inspections on the Optimal Safety Stock Level

Due to yields of less than 50% during the production of curved glass for the displays on their new cell phone series, Samsung has to deal with higher than expected production costs of several million dollars. Where there is random yield, production costs as well as holding costs can be reduced by introducing quality inspections, in which defective items are discarded before further production. To achieve the greatest cost savings, it is important to determine the optimal number and positions of these inspections across the production process which, due to several influencing parameters, is not simple. We show how the positions of inspection within a production process influence the safety stock level that is required to buffer against uncertainties due to demand and yield randomness. Our approach is the first one, combining decisions about the number and positions of inspections with inventory control strategies in a warehouse. We achieve a maximum safety stock reduction of more than 30% in our examples, which can be even larger depending on the parameter setting. For a company like Intel, reporting inventories for finished goods of nearly 1.5 billion dollars in the 2014 annual report, this allows for significant savings.

Analysis of Inventory Control and Banana Chips Agroindustry Development Strategy in Bandar Lampung

The study aims to analyze the performance of the inventory control and agroindustry development strategy banana chips. Site selection was done in the chips industry center Bandar Lampung City. Sampling was done offender census on members of banana agroindustry business group. Data analysis methods used was the analysis of economic order quantity (EOQ), SWOT and AHP. The results showed that the control of inventory through the ordering of raw materials and production capacity adjusted to do with intersystem messaging. The production process is generally carried out every 3 times a week with raw material price of Rp 3500,- per comb. Agroindustry development strategy banana chips were utilizing fabric of cooperation with other parties in the application of science and technology in order to produce quality products, banana chips, giving a sense of innovation so that the amount of consumer interest and increasing demand for banana chip, and optimization of infrastructure and facilities wereowned agroindustries effective and efficient.

Manufacturers’/remanufacturers’ inventory control strategies with cap-and-trade regulation

The increased awareness of the need for protecting the environment and policies relating to carbon emissions has resulted in manufacturers viewing carbon emissions as one of the most critical elements affecting production decisions. As a gradually maturing production form, remanufacturing plays an increasingly pivotal role in economy, environment and society. This paper extends the classical EOQ model, considers carbon emissions in (re)manufacturing activities and product transportation and builds an inventory cost model with carbon constraints. The optimal batch and quantity of manufacturing/remanufacturing and the frequency of cyclic remanufacturing are derived with and without carbon constraints through analysis of the model. At the same time, this paper investigates the impact of carbon emissions quota and its trade prices, remanufacturing ratio and different means of transportation on manufacturers’ decisions. The examples show that the batch size of manufacturing and remanufacturing is identical within the period with carbon constraints; the batch size of manufacturing without carbon constraints is less than remanufacturing with carbon constraints; the results are just the opposite in terms of the batch of remanufacturing and the number of remanufactured products. In other words, the (re)manufacturers’ total cost and carbon emissions with carbon constraints are lower than those without carbon constraints. Starting from the real-life circumstances, this article considers manufacturers’ total cost with imperfect remanufacturing, varied means of transportation, carbon quota and its trade, which have not been taken into account previously, the manufacturer’s optimal decisions are derived. Meanwhile, the analysis of carbon quota can provide some insights for governments and enterprises in terms of carbon emissions rights allocation.

МЕТОДИКА ОЦІНКИ КІЛЬКОСТІ МАТЕРІАЛЬНО-ТЕХНІЧНИХ ЗАСОБІВ ЗА УМОВ КОЛИВАННЯ ПОПИТУ НА НИХ

The effective functioning and development of the enterprise is possible only under condition of availability of the necessary reserves of materiel. . The application of the inventory control strategy according to the deviation involves determining upper and lower levels of stocks financially-technical means for consumers. When performing complex and intensive tasks, the impact on consumers negative factors, the intensity of the expenditure of materiel may vary considerably, which affects the fluctuation of demand for them. Norms of stocks of materiel that must be taken into account. However, the use of existing methods for justifying norms inventory large and diverse items of materiel requires considerable labor to the collection and processing of information and does not guarantee the reliability and flexibility of supply. The current stock does not always provide the required probability of deficit-free supply due to random demand fluctuations. To eliminate possible excess of demand of installed inventory levels and continuity of supply to be created and the safety stock. In practice, as a rule, no data on the distribution of demand or such data differ significantly from a normal distribution. Upper level inventory to the consumer can be determined from the conditions ensure the specified probability of its balanced supply of logistical assets within a certain period of time. The lower the stock level of logistics can be determined from the conditions ensure the needs of the consumer for a certain period of time, which shall not be less for the next replenishment of materiel. A direction for further development could be the technique of an estimation of reserves quality.

PRINCIPLES OF CORPORATE INFORMATION SYSTEM FOR LOGISTICS MANAGEMENT OF PETROCHEMICAL ENTERPRISES

The article describes the main aspects concerning the development of the corporate information system for logistics management of petrochemical enterprises. The functional and conceptual models of petrochemical products supply management have been composed. The authors suggest using modular design of an information system based on ERP Galaktika. Advantages of applying the client/server architecture and object-relational data model to corporate information systems are outlined. The authors recommend using ABC/XYZ analysis as the method of classifying inventory by sales and products levels to determine the optimal inventory control strategy.

Impact of Replenishment Strategies on Supply Chain Performance under e-Shopping Scenario

With the development of Information and communication technologies (ICT), the supply chain performance and its management techniques have significantly transformed. The internet revolution has bought the surge in online shopping platforms attracting millions of small size manufactures to engage in the nascent business models. The research attempts to identify the factors influencing the supply chain performance for small size manufacturers under e-shopping scenario. The system dynamics simulation approach is attempted to assess the impact of replenishment strategies on supply chain performance indicators. The results reveal the existence of bullwhip effect in the e-shopping supply chains due to backlogged orders and management decisions. The comparison between two different inventory control strategies with replenishment patterns indicates that the target stock level method performs better over economic order quantity method under e-shopping scenario.

Impact of replenishment strategies on supply chain performance under e-shopping scenario

With the development of Information and communication technologies (ICT), the supply chain performance and its management techniques have significantly transformed. The internet revolution has bought the surge in online shopping platforms attracting millions of small size manufactures to engage in the nascent business models. The research attempts to identify the factors influencing the supply chain performance for small size manufacturers under e-shopping scenario. The system dynamics simulation approach is attempted to assess the impact of replenishment strategies on supply chain performance indicators. The results reveal the existence of bullwhip effect in the e-shopping supply chains due to backlogged orders and management decisions. The comparison between two different inventory control strategies with replenishment patterns indicates that the target stock level method performs better over economic order quantity method under e-shopping scenario.

A Model to Determine Optimal Composition of Production to Obtain Maximum Profit & Reduce Overhead Costs by Linear Programming

There are many factors which put emphasize on the importance of developing pharmaceutical industry such as human health, reduced rate of using medicines, improve healthcare to global level, influence of pharmaceutical industry on exchange market, creating job and etc. Growing improvements in production systems, appearance of mechanized systems and dynamic commercial markets have highlighted the requirements of planning. This study aims to provide a model for defining the optimal composition of production in Sobhan Darou Pharmaceutical Company to obtain maximum profits and reduce overhead costs by linear programming. Lingo application is applied to reach mentioned goals. The results showed that a mathematical planning model can be used to determine minimum of total costs and inventory control strategy. Using linear programming we can take into account all perceptible and imperceptible factors to have a choice, while output models only consider quantitative values. Another advantage of leaner programming is that it can calculate production weight and rate with a systematic method which increases the efficiency and helps to have a proper choice.

Pricing and inventory control strategy for a periodic-review energy buy-back system

Along with the rapid development of economics and enhancement of industrialization, the power demand keeps rising and frequently creates mismatch between demand and supply in electricity. This provides miscellaneous energy buy-back programs with great opportunities. Such programs, when activated, offer certain amount of financial compensations to participants for reducing their energy consumption during peak time. They aim at encouraging participants to shift their electricity usage from peak to non-peak time, and thereby release the demand pressure during peak time. This paper considers a periodic-review joint pricing and inventory decision model under an energy buy-back program over finite planning horizons, in which the compensation levels, setup cost and additive random demand function are incorporated. The objective is to maximize a manufacturer’s expected total profit. By using Veinott’s conditions, it is shown that the manufacturer’s optimal decision is a state dependent (s, S, P) policy under a peak market condition, or partly an (s, S, A, P) policy under the normal market condition.

Product life cycle based demand forecasting by using artificial bee colony algorithm optimized two-stage polynomial fitting

Demand forecasting is one of the most essential components of supply chain management, which directly influences a company’s overall performance and competitiveness. However, it is difficult to accurately forecast the demand of fashion products with short life cycle and high volatility characteristics such as footwear and apparel products. An integrated demand forecasting method named Improved ABC-PF is proposed in this paper based on Product Life Cycle (PLC) theory considering the characteristics of fashion products. First, a PLC model based on cubic polynomial which is divided into two stages by the best-selling point, is established instead of traditional PLC modeling methods. Second, an improved Artificial Bee Colony (ABC) algorithm is utilized to optimize the parameters of the two-stage PLC function, which is conducted by initial population selection, optimization function design and convergence rate improvement. After that, an inventory control strategy based on PLC analysis is studied and applied in the “Precise Order” mode. Finally, the proposed method is validated by real-world data from a Chinese footwear and apparel retailer. After being compared with the other demand forecasting methods such as Moving Average (MA), Support Vector Machine (SVM) and Radial Basis Function Neural Network (RBFNN), it is indicated that the proposed improved ABC-PF method can achieve higher prediction accuracy and lower safety inventory level, which improve the overall profitability of the company, therefore generate product demand management insights for footwear and apparel enterprises.

Estimating economic losses of industry clusters due to port disruptions

Seaport operations are highly important for industries which rely heavily on imports and exports. A reliable evaluation of port risks is essential to govern the normal running of seaborne transportation and thus the industrial economies. The occurrence of a breakdown in the trade facilitators, such as ports, will disrupt the smooth flow of supply chains for the industries. The estimation of the economic loss for an industry when a port gets disrupted is a challenging task as the relationship between the port and industry clusters is complex. This study aims to develop a systematic framework for performing economic loss estimation of industry clusters due to port disruptions. The whole risk assessment is split into three stages focusing on the establishment of a network flow model, economic estimations and evaluating risk mitigation strategies. The proposed idea is demonstrated by a case study on Shenzhen port and its related manufacturing industries. A dynamic inventory control strategy used by manufacturers is found to be beneficial for mitigating port disruption risks.