Visual management and artificial intelligence integrated in a new fuzzy-based full body postural assessment. (September 2017)

• Record Type: Journal Article
• Authors: Savino, Matteo Mario; Battini, Daria; Riccio, Carlo
• Is Part Of: Computers & industrial engineering. Volume 111(2017)
• Page Start: 596
• Page End: 608
• Publication Date: 2017-09
• Subjects: Artificial intelligence -- Ergonomics -- Ergonomy -- Postural analysis -- Visual management -- Fuzzy logic -- Fuzzy sets -- Fuzzy inference engine; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.06.011
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We focus on ergo-level evaluation with a full body postural approach. We explore the use of Fuzzy logic for full body ergonomic assessment. We realize an extensive Knowledge Base for postural evaluation. The use or Fuzzy logic allows to make the data acquisition independent from the evaluation. Ergonomic assessment with Artificial Intelligence tools is able to avoid subjectivity during evaluation. Abstract: This study focuses on the problem of ergonomic evaluation for work tasks with a full-body postural approach. Although there has been much research in this area, including experimental investigations, there is still a need for objective and flexible approaches for the development of postural analysis. A new fuzzy-based full-body postural assessment tool is developed within a fuzzy inference engine (IE). Starting from an ergonomic map, the study develops a Fuzzy knowledge base system containing the main evaluation rules of the most relevant full-body evaluation checklists. The approach aims to give an integrated value of the ergonomic assessment for the postures investigated, indicating also the ergonomic incidence of each posture. The methodology is applied to an industrial case of a setup activity. A comparison is carried out with a standard integrated postural evaluation methods.