Assembly Complexity Index (ACI): A Framework to Evaluate Assembly Process for Validating a Modular Robotic Design

Abstract

The assembly of equipment necessitates varying degrees of expertise, with complexity often escalating alongside technological advancements. While automation has reduced the workload in manufacturing and assembly lines, repair and maintenance still require a significant user skillset. This research focused on developing a modular robotic system with straightforward assembly and disassembly, requiring minimal robotics expertise from end users. A modular robotic system offers benefits such as shorter repair times leading to reduced downtimes on a factory shop floor, options for task-agnostic reconfiguration and deployment, and potential reductions in initial investment costs.To validate this hypothesis, a study was conducted with twelve participants with differing expertise in tools, hardware, and construction. Direct evaluation of personal and workplace attributes such as workload, task complexity, prior expertise and learning is often indiscernible and non-comparable. Thus, it was essential to establish a tangible workflow to evaluate and monitor the design's effectiveness and any modifications' impact on assembly ease. The study employed the Task Complexity Index (TCI) and NASA Task Load Index (TLX) adapted to measure task complexity and user workload. Both TCI and TLX have been used independently in various studies and a correlation between the two was identified. Combining data on task complexity and workload provided a comprehensive evaluation of the assembly process.Results indicated a marked improvement in the Assembly Complexity Index (ACI) during the second phase of experiments due to participant learning and a lower time (p = 0.026) required for completion of a much more complicated task demanding a higher workload (p = 0.014). This research aims to establish a framework for identifying an Assembly Complexity Index (ACI) using these the subjective workload and complexity assessment tools. The study considered factors such as the number of components, operations, and tools required. In addition, it acknowledged that factors like the availability of resources, component size and weight, operation complexity, and tool availability also impact the overall assembly complexity.

Keywords: Assembly Complexity Index, modular robotic system, assembly process

DOI: 10.54941/ahfe1005643