Fractal characterization of an after-sales spare parts supply chain in telecom industry

Data series generated by complex systems exhibit fluctuations on a wide range of time scales, which often follow a scaling relation over several orders of magnitude. Such scaling laws allow for a characterization of the data and the generating complex system by fractal scaling exponents, which can serve as characteristic fingerprints of the systems in comparisons with other systems and models. In this article was developed a fractal characterization of the data series generated by the closed loop supply chain that supports the availability of spare parts in Telecom industry since this complex system displays fluctuations in its processes caused by endogenous and exogenous variables that create a difficulty for matching the recovery process with the demand process.