Using imperfect advance demand information in lost-sales inventory systems with the option of returning inventory

Abstract

KEYWORDSValue of information; imperfect advance demand information; returning excess inventory to upstream; lost-sales; inventory ABSTRACT Motivated by real-life applications, we consider an inventory system where it is possible to collect information about the quantity and timing of future demand in advance. However, this Advance Demand Information (ADI) is imperfect as (i) it may turn out to be false; (ii) a time interval is provided for the demand occurrences rather than its exact time; and (iii) there are still customer demand occurrences for which ADI cannot be provided. To make best use of imperfect information and integrate it with inventory supply decisions, we allow for returning excess stock built up due to imperfections to the upstream supplier and we propose a lost-sales inventory model with a general representation of imperfect ADI. A partial characterization of the optimal ordering and return policy is provided. Through an extensive numerical study, we investigate the value of ADI and factors that affect that value. We show that using imperfect ADI can yield substantial savings, the amount of savings being sensitive to the quality of information; the benefit of the ADI increases considerably if the excess stock can be returned. We apply our model to a spare parts case. The value of imperfect ADI turns out to be significant. . His research is focused on spare parts management, production-inventory systems, maintenance and availability management of capital goods, and the effect of design decisions on the total cost of ownership of capital goods. Much of his research is based on a close collaboration with, for example, ASML, Dutch Railways, Philips, and the Royal Airforce. He is associate editor of Manufacturing and Service Operations Management, OR Spectrum, and Flexible Services and Manufacturing. Rommert Dekker is a professor of operations research, quantitative logistics, and IT at the Erasmus School of Economics. He currently leads an industrysponsored research program on service logistics. Professor Dekker began his career working at Shell Research. During his 7 years at the company he published over 100 papers on topics including reverse logistics, service logistics, inventory control, maintenance optimization, container logistics, and transport optimization. He was also co-founder of the well-known network for reverse logistics REVLOG.

Spare parts inventory control based on maintenance planning

“…In contrast, some other approaches improve forecast accuracy at the expense of increasing the difficulty, the effort and the operational cost to predict demand, e.g. investing in a condition monitoring system (Topan et al, 2018) (see also Driessen et al, 2010). As we are only indirectly concerned with component degradation, we do not need any data or information on the degradation process.…”

“…In particular, while our method needs more data than typical time-series methods, we need considerably less data and information than approaches based on the degradation process (e.g. Deshpande et al, 2006;Wang and Syntetos, 2011) or on system monitoring systems Topan et al (2018); Lin et al (2017); Poppe et al (2017).…”

Numerical study of inventory management under various maintenance policies

“…Whereas Hariharan and Zipkin [12] consider perfect ADI, it may also be imperfect. For example, Topan et al [29] consider three types of imperfectness: The demand lead time may be stochastic, a demand that is preceded by ADI may not materialise, and a demand may materialise that is not preceded by ADI. Topan et al [29] give the setting of spare parts inventory control and condition monitoring as one example where their model applies.…”

“…For example, Topan et al [29] consider three types of imperfectness: The demand lead time may be stochastic, a demand that is preceded by ADI may not materialise, and a demand may materialise that is not preceded by ADI. Topan et al [29] give the setting of spare parts inventory control and condition monitoring as one example where their model applies. However, they do not explicitly model the degradation behavior of the critical components to derive ADI.…”

A survey of maintenance and service logistics management: Classification and research agenda from a maritime sector perspective

“…Similarly, Louit et al [82] present a model directed to the determination of the ordering decision for a spare part when the component in operation is subject to a condition monitoring program. Other related works incorporating condition monitoring information into spare parts inventory decisions can be found in [83,84,85,86].…”