Data-Driven Lean Warehousing And Hybrid Simulation To Improve Perfect Order Rate In Medical Supply SMEs

Carlos Daza-Llanos; Said Rojas-Lavado; Marcos Fernando Ruiz-Ruiz; Juan Carlos Quiroz-Flores

doi:10.15488/21025

Data-Driven Lean Warehousing And Hybrid Simulation To Improve Perfect Order Rate In Medical Supply SMEs

Carlos Daza-Llanos
, Said Rojas-Lavado
, Marcos Fernando Ruiz-Ruiz
, Juan Carlos Quiroz-Flores

Research output: Contribution to journal › Conference article › peer-review

Abstract

Medical supply SMEs in emerging markets face persistent challenges in warehouse efficiency, inventory accuracy, and service reliability, as noted in prior logistics research. This study addresses these constraints by targeting the low Perfect Order Rate (POR) of a Peruvian medical supply importer, affected by inventory discrepancies, picking congestion, and documentation errors. A data-driven Lean Warehousing model was developed, integrating 5S, ABC-based slotting, cycle counting, and poka-yoke mechanisms, and validated through a hybrid method combining a six-week pilot implementation with discrete-event simulation in Arena and FlexSim. Results show improvements in On-Time Delivery from 91.35% to 94.15%, Defect-Free Products from 95.12% to 98.89%, and Process Cycle Efficiency from 5% to 37%, raising the projected POR from 82.51% to 88.30%. These findings highlight the operational and socioeconomic relevance of Lean– Digital practices for SMEs and encourage further exploration of data-driven enhancements in regulated supply chains.

Original language	American English
Pages (from-to)	664-677
Number of pages	14
Journal	Proceedings of the Conference on Production Systems and Logistics
Volume	1
DOIs	https://doi.org/10.15488/21025
State	Indexed - 2026
Externally published	Yes
Event	8th Conference on Production Systems and Logistics, CPSL 2026 - Hybrid, Porto, Portugal Duration: 14 Apr 2026 → 17 Apr 2026

Bibliographical note

Publisher Copyright:
© 2026, Publishing in cooperation with TIB - Leibniz Information Centre for Science and Technology University Library. All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Discrete-Event Simulation
Lean Warehousing
Medical Supply Chains
Operational Reliability
Perfect Order Rate

Access to Document

10.15488/21025

Cite this

@article{154a83efa5af49a8b56edff18345cd88,

title = "Data-Driven Lean Warehousing And Hybrid Simulation To Improve Perfect Order Rate In Medical Supply SMEs",

abstract = "Medical supply SMEs in emerging markets face persistent challenges in warehouse efficiency, inventory accuracy, and service reliability, as noted in prior logistics research. This study addresses these constraints by targeting the low Perfect Order Rate (POR) of a Peruvian medical supply importer, affected by inventory discrepancies, picking congestion, and documentation errors. A data-driven Lean Warehousing model was developed, integrating 5S, ABC-based slotting, cycle counting, and poka-yoke mechanisms, and validated through a hybrid method combining a six-week pilot implementation with discrete-event simulation in Arena and FlexSim. Results show improvements in On-Time Delivery from 91.35\% to 94.15\%, Defect-Free Products from 95.12\% to 98.89\%, and Process Cycle Efficiency from 5\% to 37\%, raising the projected POR from 82.51\% to 88.30\%. These findings highlight the operational and socioeconomic relevance of Lean– Digital practices for SMEs and encourage further exploration of data-driven enhancements in regulated supply chains.",

keywords = "Discrete-Event Simulation, Lean Warehousing, Medical Supply Chains, Operational Reliability, Perfect Order Rate",

author = "Carlos Daza-Llanos and Said Rojas-Lavado and Ruiz-Ruiz, \{Marcos Fernando\} and Quiroz-Flores, \{Juan Carlos\}",

note = "Publisher Copyright: {\textcopyright} 2026, Publishing in cooperation with TIB - Leibniz Information Centre for Science and Technology University Library. All rights reserved.; 8th Conference on Production Systems and Logistics, CPSL 2026 ; Conference date: 14-04-2026 Through 17-04-2026",

year = "2026",

doi = "10.15488/21025",

language = "American English",

volume = "1",

pages = "664--677",

journal = "Proceedings of the Conference on Production Systems and Logistics",

issn = "2701-6277",

publisher = "Publish-Ing in cooperation with TIB - Leibniz Information Centre for Science and Technology University Library",

}

TY - JOUR

T1 - Data-Driven Lean Warehousing And Hybrid Simulation To Improve Perfect Order Rate In Medical Supply SMEs

AU - Daza-Llanos, Carlos

AU - Rojas-Lavado, Said

AU - Ruiz-Ruiz, Marcos Fernando

AU - Quiroz-Flores, Juan Carlos

PY - 2026

Y1 - 2026

N2 - Medical supply SMEs in emerging markets face persistent challenges in warehouse efficiency, inventory accuracy, and service reliability, as noted in prior logistics research. This study addresses these constraints by targeting the low Perfect Order Rate (POR) of a Peruvian medical supply importer, affected by inventory discrepancies, picking congestion, and documentation errors. A data-driven Lean Warehousing model was developed, integrating 5S, ABC-based slotting, cycle counting, and poka-yoke mechanisms, and validated through a hybrid method combining a six-week pilot implementation with discrete-event simulation in Arena and FlexSim. Results show improvements in On-Time Delivery from 91.35% to 94.15%, Defect-Free Products from 95.12% to 98.89%, and Process Cycle Efficiency from 5% to 37%, raising the projected POR from 82.51% to 88.30%. These findings highlight the operational and socioeconomic relevance of Lean– Digital practices for SMEs and encourage further exploration of data-driven enhancements in regulated supply chains.

AB - Medical supply SMEs in emerging markets face persistent challenges in warehouse efficiency, inventory accuracy, and service reliability, as noted in prior logistics research. This study addresses these constraints by targeting the low Perfect Order Rate (POR) of a Peruvian medical supply importer, affected by inventory discrepancies, picking congestion, and documentation errors. A data-driven Lean Warehousing model was developed, integrating 5S, ABC-based slotting, cycle counting, and poka-yoke mechanisms, and validated through a hybrid method combining a six-week pilot implementation with discrete-event simulation in Arena and FlexSim. Results show improvements in On-Time Delivery from 91.35% to 94.15%, Defect-Free Products from 95.12% to 98.89%, and Process Cycle Efficiency from 5% to 37%, raising the projected POR from 82.51% to 88.30%. These findings highlight the operational and socioeconomic relevance of Lean– Digital practices for SMEs and encourage further exploration of data-driven enhancements in regulated supply chains.

KW - Discrete-Event Simulation

KW - Lean Warehousing

KW - Medical Supply Chains

KW - Operational Reliability

KW - Perfect Order Rate

UR - https://www.scopus.com/pages/publications/105039966643

U2 - 10.15488/21025

DO - 10.15488/21025

M3 - Conference article

AN - SCOPUS:105039966643

SN - 2701-6277

VL - 1

SP - 664

EP - 677

JO - Proceedings of the Conference on Production Systems and Logistics

JF - Proceedings of the Conference on Production Systems and Logistics

T2 - 8th Conference on Production Systems and Logistics, CPSL 2026

Y2 - 14 April 2026 through 17 April 2026

ER -

Data-Driven Lean Warehousing And Hybrid Simulation To Improve Perfect Order Rate In Medical Supply SMEs

Abstract

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this