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The growth and development of fermented cocoa agroindustry as demand driven requires strengthening farmers starting from the stages of plant maintenance, processing of fermented cocoa beans and maintaining cocoa quality throughout the supply chain. Material flow cost accounting (MFCA) is used to track and measure material flows and inventories in physical and cost units. The application of this MFCA to power and waste management aims to identify the material, energy, and economic costs of primary handling of cocoa, exploring challenges and opportunities related to the environmental burden of dry fermented cocoa bean production. Analysis of product handling, energy, and waste from processing cocoa fruit into dry fermented beans focuses on when the waste is produced, the value of lost income due to by-products and the risk of low product selling value, and waste handling from the farmer side, the product processing unit, and its distribution. The percentage of cocoa beans after the sorting, ripening, and splitting processes was obtained at 14.39% per batch for further processing into dry cocoa beans. In general, solid waste from processing cocoa pods into dry fermented beans can account for around 30-40% of the total weight of processed cocoa pods. This percentage may vary depending on various factors such as processing methods used, process efficiency, and waste management practices implemented by the manufacturer or is equivalent to more than Rp242-268 per kg fruit price, to which energy losses and supporting materials must be added (435-481 million euros). MFCA results are useful for business decisions, highlighting quantity, quality, and costs that are not considered in typical financial reports. [ABSTRACT FROM AUTHOR]

Spare part supply must be maintained at a specific level to balance the demand for spare parts with the number of spare parts required for maintenance activities to perform smoothly. Based on the findings from the interview with the warehouse supervisor in the case study, it was determined that the warehouse supervisor's intuition has been used to control the inventory of spare parts thus far. According to the collected data, there are 19 types of spare parts (8,509 pieces) that have been in storage for an extended period, resulting in high storage costs, and 18 types of spare parts (884 pieces) that are in short supply, resulting in high ordering costs. The corporation desires a modification that will improve inventory control and minimize the total cost of inventory. To improve the company's control over the 229 types of shuttle machine spare parts, it is important to classify spare parts based on the inventory control method. ABC classification is used to categorize spare parts according to their usage value, VED classification is used to classify spare parts according to their critical value in the machine, and HML classification groups spare parts according to their purchase price. The best ordering variables (Q), safety stock, reorder point, and total cost is defined through continuous review control. While ordering intervals, inventory targets, and overall costs are determined by Periodic Review control variables. Using ABC, VED, and HML classification, the classification resulted in 66 spare parts. The entire saving cost of inventory cost as proposed is 2,134,213,339 IDR. [ABSTRACT FROM AUTHOR]

Inventory management is an important aspect in a business. Well managed inventory system will reduce the inventory cost. One factor that influence the decrease of inventory system performance is bullwhip effect. Bullwhip effect is a distortion of information and poor coordination at every level in the supply chain network. This study aims to reduce inventory cost by minimizing bullwhip effect using Vendor Managed Inventory Method. Inventory policy and inventory cost are calculated using Economic Order Quantity Method. Case study has been done at PT. Inti Vulkatama, a tire retreading manufacturing company located in Padang City, West Sumatra, Indonesia. In the tire retreading process, the main raw materials are in the form of camel back tread rubber (hot process) and precured tread rubber (cold process). The existing supply chain network at PT Inti Vulkatama includes supplier - manufacturer - retailer - user. There are eight retailers who become consumers in this company. The problem that is often faced by this company is the inventory management of raw tread rubber (precured tread rubber) in the cold process, namely the supply of raw material for tire treads in the cold process is not available (out of stock). It indicates that the Bullwhip Effect happens in the supply chain network. Using data in the period January 2021 - August 2021, the results of the research show the more accurate demand information and inventory policies that minimize inventory costs at PT. Inti Vulkatama. [ABSTRACT FROM AUTHOR]

Spare parts availability will support the production process, but if it has obstacles or shortcomings could stop the entire production operations. PT Automotive Padang is one of the automotive companies committed to providing exemplary services in spare parts inventory to its customer. The problem faced by PT Automotive Padang in controlling spare parts inventory is the occurrence of stock-outs on demand for spare parts so that the company carries out backorders to meet these requests with the consequence of higher ordering costs. The research methodology started by grouping the parts using the FNS (Fast, Normal, Slow) classification based on the frequency of use of parts. The fast-moving category must be subjected to tight review to ensure that parts remain available at high usage rates. This study proposed the spare part inventory control system to PT Automotive Padang using the Q model Hadley method within backorder cost per unit. Based on the calculation results, the expected stock-out cost was Rp2,719,257, or 90% less than the actual cost of the stock-out, which was Rp28,227,427. There was also a reduction in the total inventory cost of Rp59,352,643. [ABSTRACT FROM AUTHOR]

In this paper, to discuss the unit prices vary with the raw material ordering quantity and the finished production material inventory model. In this model to analysis the price of fixed ordering quantity are offered to encourage purchase more ordering quantity, even though when meeting raw material shortages. The defined price breaks up is given and obtaining optimum cycle length of the production quantity. The objective of model is to obtain the optimizing the material shortage time, total production cycle quantity and the total ordering inventory cost using price break up facility. The proposed model is developed in which use of the algorithm. [ABSTRACT FROM AUTHOR]

This research considers an ideal raw material inventory model with demand that is stock dependant. In general, retailers buy more items when raw materials are in season or when manufacturers provide bulk-order discounts. The demand rate is stock dependent, thus the price break up developed model is taken into account. Our goal is to achieve the best raw material order level, replenishment cycle time, and overall inventory cost. The model illustrates the outcomes with a numerical example for the model. [ABSTRACT FROM AUTHOR]

PT. BWI is a company based in Jakarta. PT. BWI sells building material products, namely plywood. The problem that occurs in the company is the occurrence of overstock every month. The cause of overstock is that the company does not have an inventory control policy on the products it sells. Companies only use intuition when determining when to order products from suppliers and the quantity of products ordered. In addition, there is no product classification in determining which products must be strictly controlled and prioritized. Therefore, this research aims to determine inventory classification and determine the proposed inventory control policy for PT. BWI plywood products, where the product has normal distribution. Based on the results of multi-criteria inventory classification, there are 5 products in class A, 6 products in class B, and 9 products in class C. After calculating the inventory policy using continuous review, the total proposed inventory cost can decrease by 84% of the total actual inventory cost [ABSTRACT FROM AUTHOR]

Inventories are essential in supporting the production process of a company. SMEs (small and medium enterprises) Annas is a business that moves on the production of slippers. The business problem is the lack and excess of materials requirements and uses the estimated. The research aims better to manage the material requirement planning of slipper products and reduce waste costs. The methods used are material requirement planning with the technique Lot for Lot. The results of research results obtained for the inventory of materials, selop, and soul carried out ordering materials as much as 12 times and no holding costs. On the materials, footwear makes an order 11 times, and there is a holding cost. The total inventory cost of slipper materials using the Lot for Lot Method is IDR 31,400,000. These results are lower and better than the total inventory cost contained in SMEs Annas. Also, the Lot for Lot method can reduce waste costs. [ABSTRACT FROM AUTHOR]

This study focused inventory service level of on raw, semi-finished, and finished materials for plastic goods based on existing budget. Cost limited Ng model combined with inventory grouping determination and ABC multi criteria adaptation, this study suggested three service levels for material based on reorder point system. Ng model can be developed into distribution lead time reduction with hybrid production strategy approach combination from make to stock and make to order, to further increase the efficiency of consumer supply chain. The first step was determination of ABC service level, that was adjusted according to sales input and financial budget. Second was calculation of inventory cost based on existing budget to get z service level for A, B, and C classification based on reorder point. This model can also be used to optimize grouping amount in order to minimize inventory budget and to direct supply chain management by fixing the goods provision. Lead time was recorded periodically and to notice the value of every phase in inventory. It can be developed into minimum order amount, if it is below the minimum order, then Re Order Point should be adjusted. The study was completed by a case study to investigate the proposed model. [ABSTRACT FROM AUTHOR]

This paper develops an integrated modelling of lots production scheduling and machines maintenance scheduling on flow shop with two machines. The manufacturing system produces multiple items to be delivered at a common due date. This model describes a trade-off between lot production cost and machines maintenance cost as number and quantity of lots on the series machines. The objective function of the integrated model is total cost minimization that is consisting of in process inventory lots and completed lots inventory cost, machines setup costs, preventive maintenance cost, corrective maintenance cost and rework cost on two series deteriorating machines. The step wise optimization algorithm developed to solve the mixed integer quadratic programming of the problem model. Comparison with the practice and the model sensitivity analysis are showed to clarify how the algorithm works. [ABSTRACT FROM AUTHOR]

We are developing 100-GWh heat-storage systems for use with 1000-MW Concentrated Solar Power (CSP) and nuclear reactor systems with capital cost goals of several dollars per kWh of heat storage—a factor of 50 under lithium ion batteries per unit of electricity. The capabilities of a 100-GWh heat storage system are similar to the Tennessee Valley Authority Raccoon Mountain pumped hydro facility that can provide 1652 MW(e) for 22 hours to address daily to weekly storage. The low capital cost of the Crushed Rock Ultra-large Stored Heat (CRUSH) system is only possible in large-capacity systems; thus, the CSP system average 24/7 heat inputs may exceed 1000 MW to match the heat storage capacity. Hot oil or nitrate salt is pumped from multiple solar farms or towers to the central CRUSH system and associated power block. The peak power block output may be 2 to 4 times average output with large economics of scale relative to the smaller power blocks associated with existing CSP systems. The cost savings from the large storage and the power block exceed the cost of hot oil or hot nitrate salt insulated pipelines over 10+ kilometers. The heat is stored in crushed rock in piles 20 m high and up to 250 m by 250 m on a side within an insulated floor and building structure. The sides of the rock pile are sloped rock that allow rock expansion and contraction with temperature without generating mechanical forces against walls. Heat is transferred from CSP to the crushed rock and then to the power cycle using (1) heat transfer oils for lower-temperature power systems to 400°C or (2) nitrate salts for higher-temperature power systems to 600°C. In charging mode, hot heat transfer fluid is sprayed over crushed rock and drains through the rock to the collection pans at the bottom to be reheated. Sections of rock are heated sequentially. In discharge mode cold heat transfer fluid is sprayed over crushed rock and drains through the rock to the collection pans below to deliver hot fluid to the power cycle. Heat storage costs are minimized by three features. Crushed rock is the lowest-cost storage material. The large building size minimizes the surface-to-volume ratio and thus building, insulation and foundation costs. The inventory and thus cost of oil and nitrate salt is minimized by using these fluids to transfer heat from CSP collectors to storage and then to the power block—but not for heat storage. [ABSTRACT FROM AUTHOR]

As people become more concerned about environmental issues, the effect of carbon emissions on demand becomes more obvious in Bio-materials engineering and manufacturing of other materials. Due to carbon emission and some other factors, a few of the items may deteriorate.in this regard, we have planned to build a Supplier-retailer inventory coordination model for deteriorating items with price and carbon emission dependent demand in a finite planning horizon. In both the centralized and decentralized cases, we are solving the model. The main objective of this research article is to identify the optimal cycle length for each order such that the total cost which is a combination of holding, purchasing cost, deterioration, ordering cost, and carbon emission have become minimal as possible. This study supports retailers and suppliers in reducing total inventory costs and carbon emission by computing the optimal amount of the order and optimal order interval. Finally, we are presenting numerical examples of the suggested method and its optimal results. As well as effects of changing the various parameters on the optimal total cost are also explained in detail graphically and in tabular form. A sensitivity analysis has also been conducted with the help of Mathematica version-12. In addition, several managerial insights are also highlighted. These observations are extremely managerial and informative for businesses seeking profitability while also satisfying their environmental responsibilities, as well as this study is very helpful for the government policy of any nation. [ABSTRACT FROM AUTHOR]

Pharmaceutical industry It is a genuinely global industry that is the principal supplier of products and clinical devices for hospitals all over the world. Pharmaceuticals, being the heart of the hospital, deals with a wide range of issues. This sort of issue occurs because they do not employ or do not have a structured methodology to follow. The research of several authors here represents a very significant part of the medical inventory, namely cost reduction and stockouts, which have been tackled using various techniques. The paper explains how classic statistical approaches may be used to anticipate the proposed methodology i.e., weather conditions, and to identify which limited-inventory items should be bought to reduce inventory costs and overstocking. The report concludes with a thorough assessment of the proposed technique. Using the technique proposed in this study, the overall inventory level of the concerned medical distribution organization could be lowered to a minimum. [ABSTRACT FROM AUTHOR]

A single product inventory system of non-instantaneous deteriorated items is considered with the implementation of deterministic break (DB) of service in between the replenishment cycle. DB is small compared with the whole replenishment cycle period. Initially the system starts with fixed lot size of items which will optimize the total cost of the inventory cycle. Two types of demands are incorporated such as constant rate of demand prior to DB and linear time dependent demand later DB. Throughout the replenishment cycle, deterioration rate of items is assumed as a constant. No demand is entertained at the time of observation of DB and deterioration in that period is unavoidable. Explicit expressions for optimum cycle duration and initial stock to minimize the total cost of the above considered system in a cycle are derived. Numerical illustration is given along with sensitivity analysis to validate the model. [ABSTRACT FROM AUTHOR]

Inventory is one of the important things in an agency or individual engaged in distribution. One of the main activities in a goods distribution service company is inventory control with the aim of minimizing inventory costs. The aim of this paper is to construct a mathematical model for warehouse inventory and optimize it to get the least cost. The proposed mathematical model is the EOQ (Economic Order Quantity) model. The model used is in a probabilistic environment. The step of the method i.e., determines the components of inventory costs, namely, ordering costs, transportation costs, storage costs, and purchasing costs. Then formulate a total inventory cost model and then proceed with the optimization of the model. And the last step is to do a numerical simulation as a real test of the model created. [ABSTRACT FROM AUTHOR]

The effective management of warehousing is one of the key successes for an organization's supply chain. Failing to perform proper management and activity control over warehouses leads to a higher possibility of customer satisfaction downturn and rising inventory costs. A core issue in warehouse management is the inability to obtain accurate information. Industry 4.0 makes use of technology to transform the practice in streamlining the supply chain at the operational level. A smart warehousing system is a product of technological involvement that provides a robust operation to facilitate continuous interconnected real-time information from various locations into a single database. The application of RFID technology is utilized in supporting the data integration process. This study presents a design system approach of data integration in smart warehousing. This study relied on an in-depth investigation of operation. The study found that the data integration process in smart warehousing consists of three major components: configuration, databasing, and transmission. The excellence of the research requires an enhancement to refine the novel finding using model testing. This study augments dynamics to the knowledge and stimulates higher vision for bridging the thinking to practitioners. [ABSTRACT FROM AUTHOR]

The transportation service industry in Indonesia has developed quite rapidly. Inventory control is still not right, and found that the problem of spare parts overstock was 84% of the company's standard value is 20%. This study's suitable forecasting method uses a double moving average (DMA) with the smallest MSE value of 2.466. The purpose of this research for the company is to prove the proposed effective inventory method to the company to exploit inventory costs and to avoid dead stock/waiting parts. The research on radiator materials. The optimal inventory planning system uses the Fixed Period Requirements (FPR) method. Ordering with the lot size provides the smallest cost for the ordering and storage process by 47% compared to conventional methods carried out by the company and can provide an idea of when to order and how many orders per period. It can help coordinate with suppliers to meet company needs with routine supplier evaluations with a delivery lead time of 0 days. [ABSTRACT FROM AUTHOR]

Based on the original Grey Model GM(1,1), the forecast accuracy of GM(1,1) have been modified using Fourier Series called FGM(1,1) to predict the demand of air compressor of compressor manufacturing industry. Markov Chain method have also been adopted to determine the optimal inventory with the minimum cost. The first step in this research is to determine the forecast value of demand for July 2020- December 2020 based on time series data in August 2019-June 2020. The calculation results showed that Fourier Series Grey Model (FGM) works better than the original GM(1,1), as evidenced by the better level accuracy of FGM(1,1) which are 9.66% of MAPE and 10.14% of RMSPE, while GM(1,1) gives 18.83% of MAPE and 23.64% of RMSPE. The next step is using time series data in August 2019-June 2020 and FGM forecasting results for inventory planning using Markov Chain Method. The results of the optimal inventory level can reduce the cost by 23%-64% of the company's current inventory cost. [ABSTRACT FROM AUTHOR]

In the manufacture of granulated sugar, the main raw material used is sugar cane. Additional raw materials are also needed in the manufacturing process, while additional raw materials are thohor, sulfur, phosphoric acid, and flocculants. In the production carried out, several obstacles are experienced, especially in providing raw materials, namely raw sugar cane, every month. This research aims to determine the best raw material supply method and a probabilistic additional raw material inventory model to determine the minimum total inventory cost. In this study, the Economic Production Quantity (EPQ) method was used for the supply of raw materials for sugar cane and the Continuous Review System (CRS) and Periodic Review System (PRS) models for the supply of additional raw materials for sugar production. The EPQ method is used for mass-produced types of raw materials and used alone for product sub-components. The CSR model is used to complete inventory control with a fixed number of orders but different order periods. While the PRS model is used for inventory control with the number of orders whose value varies, the interval of the ordering period is fixed. Results Based on the research obtained for The EPQ method, the total inventory cost is Rp. 124,729,898,959/month for sugarcane raw materials. The CSR Model obtained a total inventory cost of Rp. 101,328,065/year for additional raw materials. [ABSTRACT FROM AUTHOR]

Public health centre is one of the health services under the auspices of the UPTD Health Office, which is responsible for local community health services. Public health centre must manage the stock of medicines as well as possible to meet the needs of the community. The problem that occurs in the public health centre is overstock. There is a big gap between the supply and the need for medicines by the community. This can lead to high total inventory costs. Based on these problems, it is necessary to classify and plan medicines supply policies. In this study, as many as 143 types of medicines were classified using the ABC-Fuzzy Classification. This classification process produces three categories, namely very important, important, and unimportant. Furthermore, the calculation process will be carried out using the probabilistic periodic review method to determine inventory policy planning. The classification process for medicines using ABC-Fuzzy Classification analysis resulted in 21 medicines into the very important category, 33 medicines into the important category, and 89 medicines into the unimportant category. Then the results of calculations using a probabilistic periodic review resulted in a total proposed cost of Rp649,569,938, or a saving of 20.13%. [ABSTRACT FROM AUTHOR]

Coal is one of the raw materials used as a source of heat energy in several industries and Indonesia is one of the largest coal producing countries in the world and coal is spread in several areas in Indonesia. Tanjung Enim is located in South Sumatra is one of the coal-producing areas and there are many companies engaged in coal mining, one of which is FGH Ltd. FGH Ltd is one of the state-owned enterprises in Indonesia which the main activity is producing coal. However, there are several problems with coal inventory especially in 2020, where due to unpredictable coal demand, amount of coal inventory provided by FGH Ltd is "as much as possible" so it caused overstock, but there is also a stockout condition because FGH Ltd does not have a safety stock policy when that condition happened. Based on these problems, this research aims to minimize overstock and stockout of coal inventories using the Periodic Review (R, s, S) Power Approximation method then the results are Interval Review (R)=1,2 days, minimum inventory level (s)=167,675.22 tons, Maximum inventory level (S)=170,246.01 tons, and safety stock (ss)=100,306.73 tons. Then the author tried to simulate the proposed inventory policy with simple simulation in excel then the result are total inventory cost is decrease 39% from the actual condition where the proposed total inventory cost consist of total holding cost is decrease 20%, total shortage cost is decrease 100%, total procurement cost is increase 27%. [ABSTRACT FROM AUTHOR]

Inventory control problem becomes one of the most crucial parts in a company. Basically, the problem is to determine the optimal time and quantity of replenishment. But, there are many factors affected the decision such as demand uncertainty, lifetime of the product, deterioration, unit sales price and discount offered by the supplier. In this paper, we consider a mathematical model for inventory control problem. We consider a multi-item problem with inventory and price-dependent demand and all-units discount offered by the supplier. In dealing with multi-item problem, there are two replenishment policies to consider, individual order and joint order policy. Numerical examples are given with different inventory and price-dependent demand functions for each item and compare the individual and joint order policy. We found that in our numerical example, joint replenishment policy gives lower total inventory cost compared to the individual order policy. [ABSTRACT FROM AUTHOR]

Good and properly organized inventory management is essentially needed for a company in order to ensure that its production process runs smoothly. There are many factors to be considered since they can distract the inventory management such as demand behavior, the life time of goods, uncertain replenishment time, the political and economic situation, and unexpected natural disaster. There are certain risks involved with bulk replenishment such as the higher holding cost and the possibility of damage to the stored goods. On the other hand, if we order too little, the risks lie in the possibility that the production process will stop, resulting in lost sales due to the unavailability of goods. One strategy to overcome this unavailability of goods is backorder, where the customers will wait until the next replenishment to obtain their goods. This paper develops a mathematical model for inventory-dependent demand with the backorder policy applied. The decisions variables in our model are the optimal order quantity and the number of backorders, which minimize the total inventory cost. We also performed a sensitivity analysis of the optimal solution and found that the decreasing rate of the inventory is affected by the autonomous demand (α) and the increasing demand factor (β). Inventory will deplete faster as α and β increase. The number of backorders is affected by the high demand when inventory reaches zero and backorders entail a certain cost. When demand is higher and the backorder cost is relatively cheap, the number of backorders becomes higher. [ABSTRACT FROM AUTHOR]

The purpose of this study is to solve the problem of production planning to minimize overstock with forecasting methods where the results are used to form a Goal Programming model and solved by the Weighted method. Overstock problems can be solved by using the demand forecasting method by comparing the MAD, MSE, and MFE values of four forecasting methods including the Double Moving Average, Single Exponential Smoothing, Double Exponential Smoothing, and Linear Trend method. Forecasting results we obtained are then used to form the Goal Programming model. Another goal to be achieved is to reduce inventory costs and also get profit from sales so that the Weighted method is used here because each target has a different importance weight. The amount of the estimated cost of inventory due to forecast in 2020 will decrease from Rp. 8,130,505,919 to around Rp. 4,589,859,000. Sales profit is obtained with an income of Rp. 379,942,200. [ABSTRACT FROM AUTHOR]

The Economic Production Quantity (EPQ) Method is a method commonly used in inventory control problems, especially production in order to determine the optimal policy. In this study the Economic Production Quantity (EPQ) method was applied to determine the inventory control of Crude Palm Oil (CPO) and Kernel in determining the optimal amount of production so as to minimize inventory costs and maximize profits. The research was conducted by collecting data, namely data on the amount of production, the amount of distribution, procurement costs, and storage costs. The results obtained for the optimal amount of Crude Palm Oil (CPO) production per production cycle is 4.773.794,238 kg with an optimal time interval is 1,963 months and the optimal amount of Kernel production per production cycle is 1.228.927,139 kg with an optimal time interval is 1,980 months. There is a difference in inventory cost savings generated using the Economic Production Quantity (EPQ) method and the calculation based on the conditions of company's production is Rp 3.582.494,503 for Crude Palm Oil (CPO) and Rp 8.354.988,945 for Kernel. [ABSTRACT FROM AUTHOR]

PT Trakindo Utama is Indonesia's official dealer for heavy equipment, machinery, generators, forklifts and Cat parts from Caterpillar. The current problem is the company has used the min-max method in spare part inventory control but stock out often occurs in spare part inventory. Therefore, this research aimed to analyze the spare parts inventory to find out materials that need more supervision in order to minimize the possibility that can harm the company, along with inventory planning to obtain the optimal order quantity to minimize the total inventory cost. This research used ABC-FSN analysis of 167 types of 320D Excavator spare parts. ABC analysis is the classification of inventories based on the money value of the goods to the total annual investment of the stored goods, consisting of class A which is goods that give a high value, class B which is goods that give a medium value and class C which is goods that give a low value. FSN analysis is an inventory classification that groups materials into three categories, namely Fast-moving (F), Slow-moving (S) and Non-Moving (N) (deadstock). Then do the inventory planning for materials that are in the AF category. In inventory planning, demand forecasting and determination of optimal order quantities are made using two lot sizing methods, namely Part Period Balancing (PPB) and Wagner Within Algorithm (AWW).Results from ABC-FSN showed that there are 8 types of spare parts categorized as AF which are materials with high investment levels and fast movements. The lot sizing method gives the result that the PPB method produces a minimum total inventory cost compared to the AWW method. [ABSTRACT FROM AUTHOR]

The present study deals with a system of the inventory which is of deterministic form and has demand function depending on time. Holding cost of the system varies with time. Rate of deterioration is time proportional. This model of the inventory system allows shortages and also there is partial backlogging of the demand. The solution of this model is obtained in analytical manner by curtailing the cost in total of the inventory system. We have considered this model for crisp along with fuzzy environment. The result is illustrated by considering suitable numerical example. [ABSTRACT FROM AUTHOR]

We are developing 100-GWh heat-storage systems for use with Concentrated Solar Power (CSP) and nuclear reactor systems. Crushed rock fills a container up to 20 m high and 250 m by 250 m with insulated floor, walls and roof structures. Heat is transferred from the heat source to the crushed rock and then to the power cycle using (1) heat transfer oils for lower-temperature power systems to 400°C or (2) nitrate salts for higher-temperature power systems to 600°C. In charging mode, hot heat transfer fluid is sprayed over crushed rock and drains through the rock to the collection pans at the bottom to be reheated. Sections of rock are heated sequentially. In discharge mode cold heat transfer fluid is sprayed over crushed rock and drains through the rock to the collection pan below to deliver hot fluid to the power cycle. This design minimizes the inventory and thus the cost of heat transfer oil or liquid nitrate salt. The large container size minimizes the surface to volume ratio and thus insulation and structural costs. Crushed rock is the lowest-cost storage material. The goal is to drive storage capital costs down to several dollars per KWh of heat. [ABSTRACT FROM AUTHOR]

In this paper deals with an production inventory model without shortages in a fuzzy environment with fuzzy constraints for crisp production quantity or for fuzzy production quantity are rooted in fuzzy inventory management. We have applied graded mean method for defuzzifying the fuzzy general production inventory cost in trapezoidal fuzzy numbers. The aim of our work is to find optimal solution of these models by using Lagrangean method and Kuhn-tucker method finally a numerical example explained to show the uniqueness obtained in both crisp and fuzzy inventory model. [ABSTRACT FROM AUTHOR]

The efficient and effective inventory management goes a long way in the successful running and survival of an industry. In the present paper, the authors studied the existing inventory control system of an industry manufacturing gear wheels. The various types of gear wheels are made from the S45C material round bar. These gear wheels are manufacturing by various cutting inserts. The ABC analysis was performed to identify the A class inserts. Subsequently, the linear programming technique was used to establish the relationship between the consumption of A-class inserts and the production quantity of gear wheels. This relationship was used to determine the requirement of inserts for the future production quantity. The EOQ, re-order level, safety stock and total insert's inventory cost were determined for future production. The linear programming based inventory model reduced the 24-27% inventory cost as compared to the existing inventory model. [ABSTRACT FROM AUTHOR]

Inventory control is the guiding of supply, accessibility of items and storage in order to make sure an sufficient supply balance oversupply. It is referred as an internal control of an accounting system or procedure considered to assure or promote good company, the achievement avoid fraud error or security, etc. One of the difficult problems for professional is to examine, Healthcare researchers to analyze the inventory model in real life scenario. As lot of money occupied with their high holding costs in the inventories, the pharmaceutical companies cannot afford to have any money tied in excess inventories. In this proposed model, we considered a Fuzzy inventory model with shortages where the setup costs dependence on the size in step as the lot size strengthened. The inventory model contains various costs like Setup Costs, Shortage Costs, Holding Costs and Transportaton Costs. We consider the above said cost into fuzzy triangular number and to defuzzify Graded mean integration value is used. An algorithm is constructed, to find the economic order quantity along with the numerical examples for medicine organization. [ABSTRACT FROM AUTHOR]

Hospital must be aware with the management in pharmacy especially on pharmacy inventory management in pharmacy installation. Semen Padang Hospital is a facilities that provides health service that has one pharmacy as the central place that is responsible for the procurement, storage and distribution of medication throughout the hospital. But in current conditions, Semen Padang Hospital could not fulfill the demand of the medicine for its patients because there is out of stocks for several medicines at the inventory and its affect to the period of getting those required medicines for the patients where most of them have a pending issue. The number of pending receipt of medicines significantly increase month-by-month and its increasing ten times greater from July until December. This condition happened because there is no policy to manage the procurement of medication in Semen Padang Hospital. To anticipate the stockout condition of medicines, the managerial implement some solutions. However, this solution gives a negative impact for its financial aspect and their quality of service. Based on the problem, a new inventory policy is needed to reduce the number of stockout medicines and to minimize the total cost of inventory that incurred by the hospital. First the medicines will be classified into three classes by using ABC analysis based on its value of investment. The proposed medication inventory policy for class A and vital medicines are solved using probabilistic inventory model (EOQ + Safety stock) and for class B and C (Non – vital) solved using Joint Replenishment. This models are used because of the assumptions are suitable with the actual condition in Semen Padang Hospital. By using proposed inventory policy, Semen Padang Hospital has saving money potential as much 63.27% of the cost spend based on the current policy that applied right now in the last three months in 2018 (October – December 2018). [ABSTRACT FROM AUTHOR]

Spare parts are one of the important components of the production process at PT. Sari Warna Asli Textile. The production line at this company consists of dyeing, finishing, and printing. In fact, dyeing and finishing production lines often experience the absence of spare parts, while the mechanical department requires these parts. Therefore, this study discusses the improvement of inventory control of parts included in the important ABC category using a periodic review policy. The research begins with the classification of spare parts using the ABC-Fuzzy classification method followed by forecasting parts using Syntetos Boylan Aprroximation. Then, the research is continued with the determination of inventory levels, which are the maximum inventory amount (R) and time between orders (T). The minimum total inventory cost is obtained by investigating the impact of several service levels on total cost. The results show that the service level obtained by the proposed policy is higher than the service level determined by the company. It also show that the proposed policy performs better reducing total inventory cost compared to company policy. [ABSTRACT FROM AUTHOR]

This paper develops an Economic Production Quantity (EPQ) model for imperfect items by considering the rework and remanufacturing process, also generation of carbon emissions. In this model development, defective products may come from the results of regular production process and imperfect quality products returned by customers. Defective products which turned back by customers may occurs due to mistakes made by inspector during the screening process, these mistakes include classifying items that are defective as perfect quality items or incorrectly classifying non-defective items as damaged items. The defective product will be reworked at the end of the production cycle. The proposed model also considers carbon emissions emitted during the overall production cycle. This carbon emissions refer to the amount of energy consumed during the production process until the produced items are stored in the warehouse. The results obtained from the mathematical model can be used to determine the optimal number of production setup in one production cycle and the optimal regular production period length to achieve minimum total inventory related cost per unit time. [ABSTRACT FROM AUTHOR]

The Economic Production Quantity (EPQ) model is an inventory control model that can be used by a company to determine a number of certain product to minimize the total cost. One of the way to minimize the total cost incurred by a company is to determine optimal production quantity and process mean. This paper presents a modified economic production quantity model with deterioration in production process. The purpose of this paper is to develop an optimization model for determining economic production quantity and process mean by considering internal and external quality loss. The optimal production quantity (Q) and process mean (μ) are determined by minimizing the total expected cost of product per hour that include the total average quality loss, the total average material cost, the total average setup cost, the total average inventory holding cost, the total average adjustment cost, the total average maintenance cost, and the total average inspection cost, per hour. The optimal values of Q is 200 and μ is 7.655 with the total expected cost per hour is $ 364.897. [ABSTRACT FROM AUTHOR]

Countries in the world need the right steps to maintain global sustainability. This is because the effects of global warming, as a result of greenhouse gas emissions, have threatened the balance of the Earth’s ecosystem. One of the joint commitments that have been made is related to reduce carbon emissions. Practically, this commitment is intended to determine the carbon capacity limitation for each country or company, which is defined as a carbon cap. With this limit, we hope to find the best solution to reduce the amount of carbon emissions while minimizing the total transportation costs and inventory costs. In this study, we developed an inventory management model that integrates land multimodal transportation from multi factories to several customers by considering carbon emission limitation. The two land multimodal transportation used are (a) trucks which transport a product from several factories to stations and from stations to customers and (b) trains from departure stations to arrival stations for long distance shipments. The purpose of this study is to find an optimal solution that considers total costs and carbon emissions. The decision variables of this study are inventories at the factories, as well as the quantities of product deliveries. Numerical experiment results show that carbon cap affects total emissions and total costs for each supply chain activity. We also carried out a sensitivity analysis to find the relationship between decision variables and carbon cap scenarios. By changing the carbon emission limit values, the number of inventories at the factories shows different patterns. [ABSTRACT FROM AUTHOR]

This study presents an inventory model for deteriorating items” considering carbon emission and inflationary environment for single-vendorasingle-buyer. The production process is imperfect due to unreliability of process. Carbon emission is included in the model and calculated from keeping the deteriorated items, transporting, and warehousing. Emission due to transportation relies upon the fuel utilization of the vehicle, the fuel discharge, and the distance traveled. Warehouse emission relies upon the total inventory and the warehouse energy consumption per unit item. Emission due to deteriorating items is related to its disposal. “A cap-and-trade policy offers its own favorable circumstances in that emissions allowances can be distributed to minimize the policy’s negative impacts on aggressiveness and anticipate emissions spillage”. During storage, inventory has a value of time and investment period so that inflation influences decision-making in inventory management. “The purpose of this model is to determine the frequency and quantity of product delivery as well as the inventory level to minimize both carbon emission costs and the total inventory. This paper proposes a solution procedure and provides a numerical example to illustrate the application” of the proposed model. Sensitivity analysis is given to show the impact of the changes of decision variables on the model behavior. [ABSTRACT FROM AUTHOR]

Materials or inventories are essential requirements for any company in order to fulfill their customers’ needs and wants. This case study has cooperated with a construction firm, XYZ company which is located at Bukit Batok area, Singapore. The rationale behind the choice of this company is the inefficiency of systematic inventory management process in a fast growing construction company. The company also lack of proper forecasting techniques in predicting accurate demand for its main construction raw materials. Therefore, a suitable inventory control model by using the Economic Order Quantity and forecasting techniques was identified to be implemented in the company. The forecasting techniques were used to predict the optimum demand and Economic Order Quantity was applied to minimised the total inventory cost in order to achieve the research objectives. The end results of the inventory control model was evaluated by decision tree analysis. Data is collected through interview with the targeted respondents which are general managers or core members of the managerial team who have good understanding of the firm especially in the inventory system. The collected data were analysed by QM for Windows software and Microsoft Excel. This study concluded that XYZ company should practice forecasting techniques for some of the raw materials in determining the optimum demand quantity. However, Economic Order Quantity model should applied for all raw material in order to attain optimum total inventory cost. [ABSTRACT FROM AUTHOR]

Inventory management is important for any organization, especially in the field of health service which plays major role in social development. However, failing to handle inventory effectively will affect the health care services to patients. In view of this issue, practicing a systematic inventory management is very important to achieve the objective of minimizing the investment in inventory while balancing supply and demand. Therefore, current study proposed and evaluate an inventory control model by integrating nonlinear programming, forecasting techniques and decision tree for public hospitals in Malaysia. The forecasting techniques were used to predict the optimum order quantity and nonlinear programming was applied to minimize the total inventory cost in order to achieve the research objectives. The end results of the inventory control model was evaluated by decision tree analysis. Secondary data was collected from Malaysian Statistics on Medicines reports. The collected data were analyzed by QM for Windows software and Microsoft Excel. This study concluded that public hospitals in Malaysia should practice forecasting techniques in determining the optimum inventory quantity for drugs. In addition to that, the proposed nonlinear programming with budget constraint should applied to attain optimum total annual inventory cost. [ABSTRACT FROM AUTHOR]

Inventory control is an activity related to the planning, implementation and supervision and determination of material requirements in such a way that the operational needs can be met in time by investing in material inventories can be controlled at the most economical level. This paper proposes an efficient inventory management for controlling spare parts in an oil drilling company. ABC analysis is employed to classify the spare parts based on investment value. The spare part demand is then predicted using 3 forecasting methods, namely Croston, Syntetos-Boylan Approximation (SBA) and Single Exponential Smoothing (SES). The inventory level is developed by determining the optimal quantity order using an Economic Ordering quantity (EOQ) method. Safety stock and reorder level are also determined by allowing the considerations of lead time, error and service level. The existing inventory policy used by a company is calculated and compared with the proposed policy. By adopting the proposed inventory policy, the company will incur annual total inventory cost IDR 45,448,786, which is lower than the cost resulting from an existing policy IDR 51,552,528. [ABSTRACT FROM AUTHOR]

This model considered buyer-vendor for deteriorating products. The model assumes lead time demand is distributed normally based on standard deviation and mean. And buyer takes decision for damaged products. The aim of the model is to find the optimal order quantity to diminish the overall inventory cost. Finally, arithmetical representation and sensitivity analysis are given to depict the developed model. [ABSTRACT FROM AUTHOR]

The inventory cost has important impact on the production cost. In order to get the maximum circulation of funds of enterprise with minimum inventory cost, the inventory control with Lean Six Sigma is presented in supply chain management. The inventory includes both the raw material and the semi-finished parts in manufacturing process. Though the inventory is often studied, the inventory control in manufacturing process is seldom mentioned. This paper reports the inventory control from the perspective of manufacturing process by using statistical techniques including DMAIC, Control Chart, and Statistical Process Control. The process stability is evaluated and the process capability is verified with Lean Six Sigma philosophy. The demonstration in power meter production shows the inventory is decreased from 25% to 0.4%, which indicates the inventory control can be achieved with Lean Six Sigma philosophy and the inventory cost in production can be saved for future sustainable development in supply chain management. [ABSTRACT FROM AUTHOR]

Dual channel supply chain (DCSC) has been attracting many researchers' attention. Their contributions mainly are in two folds, namely pricing problem and inventory policy. However, research to address both pricing and inventory problems simultaneously are still scarce. Meanwhile in recent competitive market, product substitution is an unavoidable practice in fulfilling customer demand when the main product is unavailable. Thus how to decide price and order quantity by considering product substitution under DCSC setting is an interesting topic to address. In this paper, corresponding mathematical model incorporating such problem is proposed. This model consists of objective function measuring sales revenue and inventory cost, and some constraints to assure positive profit margin, interplaying price between online and offline channel, and positive demand. Two pricing schemes, namely Vertical Nash and Stackelberg Leadership are evaluated. The result shows that in any situation of substitution level, Vertical Nash solution provides higher financial performance than that under Stackelberg Leadership. In addition, this work's results have also revealed that there exist some threshold values differentiating when it is better off to apply Vertical Nash scenario an, when Stackelberg Leadership scenario is preferable. [ABSTRACT FROM AUTHOR]

Supply chain management has become a critical issue for modern business environments. In today's world of cooperative decision-making, individual decisions in order to reduce inventory costs may not lead to an overall optimal solution. Coordination is necessary among participants of supply chain to achieve better performance. There are legitimate and important efforts from the vendor to enhance the relation with buyer; one such effort is offering trade credit which has been a driver of growth and development of business between them. The cost of financing is a core consideration in effective financial management, in general and in context of business. Also, due to imperfect production a vendor may produce defective items which results in shortages. Motivated with these aspects, an integrated vendorbuyer inventory model is developed for imperfect quality items with allowable shortages; in which the vendor offers credit period to the buyer for payment. The objective is to minimize the total joint annual costs incurred by the vendor and the buyer by using integrated decision making approach. The expected total annual integrated cost is derived and a solution procedure is provided to find the optimal solution. Numerical analysis shows that the integrated model gives an impressive cost reduction, in comparison to independent decision policies by the vendor and the buyer. [ABSTRACT FROM AUTHOR]

This study proposes the analysis of an inventory model for linearly decreasing demand and holding cost for non-instantaneous deteriorating items. The inventory model focuses on commodities having linearly decreasing demand without shortages. The holding cost doesn't remain uniform with time due to any form of variation in the time value of money. Here we consider that the holding cost decreases with respect to time. The optimal time interval for the total profit and the optimal order quantity are determined. The developed inventory model is pointed up through a numerical example. It also includes the sensitivity analysis. [ABSTRACT FROM AUTHOR]