Safety Stock Research Articles

Dynamic shop-floor scheduling using real-time information: A case study from the thermoplastic industry

Practical production planning and scheduling systems must promptly respond to major real-time events and adjust their plans and schedules accordingly. To highlight the importance of concurrency in such systems, this paper addresses the problem of dynamic shop-floor scheduling using real-time information in a case study from the thermoplastic industry. The considered production line is organized as unrelated parallel production cells with a set of identical parallel machines in each cell. Parts are produced in batches using different molds on specific machines. Due to the size and complicated design of the molds, they require extended recovery periods (i.e., maintenance) in case of major failures. Therefore, previously developed plans and schedules need to be revised using real-time information every time a mold’s major failure occurs. The production process is subject to the following constraints: batch processing, safety stocks, dedicated machines, machine-dependent setup times, precedence constraints, mold failures, and real-time updates. The problem is formulated as a mixed-integer programming model to minimize a weighted cost function that includes tardiness and operating costs. To solve the problem, a predictive-reactive scheduling approach is introduced based on a modified simulated annealing (SA) algorithm. The developed approach utilizes an event-driven rescheduling policy. It also embeds a problem-specific neighborhood structure and solution evaluation into the modified SA algorithm. The experimental study indicates that the proposed approach generates better real-life planning and scheduling results than the methods based on dispatching rules. The findings demonstrate that the proposed SA-based predictive-reactive scheduling approach generates the solutions with about a 26.1% less tardiness cost and a 6.99% less total weighted cost (on average). In addition, the results also show the competitiveness of the proposed SA-based predictive-reactive scheduling approach compared to two other approaches based on an iterated greedy (IG) algorithm and a Tabu Search (TS) algorithm from the literature.

Manufacturing system optimization using computer-based control kanban loops

The study assessed manufacturing system optimization using computer-based control kanban loops. The study assessed JIT's effect on average throughput-time, demand fill rate, net operating income for a certain product mix complexity and manufacturing overhead level. ARENA/SIMAN and WITNESS simulation tools were used to study implementation. The Drug Process Plant's JIT system reduced end buffer inventory, shortened customer lead time, and improved visual control. The mean response of the simulated new physical system in terms of NOI was 85.54 but gave a mean response of 85.30 when implemented on the shop floor. The mean response of the simulated new physical system in terms of cycle time was 617 but gave a mean response of 634 when implemented on the shop floor. Simulated new physical system in terms of DFR gave a mean response of 93.11 when implemented on the shop floor. Overwhelmingly, the new JIT system outperformed the old physical system. Bangladesh J. Sci. Ind. Res. 57(4), 221-228, 2022

PROSES PRODUKSI GLISERIN SEBAGAI BAHAN PENOLONG DENGAN KLASIFIKASI ABC DAN MIN MAX STOCK DI PT. X

The Main problem why companies keep raw material in quantities is as a safety stock, in chase of delay in delivery from supplier so the process of production process does not stop. Inventory control of auxiliary raw materials aims to achieve optimal efficiency and efectiveness in the supply of raw materials so that there is no excess and shortage of inventory stock. So this study aims to determine whether the amount of stock the raw materials in PT. PHPO KIM - II has been efficient when compared with the result of calculation by using MRP Method. This study will be done on four supporting raw materials that used for the glycerine manufacturing process are; HCl, Ca(OH)2, Filter Aid, NaOH.

ANALISIS MANAJEMEN PERSEDIAAN BAHAN BAKU DENGAN METODE ECONOMIC ORDER QUANTITY (EOQ) PADA PERUSAHAAN PAVING SURABAYA 2 DI PAMEKASAN

Inventory management is a very important managerial function in the company's operations. Without inventory, business actors are faced with the risk that a company cannot meet the needs and desires of its customers, but if the company invests too much funds in inventory, it will cause excessive storage costs. This study aims to determine the amount of raw material inventory that is economical, to know the amount of raw material inventory to be provided, and to find out when to reorder raw materials at Surabaya paving company 2. This type of research is a descriptive quantitative research using the EOQ (Economic Order) method. ). Quantity). The data collection technique used is documentation. The results showed that the EOQ (Economic Order Quantity) method was more economical than company policy. If the company uses the EOQ method, the economical supply of sand in 2022 is 152 m^3, the frequency of purchases is 5 times, with a total inventory cost of IDR 17,329,287, the most economical supply of cement in 2022 is 2,726 sacks, the frequency of purchases is 2 times, with a total inventory cost of IDR 6,936,696, and the economical mil inventory in 2022 is 316 sacks, the frequency of purchases is 2 times, with a total inventory cost of IDR 7,955,087. The amount of sand safety stock that must be provided is 21 m^3, cement is 134 sacks, and mil is 33 sacks. The right time to restock is when the raw materials are 33 m^3 of sand, 190 sacks of cement, and 41 sacks of mil.

Matching Supply and Demand with Lead-Time Dependent Price and with Safety Stocks in a Make-to-Order Production System

We studied the ability to reduce the supply–demand mismatch of a periodic Make-to-Order (MTO) production system using safety stocks with marketing managing demand using lead-time guarantee and price as levers. The aim is to understand the interdependencies between lead-time guarantee, price, and safety stocks. We modeled the problem as an unconstrained stochastic non-linear programming problem, maximizing the expected profit per-unit time and obtaining a closed-form solution. The price is a function of the lead-time guarantee. Based on the sensitivity analysis of problem parameters, we found that lead-time competitiveness is adversely affected by a low safety stock level, MTO production rate (i.e., low supply capability), and product price (i.e., high demand volume). A shorter lead-time requires higher safety stock through reduced product and inventory holding costs. A higher price for a shorter lead-time in a lead-time-sensitive market reduces the safety stock. In a price-sensitive market, lead-time is decreased instead of the price. Demand variation results in longer lead-time and higher safety stock (provided the holding cost is low). For a higher price premium, price increases and lead-time decrease (safety stock increases). The integrated operation-marketing model captures the complex trade-offs not seen in a hierarchical model to produce better solutions.

ANALISIS PENGENDALIAN BAHAN BAKU TEPUNG TAPIOKA MENGGUNAKAN METODE ECONOMIC ORDER QUANTITY (EOQ) PADA PT. BUDI STARCH & SWEETENER, TBK

The purpose of this study is to find the optimal raw material inventory of a company if it is calculated using the EOQ method. (case study at Pt. Budi Strach & Sweetener, Tbk). The data used in this study were taken from the company's books and from interviews with the HRD personnel of Pt. Budi Strach & Sweetener, Tbk in 2021. The data used in this study are: purchase data, usage data, purchase frequency, raw material inventory data, cassava raw material ordering data, raw material storage cost data. The analysis was carried out using the EOQ formula, safety stock, reorder point, total cost, purchase frequency. The problem in this research is Pt. Budi Strach & Sweetener, Tbk in its production experience a shortage of raw materials every year because the supply of raw materials in the field is uncertain, so here the author tries to apply the Economic Order Quantity (EOQ) method to minimize various aspects in the procurement of raw material supplies. The results of this study indicate that: Control of raw materials Economic Order Quantity (EOQ) method is considered more efficient and optimal, it is proven that there is a decrease in inventory costs of Rp. 3,219,502. Judging from the company's policy, the optimal purchase of raw materials according to company policy is 1,353,378 Kg with a purchase frequency of 24 times, while according to the policy of the EOQ Method, the purchase of raw materials is 1,813,140 Kg with a purchase frequency of 18 times a year. Total Safety Stock according to EOQ policy is 15,954 Kg. Re-Order Point (Re-Order Point) according to the policy of the EOQ Method is 376,854,444 Kg. The analysis shows that the use of the EOQ method in controlling cassava raw materials at Pt. Budi Strach & Sweetener, Tbk is considered effective and efficient

Safety Stock, Warehouse Capacity, and Return of Goods in Inventory Model Development

With the increasing level of competition between companies, companies are required to be able to manage their inventory system optimally. In the pharmacy supply system, it is important to consider the uncertainty factor because the demand for medicines depends on the uncertain nature of the disease, besides that there is an expiration factor that must be considered because medicines must have an expiration date. To solve the problem of expiration, the supplier usually provides a return policy in accordance with the specified conditions. In addition, pharmacies also have limitations on warehouse capacity that must be considered. To solve the problem of limited warehouse capacity in this study, an approach to the requirements of the Karush Kuhn-Tucker method was used. From the developed model, two ordering times are obtained, namely and which will be compared to get the optimal ordering time. From the analysis of the model, it is found that the more characteristic considerations in an inventory system, the greater the total inventory cost.

Analysis of Fuel Supply Control (Palm Shell) Using EOQ Method in Pt. Charoen Pokphand Indonesia Tbk

PT. Charoen Pokphand Indonesia Tbk. (Gorontalo) is still experiencing problems in managing fuel supply where the company often experiences a lack of inventory that hinders the production process. The company also experienced excess inventory, causing storage costs to rise. For this reason, companies need to exercise inventory control. One of the analytical tools that can be used to control inventory is the "Economic Order Quantity" (EOQ). From the calculation results, it was found that the optimal number of fuel supply purchases from palm oil shells using the EOQ method is 352 tons with a purchase frequency of 3 times in one period (1 year) so that the company can save fuel procurement costs. . The total inventory cost of raw materials with an EOQ of Rp. 32,845,640 while the cost incurred by the company without using EOQ amounted to Rp. 34,731,000. The savings that can be made by the company is Rp. 1,885,360 with a Reorder Point of 81.9 tonnes and a total safety stock of 241 tonnes.

Stock Control of Enduro Matic Oil Products Using the Economic Order Quantity (EOQ) Method at DRMS#71 Motor Workshops

Problems with economical ordering, safety stock, and when to reorder (ROP) within one year. The results of the study used the EOQ method to purchase 1,470 bottles of goods with an order frequency of 1 time per year. Based on the analysis using the EOQ method, it can maintain the stability of the customer request process. With EOQ you can also reduce the cost of saving from Rp. 1,360,000 to Rp. 1,176,000.-.

Rationale and design of leveraging the HIV platform for hypertension control in Africa: protocol of a cluster-randomised controlled trial in Uganda

IntroductionThere is a high burden of hypertension (HTN) among HIV-infected people in Uganda. However, capacity to prevent, diagnose and treat HTN is suboptimal. This study seeks to leverage the existing...

Trading safety stock for service response time in inventory positioning

We study an inventory placement optimization problem where demand is sensitive to service response time, under the online retailing setting. The main challenge is to achieve the optimal trade‐off between revenue benefits from shorter delivery time and the increase in inventory cost associated with placing inventory closer to market demand. To predict the effects of modified demand under service response time variations, we introduce a demand prediction and elasticity model to quantify the sensitivity in demand for particular product categories. Of course, shortening response time by positioning products close to market demand may increase inventory costs. Hence, the team developed a novel data‐driven two‐stage stochastic programming approach complementing the demand prediction and elasticity model, which optimally trades safety stock with service response time and hence revenue increase. We then illustrate the impact of our approach through data provided by an e‐commerce retailer in North America. Our approach offers supply chain managers a general‐purpose decision support tool that optimizes the inventory network to generate recommended stocking levels for stores, distribution centers, and warehouses on a daily basis.

Product availability and stockpiling in times of pandemic: causes of supply chain disruptions and preventive measures in retailing.

The coronavirus pandemic in 2020 brought global supply chain disruptions for retailers responding to the increased demand of consumers for popular merchandise. There is a need to adapt the existing supply chain models to describe the disruptions and offer the potential measures that businesses and governments can take to minimize adverse effects from a retail logistics perspective. This research analyses the possible reasons for supply and demand disruptions using a mathematical model of a retail supply chain with uncertain lead times and stochastic demand of strategic consumers. The established concepts of supply chain management are applied for the model analysis: multi-period inventory policies, bullwhip effect, and strategic consumers. The impact of the pandemic outbreaks in the model is two-fold: increased lead-time uncertainty affects supply, while consumer stockpiling affects demand. Consumers' rational hoarding and irrational panic buying significantly increase retailers' costs due to higher safety stock and demand variability. The bullwhip effect further exacerbates the disruption. The research contributes to the recent literature on business response to supply chain disruptions by developing a model where both retailers and consumers decide on the order quantity and reorder point during a pandemic outbreak. Buying limits, continuous inventory review, government rationing, substitutability, and omnichannel fulfillment are the measures that can limit the damage of supply chain disruptions from stockpiling during the pandemic. Effective communication and price and availability guarantees can mitigate the negative impact of panic buying.

Dynamical multi-parameter sizing of DDMRP buffers in finite capacity flow-shops

The DDMRP (Demand Driven Material Requirements Planning) methodology uses buffer stocks to (i) maintain a high level of service, (ii) stop the spread of uncertainty and (iii) adapt to market changes. According to theory, the size of these buffer stocks should be defined regularly. This sizing involves several parameters and policies to update them, but very little information is available on this subject. We aim to help practitioners choose sizing policies, while maximizing the performance of a given workshop. We have developed an experimental design to compare many combinations of flow-shops and bottleneck constraints, taken from industrial use-cases, and using discrete event simulation. The results show that (i) different degrees of dynamism are needed depending on the performance metric chosen by practitioners, (ii) completely dynamic control does not systematically lead to better performance, and (iii) contrary to what the existing literature on DDMRP suggests, varying buffer sizes may be less effective than fixed ones for an important part of use-cases.

IMPLEMENTASI METODE HOUSE OF RISK PADA EVALUASI KETERLAMBATAN PROYEK RENOVASI GEDUNG AULA PP3 BLITAR UM

CV. DDD is a company engaged in construction services. In the construction of the Pp3 Blitar Hall renovation project, State University of Malang, there was a delay in project completion which had an impact on the quality of the project. In project work, there are several things that are required to be taken into consideration including finance, equipment, materials, labor, and time. So based on these considerations, the work in a project can be carried out properly. Project management needs to be done, so that the smooth running of the project can be carried out properly and optimally. The purpose of this study is to identify risk events and risk agents the factors that cause project delays. House of Risk is the method used in this research. The results of this study are the identification of risk events against the analysis of project delays, there are twelve risk events and 15 potential causes of risk events. This research also produces scenarios of five priority mitigation strategies, namely purchasing materials planned for weekly or monthly needs, looking for closer suppliers, buying lots at lower prices and sufficient safety stock and applying the material requirements planning method to find out more details of the lead time of each material.

MANAJEMEN PERSEDIAAN BAHAN BAKU KOPI BUBUK PADA UKM SIDOLE 986 DI KOTA PALU

SMEs Sidole 986 Coffe Powder UKM Sidole 986 is one of the businesses engaged in the agro-industry 
 that utilizes Robusta coffe bean as the main raw material. This study aims to determine how much economic 
 raw material purchases (EOQ) for raw material supplies in the SMEs Sidole 986, to find out how much safety 
 stock is in the, SMEs Sidole 986 to find out when is the right time for the SMEs Sidole 986 to do so. reorder 
 (ROP) for raw material inventory, and to find out the total cost of raw material inventory (TIC) in the SMEs
 Sidole 986. The results of this study indicate that the management of raw material inventory in the SMEs Sidole 
 986 using the (Economic Order Quantity) method in July-December 2021 an average of 42,02 kg. Safety stock 
 of raw materials which is always available at SME Sidole 986 is 22,84 kg. Reorder Points that must be made 
 by the SMEs Sidole 986 in July-December 2021 an average of 127,12 kg. The total cost of the raw material 
 inventory coffe powder carried out in the SMEs Sidole 986 is an average of Rp. 75.824,74.

ANALISIS PENGENDALIAN PERSEDIAAN BAHAN BAKU GUNA MEMINIMALKAN BIAYA PENYIMPANAN MENGGUNAKAN ECONOMIC ORDER QUANTITY (EOQ) DAN PERIODE ORDER QUANTITY (POQ) PADA UMKM PIGOPE

UMKM Pigope is one of the umkm in Yogyakarta with the main menu of fried bananas typical of Sulawesi served with roa and chili sauce. The main raw material for this fried banana is banana kepok. In the production process, umkm Pigope requires approximately 80 bunches of kepok bananas per month. The problem in this umkm is that there are obstacles in controlling raw materials which cause the production process to be disrupted due to damage to raw materials in storage, considering that the age of ripe bananas is not too long. From these problems, it is necessary to control raw materials in order to minimize storage costs. Based on the results of the analysis that has been carried out, it shows that the control of raw material inventory applied by UMKM Pigope is not optimal. Umkm have run out of inventory to meet consumer demand, but umkm have not been able to minimize inventory costs. The use of the Economic Order Quantity (EOQ) and Period Order Quantity (POQ) methods shows the number of economic orders as many as 48 bunches, with the purchase frequency of banana raw materials as many as 17 times the purchase of banana raw materials in one period (1 year), and the number of safety stock proposed as many as 15 bunches. With the proposed inventory control, UMKM Pigope can minimize the total inventory cost from Rp. 15,020,- to Rp. 14,195,584,-. When calculated using EOQ the company can save on inventory costs, the quantity and frequency of purchasing fewer main raw materials by taking into account safety stock and reorder points.

Primary Health Care System Strengthening Project in Sri Lanka: Status and Challenges with Human Resources, Information Systems, Drugs and Laboratory Services.

A Primary Healthcare-System-Strengthening Project (PSSP) is implemented by the Ministry of Health, Sri Lanka, with funding support from the World Bank for providing quality care through primary medical care institutions (PMCIs). We used an explanatory mixed-methods study to assess progress and challenges in human resources, drug availability, laboratory services and the health management information system (HMIS) at PMCIs. We conducted a checklist-based assessment followed by in-depth interviews of healthcare workers in one PMCI each in all nine provinces. All PMCIs had medical/nursing officers, but data entry operators (44%) and laboratory technicians (33%) were mostly not available. Existing staff were assigned additional responsibilities in PSSP, decreasing their motivation and efficiency. While 11/18 (61%) essential drugs were available in all PMCIs, buffer stocks were not maintained in >50% due to poor supply chain management and storage infrastructure. Only 6/14 (43%) essential laboratory investigations were available in >50% of PMCIs, non-availability was due to shortages of reagents/consumables and lack of sample collection-transportation system. The HMIS was installed in PMCIs but its usage was sub-optimal due to perceived lack of utility, few trained operators and poor internet connectivity. The PSSP needs to address these bottlenecks as a priority to ensure sustainability and successful scale-up.

An Integrated Model of Continuous Review Inventory and Vehicle Routing Problem with Time Windows

Item stock-out or shortage is a great issue for customer satisfaction and can be countered by providing safety stocks. This study discusses an authorized distributor of smartphone and tablet computer products in Indonesia. Currently, the company is considering a plan to take over the role of a logistics service company to reduce the total logistics costs that must be incurred by making improvements in terms of inventory management. Inventory management can also protect the company from the impact of inflation and price increases that will impose logistics costs. This study has assumed that the vehicle travel speed or travel time between two nodes is fixed. This study contributes to minimizing total logistics costs by integrating the concept of a continuous review lot size-reorder point (Q, R) inventory model with lost sales and vehicle routing problems with time windows (VRPTW). Continuous review (Q, R) inventory model with lost sales shows the retailers’ cycle demand ranges from 130 to 234 units. This condition leads to the value of the expected average annual inventory cost IDR 27.263.204.625,59. Based on the VRPTW calculation, the total distribution cost per trip is IDR 445.631.642,7. Based on the current total distribution costs, it was found that the total distribution costs were IDR 849.454.616,2, so there is a decrease in distribution costs of 47.54%. The total logistics cost that must be incurred by the company to deliver smartphone products to 10 retailers in Jakarta and its surrounding areas is IDR 27,708,836,268.29.

Smart Gas Network with Linepack Managing to Increase Biomethane Injection at the Distribution Level

The current situation in Europe calls for the need of urgent measures to find sustainable alternatives to its outer dependence on natural gas. Biomethane injection into the existing gas infrastructure is a fundamental opportunity to be promoted that, however, causes increasing complexities in the management of natural gas grids. At the gas distribution level, the lack of a monitoring system and suitable software for the simulation, management, and verification of gas networks may act as barriers to a widespread diffusion of a biomethane production and injection chain. A transient fluid-dynamic model of the gas network is developed to perform estimations of the natural gas grid capacity in situations of production-consumption mismatch, taking into account the linepack as a gas buffer stock. The model is applied to the gas distribution network of a small urban-rural area. The aim is to assess the role of the linepack in determining the gas network receiving capacity and to test smart management of pressure set-points and injection flow rate to minimize biomethane curtailment. Results show that biomethane unacceptability can be reduced to 10% instead of 27% (obtained when following the DSOs state-of-the-art current procedures), thus highlighting the importance of the implementation of transient simulation software but also underlining the need for smarter control systems, actuators, and data management platforms for a transition to smart digital gas grids.

The Impact of Macroeconomic Risk Factors, the Adoption of Financial Derivatives on Working Capital Management, and Firm Performance

This study examines macroeconomic risk factors to investigate how they affect working capital management (WCM) and, ultimately, firm performance. Additionally, we examine the effect of credit default swaps (CDSs) as a countermeasure for WCM in the presence of volatile macroeconomic risk factors. In doing so, we use firm-level data from the United States, the United Kingdom, Germany, and China between 2006 and 2020. The two-step system generalized method of moments (GMM) estimation method is employed to analyze the study′s objectives. Results show that US, German, and Chinese firms are more conservative, while UK firms are more aggressive in maintaining WCM during economic policy uncertainty. Conversely, foreign exchange risks drive the USA, the UK, and Chinese firms to lengthen their cash conversion cycle level due to fear of value loss, while the opposite is true for German firms. Nevertheless, following CDS adoption, firms are more confident in working capital (WC) investment. CDSs eliminate the need for delayed receivables and payables and increased inventory as safety stock for US, UK, and Chinese firms. Finally, CDS interaction shows that USA, UK, and German firms may boost their profitability by increasing account receivable periods to create more sales, reducing account payable periods, and holding more inventories to expedite sales operations. Alternatively, CDSs suggest an optimal level of WC investment for Chinese firms. As a result, governments should consider CDS adoption in policy decisions when business performance sinks due to macroeconomic volatility.