An Implementation Analysis of AHP-TOPSIS and Music-3D for Optimizing Spare Part Inventory Control (Case Study: PT. Bati)

<em>PT. Prima Sejati Sejahtera as one of the subsidiaries of PT. Pan Brothers Tbk. which is engaged in garment production. The company's mechanical department in managing spare part inventory is still using intuitive method, where the number of spare part order for certain periods based on spare part demands data onto the previous period. The company’s mechanical department often stock out of spare parts. Spare part’s inventory management becomes a complex issue because of the need for fast response to handle the downtime of machines, and the risk of obsolescence of spare parts. So in this research will discuss about spare part inventory control which is started with spare parts grouping by using ABC analysis method to determine the appropriate inventory control method for each group. There are 23 spare parts which included in group A. The forecast of spare part’s demands to use Croston, Syntetos-Boylan Approximation (SBA) and Single Exponential Smoothing (SES). Comparison of each forecasting method will be determined by the value of forecasting errors (MAD). It is known that there are 12 spare parts with Croston method in the best forecasting method, 6 spare parts in Syntetos-Boylan Approximation (SBA) method and 5 spare parts with Single Exponential Smoothing (SES) method. Based on the best forecasting result, it will be calculated the value of safety stock (SS), reorder point (ROP) and the optimal number of ordering (Q) using Continuous Review method for each spare part.</em>

Effective spare parts management at PT XYZ requires accurate classification based on their turnover rate. This research aims to categorize spare parts into fast-moving, slow-moving, and non-moving categories to improve inventory management efficiency and support the company's operational sustainability. From the analysis of 130 types of spare parts, it was found that 69 (53%) fell into the fast-moving category, 50 (38.5%) were slow-moving, and 11 (8.5%) were non-moving. This classification is critical because it allows the company to determine the optimal order quantity and storage location for each category of spare parts. Thus, the company can prevent stock shortages on frequently used parts, which can disrupt smooth operations. In addition, activities with the grouping of goods can increase the accuracy of the stock-taking process, making it easier to make decisions related to inventory management. The data in this study were collected through various methods, including direct observation, literature study, and analysis of company historical data. The results show that classifying spare parts based on turnover ratios can be a solid basis for more effective inventory management policies. The application of this classification, PT XYZ is expected to improve operational efficiency and optimize the use of existing resources, to contribute to the growth and desire of the company in the future. Keywords: Class-based storage method; FSN Classification; Inventory Control; Spare Parts; Turnover Ratio

System-oriented inventory models for spare parts

The aftermarket business is a highly profitable activity for companies, and they can earn considerable profits from selling spare parts. Spare parts demands are more uncertain and intermittent in comparison with finished goods and associated work in progress parts. In the aftermarket, the demand uncertainty of the spare parts for the OEMs is complicated by the fact that the other competitors, known as market players or will-fitters, supply substitutable parts usually with lower cost of production and deliver them to the market at cheaper prices. This uncertainty makes spare parts management challenging, and this study develops strategic approaches for spare parts price setting and inventory level control to further exploit the benefits of the spare parts business. This dissertation is divided into four main parts. In the first part, a brief review of inventory system policies is provided. The review starts with an introduction to the inventory systems terminology and follows with a categorization of the inventory systems with the aim of developing spare parts inventory models. Moreover, a discussion about the computations related to the (Q,r) policy is provided. An algorithm is proposed to find the optimal re-order point/lot-size and a Monte Carlo simulation is designed to evaluate the mathematical optimization solutions including the new algorithm and the other classical methods. In the second part, a literature review related to spare parts management is presented. The literature review is organized in such a way that in the beginning the inventory control policies are introduced. Then the perspective of uniqueness of spare parts on the inventory management is illustrated. Next, spare parts clustering and demand are studied and forecasting methods are reviewed. The use of Game Theory for inventory systems planning is studied. Also spare parts pricing as a strategic method to increase the profit of the suppliers is evaluated. In the third part, to investigate the profitability of spare parts business, the notion of renewal cost versus the replacement cost is proposed. The replacement cost of a product is defined as the current market price of the product and the renewal cost of a product is the acquisition cost of spares to completely renew the product excluding labor costs. These costs are calculated for some products with specific characteristics, and the ratio between the renewal cost and the replacement cost as a scale to evaluate the sustainability of the spare parts pricing is determined which declares that the spare

General Background: In the concrete manufacturing industry, the reliance on machines for production activities necessitates a robust spare parts inventory management system to ensure operational continuity. Specific Background: However, fluctuating demand for spare parts often leads to overstock or stockout situations, significantly impacting inventory costs and cash flow. Knowledge Gap: Existing studies primarily focus on static inventory management approaches, neglecting the dynamic nature of spare parts demand in manufacturing environments. Aims: This research aims to optimize total inventory costs while determining efficient order and reorder point quantities by integrating the Economic Order Quantity (EOQ) method with continuous review techniques. Results: The findings reveal an optimal order quantity of 131 units and a reorder point of 18 units, resulting in a total inventory cost of IDR 2,414,609,989—an efficiency improvement of IDR 293,152,400, equivalent to an 11% cost saving compared to previous inventory management practices. Novelty: This study innovatively employs a probabilistic approach to account for demand variability, enhancing the accuracy of inventory control measures. Implications: The outcomes suggest that implementing the proposed inventory management strategy can mitigate the risks of overstocking and stockouts, ultimately fostering improved financial performance in the company. Furthermore, the research highlights the necessity for regular inventory reviews and suggests future studies to develop more dynamic inventory control models that incorporate price fluctuations for spare parts, thereby addressing potential risks associated with cost variability.

These equations depict the following inventory situation. A nonnegative order for a single product is to be placed at the beginning of each of an infinite sequence of equally spaced periods into the future, labeled 0, 1, 2, .. Demands depleting the inventory form a nonnegative sequence of independent identically distributed random variables 40, 1, '2, * . For analytic convenience the distribution is assumed to possess a continuous positive density function 0(4) on [0, oo). An order zi placed at the beginning of period i arrives after a fixed Aperiod lag at the beginning of period i + A, and is relabeled Y(i + ), which explains (4). The pipeline vector qi at the beginning of period i consists of the inventory on hand at that point xi together with the sequence of outstanding orders to arrive in succeeding periods Y(i+ 1), Y(i+ 2)' ... , Y(i+ -1) If demand in a given period exceeds inventory on hand, two extreme cases are considered. In model I, also called the no backlogging or the lost sales case, no customer will wait, so the inventory level is conveniently thought of as being nonnegative; it is recursively generated by (5a). In model II, also called the backlogging case, all customers

In addition to equipment maintenance decisions, spare parts ordering decisions from different suppliers play a key role in reducing related costs (e.g., maintenance, inventory and ordering costs). Since suppliers may use different production technologies and materials, spare parts (or products) from different suppliers can be different in quality. Nevertheless, in recent studies, the quality of spare parts is rarely considered to incorporate both equipment maintenance and spare parts ordering. In this paper, we investigate the joint optimization of condition-based maintenance and spare parts provisioning policy under two suppliers with different product quality. We formulate a sequential-decision problem with a Markov decision process and consequently obtain an optimal maintenance and ordering policy by an exact value iteration algorithm. To improve computation efficiency, based on the principle of sequential optimization, we develop heuristic methods. Extensive numerical experiments are conducted to assess the overall performance of the developed heuristic methods. Compared to the optimal method, results showed that the average cost gap is about 2% and computation time is reduced by 94% on average under the proposed heuristic method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the observation that automobile industries tried to integrate emergency suppliers from which spare parts have different quality into maintenance schedules to avoid stockout and reduce equipment failure during the Covid-19 pandemic. Specifically, the article focuses on balancing the trade-offs between condition-based maintenance and inventory management from two suppliers with different lead times and spare parts quality for multi-unit systems. On the one hand, effective maintenance scheduling relies on spare parts for replacement to ensure the stability of production. On the other hand, inventory management needs to select the supplier with appropriate lead time and product quality to reduce the ordering cost and avoid stockout based on the degradation states of equipment. The joint optimization of these two aspects serves to reduce the total maintenance and ordering cost. Nevertheless, most existing research aims to optimize them separately. In this paper, we formulate the joint decision problem considering the two aspects based on a Markov decision process. We obtain an optimal maintenance and ordering policy by an exact value iteration algorithm and present heuristics to improve the computation efficiency when the system contains multiple machines. Practitioners can implement the proposed methodology to make condition-based maintenance and inventory management when spare parts with different qualities are ordered from two suppliers. To balance cost and computational efficiency, it is suggested to implement the optimal policy by an exact value iteration algorithm when the number of machines is small in the system and use the heuristic methods when the number of machines is large (i.e., usually larger than 3).

The spare parts inventory control is a necessary condition for equipments' safe and stable operation, which has a direct impact on enterprises' operation and economic benefits. With the development of information systems, the application of ERP in management activities provides a platform for inventory management. This paper combines the thought of ERP with spare parts inventory control, summarizes the general characteristics of spare parts management, and using quantitative analysis of inventory theory, discusses the spare parts inventory control model with certain and uncertain factors respectively; and then discusses the method application in the enterprise's ERP system. Moreover, cases of air segregation plant using ERP combined with pare parts quantitative inventory control method is discussed and evaluated by performance appraisal. The achievement of the article will guide enterprises' management related to spare parts inventory control, and provides Chinese enterprises with a new approach to improve on spare parts inventory control in the environment of ERP system.

Aiming at the inventory management problem of metro vehicle repairable spare parts, a two-echelon inventory model based on METRIC (Multi-Echelon Technique for Recoverable Item Control) theory is proposed. Firstly, analyze the state transition process of metro vehicle repairable spare parts. Secondly, establish the two-echelon inventory management model according to the inventory characteristics of metro vehicle repairable spare parts. Thirdly, take the lowest cost of spare parts as the objective, take metro availability and spare suffice rate as the constraints, apply marginal analysis method to find the optimal position of spare parts among the base and depots. Finally, take the initial spare parts of Guangzhou Metro as the research, use the optimization model based on METRIC theory to optimize the initial spare part number. The results show the model proposed in this paper has a certain significance and reference value to general metro spare part inventory management problem, and can be used in actual operation to provide decision support for the metro managers.

Given the characteristics of spare parts storage in the TG rolling plant, the main spare parts are classified and managed by the combination of the two categories of inventory circulation speed and technical criticality. The key evaluation indicators of spare parts cost, spare parts maintenance, and inventory management are evaluated by AHP. Based on this, the inventory control model based on random demand and random lead time is established, and the economic order volume, order point, and safety inventory are obtained based on cost consideration so that the inventory cost can be controlled, and then the simulation verification based on ExtendSim software is established. Finally, a reasonable and effective inventory management control strategy for the TG enterprise rolling workshop spare parts inventory reference is provided.

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

As cities grow, intercity railways are becoming increasingly popular for short trips between neighboring areas. These railways cater well to commuters and travelers, making reliable and cost-effective maintenance crucial. Timely access to spare parts is essential for ensuring the smooth operation of intercity railways. Traditionally, intercity railways lack failure probability data for spare parts, which hampers the support for spare parts ordering decisions, resulting in spare parts management primarily relying on manual experience. This approach often leads to problems like excessive inventory levels and high management costs. To enhance the reliability of intercity railway operations and reduce spare parts management costs, this paper employs the Zebra Optimization Algorithm-Least Squares Support Vector Machine (ZOA-LSSVM) to analyze the reliability of the important Weibull distribution spare parts of the intercity railway and fit the parameters of the reliability function for spare parts. Based on the failure rate, an inventory control model for intercity railway spare parts is established, aiming to minimize total costs while considering constraints such as order point, order quantity, and equipment availability. A genetic algorithm is designed to solve this model. To verify the effectiveness of the model, we select the contact network insulators of Chinese J Intercity Railway as the case study subject. By comparing the fitting performance of several methods, including ZOA-LSSVM, Genetic Algorithm (GA)-LSSVM, LSSVM, and Least Squares Regression (LSR), the effectiveness of ZOA-LSSVM is validated. The experimental results indicate that ZOA-LSSVM can provide better prediction accuracy. Based on this fitting method, spare parts inventory management is conducted. By comparing it with the traditional manual experience method, it is found that the approach proposed in this paper not only ensures the stable operation of intercity railways but also significantly reduces costs by approximately 13.6%. This result fully demonstrates the superiority of the optimization model established in this paper in practical applications and provides new ideas and methods for the management of spare parts for other intercity railways.

A stochastic model for joint spare parts inventory and planned maintenance optimisation

The OBM based on rational economic and considerations of costs, and even product warranty and after-sales service of the laptop policy shift to the professional services outsourcing services companies (OSS), instead of OEM/ ODM suppliers. The risk and cost in product warranty and after-sales service are managed and shared by OEM and OSS. In the notebook computers after-sales service business, the cost of electronic materials fluctuation in rate is high, and the service life is long, resulting in a small number of shortage - raising the cost of procurement, the majority of the state of slow moving - detract from the value of inventory. This research will be aimed at one of domestic NB ODM factory, explore the OBM warranty policy vs. different service models to study the influence of spare parts shortage, risk of slow moving, reverse logistic and inventory management. OEM face the uncertainty of demand as well as difficulty of spare parts material supply and on time delivery of customer requirements, so irrespective of whether it is in manufacturing, or information systems are required to establish an effective management model, to tie in with the OBM warranty policy and after-sales service operation mode. The company in this study encounters issues of spare parts inventory management due to unsteadiness of demand and supply. Balance the on time delivery of commit to customer and speed up the turn over of spare parts, contribution of this study is setting an efficient inventory management model - through analysis of supply chain in after service and procurement behavior, the application of forecast, inventory control and management theory. With the enhancement of supplier management, the application of this model, reduce spare parts inventory over $5,000,000 successfully since year 2009. Expect to decrease another $5,000,000 after. Achieved experience of this model can be a reference indicator for Taiwan NB ODM/OEM industry.

Spare part procurement is a complex issue and requires an accurate analysis. Stock outs of spare part can leads a great impact on production. Therefore, it is necessary to design the inventory control of spare parts that guarantee the availability of spare parts needed for supporting the maintenance activity. This paper studies the inventory policy for sewing machine spare part using hazard function to approximate the demand. Hazard function is the indicator of the effect of ageing on the reliability of the system. It quantifies the risk of failure as the age of the system increases. We use a continuous review policy based on Hadley Within Approach to calculate the optimum inventory level for critical spare parts. There are four spare parts categorized as critical spare parts, which are needle plate, feed dog, rotary and binder attachment. The optimal ordering quantity for needle plate, feed, rotary and binder attachment are 5 units, 17 units, 5 units, and 9 units, respectively and the reorder point are 2 units, 1 unit, 2 units and 1 unit, respectively. Finally, the service level achieved by the proposed policy is in a range of 95.91%-97.93%, which indicates that the inventory level of spare parts can be used to support the required parts in the maintenance activity.