scholarly journals Acquisition Pricing and Inventory Decisions on Dual-Source Spare-Part System with Final Production and Remanufacturing

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Yancong Zhou ◽  
Xudong Guo ◽  
Xiaochen Sun
Keyword(s):  
Optimal Policy ◽  
Durable Goods ◽  
Optimization Problem ◽  
Market Competition ◽  
Spare Part ◽  
Spare Parts ◽  
Stochastic Dynamic ◽  
Management Problem ◽  
Production Order ◽  
Acquisition Pricing

The life spans of durable goods are longer than their warranty periods. To satisfy the service demand of spare parts and keep the market competition advantage, enterprises have to maintain the longer inventory planning of spare parts. However, how to obtain a valid number of spare parts is difficult for those enterprises. In this paper, we consider a spare-part inventory problem, where the inventory can be replenished by two ways including the final production order and the remanufacturing way. Especially for the remanufacturing way, we consider the acquisition management problem of used products concerning an acquisition pricing decision. In a multiperiod setting, we formulate the problem into a dynamic optimization problem, where the system decisions include the final production order and acquisition price of used products at each period. By stochastic dynamic programming, we obtain the optimal policy of the acquisition pricing at each period and give the optimal policy structure of the optimization problem at the first period. Then, a recursion algorithm is designed to calculate the optimal decisions and the critical points in the policy. Finally, the numerical analyses show the effects of demand information and customer’s sensitive degree on the related decisions and the optimal cost.

A dynamic predictive maintenance model considering spare parts inventory based on hidden semi-Markov model

2012 ◽  
Vol 227 (9) ◽  
pp. 2090-2103 ◽  
Author(s):  
Qinming Liu ◽  
Ming Dong ◽  
Ying Peng
Keyword(s):  
Dynamic Programming ◽  
Markov Model ◽  
Transition Probabilities ◽  
Spare Part ◽  
Spare Parts ◽  
Stochastic Dynamic ◽  
Maintenance Strategies ◽  
Spare Parts Inventory ◽  
Optimal Maintenance ◽  
Maintenance Model

The maintenance strategies optimization can play a key role in the industrial systems, in particular to reduce the related risks and the maintenance costs, improve the availability, and the reliability. Spare part demands are usually generated by the need of maintenance. It is often dependent on the maintenance strategies, and a better practice is to deal with these problems simultaneously. This article presents a stochastic dynamic programming maintenance model considering multi-failure states and spare part inventory. First, a probabilistic maintenance model called hidden semi-Markov model with aging factor is used to classify the multi-failure states and obtain transition probabilities among multi-failure states. Then, spare parts inventory cost is integrated into the maintenance model for different failure states. Finally, a double-layer dynamic programming maintenance model is proposed to obtain the optimal spare parts inventory and the optimal maintenance strategy through which the minimum total cost can be achieved. A case study is used to demonstrate the implementation and potential applications of the proposed methods.

scholarly journals Evaluating the Readiness Level of Additively Manufactured Digital Spare Parts: An Industrial Perspective

2018 ◽  
Vol 8 (10) ◽  
pp. 1837 ◽  
Author(s):  
Niklas Kretzschmar ◽  
Sergei Chekurov ◽  
Mika Salmi ◽  
Jukka Tuomi
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Industry ◽  
Spare Part ◽  
Spare Parts ◽  
Survey Study ◽  
Lead Times ◽  
Supply Networks ◽  
Readiness Level ◽  
End Use ◽  
Technological Limitations

Additive manufacturing of digital spare parts offers promising new possibilities for companies to drastically shorten lead times and to omit storage costs. However, the concept of digital spare parts has not yet gained much footing in the manufacturing industry. This study aims to identify grounds for its selective rejection. Conducted from a corporate perspective, outlining a holistic supply chain network structure to visualize different digital spare part distribution scenarios, this survey study evaluates technical and economic additive manufacturing capabilities. Results are analyzed and discussed further by applying the Mann-Whitney test to examine the influence of the company size and the presence of 3D-printed end-use components within supply networks on gathered data. Machines’ limited build chamber volumes and the necessity of post-processing are considered as the main technical challenges of current additive manufacturing processes. Furthermore, it can be concluded that company sizes have a significant effect on perceived technological limitations. Overall, the results lead to the conclusion that the readiness level of the digital spare parts concept demands for further development.

scholarly journals Performance tradeoffs for spare parts supply chains with additive manufacturing capability servicing intermittent demand

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kyle C. McDermott ◽  
Ryan D. Winz ◽  
Thom J. Hodgson ◽  
Michael G. Kay ◽  
Russell E. King ◽  
...  
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Production Capacity ◽  
Spare Part ◽  
Spare Parts ◽  
Mixed Integer ◽  
Network Configuration ◽  
Intermittent Demand ◽  
Content Type ◽  
Demand Patterns

PurposeThe study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.Design/methodology/approachThis work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.FindingsThis research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.Research limitations/implicationsThis research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.Originality/valueThis research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

scholarly journals An Optimal Order Quantity Of Spare Parts To Minimize Total Inventory Cost Using Periodic Review Approach (R,s,s) Method In PT. XYZ Bandung

2017 ◽  
Vol 1 (02) ◽  
Author(s):  
Feviana Betsi Purba ◽  
Luciana Andrawina ◽  
Murni Dwi Astuti
Keyword(s):  
Spare Part ◽  
Spare Parts ◽  
Optimal Order ◽  
Periodic Review ◽  
Order Quantity ◽  
Inventory Cost ◽  
Inventory Policy ◽  
Total Saving ◽  
Manufacturing Company ◽  
Total Inventory

The availability of spare parts is very crucial thing for manufacturing company in order to support the continuity of production activities. PT XYZ is a manufacturing company which produces thread into fabric. In this case, inventory control of spare part is not properly managed. Inventory position of spare parts in warehouse is always more than inventory policy of the company itself or called overstock which causes total inventory cost is always high. Company only consider on the order fulfillment of spare parts to prevent downtime on the machine that increase performance of production. Hence, order quantity of spare parts is always excessive or not optimal. In this research, global inventory policy conducted in order to minimize total inventory cost is periodic review approach (R, s, S) method. This inventory policy will be calculated using power approximation and obtained total saving cost of holding cost by 31 % while total saving cost of order cost decreased by 7 %. Overall, total inventory cost minimized by 7 % or equal to Rp138.902.742.

scholarly journals Additive Manufacturing and Maritime Spare Parts: Benefits and Obstacles for the End-Users

2021 ◽  
Vol 9 (8) ◽  
pp. 895
Author(s):  
Evanthia Kostidi ◽  
Nikitas Nikitakos ◽  
Iosif Progoulakis
Keyword(s):  
Additive Manufacturing ◽  
New Technology ◽  
Spare Part ◽  
Spare Parts ◽  
Successful Implementation ◽  
Maritime Industry ◽  
End User ◽  
Space Reduction ◽  
Questionnaire Method ◽  
Industrial Context

3D printing or additive manufacturing (AM) (in the industrial context) is an innovative, as opposed to subtractive, technology, bringing new opportunities and benefits to the spare part supply chain (SPSC). The aim of this work is to capture the views of the stakeholders at the end of the chain, extruding factors that will benefit the end-user and the factors that are likely to be an obstacle, by employing the questionnaire method. Company objectives regarding spares (cost reductions, improvement of services, space reduction) have been prioritized differently by the stakeholders. The most important barriers according to the participants are the quality assurance of the spare parts made by the new technology followed by the know-how and skills of staff. Other views such as suitable parts are suggested. The practical value of this work, in addition to assessing the readiness of the industry, is that it provides guidance for the successful implementation of AM in the maritime industry.

Feeder Ship Size Optimization in Maritime Markets with Uncertainty

2021 ◽  
Vol 38 (03) ◽  
pp. 2040014
Author(s):  
Hongtao Hu ◽  
Jiao Mo ◽  
Lufei Huang
Keyword(s):  
Dynamic Programming ◽  
Stochastic Dynamic Programming ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Planning Horizon ◽  
Dynamic Programming Method ◽  
Size Optimization ◽  
Stochastic Dynamic ◽  
Shipping Company ◽  
Decision Behaviors

This paper considers the ship size optimization problem for a liner shipping company that provides feeder service between one hub port and one feeder port. In the maritime market with uncertainty, this problem becomes more challenging. This research first analyzes the decision behaviors of the shipping company. Then, a stochastic dynamic programming method is proposed to calculate the expected total volume of containers transported within the planning horizon. Using the calculated volumes as input parameters calculate the profit of each ship sizes and then determine the suitable ship size for the feeder route. Numerical experiments are performed to validate the effectiveness of the proposed method and the efficiency of the proposed algorithm.

Economic and Environmental Assessment of Spare Parts Production Using Additive Manufacturing

2019 ◽  
pp. 159-181
Author(s):  
Atanu Chaudhuri ◽  
Dennis Massarola
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Dynamic Simulation ◽  
Environmental Sustainability ◽  
Selective Laser Sintering ◽  
Spare Part ◽  
Spare Parts ◽  
Logistics System ◽  
Supply Chain Costs ◽  
System Dynamic Simulation

This chapter aims to investigate the potential economic and environmental sustainability outcomes of additive manufacturing (AM) for spare parts logistics. System dynamic simulation was conducted to analyze the sustainability of producing a spare part used in a railways subsystem using a particular additive manufacturing (AM) technology (i.e., selective laser sintering [SLS]) compared to producing it using injection molding. The results of the simulation showed that using SLS for the chosen part is superior to the conventional one in terms of total variable costs as well as for carbon footprint. Compared to the conventional supply chain, for the AM supply chain, the costs of the supplier reduces by 46%, that of the railways company reduces by 71%, while the overall supply chain costs reduce by 61.9%. The carbon emissions in the AM supply chain marginally reduces by 2.89% compared to the conventional supply chain.

Time-based responsive logistics for a maintenance service network

2019 ◽  
Vol 25 (4) ◽  
pp. 589-611 ◽  
Author(s):  
Ioannis Manikas ◽  
Balan Sundarakani ◽  
Vera Iakimenko
Keyword(s):  
Case Study Research ◽  
Spare Part ◽  
Service Level ◽  
Spare Parts ◽  
Retail Banking ◽  
Distribution Centers ◽  
Service Network ◽  
Content Type ◽  
Maintenance Service

PurposeThe purpose of this paper is to identify the main reasons for spare parts logistics failures and address logistics distribution design in order to achieve the desired level of after-sales maintenance service.Design/methodology/approachThis research is based on an empirical case study on a large corporation providing worldwide with retail banking hardware, software and services. The case study focuses on the automated teller machine (ATM) part of activities, with a focus on the spare parts distribution and after-sales service network in the Eastern Europe.FindingsThe proposed network solution of multiple distribution centers with short-cut distance saving approach will enable the case study company to redesign their spare part logistics architecture in order to achieve short response time. Research findings reveal possible spare parts delivery delays and thus the service-level agreement failures with clients in the case study company.Research limitations/implicationsThis research covers a particular supply chain environment and identified research gaps. It discusses a time-based responsive logistics problem and develops a conceptual framework that would help researchers to better understand logistics challenges of installed equipment maintenance and after-sales service.Originality/valueThis case study research shows the “big picture” of spare parts logistics challenges as vital part of installed equipment after-sales and maintenance service network, as well as emphasizes how the unique context of a market like Russian Federation can set-up a distribution network efficiently. Strategies applied to handle such service-level failures, reverse logistics aspects of repairable and non-repairable spare parts to such large ATM after-sales service network based on this longitudinal case offer value for similar scale companies.

scholarly journals Does Quality Matter? A Study on Customer Expectation in Motorcycle Repair Provider in Surabaya, Indonesia

2020 ◽  
Vol 76 ◽  
pp. 01006
Author(s):  
Dhyah Harjanti ◽  
Edbert Karlison Theodore ◽  
Shahzad Ali
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Relationship Quality ◽  
Service Providers ◽  
Positive Impact ◽  
Spare Part ◽  
Spare Parts ◽  
Repair Service ◽  
Fierce Competition ◽  
The Impact

Motorcycle has become a common vehicle in Indonesia due to its flexibility to drive around in various geographical terrain. The number of motorcycle purchases in Indonesia is increasing annually, along with the repair services and spare part selling. Abundant repair service providers create fierce competition among themselves, so many providers maintain their service quality in order to retain their customer. The aim of this research is to investigate the impact of service quality and relationship quality to customer satisfaction in motorcycle repair providers. This research is using the quantitative approach, in which the data are collected by questionnaires distributed to samples of populations. The population is the customers who have purchased repair services and spare parts for their motorcycle, and the number of samples is 100 respondents. The data are analyzed with a SmartPLS software, and the results show a positive significant impact from service quality to customer satisfaction, a positive significant impact from service quality to relationship quality, and a positive impact from relationship quality to customer satisfaction. Therefore, for the long term competitive advantage, motorcycle repair service providers have to consider their service quality and relationship quality to retain their customers.

scholarly journals Modeling Equipment Procurement Strategic Decisions Competing for Limited Available Budget under Redundant Accessory Cost

2015 ◽  
Vol 4 (2) ◽  
pp. 80
Author(s):  
C. O. Osueke ◽  
B. O. Akinnuli ◽  
O. O. Ojo
Keyword(s):  
Large Scale ◽  
Critical Factor ◽  
Spare Part ◽  
Spare Parts ◽  
Strategic Decisions ◽  
Manufacturing Company ◽  
To Come ◽  
Optimum Model ◽  
Procurement Strategies ◽  
Present Event

<p>The challenges that used to come up as a result of project failure have to do with improper planning. This is looking into future what can occur based on present event. In financing equipment or machinery, the capital in hand is a critical factor that determines equipment procurement strategies. There is need for an optimum model to control the available budget to be put in place in order to optimally allot the available budget to the machines, spare parts and miscellaneous costs under the redundant of accessory cost. This study identified the financial strategic decisions for machines, spare parts and miscellaneous costs, developed mathematical models for the identified strategic decisions, test and evaluate the performance of the developed models. In this study, three strategic decisions were considered (i.e., machines, spare parts and miscellaneous costs) and the optimum model to control the budget for machines, spare parts and miscellaneous costs are dealt with under the redundant accessory cost. This is because an existing manufacturing company or industry has high inventory of accessories which always aid the performance of machine in the industry. Therefore, it is necessary to optimally allot the available budget on the machine(s) to be procured, spare part to be stocked and miscellaneous cost. The amount allotted to machines, spare parts and miscellaneous while budgeting for year 2015 are in this ratio: Machines, ($5,263.83); Spare parts, ($27,723.09); Miscellaneous, ($4,366.03), this based on available small budget of N 6,350.000 of dollar value of US$1,079,500.00. This model is a strong decision tool for allocating available budget in the period of financial scarcity where equipment procurement for production needs must be carried out. This model is highly recommended to any manufacturing company, small, medium and large scale that equipment procurement affects their production in developed and developing countries.</p>

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