More grip on inventory control through improved forecasting: A comparative study at three companies

Wingerden, E. van; Basten, Rob; Dekker, Rommert; Rustenburg, W.D.

doi:10.1016/j.ijpe.2014.08.018

Cited by 25 publications

(10 citation statements)

References 19 publications

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“…repeatedly to account for considerable empirical inventory forecasting improvements (Eaves and Kingsman, 2004;Gutierrez et al, 2008;van Wingerden et al, 2014;Nikolopoulos et al, 2016) and, at the time of writing, it constitutes the benchmark against which other (new) proposed methodologies in the area of intermittent demand forecasting are assessed.…”

Section: Methods For Intermittent Demands and Count Data 271 Parametr...mentioning

confidence: 99%

Forecasting: theory and practice

Petropoulos,

Apiletti,

Assimakopoulos

et al. 2020

Preprint

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Forecasting has always been in the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The lack of a free-lunch theorem implies the need for a diverse set of forecasting methods to tackle an array of applications. This unique article provides a non-systematic review of the theory and the practice of forecasting. We offer a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts, including operations, economics, finance, energy, environment, and social good. We do not claim that this review is an exhaustive list of methods and applications. The list was compiled based on the expertise and interests of the authors. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of the forecasting theory and practice.

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Section: Methods For Intermittent Demands and Count Data 271 Parametr...mentioning

confidence: 99%

Forecasting: theory and practice

Petropoulos,

Apiletti,

Assimakopoulos

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Spare parts demand can either be forecasted based on historical data, advance demand information or a combination of both (Driessen et al (2010)). Since our ADI-based method represents an alternative to time-series forecasting methods for intermittent spare parts demand, we first briefly review literature those latter methods (for a more detailed review see van Wingerden et al, 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Non-parametric methods construct empirical distributions of demand, see e.g. Willemain et al (2004), Porras and Dekker (2008), van Wingerden et al (2014), and Zhu et al (2017.…”

Section: Literature Reviewmentioning

confidence: 99%

Spare parts inventory control based on maintenance planning

Zhu

Jaarsveld

Dekker

2020

Reliability Engineering & System Safety

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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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“…In reality, firms frequently manage large portfolios of spare parts that often consist of tens of thousands of individual stock keeping units (SKUs) (Guvenir & Erel, 1998;van Wingerden, Basten, Dekker, & Rustenburg, 2014). This portfolio complexity makes the detailed analysis of each part infeasible for obtaining systematic insights into the overall AM potential.…”

Section: Introductionmentioning

confidence: 99%

Assessing the potential of additive manufacturing for the provision of spare parts

Heinen

Hoberg

2019

J of Ops Management

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Spare parts are a particularly interesting application for switching production from traditional manufacturing (TM) to additive manufacturing (AM). Research assessing AM has primarily addressed cost models centering on the production process or the operations management of separate spare parts. By combining case study, modeling, and design science elements, we adopt a holistic perspective and develop a design to examine the systematic leverage of AM in spare parts operations. Contextually grounded in problems faced by a leading material handling equipment manufacturer that is challenged by common characteristics of after‐sales operations, we engage with practice to propose a portfolio level analysis examining the switchover share from TM to AM. Using a data set of 53,457 spare parts over 9 years, we find that up to 8% of stock keeping units (SKUs) and 2% of total units supplied could be produced using AM, even if unit production costs are four times those of TM. This result is driven by low demand, high fixed costs, and minimum order quantities in TM. Finally, we present the evaluation by the case company's management and highlight five areas of opportunity and challenge.

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More grip on inventory control through improved forecasting: A comparative study at three companies

Cited by 25 publications

References 19 publications

Forecasting: theory and practice

Forecasting: theory and practice

Spare parts inventory control based on maintenance planning

Assessing the potential of additive manufacturing for the provision of spare parts

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