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Liquid Handling · 2022

Establishment of low-cost laboratory automation processes using AutoIt and 4-axis robots

In most small laboratories, many processes are not yet automated because existing laboratory automation solutions are usually expensive and inflexible to use. Examples of this are autosamplers that are only compatible with one specific laboratory instrument or larger liquid handling stations that are expensive and usually self-contained.

Performance the paper reports

1 of 5
  1. Motion0.05 mmMotion accuracy: reported
  2. Volume—Volumetric accuracy: not reported
  3. Viability—Cell viability: not reported
  4. Unattended—Unattended operation: not reported
  5. Standard—Standard compliance: not reported
  • Motion / positional accuracy0.05 mm
    It has higher repeatability than the Dobot Magician (0.05 mm versus 0.2 mm), but it costs almost twice as much (approx- imately 3K € versus 1.5K €) [31] .

How hard this is to adopt

2.9 of 5, higher is easier

Each score is shown against the range the other 59 builds actually occupy, because no criterion uses the full 1–5 scale. These describe how reproducible the build is, not how good the science is.

  • Resolution

    3/1–5

    Smallest demonstrated dispense 20 uL in multi-dispense steps with 100 uL single pipetting; accuracy is supplied by the commercial BRAND electronic pipette, not the robot.

  • Throughput

    3/2–5

    Single-channel pipette handling one fluid at a time with the tip rinsed rather than ejected; completes a 96-well plate and a 24-sample AAS autosampler run unattended.

  • Parts sourcing

    2/2–4

    Requires specialized or custom-built components.

  • Skill needed

    4/2–4

    Build/operation described as low-skill or basic assembly.

  • Facilities needed

    3/2–4

    Equipment requirements not explicit; assigned moderate default.

  • Documentation

    3/2–5

    Some open documentation or files are available.

  • Validation effort

    4/2–4

    Multiple volumes and concentrations, three liquids and three processes statistically benchmarked against a trained technician (Mann-Whitney, Wilcoxon, Levene) with carryover controls; no drift study.

  • Cycle time

    1/1–4

    Explicitly slower than manual by factors of 3.5 (pipetting), 3.0 (inoculation) and 1.6 (AAS), i.e. more than twice as slow overall.

2 further criteria are recorded but not shown
  • Application Level — scored 4 (75% of records share one value), so it cannot separate one build from another.
  • Build Time (scored for only 6 of 60 records), so it cannot separate one build from another.

Both remain in the published dataset.

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Publication data

Matched by doi · retrieved 2026-07-21

Abstract

In most small laboratories, many processes are not yet automated because existing laboratory automation solutions are usually expensive and inflexible to use. Examples of this are autosamplers that are only compatible with one specific laboratory instrument or larger liquid handling stations that are expensive and usually self-contained. A flexible and inexpensive way to automate laboratory processes would be to automate existing laboratory equipment with the help of suitable robotic arms. In this study, we investigate the feasibility of such a strategy based on a low-cost 4-axis robot and freely available software. We used the scripting language AutoIt that automates any Windows-based instrument control software. Using these tools, we automated three fundamentally different laboratory processes: a pipetting process, a use as an autosampler for an atomic absorption spectroscopy instrument, and a more complex process involving the inoculation of bacterial cultures. We also integrated a conventional webcam for 2D barcode recognition. Compared to a trained professional who performed all experiments manually, all setups showed no significant differences in accuracy and precision. In summary, the tested system consisting of a 4-axis robot and freely available software is suitable for flexible automation and has potential for even more complex laboratory processes. Limitations such as a lack of collaboration and speed will be addressed in follow-up studies. The system thus represents a well-suited flexible laboratory automation system for both research and teaching purposes.

Bibliographic details

Published
2022-07-10
Journal/source
SLAS Technology
Publisher
Elsevier BV
DOI
10.1016/j.slast.2022.07.001
Type
journal-article
Language
en
Volume / issue
27 / 5
Pages
312-318
ISSN
2472-6303

Access and metrics

Open access
Yes
OA status
diamond
License
cc-by-nc-nd
Version
publishedVersion
Cited by
22
References
24
Retracted
No

Authors and affiliations

  1. Nicole RuppAlbstadt-Sigmaringen University
  2. Katrin PeschkeAlbstadt-Sigmaringen University
  3. Michael KöpplLead Discovery Center (Germany)
  4. David DrissnerAlbstadt-Sigmaringen University
  5. Thole ZüchnerCorresponding authorAlbstadt-Sigmaringen University

Topics and keywords

Biosensors and Analytical DetectionImage Processing Techniques and ApplicationsElectrowetting and Microfluidic TechnologiesLaboratory automationAutomationScripting languageSoftwareRobotComputer scienceProcess (computing)BarcodeInstrumentation (computer programming)Instrument controlProcess automation systemSimulation
Perspective and practical signals

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