The Optimization of Total Laboratory Automation by Simulation of a Pull-Strategy

Taho Yang, Teng Kuan Wang, Vincent C. Li, Chia Lo Su

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Laboratory results are essential for physicians to diagnose medical conditions. Because of the critical role of medical laboratories, an increasing number of hospitals use total laboratory automation (TLA) to improve laboratory performance. Although the benefits of TLA are well documented, systems occasionally become congested, particularly when hospitals face peak demand. This study optimizes TLA operations. Firstly, value stream mapping (VSM) is used to identify the non-value-added time. Subsequently, batch processing control and parallel scheduling rules are devised and a pull mechanism that comprises a constant work-in-process (CONWIP) is proposed. Simulation optimization is then used to optimize the design parameters and to ensure a small inventory and a shorter average cycle time (CT). For empirical illustration, this approach is applied to a real case. The proposed methodology significantly improves the efficiency of laboratory work and leads to a reduction in patient waiting times and increased service level.

Original languageEnglish
Article number162
JournalJournal of Medical Systems
Volume39
Issue number1
DOIs
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Information Systems
  • Health Informatics
  • Health Information Management

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