Periodic-review System Research Articles

Analysis of Cocoa Bean Inventory Control with Continuous (Q) and Periodic (P) Review System Methods at Majapahit Chocolate Factory

Majapahit Chocolate Factory is one of the manufacturing industries that processes cocoa beans into various chocolate products called Majapahit Chocolate. In the production process, Majapahit Chocolate Factory has not controlled raw material inventory efficiently using any method so there is still a frequent mismatch between the amount of inventory and production needs. The higher the amount of inventory, the higher the inventory costs incurred. Based on these problems, this study aims to determine the control of cocoa bean inventory to minimize the total cost of inventory at the Majapahit Chocolate Factory. The results showed that the most minimal total inventory cost was the Continuous Review System method of IDR303,863,596.70 with a savings of 1% from the Periodic Review System method and 4% from the company method. After forecasting the need for raw materials for January-December 2023 using the Weighted Moving Average method, the total demand for cocoa beans during the 2023 period is 61752 kg. Meanwhile, the size of the order quantity is 5739 kg and the reorder point is 8234 kg, so the total inventory cost required in January-December 2023 is IDR1,278,081,375.44.

Analysis of Product Inventory Control using Continuous Review System Q Method and Periodic Review System P Method to Minimize Inventory Costs

Store X is a store that sells muslim fashion products. There is a phenomenon that often occurs in one of Store X's branches, such as the shortage of jetblack hijab products in stock. This phenomenon results in the company's loss of opportunity to gain profit and has an impact on high inventory costs. Based on this, it is known that one of Store X’s branches does not yet have a good inventory system, so it is necessary to apply optimal inventory methods and minimize inventory costs. This study uses a quantitative approach to data collection methods of interviews, literature studies, and company historical data. The data analysis method used is the SMA, WMA, and SES methods with each of the two conditions. As well as using the Continuous Review System method (Q method) and the Periodic Review System method (P method) for the calculation of inventory policy and total inventory costs. Based on the results of the study, it was found that the Q method determines the optimal ordering lot quantity and the point of having to reorder goods. This resulted in the stock in the warehouse always being replenished on time so that there were no excess or shortage of inventory and customer requests could be fulfilled so that inventory costs could be minimized. Based on this statement, it is stated that the Q method is suitable for the company because it provides an optimal inventory policy and minimizes inventory costs by 5.90% or IDR 44,771,467 of company costs.

Analisis Pengendalian Persediaan Farmasi di Rumah Sakit Awal Bros Batam

Prescription delays at Pharmacy Department services Awal Bros Batam Hospital during the month of October 2015 until September 2016 influences the impact on the quality of hospital services and going on back order ending with financial problems to Awal Bros Batam hospitals. The author wants to identify problems that occur for improving efficiency and effectiveness of services pharmacy inventory control at Awal Bros Batam Hospital and overall improving the quality of hospital services. This study is an operational research study to develop a pharmaceutical inventory control models. The first model, in this study will be made use of ABC analysis, investment analysis ABC, and ABC critical index, to determine pharmaceutical supplies into groups A, B and C. Furthermore, will be calculated EOQ and ROP, as well as the efficiency of TIC. Conducted in-depth interviews with informants. The second model, the method Periodic Review System, Order up to the level, in this study also conducted an analysis 10 largest inventory investment by ABC and ABC average user through the assessment of inventory, ITOR and PNP on Awal Bros Batam hospital over a period of 12 months. In the second method is expected to avoid overstocking pharmaceuticals with high investments that may affect the cash flow of the hospital. Pharmacy inventory control at Awal Bros Batam Hospital has not performed optimally, although every month have made the ABC analysis Investments and apply maximum and minimum stock method is simple. This research, produce policy recommendations for the Awal Bros Batam Hospital to help the management to improve ppharmacy inventory control and solve the problems in the pharmaceutical stock out.

Replenishment and transshipment in periodic-review systems with a fixed order cost

Small businesses with many stocking locations face high ordering costs and imbalanced inventories. To address those challenges, we consider an inventory system of multiple retailers: each has Poisson demand and backorders are permitted. They order together periodically and there is an opportunity to transship available inventory between retailers in each order cycle. Each order incurs a fixed cost, and there is a variable transshipping cost, a holding cost for inventory, and a penalty cost for backorders. The system aims to determine a feasible ordering and transshipping plan which minimizes the long-run average total cost over time. We provide an analytical approach to evaluating costs, construct bounds to search for the optimal order interval, order-up-to level, and timing of transshipment, and determine the amounts to transship based on a marginal cost. Our numerical studies find that, first, the optimal order interval is between that in the no-transshipment case and an EOQ-like calculation. Second, the optimal timing of transshipments is in the middle of an order cycle or a little later. Third, the optimal order interval and timing of transshipments are insensitive to the introduction of differences between retailers. Fourth, transshipment effectively reduces costs, especially when transshipment costs are low or different between retailers. These findings can simplify the task of cost optimization in complex inventory systems and develop practical measures to further reduce costs.

Inventory Control Analysis with Continous Review System and Periodic Review System Methods at PT. XYZ

Companies must have various strategies in order to survive and face the competition in the retail industry, where the strategy can be in the form of inventory control. The objective of this research is to categorize products owned by PT. XYZ based on the ABC analysis method, to analyze the best forecasting method for PT. XYZ for Filo Compound, Meses Valentino and Mercolade Dark 1 KG, to analyze the total cost using Q-Method & P-Method, and last to compare among Q-Method, P-Method and PT. XYZ’s policy. By doing ABC analysis, company is able to know which products to be prioritized. Forecasting is the first step to find out how much demand is expected in the future by analyzing demand data from the previous period. By having the smallest error which is reflected by MAD and MSE value, Trend Projection is the best method for forecasting as compared to the other five methods. Furthermore, this research is calculating the total cost by using the Q method and P Method to find out the best method with the smallest total cost for PT. XYZ. Q method is the best for Filo Compound and Meses Valentino with the cost saving as much as Rp 38.582.771,08 and Rp 43.215.539,68. While for the Mercolade Dark 1 KG, P Method is the best method with the cost saving as much as Rp 200.290.337,56.

MANAJEMEN PERSEDIAAN OBAT DENGAN PENDEKATAN PERIODIC REVIEW SYSTEM

Background: Continuity of drug availability in hospitals with no excessive supplies is still a problem. The range of inaccuracies in the plan for drug needs can be wasteful in procurement costs and affect the continuity of health services. Hospitals need to improve historical processing data on drug absorption to optimize drug demand planning.
 Objective: The research aimed to simulates optimizing the planning and control of drug inventory using the periodic review system.
 Methods: Case study research to plan drug needs, using daily drug uptake data longitudinally (2014-2017). The obtained formulas are used to perform simulations by comparing drug supplies based on existing methods with optimization methods on accurate uptake data in 2018. Interviews In-depth research is carried out on informants selected based on the relationship with system. Data analysis was performed using the t-test statistical test and qualitative data were analyzed using open coding.
 Results: An assessment of 10 types of drugs, each of 5 drugs has carried out in the fast moving and slow-moving groups. Eight out of the ten drugs reviewed, there were significant differences in drug supply between the existing method and the periodic review system method. The price of drug supplies during 2018 is Rp.13,315,337,556, while the existing method is Rp. 16,481,465,208. There were 25 cases of drug shortages worth Rp. 655,282,174 in the periodic review system method that is lower than the existing method, which is 31 instances of drug shortages worth Rp.756,743,295.
 Conclusion: The periodic review system method has advantages compared to existing methods in terms of fewer inventories and cost needs, and the occurrence of fewer drugs shortages and the budget to finance the drug shortages rates. Thus periodic review system method has the potential to improve the planning of drug needs in hospitals.
 

Policy Making in Optimizing Inventory Control with Continous and Periodic Review Method at PT. XYZ

PT. XYZ is a company enganged in the garment sector that produces office uniforms, polo t-shirts and t-shirts with the highest demand for polo t-shirt products from lacos 20S Black cloth. Based on company data and the results of interviews with informants, it found that companies often eperience stockout and overstock of supplies of lacos 20S black cloth due to fluctuating demand. This study to control inventory by comparing the company method with the method of Continuous Review (s,S) System, (S,Q) System and Periodic Review (R,s,S) System, (R,S) System to obtain minimum total cost of inventory. Based on the calculation using the company method, the total cost of inventory is Rp 643.487.400 and the minimum total cost of inventory using the Continuous Review (s,Q) System method is Rp 635.880.585 with savings of Rp 7.606.815 and the percentage of cost reduction is 1,18%. The forecasting needs for April 2021 to March 2022 using the Continuous Review (s,Q) System method, the order quantity is 378 Kg and the reorder point is 133 Kg with a total inventory cost is Rp 767.415.089.

The Establishment of Decision Making Support Tool for Inventory Control and Production Planning with Periodic Review System and Linear Programming Approach

PT. Mortars is an instant cement producer with many product variants. Some problems that PT. Mortars encountered are uncertainty of demand, limitation on production capacity, and inventory capacity, which caused product shortages and high inventory costs. The production scheduling process is produced manually so it requires a long time, relying on the ability and experience of the production planner which is vulnerable to mistakes. Therefore, new methods and tools are needed for inventory control and production scheduling to make sure goods are delivered to customer just in time while maintaining operational efficiency. Periodic review system (R,S) and (R, s, S) methods are proposed in this study to improve inventory parameters and reorder systems that have an impact on service levels and inventory costs. The tools are designed using Microsoft Excel software with solver add-ins functions and linear programming approaches to generate optimal production schedule decisions automatically. In order to determine the level of service and inventory costs generated by each method, a simulation is conducted by using the tools that have been made. The simulation of the existing method produces a service level of 98,64% and a total inventory cost of Rp. 1.167.160.494. The periodic review system (R, S) method resulted in increasing service level of 0,96% and lower inventory cost of Rp. 15.130.801 while the periodic review system (R, s, S) method resulted in increasing service level of 1,29% and a lower inventory cost of Rp. 448.653 compared to the existing method. The periodic review system (R, S) method produces the lowest inventory costs while the method (R, s, S) produces the highest service level compared to other methods.

Inventory Control of Vegetable Oil Products Using Continuous Review System (Q) Approach and Periodic Review System (P) Methods in Retail Companies: A Case Study of Indonesia

Retail companies are businesses that have a significant role in providing quality staples to improve public health. Every retail company wants the production inventory control system to run well to meet consumer demand. Suppose the amount of inventory ina retail company is too small. In that case, it will disrupt consumer demand for products that consumers want to buy and lose the opportunity to earn profits if an order is more significant than forecast. Meanwhile, if product inventory exceeds the need for a product, it will cause high costs, and if stock is stored for too long, it will result in damage and expiration. This retail company sells quality products and provides a wide range of excellent and complete products and makes it easier for customers to find their needs as one of the best. A company that needs to have a product control system to maintain sales and sell quality products and finally compete with other national and foreign retail companies. However, the current product inventory processing is not optimal because it is only based on previous inventory data. It can be seen from the varying amount of inventory and the high frequency of ordering. This study aims to obtain the most optimal comparison results by using the minimum total cost criteria and minimizing the cost of purchasing the product. This study compares two methods, namely the Continuous Review System (Q) method and the Periodic Review System (P) method. The most suitable method was the Q method with the total inventory cost of Vegetable Oil Products of Rp in this study. 13,371,600 with an efficiency of 42% of the entire inventory costs incurred by retail companies.

Optimization of Raw Material Inventory Control CV. Dirga Eggtray Pinrang Using Probabilistic Model with Backorder and Lostsales Condition

This research discusses about the comparison of raw material inventory control CV. Dirga Eggtray Pinrang. It starts with forecasting inventory for the next 12 periods using variations of the time series forecasting method, where the linear regression method provides accurate forecasting results with a Mean Absolute Percentage Error (MAPE) value of 1,9371%. The probabilistic models of inventory control used are the simple probabilistic model, Continuous Review System (CRS) model, and Periodic Review System (PRS) model. The CRS model with backorder condition is a model that provides the minimum cost of Rp. 969.273.706,20 per year compared to another probabilistic model with the largest difference of Rp. 1.291.814,95 per year, with the optimum number of order kg, reorder level kg, and safety stock kg.

Consumable Material Spare Part Management Control in Electricity Transmission System

Overstock spare part in the Electric Power Transmission System will affect the inefficiency in the asset management of the company. While the spare part stockouts in the company will disrupt the maintenance process of the electric transmission system, which then lead to power outages. Overstock spare parts are caused by several factors, such as forecasting errors in material requirements, intermittent requests, so it is difficult to determine the optimal order quantity. On the other hand, the unavailability of spare parts will affect the reliability of the electrical energy transmission system, which has the potential in causing a massive power outage. Monte Carlo simulations help to show the more concrete picture of the spare parts inventory condition using a periodic review (R, S) system approach. Divination of the combination of S and R parameters is very influential on the success of spare part control. Spare part classification is used for understanding the demand characteristics and the level of criticism. Moreover, the analysis of simulation results will show the information on supply fulfilment strategies to overcome the problems of either spare parts availability or spare parts overstock.

Solving a Joint Pricing and Inventory Control Problem for Perishables via Deep Reinforcement Learning

We study a joint pricing and inventory control problem for perishables with positive lead time in a finite horizon periodic‐review system. Unlike most studies considering a continuous density function of demand, in our paper the customer demand depends on the price of current period and arrives according to a homogeneous Poisson process. We consider both backlogging and lost‐sales cases, and our goal is to find a simultaneously ordering and pricing policy to maximize the expected discounted profit over the planning horizon. When there is no fixed ordering cost involved, we design a deep reinforcement learning algorithm to obtain a near‐optimal ordering policy and show that there are some monotonicity properties in the learned policy. We also show that our deep reinforcement learning algorithm achieves a better performance than tabular‐based Q‐learning algorithms. When a fixed ordering cost is involved, we show that our deep reinforcement learning algorithm is effective and efficient, under which the problem of “curse of dimension” is circumvented.

Evaluasi Persediaan Bahan Baku Dengan Menggunakan Pendekatan Metode Continuous Review System Dan Periodic Review System

Planning and controlling the raw material inventory is carried out in such a way as to meet the needs of raw materials appropriately and at low cost. The problem with plate raw materials is that there is no appropriate method of controlling raw material supplies. Control of raw materials at this company is sometimes erratic due to unstable market demand. Experiencing an accumulation of raw materials when product demand decreases and there is a shortage of raw materials when product demand increases. This study aims to determine a probabilistic inventory model that is good for determining the order quantity, ordering time and safety stock by considering the minimum total cost. Based on the analysis and calculation results, the total inventory cost according to company policy is Rp. 14,734,832 / year, the total cost of the Q model is Rp. 16,300,517 / year with q value of 1,484, r is 965, ss 104, α of 0.013 and S of 2.449 and the total cost of inventory in the P model is Rp.6,384,473 / year with a T value of 0.019, R of 2.264, ss of 105 and α of 0.013. The results show that the Periodic Review System inventory model has an optimal total cost of inventory. Keywords: Inventory Control; Continuous Review System; Periodic Review System; Probabilistic.

Dynamic Simulation to Minimize Inventory Cost of Coal Considering Uncertainty Demand of Product

This paper briefly discusses the inventory management of coal in a cement industry. The cement company uses coal as fuel in the production process. Continuous production process must be maintained, thus the coal supply must be met to the production demand. In this study, we develop a dynamic simulation of coal inventory control system. We implemented periodic review system (P system) and continuous review system (Q system) method. Our simulation scenario consider some decision variables such as supply, variation of demand, and fluctuation of demand in order to understand the behaviour of the proposed model. This method is expected to provide recommendations for improve the inventory control policies in determining the optimum amount of coal in the warehouse and the optimal interval between orders with a minimum total inventory cost at uncertainty demand condition of product clinker and cement.

Inventory Renewal for a Perishable Product: Economies of Scale and Age-Dependent Demand

We consider a finite-horizon, periodic-review system for a perishable product at a retailer that faces stochastic, age-dependent demand and loses excess demand, if any. For this system, we build three models that capture two sources of unfilled demand, insufficient inventory and inappropriate age, and penalize them at different rates. The models are characterized by increasing replenishment flexibility, and the goal of each model is to identify when to place an order and the quantity whenever an order is placed. In the first model, reorder intervals are equal. In the second model, reorder intervals can vary across orders. In the third model, reorder intervals continue to remain flexible but the retailer can also partially salvage her inventory whenever she has excess inventory. Using the models, we explore the effect of lost-sales penalties on the structure of the optimal value function. We find that the inventory-related cost in a period may lack convexity if the ratio of penalties for stockout and high age is below a threshold, which percolates to the value function as well. We also identify properties of the optimal replenishment policy for the three models. Finally, we conduct numerical experiments to identify the marginal value added by the flexibility in reorder intervals and the option to partially salvage inventory as a function of model parameters.

Spreadsheet-based supply chain simulation for teaching risk pooling combined with facility location

Inventory risk pooling is the use of centralized inventory to maintain lower overall inventory and safety stock. Generally, in a decentralized system with no risk pooling, a retailer maintaining its own inventory and safety stock requires higher levels of inventory than would be if the inventory was pooled at a centralized location. Most pedagogy relies on algebraic formula-based examples, which has two issues: (1) student struggle visualizing variability concepts and algebraic notation and (2) the location of the centralized inventory location and its effect on lead times are often ignored or assumed to be negligible. To address these issues, the spreadsheet-based simulation offers visual cues of the inventory reduction benefits, as well as demonstrating the impact of the facility location. The simulation was developed using MS Excel, and has a simple, easy-to-use interface, as well as easy-to-understand graphical and statistical output. Both undergraduate and MBA students respond favorably to the simulation because it helps them understand the math concepts, and it strengthens their spreadsheet skills. The inventory policy is an order-up-to-level with a weekly periodic review system. Backorders must be filled. Inputs include the number of customers, desired service level, weekly customer standard deviation of demand, lead times and inventory order-up-to levels. Outputs include weekly and annual inventory and service levels for both the decentralized and centralized (risk pooling) systems.

Optimizing constant pricing and inventory decisions for a periodic review system with batch ordering

In business practice the misalignment between frequent inventory adjustments and a sticky price is common. Motivated by Pipi Milk, a diary manufacturer who commits its customer at a fixed price for a whole year meanwhile weekly replenishes its cheese product stock at a specific batch size, this paper develops an integrated constant pricing and inventory control model in a periodic-review system with batch order consideration. For such a system, our focus is on an (nQ, r)-p policy: the price p is determined and committed at the beginning of the planning horizon; inventories are managed based on an (nQ, r) policy with reorder level r and order quantities at non-negative integer multiples of batch size Q. With a fixed ordering cost included, we develop an efficient algorithm to compute the optimal policy parameters with the purpose to maximize the expected long-run average profit. We also numerically investigate the policy performance and verify its advantages by comparing to a sequential optimization of price and inventory decisions. Finally, managerial insights are generated.

Determining the Optimal Order Quantity with Compound Erlang Demand under (T,Q) Policy

Management of electric equipment has a direct impact on companies’ performance and profitability. Considering the critical role that electric power materials play in supporting maintenance operations and preventing equipment failure, it is essential to maintain an inventory to a reasonable level. However, a majority of these electric power materials exhibit an intermittent demand pattern characterized by random arrivals interspersed with time periods with no demand at all. These characteristics cause additional difficulty for companies in managing these electric power material inventories. In response to the above problem, this paper, based on the electric power material demand data of Shanghai Electric Power Company, develops a new method to determine the optimal order quantity Q⁎ in a cost-oriented periodic review (T,Q) system, whereby unsatisfied demands are backordered and demand follows a compound Erlang distribution. Q⁎corresponds to the value of Q that gives the minimum expected total inventory holding and backordering cost. Subsequently, an empirical investigation is conducted to compare this method with the Newsvendor model. Results verify its superiority in cost savings. Ultimately, considering the complicated calculation and low efficiency of that algorithm, this paper proposes an approximation and a heuristic algorithm which have a higher level of utility in a real industrial context. The approximation algorithm simplifies the calculation process by reducing iterative times while the heuristic algorithm achieves it by generalizing the relationship between the optimal order quantity Q⁎ and mean demand interarrival rate λ.

International Election Observer Recommendations and UN Human Rights Mechanisms: Toward a More Robust System of Global Accountability on Democracy and Human Rights

ABSTRACTIn the last decade, states around the world have begun to pass and enforce laws that restrict fundamental rights and freedoms and effectively close off political space. Faced with the challenge of closing political space, there is an urgent need to deepen the linkage between election observation assessments and reporting, and the United Nations’ human rights mechanisms and system. In this article, the authors argue that the election assistance and human rights communities must work together to promote a cohesive framework for accountability on all human rights, including electoral rights. Stronger links and reporting from election observation missions into the Universal Periodic Review and treaty body system can function as part of a strengthened international human rights accountability mechanism, using UN mechanisms and related obligations accepted by states.

The discrete-time EOQ model: Solution and implications

Consideration is given to the classical EOQ (with backorders) model, where one of its original assumptions is modified. Instead of being continuous, time forms a sequence of indivisible quanta (unit periods). The implications of this assumption, common in the analysis of periodic review policies, are explored for deterministic demand. Modeled as an inventory system under the (S, T) policy, long-run average cost is derived, and it is shown that optimal control involves the solution of a two-dimensional non-convex integer optimization problem. Properties are established, leading to a solution algorithm which guarantees optimal S and T determination with (at most) three cost-function evaluations. It is shown that, contrary to intuition, the classical EOQ optimal cost is not a lower bound for the system studied. This is exploited to develop distribution-free lower bounds for stochastic periodic review systems together with properties rendering them useful in inventory optimization.