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Forward cycle time distributions for returnable transport items

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Abstract

Forward cycle time (FCT) distributions for returnable transport items (RTIs) are developed for periods where incomplete data is available, and these distributions are utilized to create an estimate of future container returns. Such forecasts are important inputs to inventory control models for RTI and production models in remanufacturing, and the objective of this paper is to implement a method that incorporates appropriate trend and seasonality. A FCT distribution provides the probability that a container filled in a specific period (week or month) will return in a specified time. The method used to estimate FCT distributions employs an adaptive exponential smoothing method that accounts for seasonality to forecast the parameters of a lognormal distribution for FCT in future periods. This distribution is used to calculate discrete FCT probabilities, estimate container returns, and calculate the estimated mean and standard deviation of cycle time for periods with incomplete data. The estimation process continues through the future periods for which an prediction of container returns is needed. Validation of the method is provided by comparing estimates created using historical data with periods where the actual FCT distributions are known. The resulting cycle time distributions are highly accurate, allowing companies employing RTI in practice to use the method to predict the number of containers that will be available to accommodate future production.

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Acknowledgements

The authors thank two anonymous reviewers for comments and suggestions which improved the paper significantly.

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  1. Department of Economics and Business, Virginia Military Institute, Lexington, VA, 24450, USA

    Barry R. Cobb

  2. Department of Marketing, Missouri State University, Springfield, MO, 65897, USA

    Linda Li

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Correspondence to Barry R. Cobb.

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Cobb, B.R., Li, L. Forward cycle time distributions for returnable transport items. Jnl Remanufactur 12, 125–151 (2022). https://doi.org/10.1007/s13243-021-00105-2

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