Safety Stock Research Articles

Risk-based inventory scheduling framework to fulfill multi-product orders within a production network

Production facilities are critical components of the global economy and supply chain. Firms are forced to balance several competing objectives—from reducing operating costs by managing inventory to increasing profits by satisfying customer demand. The act of scheduling material through an interconnected production network is analytically challenging; therefore, stakeholders require statistical insights to strengthen the decision-making process. This inventory scheduling application allows decision-makers to monitor the status and impact of numerous production parameters while aiming to mitigate the propagation of schedule risk through the system. This work presents a material planning framework that (i) jointly represents work center and material relationships and (ii) integrates stochastic methods to assess potential risk. Using network flow optimization and Monte Carlo simulation, this work accommodates three primary considerations: (i) safety stock, and other inventory restrictions, (ii) multi-product order satisfaction, and (iii) costs derived from holding inventory and delaying orders. An illustrative example examines the impact of twelve experimental scenarios on order fulfillment, work center utilization, and material inventory and production.

Measurement of the impact of buffer stock intervention on food security of smallholder farmers in Ghana by means of the nutrient-content household dietary diversity index

Measurement of the impact of buffer stock intervention on food security of smallholder farmers in Ghana by means of the nutrient-content household dietary diversity index

RETRACTED ARTICLE: Sustainable and optimal design of Chinese herbal medicine supply chain network based on risk dynamic regulation mechanism

We propose a robust fuzzy design model for a sustainable closed-loop supply chain network. The model is based on a risk dynamic regulation mechanism. In this way, we can solve the problem of sudden disruptions and uncertain demand in the supply chain of Chinese herbal medicines. We also develop a hybrid algorithm solution to solve the model and design a resilient supply chain network. The specific steps are as follows: (1) The risk dynamic regulation mechanism is created with strong risk resistance by considering the information sharing platform, facility defense, drying station scheduling, safety stock, and shared inventory. (2) Based on the dynamic risk regulation mechanism, we establish a sustainable Chinese herbal medicine supply chain network design model. Then, we use the robust fuzzy method and the epsilon constraint to deal with the uncertainty and integrate the model. (3) We introduce opposition-based learning, cosine convergence factor, and levy flight to the original Whale and Grey wolf algorithms to obtain the Hybrid algorithm, which is used to solve the processed model. The results show the model and algorithm proposed in this paper have strong applicability and advantages in designing closed-loop supply chain networks for Chinese herbal medicine and provide references for relevant decision-makers.

Hydrogen supply chain and refuelling network design: assessment of alternative scenarios for the long-haul road freight in the UK

Shifting from fossil fuels to clean alternative fuel options such as hydrogen is an essential step in decarbonising the road freight transport sector and facilitating an efficient transition towards zero-emissions goods distribution of the future. Designing an economically viable and competitive Hydrogen Supply Chain (HSC) to support and accelerate the widespread adoption of hydrogen powered Heavy Goods Vehicles (H2-HGVs) is, however, significantly hindered by the lack of the infrastructure required for producing, storing, transporting and distributing the required hydrogen. This paper focuses on a bespoke design of a hydrogen supply chain and distribution network for the long-haul road freight transportation in the UK and develops an improved end-to-end and spatially-explicit optimisation tool to perform scenario analysis and provide important first-hand managerial and policy making insights. The proposed methodology improves over existing grid-based methodologies by incorporating spatially-explicit locations of Hydrogen Refuelling Stations (HRSs) and allowing further flexibility and accuracy. Another distinctive feature of the method and the analyses carried out in the paper pertains to the inclusion of bulk geographically agnostic, as well as geological underground hydrogen storage options, and reporting on significant cost saving opportunities. Finally, the curve for H2-HGVs penetration levels, safety stock period decisions, and the transport mode capacity against hydrogen levelized cost at pump have been generated as important policy making tools to provide decision support and insights into cost, resilience and reliability of the HSC.

Analysis of EOQ (Economic Order Quantity) as a Basis for Controlling Multi Item Raw Materials at Laatunsa Bakery Tasikmalaya

The goals of this study were to analyze the most cost-effective requirements for the primary raw materials based on the requirements of Laatunsa Bakery for the 2020–2021 period, due to the excessive frequency of raw material acquisitions, the inventory procedure results in a high cost expenditure; to examine the total cost of the primary raw material inventory that must be paid by Laatunsa Bakery for the 2020–2021 period, to analyse the frequency of purchases that are necessary; to analyze the quantity of safety stock (safety stock); to analyze the timing of reordering (reorder point), and to analyze the Laatunsa Bakery's primary raw material inventory control utilizing the EOQ method. Data gathering was place between November 2021 and February 2022. All information pertaining to the acquisition of the primary raw material inventory required for production, as well as the associated expenses of raw material inventory was utilized. This study adopted Economic Order Quantity as the analytical technique approach.
 The study's findings utilizing the EOQ approach revealed that the inventory of raw wheat cost Rp. 585,581.45, a savings of Rp. 2,613,934.94. Additionally, saving Rp 2,559,472.21 on sugar raw materials costing Rp 585,582.23 is possible. Additionally, the cost of the raw ingredient for butter is Rp. 585,582.23, saving Rp. 2,559,472.21. Additionally, the cost of the raw material for eggs is Rp 952,399.69, saving Rp 3,355,584.19. Additionally, the developer can save IDR 1,132,400.99 on the IDR 590,582.81 in raw materials.When compared to conventional method, the EOQ method can reduce inventory costs and optimize the need for raw materials. The EOQ approach is utilized using Microsoft Excel for the calculation.

Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining

The coronavirus pandemic has affected not only health but also the economy. The use of big data in finding information can be used to gain profits that logistics companies can utilize to survive during the pandemic. This study conducted text-mining research on service consultant sites in the logistics sector. This study aims to present frequency diagrams, analyze sentiment using the National Research Council (NRC) lexicon, present bigrams, and seek knowledge about strategies to minimize shipping costs and maintain inventories of manufactured goods. The words "supply", "chain", and "COVID-19" are words that are used frequently throughout the article. The results of this study showed that the words that often appear from word excavation are the words "supply", "chain", "logistics", "kpis," and "inventory". Then emotion trust becomes an emotional word that often appears in articles. The words "Supply" and "pandemic" are the words that seem the most positive and negative words, respectively. The words "COVID-19", "safety stock", and "inventory management" are words that often appear together. The result of discovery knowledge is that logistics consultants offer emotions of trust and provide many insights on minimizing shipping costs and maintaining inventory during a pandemic.

METODE MARKOV CHAIN DALAM PENGENDALIAN PERSEDIAAN UNTUK PERENCANAAN BIAYA PERSEDIAAN BAHAN BAKU PADA TOKO AIRIN BAKERY & CAKE SHOP

Airin Bakery & Cake Shop produces various kinds of cakes and bread. This shop is often faced with problems that occur, namely the supply of raw materials that are insufficient or excess so that the production process does not go well. This study aims to determine the ordering capacity and the right time to order raw materials to minimize the total cost of raw material inventory using the silver meal method. The total inventory cost is Rp. 14,637,947.4 less than the cost set by the company. Inventory control, which is a stochastic process, can also be carried out without regard to safety stock, lead time, and reorder points. The stochastic process of total inventory can be described by a finite number of states. The probability of transitions between these states is described by a markov chain. The markov chain method can predict future raw material inventory costs. After making several states on the amount of raw material inventory, a prediction of the future raw material inventory costs of Rp.31.747.932,98 is obtained

Analysis of Raw Materials Inventory Control Using Economic Order Quantity (EOQ) (Case Study of Synthetic Leather Raw Materials at Borselly)

The purpose of this study was to find out how the implementation of synthetic leather raw material inventory control has been carried out by Borselly, whether applying the EOQ method in controlling raw material inventory at Borselly is more optimal than without using the EOQ method. The method used in this research is a descriptive method with a quantitative approach with technical data collection through interviews, observation, literature study, and documentation. The data analysis tool used in this study is by using the Economic Order Quantity (EOQ) such as purchase frequency, safety stock, reorder point (ROP), and total inventory cost (TIC). Based on the research results, it is known that applying the EOQ method calculation has an effect on the company being better, the company can also make inventory costs more efficient and optimize inventory compared to policies using conventional methods

Evolutionary dynamics of supervision-compliance game on optimal pre-positioning strategies in relief supply chain management

Emergency supply reserves are indispensable material bases in relief supply chain management. However, limited in-kind relief resources stockpiled in government-managed depositories may fail to meet the surging demand following the disaster. This paper develops an optimal pre-positioning strategy for emergency supplies with pre-purchasing contracts between local governments (LGs) and emergency supply manufacturers (ESMs) to properly address demand uncertainty in different disaster scenarios. Physical materials and production capacity are integrated into a holistic and hybrid reserve model to mitigate overstock or stock-out risks. Applying an evolutionary game-theoretic framework, contract enforcement has been extensively analyzed to avoid LGs dereliction of duty and ESMs’ breach of contract. A novel dynamic penalty mechanism is proposed to control the fluctuations in strategy choices and effectively improve ESMs’ compliance without LGs’ excessive inputs on supervision. The numerical simulation results, along with sensitivity analyses on major cost-accounting, demand characteristics, and environmental parameters, show that safety stock is the primary guarantee in most cases, while reactive stock acts as an important supplement for disasters with long-term consequences. The joint reserve policy (except for no action strategy) outperforms the price-only contract on the total reserved quantity of emergency supplies at a lower long-term average cost. The initial state and cost-benefit structures dominate the complex interplay and periodical fluctuations in the supervision-compliance game. The doomed cycle of order, disorder, and reorder in contract performance management can be well managed under the proposed dynamic penalty mechanism, which appears much more efficient and incentive-compatible in promoting both parties to fulfill their obligations.

Enhancing global supply chain resilience in the Indonesian medical device industry: a dynamic capability perspective

PurposeThis paper aims to understand how the global supply chain in the medical device industry embraces resilience by adopting agility approach following COVID-19.Design/methodology/approachThis study adopts an interpretative approach to examine the qualitative data drawn from interviews and observation under dynamic capability theory. The data collection concerned multiple stakeholders involved in purchasing and supply management in the medical device market: manufacturing suppliers, channel partners, hospital management and end-users. The coding analysis uses an application that helps the researchers categorise the nodes and extend the existing literature.FindingsThe findings show that global supply chain leaders leverage the dynamic capability by centralising the business process decision to respond to the shifting demand from the local governments to the national health ministry, shaping the partnership style from the area- to the funnel-based agreement, even though it exposes a risk of product acceptability from the end-users, encouraging the distributor to convert just-in-time approach into holding safety stock to avoid penalty from missing the procurement target even and restructuring the local partners’ debts to manage long-term performance.Originality/valueThis study extends the emerging literature in international business by underpinning dynamic capability theory.

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.

Penerapan Metode Buffer Stock dalam Prediksi Ketercukupan Bahan Baku

UD. Elvajaya has sales and purchases of stock of bag raw materials, but until now UD. Elvajaya experienced difficulties in terms of predicting or estimating the calculation of raw materials according to incoming orders. Raw materials often experience advantages and disadvantages in the ongoing process of making bags, causing service to customers to experience delays in the process of making and shipping goods to be delayed. The absence of proper calculations when there is an incoming order results in an unstable stock of raw materials with the number of incoming orders. In making raw material reports, books are still used as storage so that raw materials are not controlled. This study proposes the application of the buffer stock method to overcome existing problems. With the existence of a prediction system for the adequacy of raw materials using the buffer stock method, it can assist in the process of calculating raw materials to be purchased according to incoming orders so as to reduce the risk of stock shortages in the ongoing manufacturing process. The buffer stock method has several advantages, namely, minimizing risks in production regarding insufficient raw materials, being able to handle ordering requests with quite a large number. With this system, it is hoped that the problems faced by UD owners can be resolved. This research produces a prediction of how many raw materials will be issued for the following month by looking at the bag orders in the previous month. UD.Elvajaya produces 1440 cm of Buffer Stock for fabric raw materials, 1440 cm of zippers, 2160 cm of hose, 2160 cm of bisban, 15 threads, and 44 zipper heads.

Theoretical evaluation of the tritium extraction from liquid metal flows through a free surface and through a permeable membrane

Effective tritium extraction from PbLi flows is a requirement for the functioning of any PbLi based breeding blanket concept. For a continuous plant operation, the removal of the tritium dissolved in the PbLi has to be performed in line and sufficiently fast. Otherwise, tritium inventories in the liquid metal, start-up inventories and buffer inventories would be excessive from the safety point of view. Moreover, a slow response of the tritium extraction systems could also compromise the tritium self-sufficiency of the plant. A promising solution to this problem is to use highly permeable membranes in contact with the PbLi flow to promote the extraction via permeation. This technique is usually known as Permeation Against Vacuum (PAV). As an alternative, tritium could be extracted directly by permeation through a fluid free surface (FS) in contact with vacuum. In both configurations, the dynamics of tritium transport is ruled by a combination of convection, diffusion and surface recombination. In this paper, the tritium extraction processes in the FS and PAV configurations are studied in detail. For the first time, general analytical expressions for the extraction efficiency are derived for both techniques in a Cartesian geometry. These expressions are general in the sense that they do not impose any kind of assumption concerning the permeation regime of the membrane or the fluid boundary layer. The derived expressions have been used to analyze numerically the response of both configurations in a close loop system, such as the one of DEMO. The presented methodology allows comparing the FS and PAV configurations, assessing in which conditions one will be behave better than other.

Simulation-Based Approach for Multi-Echelon Inventory System Selection: Case of Distribution Systems

Due to the current complexity of the supply chain, multi-echelon inventory management has become challenging while also being an interesting field of research as it allows efficient control of supply chain interdependencies. It became clear to many researchers that analytical models are no longer effective for addressing the multi-echelon inventory management problem. Simulation can be used to assess and quantify the impact of each inventory strategy on a supply chain performance. Our paper aims to provide a simulation-based approach to guide decision makers select and validate a multi-echelon distribution inventory system. The proposed approach is composed of four major steps that involve characterization of the current supply chain, conceptual modeling of the multi-echelon inventory system alternatives, and finally, simulation modeling using appropriate simulation software to compare and test different options. The approach was also tested and validated through an application to the case of the Moroccan pharmaceutical products supply chain in the public sector. The results of the simulation demonstrated that adopting an installation stock policy at all levels of the supply chain with an allocation of safety stocks in the most downstream stages is the best and most appropriate alternative for the pharmaceutical supply chain under study.

Inventory Control for MSME Products Using the Q Model with Lost Sales Condition Based on Products Sales Forecasting

Micro, Small and Medium Enterprises (MSMEs) have an important role in economic development in order to achieve thq quality of economic growth. Intense competition among MSMEs requires MSMEs to have a good inventory control that can help them minimize costs and maximize profits. One of the MSMEs that often experiences problems in inventory control is Sabun Bening Official. To solve the inventory problems in Sabun Bening Official, Holt-Winter Exponential Additive forecasting method is used as a guide to predict future product demand because product demand graph is seasonal and has trend pattern. After getting the value of product demand forecast, inventory control calucaltions are carried out using the Q Model probabilistic inventory method with lost sales condition. The uncertain and fluctuating demand causing the inventory system in Sabun Bening Official is probabilistic and the company will lose sales if it does not able to fulfill customer demands. Based on the research results, product forecasting for the coming period and inventory control policies which include the optimal number of product order, safety stock, reorder point, and product inventory costs can be obtained.

Development of a simulation-based optimization approach to integrate the decisions of maintenance planning and safety stock determination in deteriorating manufacturing systems

In this article, a stochastic model is presented to schedule the maintenance tasks and control the inventory simultaneously in an unreliable deteriorating production system. The optimal planning of these aspects improves the productivity of the production system and reduces the costs. The shift time of the states follows a general continuous distribution. The time of maintenance is also considered as a random variable, and a buffer stock is maintained to avoid possible shortage and satisfy the demand during the performance of maintenance. The purpose of this study is to integrate the decisions of safety stock determination and maintenance scheduling to minimize the expected total cost of the system. Due to the complexity of the equations of the model, at first, a genetic algorithm (GA) is employed for optimization. To validate the GA solutions, they are compared with those obtained by a grid search algorithm. It is found that the differences between the optimal values of the objective function (ECT) in GA and grid search are almost small and, in some cases, only 5.58% and 2.03%. This result indicates the validity of the solutions obtained by the GA. In the next step, to speed up the run time of the proposed GA, a Monte Carlo simulation approach is developed, and the GA is combined with the simulation approach. In particular, the fitness function of each chromosome is obtained using the proposed simulation approach. In order to examine the performance of the proposed simulation approach, the results of simulation are compared with the findings on optimization by the GA. This comparison indicates that the difference between the values of ECT calculated through the GA and simulation is averagely 4.55%, which is negligible. The results denote the appropriate performance of the model and the efficiency of the proposed hybrid approach. Finally, comprehensive sensitivity analyses are performed regarding the parameters of the model.

Optimal Commodity Storage: Privately and Publicly Financed Storage Compared

<p><big>Consideration of optimal commodity storage with different discount rates. Finding that, even with a lower discount rate than private storage, optimal government-financed storage may not narrow price fluctuations compared with optimal privately financed storage because a government has to choose a probability of buffer stock failure greater than zero to economize on storage costs that could conceivably become very large. There is no presumption that government financed storage would be larger, with narrower intervention bands and more stable prices, than with privately-financed storage. The welfare enhancing effect of government financed storage compared to private storage is therefore indeterminate.</big></p>

Creating safety stock populations of two of the smallest threatened freshwater fishes of Europe

Creating safety stock populations of two of the smallest threatened freshwater fishes of Europe

Pengendalian Persediaan Bahan Baku Untuk Menunjang Kelancaran Proses Produksi Filter A-5828 (Studi Kasus di Industri Komponen Otomotif)

The production process is a core activity of a company. Production can run smoothly. Agricultural raw materials which are input from the production process are available as needed. The availability of raw materials cannot be separated from planning and control. With the supply of raw materials, the company can meet consumer demand. The raw material inventory system in a company is a part that plays a very important role for a company engaged in manufacturing, in this section it acts as the procurement of raw materials needed by the production process. The high frequency of purchases can result in the large cost of supplies being incurred by the company. This study aims to see the analysis of raw material inventory using the Economic Order Quantity (EOQ) method to increase efficiency in the total cost of inventory. The EOQ method is supported by a Reorder Point (ROP) and Safety Stock. By using EOQ, ROP, and Safety Stock, the company will see the number of orders that must be made, the point of reorder and the amount of safety stock. The total inventory cost was Rp. 3,193,000, 1 roll of Safety Stock and 2 rolls of Reorder Points for 15mm UNP raw materials and Rp. 3,843,600, 2 rolls of Safety Stock and 3 rolls of Reorder Points for 5mm Woll raw materials.Keywords: Production Process, Raw Material, EOQ, Safety Stock, Reorder Point.

The Role of Demand Forecasting Analysis (Case Study: Bio Farma for Papua Area)

Bio Farma as the only vaccine manufacturer in Indonesia, divides its marketing area for vaccine distribution throughout Indonesia, represented by marketing representatives in 34 provinces in Indonesia. Segmentation based on geography for vaccine products is divided into five regions, one of the region is Papua. The forecast method used in Bio Farma for Papua Area is still manual. Marketers order vaccines from central Bio Farma and make forecasts if product stock is empty. If the product is empty, a buffer stock will be created. With the buffer stock system that has been implemented so far, there are often problems with excess product which causes the product to expire. From the data, the total loss due to overstock is Rp. 14,161,693 in 2022. If consumer demand falls short of expectations, it will definitely have an impact on the manufacturing of high inventory value, even leading to lost opportunities for sales. That is the fundamental issue with this research. The goal of this research is to identify the possible causes for the overstock and to identify a suitable solution for those issues. There are five things consist of root causes the problem; (1) fully manual forecasting, (2) low sales forecast accuracy, (3) sales forecasting based on sales of the last one or two months, (4) lack of employee knowledge about sales forecasting, (5) significant gap between target and actual sales. The alternate strategy recommended is to provide a forecasting technique that is suitable for the company. Different forecasting techniques were selected to be compared in order to determine which may be used to improve forecasting accuracy. The forecasting techniques that are employed are the 3-month simple moving average, the 5-month simple moving average, the 3-month weighted moving average, the 5-month weighted moving average, and exponential smoothing. By using the MAD and MAPE measurement tools, exponential smoothing showed the most acceptable accuracy result.