Calculation Of Safety Stock Research Articles

ANALYSIS OF INVENTORY MANAGEMENT IN A BAKERY INDUSTRY

This case study analyzes the wheat stock management, a crucial input in the bakery industry, in a company located in the Greater Vitória region, Espírito Santo, Brazil. Using the case study methodology, the objective is to identify ways to save and reduce costs, considering the company's logistics and production needs. The Economic Order Quantity (EOQ) system through the Continuous Review Model is employed in the analysis of Inventory Management. Prioritizing the French bread, the best-selling product, the application of the ABC method highlights wheat flour as essential. The calculation of lead time, safety stock, and economic order quantity proved promising; however, delivery logistics pose a challenge. The 600-bag limit per truck and the location in a residential area hinder larger orders. The proposed safety stock does not even cover a day's production, requiring adjustments to prevent interruptions. Although the continuous review model presents advantages, logistical and operational limitations must be considered. A hybrid approach may be more suitable to ensure operational efficiency and continuity of operations.

Demand Driven Material Requirements Planning: An Inventory Optimization Model

When dealing with stochastic multi-state production and distribution systems, determining the appropriate quantity of safety stocks on hand may be tricky. We often limit existing solutions for maximizing safety stock levels while keeping cost, objectives and service level constraints in mind to a subset of multi-stage inventory challenges, such as strictly serial architectures or specialist two-stage production/distribution systems. This may make achieving ideal stock levels while meeting cost objectives and sustaining service levels problematic. This is due to the underlying assumption in these systems that cost and service level are directly proportional to one another. Controlling unpredictability and satisfying customers are inventory management?s most important tasks. DDMRP (Demand-Driven Material Requirements Planning) dynamically adjusts inventories to handle unpredictability and improve customer service. This is done to improve crisis management. This achieves ?demand-driven material requirements planning.? This study presents a DDMRP-specific safety stock calculation. The inclusion of this formula aids in the preservation of mathematical consistency. When dealing with a model based on normal probability distributions, the major focus is discovering and applying the parts necessary for safety stock computation. One of the most well-known fast-moving consumer goods (FMCG) firms in South East Asia is the major focus of a case study to validate the proposed strategy. To build a scientific model, the study adopts a probabilistic strategy. The primary goal of this model is to aid in the process of identifying appropriate levels of safety stock and inventory at the distributor level, which will ultimately allow for a customer fill rate of 99%. A distribution network will be employed to achieve this purpose. The model provides a complete framework for estimating optimum safety stock levels and reorder points while accounting for the stochastic nature of demand and including critical elements. This enables more precise forecasting of future demand. This contributes to better inventory management practices and promotes customer satisfaction.. KEYWORDS :DDRMP, Demand level, Distribution network, Safety Stock Model.

Analisis Break Even Point dan Margin of Safety Sebagai Alat Perencanaan Laba Pada Usaha Tahu Sumber Mulya Kota Bengkulu

The purpose of this study was to determine the application of BEP and MOS as a profit planning tool in the Usaha Tahu Sumber Mulya in Bengkulu city. The data collection method used is unstructured interviews and documentation with qualitative and quantitative analysis methods using Break Even Point analysis. The results of the research, BEP the contribution ratio per unit of tofu was 41% with a business profit rate of 35.3% with a margin of safety of 86.1%. While the where the contribution ratio per unit of tofu was 49.2% with a business profit level of 44.1%, the level of security or margin of safety in 2022 was 89.8%. The use of BEP and Safety stock calculation provides an overview of the Usaha Tahu Sumber Multa in Bengkulu City, you can see the BEP for tofu production and safety stock in the warehouse, this is so that the production process continues and obtain the desired profit .

Multi-Item Inventory Control Using Economic Order Quantity (EOQ) Model with Safety Stock, Reorder Point, and Maximum Capacity in Retail Business

The presence of retail businesses in Indonesia has many positive impacts on the community, especially in improving the economy. The existence of buying and selling transactions involving suppliers, retailers, and the community as consumers can play a role in improving the national economy. Retail can be called a bridge for suppliers and consumers to meet their needs. The diversity of consumer needs requires retailers to provide a variety of products from many suppliers. Efforts that need to be made by retail businesses in order to minimize costs incurred are by controlling inventory. To prevent excessive expenditure, the inventory control method used is to apply the Economic Order Quantity (EOQ) model. The EOQ model can provide the optimum total inventory cost by adjusting the frequency of orders placed over a period of time. After obtaining the total inventory cost, the calculation of safety stock, reorder point, and maximum capacity can also be applied so that the inventory costs incurred can be minimal.

Sistem Perencanaan Manajemen Logistik Obat di Puskesmas

Background: Drug planning is a process of selecting drugs and health supplies to determine the type and amount of drugs in order to meet drug needs at the puskesmas. Planning for drug needs at the Waruroyom Health Center is still not in accordance with real needs. This is often a gap between the drug requirements requested by the puskesmas and the drugs provided by the health office. The purpose of this study was to find out about the drug planning process at the Waruroyom Public Health Center Methods: this type of research is a qualitative research with in-depth interview method, the data is collected by means of observation, documentation, and the validity of the data using triangulation techniques. Results: The results showed that the drug planning process still had obstacles in the process of calculating drug requirements so that it still caused vacancies and excess quantities of drugs that could affect the process of procuring drug needs and losses due to the accumulation of drug stock. Conclusion: Based on the research results of the Waruroyom Health Center to increase knowledge of calculating drug needs for drug needs planning managers to apply the EOQ, ROP, and Safety stock calculation methods to avoid drug vacancies and excess drug stock and combine ABC and VEN methods in determining the types of drugs that will be prioritized to be administered.

A nonparametric approach for setting safety stock levels

In practice, lead time demand (LTD) can be skewed, multi‐modal or highly variable, and these factors compromise the validity of typical approaches used for setting safety stock levels. Motivated by encountering this problem at our industry partner, we develop an approach for setting safety stock levels using the bootstrap, a widely used statistical procedure. Existing bootstrap approaches for inventory management either operate directly on observed LTD or assume deterministic lead times, permitting direct application of the bootstrap approach for univariate quantile estimation. As LTD is a convolution of multiple random demands over a random lead time, a multivariate bootstrap approach is required. As we demonstrate, when lead times are stochastic, our multivariate approach provides improved safety stock estimates. We develop a multivariate central limit theorem for the bootstrap mean and bootstrap quantile—components of the safety stock calculation—highlighting why the generalization of these bootstrap methods is critical for inventory management. These results provide a theoretical underpinning for the bootstrap estimator of safety stock and permit the construction of confidence intervals for safety stock estimates, allowing decision makers to understand the reliability with which the desired service level will be achieved. Building on our theoretical results, and supported by numerical experiments, we provide insights on the behavior of the bootstrap for various LTD distributions, which our results demonstrate are critical when employing the bootstrap method. Implementation of our approach with our industry partner resulted in an inventory investment reduction of $1.17 million combined with an overall increase in service level. Our approach is general and can be implemented without modification in other settings.

Implementation of Raw Material Inventory Control System to Increase Sales of Hand Batik

This study aims to explain about how to control the supply of raw materials in the Batik Tulis Trading Business "Jetis Sidoarjo". The method used in the quantitative approach. The research approach in this thesis uses a quantitative research approach with a descriptive approach. In the object of this research, namely the implementation of a raw material inventory control system to improve the quality of batik production in Kampoeng Batik Tulis Jetis SMEs. The subjects in this research are the UMKM Kampoeng Batik Tulis Jetis, Lemahpuro Village, Sidoarjo District, Sidoarjo Regency, East Java. With descriptive research, the researcher only intends to describe (describe) or explain the symptoms that are currently happening. The results of this study can be concluded that using the calculation of safety stock and reordering is more effectively used in controlling raw material inventory when compared to current company policies. Companies can predict or avoid shortages or excess raw materials that can result in disruption of the production process by setting a safety stock calculation and also setting a re-order point, so the company can know or predict when to reorder and obtained with minimal inventory costs.

Forecasting Thinner Number 7 Sales Using ARIMA (Autoregressive Integrated Moving Average) Method

PT. DCN Indonesia is a paint distributor company. In the provision of paint and all devices including thinner often require a keepatan in its provider. This research is done to obtain thinner demand forecasting and determine the amount of stock that must be available in storage in order to at any time meet the impromptu demand that is one of the problems. ARIMA is a forecasting method that is suitable for such cases because it has advantages in the use of data with fluctuating patterns. The results achieved in this study got the ARIMA model (1, 0, 4) which means that the forecasting results are influenced by the results of observations one month ago san error four months ago. obtained the results of the sale of thinner of 8 liters and after going through the calculation of safety stock resulted in inventory planning calculations of 120 liters.

The Konfigurasi Sistem Database Enterprise Resource Planning (ERP) Berbasis Open Source Berdasarkan Material Requirement Planning (MRP)

Cahaya Citra Alumindo is a company engaged in manufacturing. In planning raw materials, there are several problems that occur, namely production planning is still limited in its calculations because there is no structured recording available. In addition, the flow of document information in each division is still done manually, so that it can hamper the company's business processes. From the results of the study, the total net weight of car wheel products based on waste calculations was 23,150.35 kg, from the calculation of reorder points and safety stock, it was found that the raw material requirements for a 3 month period were 20,852.35kg with a lead time of 7 days, and the lowest inventory cost. low with the lot for lot method of Rp. 836,140,000. While the results of enterprise resource planning, from the validation results, the System Usability Scale (SUS) test obtained a value of 26.67 which included Acceptable, in the Grade Scale it got a value of C and Adjective. The rating gets Good, the result of the user experience of the Odoo ERP system has a User Friendly UX.

Adaptive model to increase resilience for emerging supply chains within the circular economy – “Zirkelmesser” an innovative case study

Variations in quantity, quality and time availability of input materials pose a major risk to circular supply chains (CSC) and require new models for creating and evaluating adaptive and resilient CSC in the circular economy (CE). This can be achieved through consistent modelling of the overarching relationship between resource input- and output streams, without neglecting the associated risks.The model proposed below consists of five components based on five resilience requirements for supply-chains (SCs). It provides a data-based recommended course of action for managers with a low entry-barrier. It consists of a CSC visualization, safety stock calculation, risk monitoring for each SC node, reporting logic, and a measurement catalogue. The inspiration for this model came from an innovative case study (“Zirkelmesser”) in the metal processing industry, where secondary products and materials are used to produce new products. Here, the problem of maintaining the resource supply arose and led to resilience issues. The mentioned case study serves as an application example for the model application and contributes to making emerging circular supply chains predictable and more controllable, thus increasing their resilience.

Reducing Spare Part Inventory Cost with Shortage Elimination through Probabilistic Economic Order Quantity

Company Z had an inventory of fast moving spare parts where the demand pattern for these spare parts fluctuated every month and there were several months in which the demand was zero. In addition, company Z did not have a safety stock for these spare parts, so the risk of shortage for these spare parts was quite high. This study aimed to reduce fast moving spare part inventory costs and prevent the risk of shortage by determining the optimal order quantity and re-ordering time. The inventory control model used to determine the optimal order quantity was the Probabilistic Economic Order Quantity (Probabilistic EOQ). This model is appropriate to use in conditions of unstable demand and it requires the calculation of safety stock to prevent shortage. Research data in the form of data on demand, lead time, purchasing cost, ordering cost, carrying cost, and shortage cost were collected through company documents. The data that had been collected was then processed using an excel spreadsheet. Demand forecasting for the next 12 months was carried out using the Croston method. Forecasting results were used as input in calculating the optimal order quantity on Probabilistic EOQ. Furthermore, data processing was run by calculating the safety stock and reorder point. The total inventory cost with Probabilistic EOQ was calculated and compared with the company’s total inventory cost to determine whether Probabilistic EOQ is able to create inventory cost reduction. The results showed that Probabilistic EOQ enabled the company to reduce its inventory cost up to 57.85%.

Forecasting of lead-time demand variance: Implications for safety stock calculations

Lead-time demand forecasting constitutes the backbone of inventory control. Although there has been a considerable amount of research on forecasting the mean lead-time demand, less has centered around forecasting lead-time demand variance, especially in the case of stochastic lead-times. This represents an important gap in the literature, given that safety stock calculations rely explicitly on the lead-time demand variance (or equivalently the variance of the lead-time demand forecast error for unbiased estimators). We bridge this gap by exploring the viability of three strategies to estimate the variance of the lead-time demand forecast error under stochastic lead-times: (1) aggregating the per period variance of forecast errors over the lead-time, which is the classical approach; (2) considering the variance of the aggregated (over the lead-time) forecast error; (3) considering the variance of the forecast errors resulting from temporally aggregated (over the lead-time length) demand. Analytical results are derived for a first order autoregressive moving average ARMA(1,1) demand process for both a single exponential smoothing and the minimum mean squared error forecasting method. A numerical investigation assesses the effects of demand autocorrelation and lead-time variability on the accuracy of each strategy, and the conditions under which one outperforms the others. The results show that the classical strategy presented in textbooks appears to be the least accurate one, except for cases with a high negative demand autocorrelation. An analysis of the inventory control performance also reveals that the classical strategy often leads to higher inventory costs and lower service levels for positive autocorrelation.

ANALISIS KINERJA MANAJEMEN PERSEDIAAN PRODUK UD. SINAR JAYA KARANGASEM

Inventory plays an important role in the company's operational activities, it is necessary to do inventory management in order to minimize losses caused by the large inventory costs. This research is conducted at UD. Sinar Jaya, aims to determine the performance of product inventory management and whether it’s efficient or not. Research data are obtained through interviews and observations. Descriptive analysis technique is used, which describes systematically several stages starting with ABC analysis, EOQ calculation, safety stock calculation, re-order point calculation, maximum inventory calculation, inventory turnover calculation, and comparing the total inventory cost between the method applied by the company with the EOQ method. Results show that product inventory management performance is not efficient. This is indicated by the total cost of inventory incurred using the company method in 2019 amounting to IDR 43,058,137. The product inventory management system that should be carried out is to classify products with ABC analysis, then determine EOQ of 1,208 units, determine safety stock of 518 units, and determine the re-order point of 1,099 units for each classification at unit A, so that the total cost of inventory incurred is only IDR 32,716,517 or 24.02 % lower than the actual application of company methods.
 Keywords: ABC analysis, EOQ, inventory costs

Analysis of raw material inventory for insecticide packaging bottle with material requirement planning: a case study

PT. Agricon mostly produces 1L package (bottle) pesticides named Spontan insecticide. This study was conducted to analyze and determine the stock inventory of 1L bottles for determining an effective ordering schedule based on the calculation of safety stock and reorder points to optimize planning and inventory. Material Requirement Planning (MRP) method used to determine the effective scheduling of 1L bottle products. Material Requirement Planning is one method used to determine scheduling with advantages such as reducing inventory, reducing set up costs, and reducing idle time. The proposed order scheme for ordering 1L insecticide packaging bottle improve the company on reducing the frequency for ordering bottles from 7 times to 5 times and inventory is more stable and close to demand quantity

Application of MRP System for Control of Raw Material Inventory with EOQ Lot Sizing

PT. Skala Maxima Griya Workshop 1 is a company who produces TV cabinets. Raw materials stored in Workshop 1 warehouse are very piling up to over stock. Forecasting is done using a method that is in accordance with the request pattern. Then the best forecasting method is chosen based on MSE, MAD, SDE, MAPE, ME, and MPE the smallest. Forecasting results are used to create a MPS. The data from the MPS is used to calculate safety stock and make product MRP. The results of MRP products are used to calculate gross requirements, lot sizing, and MRP of raw materials. This research uses lot sizing technique EOQ. After calculating the results obtained that the selected forecasting method is DES with alpha 0.1. The safety stock calculation also shows good results where the safety stock that must be prepared by the company is not too much the majority of value if in the round up is 1. The MRP calculation with lot sizing EOQ also shows a good thing where there is a savings in raw material costs of Rp 10,800,000 .00 or 54.18% after using this method.

PENERAPAN METODE DISTRIBUTION REQUIREMENT PLANNING UNTUK MEMINIMASI BIAYA DISTRIBUSI PT SEKELUARGA

Along with increasingly intense competition in any industry or business sector. Demand companies to use methods in order to win the competition. One of them is by doing fast distribution. PT Sekeluarga is one of the companies that distribution of LPG. PT Sekeluarga still has problems such as the inability to distribute goods according to demand, causing a break in the distribution chain and causing scarcity of LPG that occurs at the lowest distribution level or the community. The study was conducted using the Distribution Requirement Planning (DRP) method in addition to that there are also Lot size calculations with Fixed Order Quantity (FOQ), safety stock calculations, and forecasting. The Total Cost (TC) using the company method is Rp. 14,563,117.00. while the Total Cost (TC) using the Distribution Requirement Planning (DRP) method is Rp. 11,676,354.17. From the results of the Total Cost comparison it is found that the Total Cost with the Distribution Requirement Planning method is cheaper when compared to the company method. And by using the Distribution Requirement Planning method also obtained an efficiency of 19.82%.

A Non-Parametric Approach for Setting Safety Stock Levels

In practice, lead time demand (LTD) can be non-standard: skewed, multi-modal or highly variable; factors that compromise the validity of the classic approaches for setting safety stock levels. Motivated by encountering this problem at our industry partner, we develop an approach for setting safety stock levels using the bootstrap, a widely-used statistical procedure. We extend prior research that has used the bootstrap for quantile estimation to address the multi-parameter estimation of safety stocks. We develop a multivariate central limit theorem for the bootstrap mean and bootstrap quantile -- components of the safety stock calculation -- highlighting why the generalization of these bootstrap methods is critical for inventory management. These results provide a theoretical underpinning for the bootstrap estimator of safety stock and permit the construction of confidence intervals for safety stock estimates, allowing decision makers to understand the reliability with which the desired service level will be achieved. Building on our theoretical results, and supported by numerical experiments, we provide insights on the behavior of the bootstrap for various LTD distributions, which our results demonstrate are critical when employing the bootstrap method. Implementation results with our industry partner indicate our approach is quite effective in setting safety stock levels.

Dynamic Safety Stock Considerations - A simulation based comparative analysis

The focus of the study is to conduct a comparative analysis of the most widely adopted methods of safety stock calculation. Firstly, it aims to identify the most widely adopted methods of safety stock calculation and investigate their strengths and weaknesses. Secondly, the thesis aims to analyse the demand patterns that operations managers often encounter and their behaviours. The safety stock calculations will then be compared to one another by running a simulation with different demand patterns using each of them. Finally, recommendations will be made on which demand patterns, if any, each of these methods is best applied to.

ANALISIS PENGELOLAAN OBAT SEBAGAI DASAR PENGENDALIAN SAFETY STOCK OBAT DI PUSKESMAS GANRA KABUPATEN SOPPENG

Drug management is an important aspect that include of planning, procurement, acceptance, storage, distribution, to the destruction of drugs. Drug management is a very important thing that needs to be considered, considering that with management that is not in accordance with the proper procedures, overlapping problems will occur. The Pharmacy Installation of the Soppeng District Health Office has carried out drug management but there are still a number of problems namely inadequate human resources, and inadequate facilities. This study aims to determine how the management of drugs in the Department of Health and Community Health Center Soppeng Ganra. This research is a descriptive analysis with a quantitative approach using observational methods. Data collection was carried out using the interview method through questionnaires. The results showed that the management of drugs in the Department of Health and Puskesmas Ganra, Soppeng Regency was not optimal because there were still many shortcomings such as controlling safety stock that had not used good calculations. The results of data percentage based on two different methods obtained 3.48% based on the proposed planning in 2018 and 96.51% using the planning method based on the calculation of safety stock.

Waste and Accurate Management of Raw Material Inventory in Wood Companies

Data obtained from the statistical office shows that Lumajang Regency, in general, is one of the largest albasia wood producers in East Java Province. Albasia wood is basically easily cultivated and minimal maintenance and is able to grow well even though the land is categorized as infertile. This is what makes people more interested in growing Albasia wood. The research objective is to analyze the optimal albasia wood raw material volume needed, to analyze the total cost of supplies, to analyze when a reorder point for albasia wood raw material is carried out, to analyze the amount of albasia wood safety stock that must be provided. Direct observation and observation activities in the field as well as taking documentation, interviews and discussions with CV. JAZINDO employees. Data Analysis Data analysis was done in a descriptive qualitative manner by recording to describe the state of the object under study based on facts and conditions that occurred in the field. Based on the results of data collection, calculation and analysis of data in 200 cm albasia wood are 945 m3, and for 260 cm albasia wood is 72 m3. Purchase of raw materials needs to be done after the inventory reaches the ROP limit. Safety stock calculation, obtained safety supplies for each type of albasia wood, namely 1543 m3 for albasia 100 cm wood, 548 m3 for albasia 130 cm wood, 848 m3 for albasia wood 200 cm, and 56 m3 for albasia wood 260 cm. With the EOQ method, it is recommended to order wood at calculated intervals.