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Improving the diagnostic process for robotic lawnmowers: After-sales efficiency benefits from an Experimental Diagnostic Tool
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
2022 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

An Experimental Diagnostic Tool (EDT) was developed to increase the efficiency of the diagnostic process of robotic lawn mowers which resulted in a 200% productivity increase when utilizing a proposed formula specifically designed for the diagnostic process of robotic lawn mowers. The tool does not only extract and process data from the robotic lawn mower wirelessly but also highlights potential faults through an intuitive and easy-to-use interface - empowering servicing technicians who perform the diagnostics to perform at a higher level.

Further, efficiency is a term widely used in various domains and contexts when measuring the capacity of a process. Proposed general definitions of the term have been given by previous authors and researchers. However, due to a lack of universally set definitions which fit all situations, the term remains ambiguous when improvements to a specific process are needed. The unclear definition is due to the variations within each process affecting the definition of both the term itself, but also similar terms fundamentally connected to it such as productivity, performance, and profitability. The following report contains an investigation of exploratory research where the understanding of efficiency and its related concepts are analyzed within the after-sales diagnostic process of robotic lawn mowers.

Place, publisher, year, edition, pages
2022. , p. 58
Keywords [en]
After-sales, Diagnostics, Efficiency, Embedded Systems, ESP32, Process, Productivity, Raspberry Pi, Robotic Lawn Mower, System Development
National Category
Embedded Systems Computer Systems Robotics and automation Computer Engineering
Identifiers
URN: urn:nbn:se:hj:diva-58399ISRN: JU-JTH-DTA-1-20220177OAI: oai:DiVA.org:hj-58399DiVA, id: diva2:1692412
External cooperation
Globe Technologies
Subject / course
JTH, Computer Engineering
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Examiners
Available from: 2022-09-05 Created: 2022-09-01 Last updated: 2025-10-13Bibliographically approved

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CiteExportLink to record
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