Multi-Objective Optimization of an Assembly Layout Using Nature-Inspired Algorithms and a Digital Human Modeling Tool.

OCCUPATIONAL APPLICATIONSIn the context of Industry 5.0, our study advances manufacturing factory layout planning by integrating multi-objective optimization with nature-inspired algorithms and a digital human modeling tool. This approach aims to overcome the limitations of traditional planning methods, which often rely on engineers' expertise and inputs from various functions in a company, leading to slow processes and risk of human errors. By focusing the multi-objective optimization on three primary targets, our methodology promotes objective and efficient layout planning, simultaneously considering worker well-being and system performance efficiency. Illustrated through a pedal car assembly station layout case, we demonstrate how layout planning can transition into a transparent, cross-disciplinary, and automated activity. This methodology provides multi-objective decision support, showcasing a significant step forward in manufacturing factory layout design practices.

Rationale: Integrating multi-objective optimization in manufacturing layout planning addresses simultaneous considerations of productivity, worker well-being, and space efficiency, moving beyond traditional, expert-reliant methods that often overlook critical design aspects. Leveraging nature-inspired algorithms and a digital human modeling tool, this study advances a holistic, automated design process in line with Industry 5.0. Purpose: This research demonstrates an innovative approach to manufacturing layout optimization that simultaneously considers worker well-being and system performance. Utilizing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) alongside a Digital Human Modeling (DHM) tool, the study proposes layouts that equally prioritize ergonomic factors, productivity, and area utilization. Methods: Through a pedal car assembly station case, the study illustrates the transition of layout planning into a transparent, cross-disciplinary, and automated process. This method offers objective decision support, balancing diverse objectives concurrently. Results: The optimization results obtained from the NSGA-II and PSO algorithms represent feasible non-dominated solutions of layout proposals, with the NSGA-II algorithm finding a solution superior in all objectives compared to the expert engineer-designed start solution for the layout. This demonstrates the presented method's capacity to refine layout planning practices significantly. Conclusions: The study validates the effectiveness of combining multi-objective optimization with digital human modeling in manufacturing layout planning, aligning with Industry 5.0's emphasis on human-centric processes. It proves that operational efficiency and worker well-being can be simultaneously considered and presents future potential manufacturing design advancements. This approach underscores the necessity of multi-objective consideration for optimal layout achievement, marking a progressive step in meeting modern manufacturing's complex demands.

Carotid artery atherosclerosis among 65-year-old Swedish men - a population-based screening study.

OBJECTIVE: There are limited contemporary epidemiological data on the prevalence of carotid atherosclerosis in the general population. The aim was to determine the prevalence of and risk factors associated with carotid artery atherosclerosis among 65-year-old men. METHODS: This was a population-based screening study. All 65-year-old men in the County of Uppsala, Sweden, who attended screening for abdominal aortic aneurysm (AAA) 2007-2009, were invited for duplex scanning of the carotid arteries. RESULTS: Of 4801 men invited, 4657 (97%) accepted. Carotid plaques (>2 × 6 mm) were observed in 1169 (25%) men, 94 (2.0%) had carotid stenoses (50-99%), and 15 (0.3%) had occluded carotid arteries. In a multivariate logistic regression model, smoking (OR 1.7, 95% CI 1.5-1.9), hypertension (1.5, 95% CI 1.3-1.7), diabetes mellitus (1.2, 95% CI 1.0-1.5), and coronary artery disease (1.5, 95% CI 1.3-1.8) were associated with prevalence of carotid atherosclerosis (plaque and/or stenosis). The use of antiplatelet agents and statins in participants with a carotid plaque was 20% and 29%, respectively. The corresponding figures in participants with a stenosis were 42% and 41%. CONCLUSIONS: This study offers contemporary data on the prevalence of carotid atherosclerosis in a population-based cohort of 65-year-old men. Most of those at risk had no other clinical manifestation of atherosclerosis, and therefore had no secondary prevention.

Digital test assembly of truck parts with the IMMA-tool--an illustrative case.

Several digital human modelling (DHM) tools have been developed for simulation and visualisation of human postures and motions. In 2010 the DHM tool IMMA (Intelligently Moving Manikins) was introduced as a DHM tool that uses advanced path planning techniques to generate collision free and biomechanically acceptable motions for digital human models (as well as parts) in complex assembly situations. The aim of the paper is to illustrate how the IPS/IMMA tool is used at Scania CV AB in a digital test assembly process, and to compare the tool with other DHM tools on the market. The illustrated case of using the IMMA tool, here combined with the path planner tool IPS, indicates that the tool is promising. The major strengths of the tool are its user friendly interface, the motion generation algorithms, the batch simulation of manikins and the ergonomics assessment methods that consider time.