{'fraction_non_alphanumeric': 0.02028397565922921, 'fraction_numerical': 0.001352265043948614, 'mean_word_length': 5.166666666666667, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Digital Human Modeling of Obese & Aging Workers in Automotive Manufacturing

Digital human modeling has become an important tool in several industries, particularly in manufacturing. However, when these models are used, their use is often limited to “50th percentile” male and female models. The dimension is typically not explicitly named, but is inferred to be stature. The U.S. population is growing in size and age, which increases the range of abilities and limitations of the workforce. The objective of this study was to improve the understanding of how to better create and utilize digital human models that reflects a worker population that is diverse in stature, weight, and age. Previous research has yet to adequately incorporate this range of human population diversity into human digital modeling used in industrial modeling applications. Through use of CATIA Delmia (Dassault Systémes), a popular digital human modeling software tool, this research investigates how modeling software can be utilized in a number of ways to depict variations in worker size and age, for planning manual assembly and other work tasks. Validation of the models was assessed through filming, questionnaires, and interviews of workers in an automobile assembly plant. This research was able to show the limitations of current applications of human modeling with respect to the age, weight, and stature of a diverse worker population and provides suggestions for how to improve modeling.