Optimization of Inventory Controlling System Using Integrated Seasonal forecasting and Integer Programming

Micro, Small, and Medium Enterprises (MSMEs) in the food and beverage sector is one of the sectors negatively affected by the COVID-19 outbreak, even though this sector is one of the largest contributors to the Gross Domestic Product of the non-oil and gas industry in Indonesia. This study intends to provide an overview of solutions in the form of case studies on the Mahkota Caman MSME in Bekasi, Indonesia, which experienced a decline in sales during the pandemic, resulting in overstock and damage to non-durable raw materials. As a result, it leads to an increase in inventory costs and even a loss of sales. The solution offered by this study is an optimization of production planning, namely determining what products and how many of these products should be produced in a certain period. The method used is goal programming, both with and without priority, so that Mahkota Caman can meet consumer demands, and minimize production costs, while minimizing the purchase of raw materials. The results of this study indicate that the optimal optimization method used by Mahkota Caman is goal programming with priority because it provides a more efficient solution to production costs and the purchase of raw materials. Based on the results of this study, it is recommended that optimization methods be used by MSMEs in the food and beverage sector during a pandemic, and to avoid using only feeling in production planning.

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.

Joint managed inventory is an advanced supply chain inventory management tool, which will effectively tackle the complicated problem between the inventory cost of supply chain and service level. The research on inventory model and its’ control under JMI environment is a hot issue at present. In this paper, the authors deeply discuss the question of the inventory time costs about the multi-product and multi-echelon control model and its’ replenishment strategy under JMI environment. With considering the foundation of JMI and time cost, the authors propose the multi-product multi-echelon inventory cost control model under time cost. Then formulate corresponding replenishment strategy. At last, through a numerical example, the authors discover that the multi-product multi-echelon joint inventory management based on time cost can effectively reduce the total inventory costs and improve the competitiveness of the entire supply chain.

Purpose: This study aims to identify inventory control and costs incurred by the company, analyze inventory cost control for green spinach seeds using the EOQ model VII method, and analyze cost efficiency for green spinach seed inventory. Methodology: The analysis used the EOQ method to determine the optimal order quantity for green spinach seeds at CV Amatta Mulya Barizi. Results: The EOQ method resulted in an optimal order quantity of 2,280 grams per order. The inventory costs for green spinach seeds amounted to IDR 273,642.00 per order or IDR 3,283,704.00 per year. Findings: The study found that the EOQ method is more efficient compared to the company’s current method, allowing the company to save IDR 586,296.00 annually on green spinach seed inventory costs. Novelty: This research provides new insights into the application of the EOQ model VII for seed inventory management, highlighting significant cost savings. Originality: The study offers a detailed analysis of inventory control and cost efficiency for green spinach seeds, contributing to better inventory management practices. Conclusions: The EOQ method is more efficient for inventory management of green spinach seeds at CV Amatta Mulya Barizi, resulting in considerable cost savings. Type of Paper: Empirical Research Article

Inventory constitutes the substantial portion of the cost of production of firms. Conglomerate firms faced a challenge pf dwindling return due to the huge cost of production of which inventory constitute the larger portion. Studies have shown that effective inventory management which entails forecasting, acquisition, transportation, inspection, material handling, storing, warehousing, suppliers’ management and inventory security are germane in reducing the cost of production to the barest minimum and enhance the returns. This study examined the effect of inventory control (inventory procurement control, inventory security control and inventory usage control) on the financial performance of listed conglomerate firms in Nigeria. The study adopted both field and empirical survey research design. The population of the study constitutes the entire six (6) listed conglomerates as at 31st December, 2018. The target population represent 108 staff of the finance and store sections out of which seventy-two were selected using quota sampling techniques for the administration of structure questionnaire, while total enumeration technique was used for the secondary data. The research instrument was validated by checking the constructs of the questions in the questionnaire using content validity. Cronbach Alpha reliability test was carried out and the result showed that the research instrument is reliable with an overall value of 0.988 which is greater than 0.70-0.80 threshold. 68 out of 72 administered structured questionnaire were retrieved representing 94.4% retrieved and used for the analysis. Secondary data extracted from the audited annual reports and accounts for a period of twenty-two (22) years yielding 110 unbalanced firm year observations were used. Descriptive and inferential statistics were employed for testing the hypotheses. The findings revealed that: inventory control significantly affects financial performance of listed conglomerate firms in Nigeria (Adj.R2= 0.873, F(3,65)=10.19, p< 0.1); inventory procurement control has significant positive effect on financial performance (β= .628, R2= 0.565, t(67)= 3.494, p <0.1); inventory security control exerts significant positive effect on financial performance (β= .535, R2= 0.706, t(67)= 2.684, p< 0.1); and inventory usage control significantly and positively influence financial performance (β= .531, R2= 0.492, t(67)= 2.844, p <0.1). Also, inventory turnover period exerted insignificant positive effect on financial performance (β= 4.64, R2= 0.006, t(108)= 0.83, p> 0.1). The study concluded that inventory control significantly influence financial performance of listed conglomerate firms in Nigeria. The study recommended that management of the firm should improve on suppliers’ strategic relationship and provides adequate automated security for monitoring the movements of inventory in the firm.

In order to ensure the uninterrupted continuity of their activities, businesses have to keep certain levels of inventory in market conditions that cannot be precisely measured and easily predicted, such as uncertainty in demands and lead times, fluctuations in prices. Inventory for health businesses that produce health service output as a result of business activities; means materials that must be kept for examination, treatment and diagnosis and that directly affect human health. For this reason, the management of medical inventory is very important both for human health and for the financial continuity of hospitals. In this study, which explains the inadequacy of the current medical consumable inventory control method used in the operating room unit of the hospital, which is the subject of the study, by using simulation and optimization techniques, and saving inventory costs by designing alternative inventory control models to the current situation; first of all, the current medical consumable inventory of the operating room were examined by ABC-VED analysis. Then, the new inventory control model, which was created using the (s,S) inventory control policy, in order to be an alternative to the existing inventory control management and current inventory control management of the operating room, was modeled using the stochastic modeling approach in the Arena Simulation package program, using real life data from the hospital. The simulation model is run for both inventory control models and the inventory costs of the materials are calculated for both inventory control models. In the last part of the application, the (s,S) inventory control model, which was designed as an alternative to the current situation, was optimized for the selected materials using the OptQuest optimization tool in the Arena Simulation program. As a result of the optimization, the minimum, maximum and reorder point parameters of the materials used in the study were re-determined to optimize the inventory cost of the materials. By using the optimized inventory parameters (s,S), the inventory control model was run again and the inventory costs of the selected materials were calculated for the third and final time. Finally, the outputs of the three inventory control models were analyzed and it was concluded that the lowest inventory cost value with a confidence level of 95% was achieved by using the optimized (s,S) inventory control model and the current inventory control method of the operating room was insufficient in terms of cost.KeywordsHealthcare inventory managementInventory control(s,S) inventory policySimulationOptimization

This paper presents a new operation scheme of UPFCs to minimize power production and delivery costs. In the normal operation state of a power system, the production costs of active power can be minimized by economic power dispatch, and delivery costs due to transmission system loss can be also minimized by active power control of UPFC, incorporated with minimization of production cost. In order to determine amounts of active power reference of each UPFC required for the cost minimization, an iterative optimization algorithm based on the power flow calculation using the uncoupled UPFC model is proposed. For verification of the proposed method, intensive studies have been performed on a 5-bus sample system and a 10 unit 39-bus New England System equipped with UPFCs.

Many argue that the focus point (and perhaps the linchpin) of successful supply chain management is inventories and inventory control. So how do food and agribusiness companies manage their inventories? What factors drive inventory costs? When might it make sense to keep larger inventories? Why were food companies quicker to pursue inventory reduction strategies than agribusiness firms? In 1992, some food manufacturers and grocers formed Efficient Consumer Response to shift their focus from controlling logistical costs to examining supply chains (King & Phumpiu, 1996). Customer service also became a key competitive differentiation point for companies focused on value creation for end consumers. In such an environment, firms hold inventory for two main reasons, to reduce costs and to improve customer service. The motivation for each differs as firms balance the problem of having too much inventory (which can lead to high costs) versus having too little inventory (which can lead to lost sales). A common perception and experience is that supply chain management leads to cost savings, largely through reductions in inventory. Inventory costs have fallen by about 60% since 1982, while transportation costs have fallen by 20% (Wilson, 2004). Such cost savings have led many to pursue inventory-reduction strategies in the supply chain. To develop the most effective logistical strategy, a firm must understand the nature of product demand, inventory costs, and supply chain capabilities. Firms use one of three general approaches to manage inventory. First, most retailers use an inventory control approach, monitoring inventory levels by item. Second, manufacturers are typically more concerned with production scheduling and use flow management to manage inventories. Third, a number of firms (for the most part those processing raw materials or in extractive industries) do not actively manage inventory. Many agribusiness firms do not actively manage inventory. This does not mean that they ignore inventory. Rather, they hold large inventories because any potential savings from inventory reductions are far outweighed by the inventory-induced reductions in production, procurement, or transportation costs. Often economies of size cause long productions runs which lead to inventory accumulation. Simultaneously, seasonality leads to inventory buildups of key inputs like seed as well as outputs like corn. Economies in procurement such as forward buying in the food industry and quantity discounts increase inventories. Similarly, unit trains and other forms of bulk shipping discounts contribute to inventory buildups. Yet, such firms must be alert to changing conditions that may require more exact inventory management. One example would be if crops are marketed as small lots of value-added grain instead of commodities. Production proliferation in the seed industry may be another instance. Finally, whether due to food safety concerns, GMOs, food labeling, or the growth of organic food markets, identity preservation requires more precise inventory control.

A research has been conducted on the use of multiple-goal linear program model to solve multi goals by taking the case of optimization of production planning at CV. Amanda Makassar during the Covid-19 period. In this research, four goals were formulated, that were (i) the fulfillment of the number of market demand, (ii) maximizing income, (iii) minimizing production costs, and (iv) maximizing working hours. Then for the optimal solution using LINGO 18 software. Based on the research results, the optimal production plan during the Covid-19 period resulted from the two different models for original brownies products where the results of the dual-purpose linear program model without target priority produced 16.118 original brownies and 32.400 packages from the dual-purpose linear program model with priority target with weight. For cream cheese brownies, there are 3.000 packages, 18.000 packages of sarikaya pandan brownies, 3.600 packs of choco marble brownies, pink marble brownies, tiramishu marble brownies, roasted brownies, and 1.800 packs of cappuccino marble brownies. Chocolate bananas bolen, pineapple molen, and chocolate ganache in 840 packages. Then for 15.000 packs of blueberry brownies, 960 packs of strawberry brownies, 360 packs of dry brownies, 2.400 banana cheese brownies, 300 packs of cheese bananas bolen, 600 packs of peanut butter, and 9.000 packs of pandan cake for a month. The maximum revenue obtained by the company with a multiple-purpose linear program model without target priority is Rp.628.602.000.- and the minimum production cost that the company must pay is Rp.495,048,300,-. Then for the multiple-purpose linear program model with target priority accompanied by a weight of Rp.4.299.480.000.- and the minimum production cost is Rp.3.394.366.000. The result shows that optimization using a multiple goal linear program model with goal priority provide optimal production which results in greater profit compared to the process (optimization) carried out by the company so far, which is only based on the number of demand.

This paper derives the optimal solution for a distributionally robust multi-product newsvendor problem, in which different products are produced under a capacity constraint, while only the mean and variance of the product demand are known. The problem aims to find a capacity allocation scheme to minimize the system cost of the worst-case among all possible demand distributions. When the total capacity is among certain ranges, the optimal solution has a closed-form. For other ranges, the optimal solution can be derived by solving one equation. The solution shows that there exist a number of threshold values for the capacity, below which some products are neglected (allocated with zero capacity). Besides, in the optimal solution, which products are prioritized for production is determined by the order of an index measured by the unit production cost, unit shortage cost, demand mean, and demand variance. For a special case where the cost structures for different products are identical, a closed-form solution is derived for any total capacity value. For this special case, the index order is simply determined by the coefficient of variation of each product demand. Sensitivity analysis shows that when the capacity is abundant, a larger demand variability of one product may cause a higher production quantity for this product; while if the capacity is tight, a larger demand variability cause a lower production quantity. For a set of test problems, the performance of the robust optimization solution is quite close to that of the stochastic optimization solution.

PurposeThe purpose of the research has been the primary consideration and evaluation of a cost effective, reliable, robust and simple process of radio frequency identification (RFID)-based stock control, asset management and monitoring of concrete safety bollards used in the road environment. Likewise, the consideration of the use of the same system and technology to other items in and around the general road infrastructure.Design/methodology/approachThe research approach undertaken has been an evaluation of the use of currently available RFID technology, with a key emphasis on low cost, ease of use, reliability and convenience. Practical field exercises completed in considering the relevant RFID tags and readers and associated software and apps and necessary software integration and development have been undertaken. At the same time, evaluating the specific limits created in the specific environment is being applied. Of particular interest has been the use of a moving scan in a vehicle drive-through or pass-bye, type reading system. This has been determined to be viable and completely practical, drastically reducing the key issue of time-taken. Practical application of the system from idea to real life application has been undertaken. The integration of the use of the RFID tag and reader system with necessary and related software to database upload and storage has been established. The creation of an online facility to allow the appropriate use of the data and to include the convenient output of an asset report has been undertaken.FindingsThe findings have provided the necessary insight confirming the use of RFID technology as a simple yet reliable, cost effective and adaptable stock control, asset management and geo-locating system in the road environment. The use of such systems in this particular environment is in its infancy, and is perhaps novel and original in the specific aspect of using the system to stock control, manage and monitor road safety concrete bollards and other roadside objects in the road environment.Originality/valueTo establish if in fact, stock control geo-locating can be reliably undertaken with the use of RFID tags and readers in the specific road and road construction environment, particularly with the use of moving RFID reading of passive tags. To establish the minimum requirements of a field usable RFID tag and reader, specifically applicable to the concrete safety bollards, however to other roadside furniture. To identify the minimum requirements of a function, simple app to minimise general requirements of the overall stock control and monitoring of the RFID-tagged objects. To establish the possibility of reading the tag data, global positioning system (GPS) location and video imaging footage as a single operation function. To determine the basic parameters or limits of the GPS geo-locating, on the proposed products selected and overall system. To determine the current best practice in respect of reasonable accuracy and detail in relation to price considerations to a fully function stock control and monitoring system. To identify the minimum requirements of an online database to receive, house and provide ongoing access to and report on the data. To identify the key differences and benefits between traditional stock control and monitoring systems, against that of proposed RFID tag, read and geo-locating system.

Optimal selection of cutting speed, feed rate, depth of cut, and the number of passes is important in machining operations due to significant influence of these parameters on machining quality and machining economics. It is an essential part of a computer integrated manufacturing system. In this paper, an optimization model based on minimum production cost for multi-pass turning operations is presented. Tool life, surface roughness, cutting force, cutting power as well as limits on cutting speed, feed rate, and depth of cut are incorporated in the model as constraints. Optimal solutions are found by an integer programming solution approach. A turning example is given for illustration. The model generates much lower unit production costs compared with the results from the literature and machining data handbook.

This paper discusses the Two-Stage Guillotine Cutting Stock Problem (2GCSP) in the garment industry, namely how to determine the two-stage guillotine pattern that is used to cut fabric stocks into several certain size t-shirt materials that are produced based on the demand for each size of the shirt. 2GCSP is modeled in the form of Linear Integer Optimization and finding solutions using the Branch and Bound method. In this paper also presented a Graphical User Interface with Maple software as an interactive tool to find the best fabric stock cutting patterns. The results show that the optimal solution can be determined by solving numerically using the Branch and Bound method and Maple optimization packages. The solution is shown with an illustration of the pattern and the amount of fabric cut based on the pattern.

Designing product lines with substitutable components and subassemblies permits companies to offer a broader variety of products while continuing to exploit economies of scale in production and inventory costs. Past research on models incorporating component substitutions focuses on the benefits from reduced safety-stock requirements. This paper addresses a dynamic requirements-planning problem for two-stage multi product manufacturing systems with bill-of-materials flexibility, i.e., with options to use substitute components or subassemblies produced by an upstream stage to meet demand in each period at the downstream stage. We model the problem as an integer program, and describe a dynamic-programming solution method to find the production and substitution quantities that satisfy given multi period downstream demands at minimum total setup, production, conversion, and holding cost. This methodology can serve as a module in requirements-planning systems to plan opportunistic component substitutions based on relative future demands and production costs. Computational results using real data from an aluminum-tube manufacturer show that substitution can save, on average, 8.7% of manufacturing cost. We also apply the model to random problems with a simple product structure to develop insights regarding substitution behavior and impacts.

This project researches into Digital Stock Control methods in retail companies within the UK and investigates whether a stock control system can be improved within an organisation. This involves research on stock control systems and also looks into the new advanced system that Argos will introduce in the future to come. This project has an insight into the employees of Argos whether they understand the current system and the new system. This investigation was carried out to find out if the employees of Argos understood the stock control system. Who out of the full-time and part-time employees had the most knowledge, what the employees think of the system, and finally what do the employee think of the new stock control system. The data was gathered by using a quantitative method, which was an introduction of questionnaires. The project examines the characteristics between the two sets of employees, full-time and part-time, the knowledge within the employees of Argos had a major similarity. It looks at both sets of employees with very symmetrical opinion regards to the new system and the knowledge they have. Its also considers the current stock control system the knowledge. It researches the full-time employees and what knowledge they have regards to the knowledge to the part-time employees.