NIST - National Institute of Standards and Technology

04/30/2026 | Press release | Archived content

A Semi-Markov Chain approach to temporally quantify critical materials across multiple product life cycles: Hard Disk Drives

Published
April 30, 2026

Author(s)

Nehika Mathur, Yong Han Kim, Ritbik Kumar, JW Sutherland

Abstract

The development of suitable data infrastructure that identifies, tracks and quantifies potentially recoverable critical materials (CMs) secondary sources is necessary to plan for long-term CM supply security. The developed Semi-Markov Process (SMP) model temporally quantifies and characterizes individual material streams in Hard Disk Drives (HDDs). The model addresses gaps in current literature by taking a disaggregated approach to tracking individual materials in complex products subject to different end of use (EoU) pathways and integrates product lifecycle 'sojourn' times to compute retained material quantities. The SMP shows promise as a fundamental approach to developing reinforcement learning systems to optimize long-term objectives.
Proceedings Title
CIRP Annals
Conference Dates
August 23-29, 2026
Conference Location
Turin, IT
Conference Title
CIRP General Assembly
Pub Type
Conferences

Keywords

Manufacturing, Modelling, Semi-Markov approach

Citation

Mathur, N. , Kim, Y. , Kumar, R. and Sutherland, J. (2026), A Semi-Markov Chain approach to temporally quantify critical materials across multiple product life cycles: Hard Disk Drives, CIRP Annals, Turin, IT, [online], https://doi.org/10.1016/j.cirp.2026.04.101, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=961402 (Accessed May 2, 2026)
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