The Experts below are selected from a list of 106365 Experts worldwide ranked by ideXlab platform
Rommert Dekker - One of the best experts on this subject based on the ideXlab platform.
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spare parts Inventory Control based on maintenance planning
Reliability Engineering & System Safety, 2020Co-Authors: Sha Zhu, Willem Van Jaarsveld, Rommert DekkerAbstract:For many maintenance organizations, on-condition maintenance tasks are the most important source of spare part demand. An uneven distribution of maintenance tasks over time is an important cause for intermittency in spare parts demand, and this intermittency complicates spare parts Inventory Control severely. In an attempt to partially overcome these complications, we propose to use the maintenance plan, i.e. the planned maintenance tasks, as a source of advance demand information. We propose a simple forecasting mechanism to estimate the spare part demand distribution based on the maintenance plan, and develop a dynamic Inventory Control method based on these forecasts. The value of this approach is benchmarked against state-of-the art time series forecast methods, using data from two large maintenance organizations. We find that the proposed method can yield cost savings of 23 to 51% compared to the traditional methods.
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an Inventory Control system for spare parts at a refinery an empirical comparison of different re order point methods
European Journal of Operational Research, 2008Co-Authors: Eric Porras, Rommert DekkerAbstract:Inventory Control of spare parts is essential to many organizations, since excess Inventory leads to high holding costs and stock outs can have a great impact on operations performance. This paper compares different re-order point methods for effective spare parts Inventory Control, motivated by a case study at a large oil refinery. Different demand modeling techniques and Inventory policies are evaluated using real data.
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Inventory Control in hybrid systems with remanufacturing
Management Science, 1999Co-Authors: Erwin Van Der Laan, Marc Salomon, Rommert Dekker, Luk N. Van WassenhoveAbstract:This paper is on production planning and Inventory Control in systems where manufacturing and remanufacturing operations occur simultaneously. Typical for these hybrid systems is, that both the output of the manufacturing process and the output of the remanufacturing process can be used to fulfill customer demands. Here, we consider a relatively simple hybrid system, related to a single component durable product. For this system, we present a methodology to analyse a PUSH Control strategy (in which all returned products are remanufactured as early as possible) and a PULL Control strategy (in which all returned products are remanufactured as late as is convenient). The main contributions of this paper are (i) to compare traditional systems without remanufacturing to PUSH and to PULL Controlled systems with remanufacturing, and (ii) to derive managerial insights into the Inventory related effects of remanufacturing.
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production planning and Inventory Control for remanufacturable durable products
1996Co-Authors: Marc Salomon, E A Van Der Laan, Rommert DekkerAbstract:In this paper we focus on production planning and Inventory Control in systems where manufacturing and remanufacturing operations occur simultaneously. Typical for these hybrid systems is, that both the output of the manufacturing process and the output of the remanufacturing process can be used to fulfil customer demands. This process interaction together with other process interactions and various sources of uncertainty make production planning and Inventory Control in hybrid systems more complex than production planning and Inventory Control in traditional systems. The objectives of this paper are to demonstrate some of the effects of remanufacturing on production planning and Inventory Control, and to indicate various actions that can be taken by remanufacturing companies to improve their cost-efficiency. In particular, the issues of how much and where to keep (safety) stocks, how much and when to manufacture and remanufacture, and how to reduce the various sources of system uncertainty will be addressed. In this context we study a relatively simple hybrid system, related to a single component durable product. The behaviour of this system is numerically evaluated both under a PUSH-remanufacturing strategy (in which all returned products are remanufactured as early as possible) and under a PULL-remanufacturing strategy (in which the timing of remanufacturing operations depends on a combination of market demands for new products and market supply of returned products).
Ickhyun Kwon - One of the best experts on this subject based on the ideXlab platform.
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an adaptive Inventory Control model for a supply chain with nonstationary customer demands
Lecture Notes in Computer Science, 2006Co-Authors: Jungeol Baek, Chang Ouk Kim, Ickhyun KwonAbstract:In this paper, we propose an adaptive Inventory Control model for a supply chain consisting of one supplier and multiple retailers with nonstationary customer demands. The objective of the adaptive Inventory Control model is to minimize Inventory related cost. The Inventory Control parameter is safety lead time. Unlike most extant Inventory Control approaches, modeling the uncertainty of customer demand as a statistical distribution is not a prerequisite in this model. Instead, using a reinforcement learning technique called action-reward based learning, the Control parameter is designed to adaptively change as customer demand pattern changes. A simulation based experiment was performed to compare the performance of the adaptive Inventory Control model.
Haitao Liao - One of the best experts on this subject based on the ideXlab platform.
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Joint Production and Spare Part Inventory Control Strategy Driven by Condition Based Maintenance
IEEE Transactions on Reliability, 2010Co-Authors: Mitchell Rausch, Haitao LiaoAbstract:Throughput of a manufacturing process depends on the effectiveness of equipment maintenance, and the availability of spare(service) parts. This paper addresses a joint production and spare part Inventory Control strategy driven by condition based maintenance(CBM) for a piece of manufacturing equipment. Specifically, a critical unit is continuously monitored for performance degradation during operation. The amount of degradation is utilized to initiate replacement actions in conjunction with spare part Inventory Control under both production lot size, and due date constraints. A degradation limit maintenance policy is combined with a base stock spare part Inventory Control policy to manage the manufacturing process. The objectives are to minimize the spare part Inventory, and the expected total operating cost. Constrained least squares approximation, and simulation-based optimization are utilized, in a heuristic two-step approach, to determine the optimal base-stock level of spare parts, along with the preventive maintenance threshold. The resulting joint decision ascertains the allowed stockout probability for spare parts, while incurring the minimal operating cost for the required production within a fixed production duration. A case study of an automotive engine manufacturing process is provided to demonstrate the proposed decision-making methodology in practical use.
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spare parts Inventory Control considering stochastic growth of an installed base
Computers & Industrial Engineering, 2009Co-Authors: Tongdan Jin, Haitao LiaoAbstract:Installed base is a measure describing the number of units of a particular system actually in use. To maintain the performance of the installed units, spare parts Inventory Control is extremely important and becomes very challenging when the installed base changes over time. This problem is often encountered when a manufacturer starts to deliver a new product to customers and agrees to provide spare parts to replace failed units in the future. To cope with the resulting non-stationary stochastic maintenance demand, a spare parts Control strategy needs to be carefully developed. The goal is to ensure that timely replacements can be provided to customers while minimizing the overall cost for spare parts Inventory Control. This paper provides a model for the aggregate maintenance demand generated by a product whose installed base grows according to a homogeneous Poisson process. Under a special case where the product's failure time follows the exponential distribution, the closed form solutions for the mean and variance of the aggregate maintenance demand are obtained. Based on the model, a dynamic (Q, r) restocking policy is formulated and solved using a multi-resolution approach. Two numerical examples are provided to demonstrate the application of the proposed method in Controlling spare parts Inventory under a service level constraint. Simulation is utilized to explore the effectiveness of the multi-resolution approach.
Jungeol Baek - One of the best experts on this subject based on the ideXlab platform.
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an adaptive Inventory Control model for a supply chain with nonstationary customer demands
Lecture Notes in Computer Science, 2006Co-Authors: Jungeol Baek, Chang Ouk Kim, Ickhyun KwonAbstract:In this paper, we propose an adaptive Inventory Control model for a supply chain consisting of one supplier and multiple retailers with nonstationary customer demands. The objective of the adaptive Inventory Control model is to minimize Inventory related cost. The Inventory Control parameter is safety lead time. Unlike most extant Inventory Control approaches, modeling the uncertainty of customer demand as a statistical distribution is not a prerequisite in this model. Instead, using a reinforcement learning technique called action-reward based learning, the Control parameter is designed to adaptively change as customer demand pattern changes. A simulation based experiment was performed to compare the performance of the adaptive Inventory Control model.
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adaptive Inventory Control models in a supply chain with nonstationary customer demand
Journal of Korean Institute of Industrial Engineers, 2005Co-Authors: Jungeol Baek, Chang Ouk Kim, Jin JunAbstract:Uncertainties inherent in customer demand patterns make it difficult for supply chains to achieve just-in-time Inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. In this paper, we propose two intelligent adaptive Inventory Control models for a supply chain consisting of one supplier and multiple retailers, with the assumption of information sharing. The Inventory Control parameters of the supplier and retailers are order placement time to an outside source and reorder points in terms of Inventory position, respectively. Unlike most extant Inventory Control approaches, modeling the uncertainty of customer demand as a stationary statistical distribution is not necessary in these models. Instead, using a reinforcement learning technique, the Control parameters are designed to adaptively change as customer demand patterns change. A simulation based experiment was performed to compare the performance of the Inventory Control models.
Siti Zubaidah Ismail - One of the best experts on this subject based on the ideXlab platform.
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Product-Service System (PSS) for Inventory Control: Analysis using Delmia QUEST simulation modelling based on the production line
'Springer Science and Business Media LLC', 2021Co-Authors: Farah Ameelia Mohammad, Siti Zubaidah IsmailAbstract:Product service system (PSS) rises surprising opportunities and purposes for companies and customers, it is in demand a set of products and services capable of fulfilling a customer’s need. Companies and customers play an important role in development from traditional product-based business model to PSS, focusing specifically on the manufacturing sector industry. Based on a traditional marketing perspective, the notion of PSS originates from the shift of marketing focus from products to a more complex combination of products and services supporting production and consumption. The primary aim of positivity can be attained if the production line system is designed, based on system use, to avoid waste and if services are developed with products. This research describes how process flow in the production line and how Inventory Control related to PSS based on the generated result by simulation software. PSS and Inventory Control have not come together. From manufacturing industry perspectives, there is not a standard approach to implement PSS Inventory Control. Inventory Control in PSS creates a more extensive set of uncertainties that the factory needs to manage due to the enhanced scope and complexity of the product and service offering. The research is carried out by using the Delmia QUEST model simulation to develop visual documentation based on the production line process. Results generated by QUEST conclude that the difference in the result obtained shows that the condition of failure and without failure in the production line affected the data regarding PSS for Inventory Control
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Developing palm oil Inventory Control system using Ms Excel macro
'Universiti Malaysia Pahang Publishing', 2021Co-Authors: Al-hadi, Abdulsalam Khaled Abdullah, Siti Zubaidah IsmailAbstract:The palm oil sector is just one of the popular sectors in Malaysia that offer one of the highest exports to Malaysia's economy. This study handles the research study of Inventory Control for Malaysian palm oil plantation. The existing Inventory Control cannot be running smoothly when the Inventory are managed in different user interface systems which is by utilizing manual Inventory Control like Microsoft Excel and handwriting documents. Data collection was gathered with the targeted respondents, they are core members of the management team who have a great experience as well as understanding of their Inventory system. In order to make PSS Inventory Control much easier as well as organized, an Inventory application system is developed utilizing MS Excel Macro. The outcomes of this research study are a computerized supply Control system that beneficial, crucial, and also much better substitute for a hand-operated administration system and quick handling
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Designing Product-Service System Inventory Control: System Requirements Analysis of Raw Material in Automotive Industry
iMEC-APCOMS 2019, 2020Co-Authors: Farah Ameelia Mohammad, Siti Zubaidah IsmailAbstract:During the past decade, growing attention to Product-Service System (PSS) is given a massively important role in development from traditional product-based business model to provision of industrial services. Every production task will incur some level of Inventory, and this requires the collection and processing of both physical and information elements. Inventory Control in PSS creates a more extensive set of uncertainties that the automotive industry needs to manage due to the enhanced scope and complexity of the product and service offering. There is a limited diffusion of new business models, especially by the automotive industry, and in particular in managing Inventory Control of raw material. To deal with this difficulty, this paper aims: firstly, suggests a generic model using IDEFØ for systematic and comprehensive analyses of how PSS Inventory Control characteristics in raw material integrate. Finally, this paper proposes the Inventory of raw material in automotive industry characteristics to make it possible to better understand the dynamics of scope and complexity of the product and service offering.
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Integrating comprehensive industrial raw material delivery planning and product-service system Inventory Control
Penerbit UMP, 2020Co-Authors: Norhamiza Hamzah, Siti Zubaidah IsmailAbstract:Product Service Systems (PSS) are integrated product and service offerings that provide superior customer value in industrial applications for planning, Inventory Control, delivery planning and a use jointly defined. Delivery planning is a particular challenge in providing personal security services. A good delivery planning is can minimize problem from great complexity subject to various constraints within a large solution space. Organizations offering PSS services or industrial services suffer from decision support to put in place robust capacity planning strategies in highly dynamic and uncertain environments. This paper presents a simulation-based approach to capacity planning. The goal of this project to identify potential routes of integration between two factors deliveries planning and PSS Inventory Control that could improve the delivery performance based on the raw material industry. Emphasis is placed on capacity planning for PSS Inventory Control and delivery planning. By using IDEFØ (Integration Definition for Function) generic modelling and Delmia Quest simulation software in this research able to achieve the time required. IDEFØ includes a well-tested language and a comprehensive system modelling technique. Meanwhile, Delmia Quest software will provide real time simulation for production process and generated report for actual operational situation. After a few general considerations on robust capacity planning for the Control and delivery of technical support Inventory using scenario simulations,the main elements of the agent-based simulation method are presented. The most important parameters given by company A, the Control parameters and the performance indicators are discussed and the scenario planning process based on the simulation is described. This research improves the productivity rate by increasing the flexibility in time to respond towards customer needs and improve delivery performance
