Automatic assessment of the ergonomic risk for manual manufacturing and assembly activities through optical motion capture technology

Abstract Safeguard the operator health is nowadays a hot topic for most of the companies whose production process relies on manual manufacturing and assembly activities. European legislations, national regulations and international standards force the companies to assess the risk of musculoskeletal disorders of operators while they are performing manual tasks. Furthermore, international corporates typically require their partners to adopt and implement particular indices and procedures to assess the ergonomic risks specific of their industrial sector. The expertise and time required by the ergonomic assessment activity compels the companies to huge financial, human and technological investments. An original Motion Analysis System (MAS) is developed to facilitate the evaluation of most of the ergonomic indices traditionally adopted by manufacturing firms. The MAS exploits a network of marker-less depth cameras to track and record the operator movements and postures during the performed tasks. The big volume of data provided by this motion capture technology is employed by the MAS to automatically and quantitatively assesses the risk of musculoskeletal disorders over the entire task duration and for each body part. The developed hardware/software architecture is tested and validated with a real industrial case study of a car manufacturer which adopts the European Assembly Worksheet (EAWS) to assess the ergonomic risk of its assembly line operators. The results suggest how the MAS is a powerful architecture compared to other motion capture solutions. Indeed, this technology accurately assesses the operator movements and his joint absolute position in the assembly station 3D layout. Finally, the MAS automatically and quantitatively fill out the different EAWS sections, traditionally evaluated through time- and resource-consuming activities

Evaluating the Prospective Benefits of Physical Demands Description (PDD) Data Created from Job Simulations

A physical demands description (PDD) is a document that results from the systematic procedure to quantify, and evaluate all of the physical and environmental demand components of all essential and non- essential tasks of a job. PDDs provide important information to individuals involved in the treatment of work-related musculoskeletal disorder (WMSD). The information contained within a PDD may provide insight into what may have led to a WMSD. Research has uncovered concerns with the current methods of development related to the quality and quantity of information contained in the PDD documents (Coffey, Vandergriendt, & Fischer, 2016). Missing or low quality information contained with a PDD document may have adverse effects on the return to work (RTW) process where they are typically used as a comparison vehicle against an injured workers functional abilities (S. Isernhagen, 2006). Recent advances in digital human modeling software (Ward, Stephens, & Cort, 2015) have provided users the ability to quickly generate PDDs from digital human model (DHM) simulations of entire jobs, referred in this work as the ePDD, for electronic PDD. This development provides the possibility to overcome some of the challenges with the current methods of PDD development, as a simulation of an entire job could minimize or eliminate the possibility for missing information in the PDD if all job tasks are modeled. The objective of this investigation was to gather user thoughts, opinions, and beliefs regarding PDD use in the RTW process, and to examine thoughts on the ePDD as a tool in RTW. Semi structured one-on-one interviews were conducted with nineteen (16) participants with professional experience facilitating the RTW of injured workers for longer than one (1) year professionally. Interviews were ninety-three minutes (93 ±29) in duration and were conducted in person or via telephone based on participant preference. Participants were provided with samples of both the traditionally developed PDDs and ePDDs prior to the interview and were asked to review the documents. Participants were asked to gather their thoughts on the use of PDD data in the RTW process and their thoughts on the novel method of PDD development via DMH. Field notes were taken, and audio of the interview was recorded and transcribed verbatim. Transcriptions were analyzed using QSR International NVivo 12 analysis software. Transcripts were thematically analyzed by two (2) researchers following the reflexive inductive thematic analysis process outlined by Braun and Clarke (Braun & Clarke, 2006). It was uncovered that participants believe PDDs are used primarily to serve as a comparison tool in the job match process. PDDs are used as a comparison tool to ensure a worker under typical circumstances can perform their entire preinjury duties, and to inform job modification efforts in attempts to minimize the amount of time an injured employee spends away from work. Participants also believed that PDDs or similar type documents are not consistently used in the RTW process and may be overlooked in a significant number of cases. Areas of improvement for PDDs include: improving quality of information contained within the documents, standardization of the information contained within the documents in order to increase ease of use, and attempting to align the information presented in PDDs with common information provided by healthcare providers to facilitate easy comparison. When it came to the ePDD, it was found to not be a suitable replacement for the PDDs used currently. Participants believed that the ePDD: contains a significant amount of information, were difficult to read overall, and contained information that would not be useful to professionals in the RTW process. The ePDD provides a video of the job being performed and both graphical and text presentation of relevant PDD information. It was believed that the ePDD might be harmful to the RTW process as some users may not be able to extract the required information and may become confused when using the ePDD. While the ePDD may not be a useful tool overall in RTW, there were benefits found with the ePDD, most notable the visual presentation of information. While the ePDD as a whole is believed to contain too much information and be difficult to read, the graphical nature of the presented information was believed to facilitate simple communication and potentially minimize issues gathering specific information from the document. Improvements to current PDD documents should be focused on addressing concerns related to what information the documents present, how the documents present that information, and how that information may or may not be used in current RTW practice. The ePDD is not a suitable replacement for current PDD documents in RTW, however could serve as a useful addition, providing visual information lacking in typical PDDs. Future work related to the use of PDDs in RTW should gather information from other groups relevant in RTW who may use or interact with PDDs, such as but not limited to health care practitioners, disability insurance professionals, worker advocates such as union representatives and workers who have been through the RTW process