Demand forecasting and inventory control: A simulation study on automotive spare parts

Rego, José Roberto do; Mesquita, Marco Aurélio de

doi:10.1016/j.ijpe.2014.11.009

Cited by 75 publications

(29 citation statements)

References 37 publications

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“…They also demonstrate how to extend supply chain model with demand stationary to obtain optimal safety stock placement, particularly in short distribution products by simulation. Rego and Mesquita () do a large‐scale simulation study on spare parts demand forecasting and inventory control to select best policies within each stock‐keeping unit (SKU) category. Chu et al.…”

Section: Literature Reviewmentioning

confidence: 99%

System dynamics simulation‐based model for coordination of a three‐level spare parts supply chain

Zhao

Chang

et al. 2019

Int Trans Operational Res

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In some spare parts distribution systems for consumption goods, a portion of consumers’ demand is met by inventories in maintenance outlets, while the remaining portion is satisfied with emergency orders from the supplier, which can enhance customers’ satisfaction but cause added order‐processing costs and transportation costs. Faced with the trade‐off between the supplier's and outlet's profits, it is highly crucial to design and coordinate a supply chain in a way that determines to what extent each level should hold inventories by considering classification of spare parts. Therefore, in this paper, a system dynamics approach is used to design a three‐level supply chain simulation model consisting of one business unit, one distribution center, and one maintenance outlet. The business unit and distribution center belong to one company, so we consider them as one supplier. Therefore, we focus on the coordination between the distribution center and the maintenance outlet. The objective is to propose a contract to enhance these two parties’ profits. Through numerical analysis, we provide a contract with which the spare parts in class A are differentiated in their normal and emergency procurement prices and the spare parts in class B and class C have a prescribed customer service level. Using this type of contract, both distribution center's and maintenance outlet's profits can be enhanced, and the management process can be simplified.

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Section: Literature Reviewmentioning

confidence: 99%

System dynamics simulation‐based model for coordination of a three‐level spare parts supply chain

Zhao

Chang

et al. 2019

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

“…The occurrences of backorder result in extra costs related to urgent ordering and transporting; both raise the fixed cost of backorders. Here, the fixed backorder costs are established as doubled the fixed regular production cost (Rego and Mesquita, 2015). All these cost-related parameters are converted to dollars using 1 euro equals 1.07 US dollar (rate obtained on Jan. 22, 2017), and the calculated values are listed in Table 1.…”

Section: Data Sourcesmentioning

confidence: 99%

Shop floor lot-sizing and scheduling with a two-stage stochastic programming model considering uncertain demand and workforce efficiency

2017

Computers & Industrial Engineering

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Efficient and flexible production planning is necessary for the manufacturing industry to stay competitive in today's global market. Shop floor lot-sizing and scheduling is one of the most challenging and rewarding subjects for the management. In this study, a two-stage stochastic programming model is proposed to solve a single-machine, multi-product shop floor lot-sizing and scheduling problem. Two sources of uncertainties are considered simultaneously: product demand from the market, and workforce efficiency, which is the major contribution of this study. The workforce efficiency affects the system productivity, and we propose different distributions to model its uncertainty with insufficient information.The model aims to determine optimal lot sizes and the production sequence that minimizes expected total system costs over the planning horizon, including setup, inventory, and production costs. A case study is performed on a supply chain producing brake equipment in the automotive industry. The numerical results illustrate the usefulness of the stochastic model under volatile environment, and the solution quality is analyzed. AbstractEfficient and flexible production planning is necessary for the manufacturing industry to stay competitive in today's global market. Shop floor lot-sizing and scheduling is one of the most challenging and rewarding subjects for the management. In this study, a two-stage stochastic programming model is proposed to solve a single-machine, multi-product shop floor lot-sizing and scheduling problem. Two sources of uncertainties are considered simultaneously: product demand from the market, and workforce efficiency, which is the major contribution of this study.The workforce efficiency affects the system productivity, and we propose different distributions to model its uncertainty with insufficient information. The model aims to determine optimal lot sizes and the production sequence that minimizes expected total system costs over the planning horizon, including setup, inventory, and production costs. A case study is performed on a supply chain producing brake equipment in the automotive industry. The numerical results illustrate the usefulness of the stochastic model under volatile environment, and the solution quality is analyzed. Highlights• A two-stage stochastic programming model for lot-sizing and scheduling is proposed.• Two uncertain factors, product demand and workforce efficiency are considered.• The numerical results of optimal production sequence and quantities are illustrated.• The significance of stochastic model is presented, and solution quality is analyzed.

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“…Leifker et al (2014) presented two approaches for dealing with the problem of extending maintenance or supply contracts for spare parts of discontinued products: one includes the use of a continuous-time dynamic program and the other makes use of a two-stage stochastic algorithm. Rego and Mesquita (2015) presented a case study on spare parts inventory management, comparing several methods using different forecasting techniques and inventory management policies by simulating with field data (10 032 spare parts references); results of the simulations allowed the recommendation of best…”

Section: Literature Reviewmentioning

confidence: 99%

Discontinued Products - An Empirical Study of Service Parts Management

Ferreira

Arantes

Silva

2017

Proceedings of the 6th International Conference on Operations Research and Enterprise Systems

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The procurement and inventory management of service parts for discontinued products has often been overlooked by companies, resulting in several problems such as stock outs, rush orders or obsolete stocks. Accordingly, the main aim of this work is to develop a methodology to deal with these issues following product discontinuation. To this end, an empirical study -based on action research principles -was carried out in a producer of household appliances, which is bound by law to provide service parts for its products for a period of 15 years after they have been discontinued. The work was developed in three stages: characterization of the company situation; definition of a procedure to eliminate obsolete stocks; and definition of a procedure to manage active service parts. The resulting methodology and respective procedures are presented and the results obtained with the implementation are discussed.

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Demand forecasting and inventory control: A simulation study on automotive spare parts

Cited by 75 publications

References 37 publications

System dynamics simulation‐based model for coordination of a three‐level spare parts supply chain

System dynamics simulation‐based model for coordination of a three‐level spare parts supply chain

Shop floor lot-sizing and scheduling with a two-stage stochastic programming model considering uncertain demand and workforce efficiency

Discontinued Products - An Empirical Study of Service Parts Management

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