Examining the relationship between human factors related quality risk factors and work related musculoskeletal disorder risk factors in manufacturing.

This study addresses the relationship between human factors (HF) related quality deficits in manufacturing and work-related musculoskeletal disorder (WMSD) risk factors in production staff. A recent systematic review identified 60 HF-related quality risk factors (QRFs) in manufacturing related to product, process and workstation design stages. We investigate the extent to which these identified QRFs are also WMSD risk factors.

Examining the fatigue-quality relationship in manufacturing.

A recent systematic review identified 73 empirical studies that linked human factors (HF) with manufacturing quality. Human fatigue was noted as a frequent (n = 26) issue in the HF-quality relationship - a finding that warrants closer examination. We extend this review by investigating the relationship between fatigue and manufacturing quality by identifying how fatigue has been conceptualized and measured, and we attempted to quantify their relationship.

Production quality and human factors engineering: A systematic review and theoretical framework.

The purpose of this paper is to systematically examine available empirical evidence on the impact of human factors (HF) in the design and management of manufacturing operations on system quality performance. A systematic review was conducted to map the linkages between the human-system fit in the design of operations systems (OS) with production quality. A total of 73 empirical studies were identified linking HF to OS performance in manufacturing.

Classifying work rate from heart rate measurements using an adaptive neuro-fuzzy inference system.

In a new approach based on adaptive neuro-fuzzy inference systems (ANFIS), field heart rate (HR) measurements were used to classify work rate into four categories: very light, light, moderate, and heavy. Inter-participant variability (physiological and physical differences) was considered. Twenty-eight participants performed Meyer and Flenghi's step-test and a maximal treadmill test, during which heart rate and oxygen consumption (VO2) were measured.

Removing the thermal component from heart rate provides an accurate VO2 estimation in forest work.

Heart rate (HR) was monitored continuously in 41 forest workers performing brushcutting or tree planting work. 10-min seated rest periods were imposed during the workday to estimate the HR thermal component (ΔHRT) per Vogt et al. (1970, 1973).

Adaptive neuro-fuzzy inference systems with k-fold cross-validation for energy expenditure predictions based on heart rate.

This paper presents a new model based on adaptive neuro-fuzzy inference systems (ANFIS) to predict oxygen consumption (V˙O2) from easily measured variables. The ANFIS prediction model consists of three ANFIS modules for estimating the Flex-HR parameters. Each module was developed based on clustering a training set of data samples relevant to that module and then the ANFIS prediction model was tested against a validation data set.

Estimating oxygen consumption from heart rate using adaptive neuro-fuzzy inference system and analytical approaches.

In new approaches based on adaptive neuro-fuzzy systems (ANFIS) and analytical method, heart rate (HR) measurements were used to estimate oxygen consumption (VO2). Thirty-five participants performed Meyer and Flenghi's step-test (eight of which performed regeneration release work), during which heart rate and oxygen consumption were measured. Two individualized models and a General ANFIS model that does not require individual calibration were developed.