Automated Loading and Unloading Operations: A Systematic Review

Övrigt konferensbidrag, 2023

Purpose
Material handling has witnessed changes with automations occurring in the transport sector. The increasing implementation of autonomous trucks lays questions on the loading and unloading operations that the conventional truck driver used to perform. Loading and unloading operations interface warehouses and transportation. Conventionally characterised by the manual operating nature causing inefficiencies and discontinuities, automated loading and unloading (ALUL) benefit by enhancing workflows, improves performance, and reduces losses. Despite these benefits, research on ALUL is minimal. This article i) details focus of ALUL systems in research, ii) indicates adopted evaluation indicators and iii) highlights key enablers and impediments witnessed during implementation.

Methodology
Developments are assessed by carrying out a systematic literature review including published literature, technical articles etc. Review is initiated by identifying appropriate keywords, coupled with Boolean operators, to retrieve literature from scientific databases.

Findings
Research on LUL reveal a classified research focus on perception systems, manipulators, and general solution type. Operating time was identified to be a commonly evaluated performance parameter despite research revealing diverse parameters. The review highlights i) variable loading and unloading methods with changing good types. ii) Complexities in identifying and manipulating goods. iii) Frequent human involvement, and iv) high implementation costs and associated infrastructural modifications to influence implementation despite many enablers supporting the implementation of this technology. Despite the above issues, commercial solutions with varied degrees of automation are available and are listed in this article.

Practical implications
ALUL systems are described comprehensively providing a detailed representation of existing knowledge regarding ALUL, making selection easier for interested industries and guiding them through the transformation process.

Originality
Research aids in determining function-specific systems enabling a detailed understanding of ALUL systems.