Engineering Economy Pioneers

Thuesen, Gerald J.

doi:10.18260/1-2--8344

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, it inherits the detectability characteristic D i associated with the C i failure cause. Based on the detectability of H i and the distance between the considered location and the hazard cell, its impact I H i ðx r , y r Þ can be defined as shown in Equation (1), which is derived from the relationship between these parameters.…”

Section: Fmea-based Mathematical Model For Rfmentioning

confidence: 99%

“…This demand stems from various factors, including socioeconomic backgrounds and the busy day‐to‐day lifestyles of individuals, which make manual cleaning difficult. [ 1 ] Additionally, concerns regarding labor health have arisen due to the repetitive nature of cleaning tasks. [ 2 ] The high demand for floor‐cleaning robots, driven by the aforementioned reasons, has led to continuous research aimed at improving their performance.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

FMEA‐Based Coverage‐Path‐Planning Strategy for Floor‐Cleaning Robots

Wijegunawardana,

Samarakoon,

Muthugala

et al. 2023

Advanced Intelligent Systems

View full text Add to dashboard Cite

Floor‐cleaning robots play a crucial role in both industrial and domestic spaces. However, these robots often face challenges due to hazardous components in their environment, which can cause them to fail and prevent them from performing at their best. This situation necessitates continuous research in the field of floor‐cleaning robots. However, most of these efforts focus on improving the robots’ perception capabilities by incorporating additional sensors. Nevertheless, incorporating more sensors is an expensive solution for most cleaning robots. Alternatively, in this research, the feasibility of introducing a safe path on a predefined hazard map is explored. The proposed method aims to trade‐off between area coverage and the safety of the cleaning robot. Herein, the failure mode and effect analysis (FMEA) method is introduced as a tool to classify the hazards and implement a safety‐ensured coverage path‐planning process. In this approach, the risk factor defined for a point in the environment serves as the key parameter to assess the safety of the algorithm's suggested path. To validate and evaluate the proposed method, this article utilizes the hTetro mobile robot. In the experimental results, it is demonstrated that the proposed method can reduce high‐risk movements of the robot compared to existing methods.

show abstract

Section: Fmea-based Mathematical Model For Rfmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%