Order Lot Size Research Articles

Mitigating data inaccuracy and supply chain challenges in Western Romania's automotive industry

The purpose of this paper was to emphasize the importance of data accuracy within internal logistics systems and their extended influence on supply chains in automotive industry through 6-month multiple case studies conducted on 3 first tier original equipment manufacturers (OEM) based in Western Romania. The study investigates the most common causes of data inaccuracies among automotive suppliers and their approaches to reduce consequential supply chain issues and be more agile. Data collection and analysis revealed that main issues arise due to ordering quantities mismatching actual customer demand, a wide range of order lot sizes, lead times and delivery reliability concerns and the reluctance to shift away from mainstream cost-effectiveness and towards strategic added value thinking. These issues sourced significant other related operational challenges such as excessive inventory, short-term stockouts and subsequent express shipping services or product-related inconveniences (quality and capacity levels, contracted volumes and dedicated lines). The paper sources different logistics and supply chain strategies used by the 3 OEMs, their features and operational performance, as well as their overall effectiveness, which can be applied by other automotive industry suppliers to improve own results. Introducing more reliable real-time data collection tools and performance metrics has started hauling more focus towards solving these prevalent issues with some ongoing improvement projects showing up to 25% better results. For one of the 3 OEMs introducing a new warehouse management system has already sourced an overall quality increase (5 percentage points) due to a 60% higher utilization of its production equipment.

Integrated Multi-Vendor Single-Buyer Inventory System Model in Textile Waste Processing Industry

PT. Superbtex Nonwoven Division is one of the industries implementing a green manufacturing system in Bandung by using textile solid waste as raw material and processing it into value-added finished products. However, the solid waste generated by consumers and garment factories is very large and cannot be accommodated in its entirety by PT. Superbtex Nonwoven Division. Another problem arises in terms of inventory both for vendors and buyers; delivering waste from vendors to buyers in small quantities and frequently can lower inventory costs for buyers, but concurrently raise transportation expenses for vendors, and vice versa. Therefore this research was conducted to solve the problem of an integrated multi vendor-single buyer inventory system that considers independent transportation, sorting, and disposal to find the minimum total system cost by finding the optimal value of order lot size, delivery frequency, and proportion of order lot size. that each vendor needs to send to the buyer. Problem-solving is done using the Mixed Integer Non Linear Programming (MINLP) method with the LINGO 18.0 solver. The results obtained from this study stated that the sorting costs at vendor 1 (S1), the sorting costs at the buyer (Sb), the transportation variable costs (Fy), the delivery truck capacity (X), and the demand rate (D) have a significant effect to changes in total system cost (TC). So that the five parameters need to be estimated carefully to determine the optimal system cost.

Environmental strategies for a healthcare system with green technology investment and pandemic effects

Today the healthcare industries struggle to cope with the ecological and social challenges for their customer services even while we are entering into a post-pandemic economy. Hospitals are quickly running out of essential medical supplies and firms are fraught to keep up with the rise in pent-up demand due to ongoing supply chain issues caused by the troubles from the pandemic. Therefore, we must design a sustainable inventory strategy for managing the healthcare supply chain (HSC) to ensure customer service and net-zero economy. This study explores sustainable inventory policies in a pandemic situation while considering the transport cost as proportional to COVID-19 intensity. We assume that the pharmaceuticals items have a predictable shelf-life and demand rate directly relates to the effectiveness of the investment in service facilities. The model incorporates the carbon emissions during the activities of transport, production, and storage, which are intended to be cut by green investment. The proposed scenario is modeled as an optimization problem and a solution approach has been designed for finding the sustainable inventory strategies such as order lot-size, delivery lead time, amount of green and service investment with the objective of reducing CO2 and overall cost. Key managerial insights into the influence of pandemic are extracted through the study of numerical and sensitivity. The suggested model is validated in the healthcare sector. The novelty of this research is examining the effect of green investment and COVID-19 pandemic on HSC. This work also reveals how green technology can play a vital role in managing the HSC issues caused by the pandemic in the post-COVID-19 environment.

Analisis Pengendalian Persediaan Bahan Baku Biji Plastik Dengan Metode Probabilistik Di UD. ACC Plastik Sememi, Benowo, Surabaya

UD ACC Plastics is a business in the field of plastic products that are produced, namely Hangers made from PP (polypropylene) plastic. Planning and controlling raw materials is very important for plastic companies with manual cupola especially UD. ACC Plastic. Fluctuating demand from customers resulted in excess and shortage of raw materials at UD. ACC Plastic. For that we need a definite and optimal calculation. In this case, an analysis of the planning and control of raw materials is carried out using the probabilistic method of the P Back Order model. To find out the order time interval, safety stock, lot order size, and inventory costs. Inventory and Control is done by probabilistic calculation of the P Back Order model with the Hadley Within solution by doing iterations and selecting the best solution with the minimum total inventory cost. Calculation results obtained total minimum inventory costs and optimal inventory system. In the raw material inventory of plastic pellets, the total cost of Rp. 204,325,752 with order intervals every 23 days or 0.062 years, order lot sizes of 415 kg, safety stock of 134.59 kg and a maximum order of 550 kg. The service level provided was 99.96%.

Penerapan Pengendalian Persediaan Material Dinamit/Expogel Menggunakan Metode Inventori Probabilistik Model Q-Back Order di PT Pindad (Persero)

PT Pindad (Persero) is in charge of producing commercial military products for the benefit of the government and private sector. However, in its production activities, the company has difficulties in controlling the inventory, one of which is in the dynamite/expo gel component. Stock control using probabilistic inventory method Q-back order model is used to balance between the needs of goods that must be provided and maintain the decrease in sales due to the shortage of goods. This study aims to determine the size of the order lot that minimizes the cost of supplies on the dynamite/expo gel component at PT Pindad (Persero). The optimal order lot size of the calculation result was with service level of 97.77%. The comparison with company policy showed a decrease in total inventory cost of 0.6% and a decrease in storage costs of 88%.

PERENCANAAN PERMINTAAN BAHAN BAKU DAN PENENTUAN UKURAN PEMESANAN (LOT SIZE) OPTIMAL DI GUDANG KIMIA MARUNDA

<p><em>This research was conducted on companies that store and distribute chemical raw materials (sodium sulfate) to industrial companies. The problem that occurs is that the company does not have a medium-term raw material demand plan to determine the optimal order size to suppliers as storage in the warehouse. Given that ordering is also important to note because it has an impact on the total cost of inventory from ordering costs and holding costs. The purpose of this study is to forecast to find out the demand for raw materials in the future so that the company has an estimate for planning future demand for raw materials and calculates several ordering methods (lot size) to get the optimal order size.</em></p><p><em>Solving problems using forecasting methods (Moving Average, Weight Moving Average, Exponential Smooth), and lot size methods (Economic Order Quantity, Period Order Quantity, Least Unit Cost, Part Period Balancing). The results of the analysis, forecasting to determine the demand for raw materials for the next year using the Exponential Smooth method because it has the smallest MAD MSE MAPE value, and the ordering lot size using the Part Period Balancing method because it has the minimum total inventory cost of Rp. 14,128,706,027 or 23.5% more efficient than the usual ordering used by companies.</em></p>

Sale through dual channel retailing system— A mathematical approach

This paper deals with a dual channel inventory model where capacity of the market of a particular product is uncertain. The demand rates of the traditional consumers and the online consumers are segregated from total capacity of the market. The trust vale and acceptance rate of the product by the online consumers and utility functions comprising of value of the product, trust value of the online purchasing and some costs associated with risk, traffic, opportunities, etc., determine the demand rates of the products in offline and online channel. In this model, one retailer has offline and online options to sale the products. The objective of the retailer is to find out optimal pricing, order lot size and reorder point for maximizing jointly the average expected profit from offline and online channel. A mathematical model is analyzed to find out the optimal values of variables. Finally, a numerical example is illustrated to justify the proposed model.

A Sustainable Approach for Smart Supply Chain with Quality Humiliation and Carbon Emission Cost

Most decisive principles affecting customers’ ordering decision is quality of the products. The intention of the work is to provide the sustainable decisions such as order lot-size and total number of lot-size to create a smart SC in view of minimum carbon emissions and joint total cost. This research considers an imperfect production vendor-buyer inventory system involving quality degradation of raw material and carbon emission cost. The vendor’s production process produces some imperfect products, even manufactured products inspect twice, which are examined by buyer and those are return back to vendor in the subsequent shipment. We incorporate the emissions throughout the production processes, transport and storage. Mathematical based inventory model is developed to attain the sustainable decisions which are illustrated numerically.

Inter-dependent lead-time and ordering cost reduction strategy: a supply chain model with quality control, lead-time dependent backorder and price-sensitive stochastic demand

This research work addresses an inter-dependent reduction strategy of lead time and ordering cost in a two-stage single vendor and single buyer supply chain model with price-sensitive stochastic demand. Buyer’s backorder rate is a variable, as it depends on the variable lead time. Quality improvement is another aspect of this study. The objective of this study is three folds. Firstly, reducing the lead time and ordering cost simultaneously. Secondly, improving the quality of products and third, optimizing order lot size, lead time, process quality parameter, safety factor, ordering cost, lead time crashing cost, backorder rate, and the number of deliveries so that the joint expected total profit becomes maximum. Stackelberg game and Joint decision, both approaches are discussed. Numerical result shows that the Joint decision approach gives better result than the Stackelberg game approach. Sensitivity analysis for Case-III with respect to some key parameters has been carried out.

An analysis of retailer’s inventory in a two-echelon centralized supply chain co-ordination under price-sensitive demand

As the industrial environments become more competitive, managing specific inventory levels and coordination between channel members of a companies supply chain is very much crucial. In this paper, we have analyzed a two-echelon supply chain containing a manufacturer and a retailer in which the manufacturer offers a single product to the retailer and the retailer takes the responsibility of managing the inventory of the product. The products deteriorate at the retailer warehouse at a constant deterioration rate. We have generalized our model for two different demand functions faced by the retailer from the customers’ side. The demand functions are (a) a linear function of price (b) an iso-elastic function of price. The shortage is also allowed and partially backlogged with a constant backlogging rate. Total profit of the supply chain under two different demand scenarios is evaluated for a joint centralized coordination. The prime objective of our paper is to compare the total profit under two different demand functions in joint centralized coordination such that the channel member can decide their optimal sales price, inventory scheduling of retailer, ordering lot size to maximize the total profit. A numerical example has been illustrated to validate the theoretical results. Also, sensitivity analysis of some key parameters is carried out which gives some managerial applications. The findings of this paper demonstrate that linear demand would increase the joint profit of a centralized system. This analysis has an important guiding significance for the supply chain coordination of deteriorating items under linear and iso-elastic demand.

Lead-time Dependent Ordering Cost Reduction and Trade-credit: A Supply Chain Model with Stochastic Demand and Rework

This study focuses on an integrated vendor-buyer supply chain model where the lead-time and ordering cost reduction act dependently. The lead time demand of a product follows a normal distribution. The manufacturing process is imperfect. During production run time, a certain percentage of defective products are produced, which are immediately reworked. Trade-credit financing has been taken into consideration. The goal of this study is to minimize the joint total expected cost by providing an inter-dependent reduction strategy of lead-time and ordering cost along with the determination of the optimal values of lead-time, number of deliveries, order lot size, ordering cost, lead-time crashing cost, and the joint total expected cost. A solution algorithm and a numerical example are presented to illustrate and establish the integrated model. This model can be used in textiles, automobiles and computers industries.

Two phases inventory model with variable cycle length under discount policy

This study deals with single stage inventory model where two phases are involved in an inventory cycle. In the first phase of the cycle, demand depends on both of inventory level and selling price while in the second, the demand depends on price only. Discount policy in selling price is offered in the second phase and inventory level at the end of the cycle is taken to be zero. Two models have been constructed on infinite time horizon. In the first model the demand rate is taken as the sum of two linear functions of inventory level and selling price and, in the second model, it is taken as a product of two power functions of inventory level and selling price. Our objective is to maximize average profit by considering ordering lot size and selling price as decision variables. Numerical examples of each model have been provided. The optimality criteria for the solutions are also checked by both graphically and numerically. Sensitivity analysis for different parameters in both models has been discussed in details to check the feasibility of the models.

Perencanaan dan Pengendalian Persediaan Bahan Baku serta Komponen Mbox di PT. X

The development of the industrial now increasingly rapid because the companies compete each other to be excellent in their fields. Companies can survive in the midst of competition if the company is able to increase efficiency. One of the way is to control inventory. This research was conducted to make the planning and control of the optimal needs of raw material and component at PT. X by applying the Wagner Within Algorithm method to achieve the Mbox production target. Types of raw materials and component in forming one Mbox product unit consist 18 types of component and 6 types of raw materials. Data processing will be done by setting the Mbox request every period. After that, inventory control costs are calculated using the 3 step Wagner Within Algorithm method. From the calculation results obtained by order lot size which results in a total inventory cost of Rp. 54.109.030. with component production every period must be fulfilled and raw material ordering is done at the beginning of the period to meet the production needs to entire period. Except for 1,5 mm steel plate order, which are ordered 6 times. The difference is due the calculation results from the Wagner Within Algorithm method which requires bookings made at certain periods.

Optimizing profit for pricing and advertisement sensitive demand under unreliable production system

ABSTRACT This article deals with an imperfect economic production quantity (EPQ) model with an unreliable production system where the customers' demand depends on both selling price and advertisement. During the long run production process the machinery system goes into ‘out-of-control’ state after a random time τ and after that the system produces both perfect and imperfect quality items together. The imperfect or defective quality items are reworked to get it back as the perfect ones at a cost just after the regular production run time. The production process of imperfect quality items depends on the reliability of the machinery system where the failure rate may be variable. Here, we consider that the random time variable τ follows the two parameters ‘Weibull distribution’. The objective of this article is to maximize the expected average profit function of the unreliable system with respect to ordering lot size, selling price and frequency of advertisement. We use the incomplete gamma function to formulate the expected average profit function. The model is validated by numerical examples and sensitivity analysis is provided to illustrate the model.

PERENCANAAN PERSEDIAAN KOMPONEN PADA PERUSAHAAN ORIGINAL EQUIPMENT MANUFACTURER MENGGUNAKAN METODE PERSEDIAAN DETERMINISTIK DINAMIS

Determination of inventory of raw materials and components is needed to support the smoothness of the production process. Inventory management is done, in order to determine optimum inventory level, order lot size and reorder time that can minimize total inventory cost. This research applies some method in dynamic deterministic inventory model by comparing those method based on the lowest inventory total cost. This model solved basic inventory management problems, which are; the amount of goods to be ordered for each time the order made , when the order need to be made (r) and safety stock level. Based on this research, it is known that company may decrease its inventory cost by implementing suggested inventory method

Multi-echelon Supply Chain Model for Deteriorating Products in a Fuzzy Deterioration Environment

Purpose: This research analyses the optimal inventory strategy for a deteriorating product with imprecise deterioration rate in a single supplier-buyer supply chain system with realistic factors. Design/methodology/approach: The integration of production and distribution inventory system is crucial in practice for minimizing a firm's cost while the effect of deterioration cannot be ignored as it affects the entire inventory system. Nowadays managers have begun to recognize that effectively managing deterioration risks in their business operations plays an important role in successfully managing their inventories. Here, the deterioration rate is treated as the triangular fuzzy number. Also we use the extension principle method to define the membership function of the fuzzy total cost and defuzzify by the centroid to find the estimate of the total cost in the fuzzy sense. Findings: A methodology has been proposed through mathematical model which involves designing an iterative algorithm to achieve optimal decisions such as order lot-size and total number of deliveries from the supplier to buyer. Originality value: The effects of varying the central parameter values on the optimal solution are performed by numerical and sensitivity analysis so as to highlight the differences between crisp and the fuzzy cases.

DRP: Joint Requirement Planning in Distribution Centre and Manufacturing

Companies are always seeking differentiation from their competitors. Efforts are made by providing the best service to consumers, fast order fulfillment, reliable delivery times, and better response to inquiries about products, orders, and deliveries. This paper aims to provide an overview of joint distribution planning between distribution centre and manufacturing industry with DRP logic. Distribution Resources Planning (DRP) is a method that can be used to integrated inventory policy in distributors and manufacturing. DRP implementation starts from managing sales forecasts, creating master schedules, and running DRP. The DRP represents a way of thinking with respect to managing the entire function of distribution. The DRP Method can be known the optimal number of order lot sizing, frequency of ordering, safety stock at each distribution centres. DRP can reduce the frequency of ordering so that the cost of the order becomes minimize. DRP implementation reduces 23,9% of order frequency and saves order cost 42,9%.

Optimal production model with quality sensitive market demand, partial backlogging and permissible delay in payment

In this study, we consider an imperfect production inventory system with quality of the products dependent market’s demand structures and allowable delay in payments. Two alternative approaches of trade credit policies have been discussed when the manufacturer could not pay the due amount to the supplier within the credit period offered. Here, a new cycle is begun with new production when the manufacturer’s inventory touches to a certain level of shortages. The cycle also ends when backlogged inventory level is reached a certain level. The backlogging rate for the player is dependent on waiting time. The production cost of the manufacturer varies with ordering lot size and quality of product. The behavior of the model under integrated system is analyzed. The sensitivity of the key parameters is examined to test feasibility of the model. Finally, a numerical example is provided to investigate the proposed model.

Promotional effort and quality sensitive two echelon production inventory model with partial backlogging

This study deals with the modelling aspect of a two echelon imperfect production system in the presence of the promotional effort of the retailer. The production cost of the system varies with both the ordering lot size and quality of product, and the demand of the product depends on the quality of the product. The inventory level for the manufacturer starts with shortages and new production and the inventory level for the retailer also begin with shortages and new product lot. The cycle ends for both the players with also backlogged inventory. The backlogging rate for each of the player is dependent on waiting time. The behaviour of the model under integrated system is analysed. In the decentralised structure, retailer Stackelberg model are also discussed. The sensitivity of the key parameters is examined to test feasibility of the model. Finally, a numerical example is provided to investigate the proposed model.

A joint internal production and external supplier order lot size optimization under defective manufacturing and rework

The traditional production-inventory problems do not consider joint production and order lot sizes in manufacturing systems. This paper considers a defective system to jointly decide on order and production lot sizes in a manufacturing company. The manufacturer produces items with finite processing rate where a percentage of these items are of imperfect quality. At the end of production process, the rework of imperfect items is carried out. The demand rate and the number of defective items are considered to be uncertain parameters. The aim is to determine optimal number of sub-production cycles, as well as optimal order quantity. To address this problem, we first define the problem and describe its characteristics, build the model via deriving total cost function, design an appropriate solution algorithm, and then illustrate and evaluate the results. The solution algorithm is based on an ant colony optimization (ACO) which is enhanced by an adaptive learning strategy. A numerical example is presented and discussed, and the results are compared with basic ACO and genetic algorithm (GA). Finally, sensitivity analysis and robustness analysis are performed and discussed. The observed results reveal the robust performance of proposed approach against basic ACO and GA. Moreover, we observed that the performance of basic ACO and GA is approximately the same, and the basic ACO is more robust than GA in our experiments.