Manufacturing

Participating core and specialty programs: Center for Maritime Safety and Health Studies, Center for Occupational Robotics Research, National Center for Productive Aging and Work, and Safe●Skilled●Ready Workforce.

Safety and health professionals, employers, labor organizations, standard setting bodies, and robotics manufacturers use NIOSH information to prevent injuries related to human-machine interaction among manufacturing workers.

NOTE: Goals in bold in the table below are priorities for extramural research.

  Health Outcome Research Focus Worker Population* Research Type
A Fatal and non-fatal injuries Contacts with traditional machines Many manufacturing workers (especially those using assembly lines and conveyor belts), vulnerable workers, workers with non-standard work arrangements Intervention Translation
B Fatal and non-fatal injuries Emerging technologies (e.g., robotics, advanced manufacturing) Workers who interact with emerging manufacturing technologies Basic/etiologic

Intervention

C Fatal and non-fatal injuries Codes and other methods needed to identify robot-related injuries Workers who interact with emerging manufacturing technologies Surveillance research

* See definitions of worker populations

Activity Goal 6.5.1 (Basic/Etiologic Research): Conduct basic/etiologic research to better understand the relationship between emerging automation technologies (such as collaborative robots) and injuries (or injury reduction) among manufacturing workers.

Activity Goal 6.5.2 (Intervention Research): Conduct studies to develop and assess the effectiveness of interventions to prevent machine-related injuries among manufacturing workers.

Activity Goal 6.5.3 (Translation Research): Conduct translation research to understand barriers and aids to implementing effective interventions to prevent injuries from contact with traditional machines among manufacturing workers.

Activity Goal 6.5.4 (Surveillance Research): Conduct surveillance research to develop new methods to identify robot-related injuries among manufacturing workers.

Burden

In 2015, among over 15 million U.S. manufacturing workers, traumatic injury incidents led to 353 fatalities and approximately 425,700 non-fatal injuries, of which 122,610 involved missed work days [BLS 2016a,b,c]. One of the leading causes of fatal and non-fatal injuries was interaction with machines. The highest risk machines were: material and personnel handling machinery (e.g., conveyors and cranes); and metal, woodworking, and special material machinery. In addition to traditional machinery-related injuries, rapid advances in automation technologies (e.g., fixed robots, collaborative and mobile robots, and exoskeletons) have introduced additional, less understood sources of workplace hazards in manufacturing workplaces. Despite limited occupational surveillance data, 61 robot-related workplace fatalities were reported between 1992 and 2015 [Division of Safety Research 2017]. The robotics industry has predicted a worldwide increase in adoption of industrial robots and they estimated 1.4 million new robot installations in factories worldwide [IFR 2016]. Manufacturing workplaces adopting emerging technologies may expose workers, particularly vulnerable workers or those with non-standard work arrangements, to higher risks of injury or death associated with unfamiliarity of emerging technologies or safety practices. For instance, in 2016, both an auto parts supplier and a staffing agency were fined for failing to follow established safety practices in the death of a 20-year-old temporary worker involving a robot-related incident [OSHA 2016].

Need

To reduce the national burden related to incidents involving traditional machines in the manufacturing industry, continued research is needed on intervention and dissemination strategies to promote safe machine control and maintenance procedures, and on translating effective evidence-based interventions into workplace practice. Research efforts also are needed on tracking and preventing injuries and fatalities among 1) vulnerable workers or workers in non-standard work arrangements; and 2) worker populations who utilize or interact with machinery for material handling (e.g., conveyors) and processing (e.g., metal or woodworking machines). Rapid growth in the use of robotics and other emerging manufacturing technologies are likely to introduce new risks or exacerbate existing risks to workers due to potential unforeseen hazards, unanticipated human-robot interaction consequences, and lack of experience with new automation machines in varied work settings. There is a need to expand U.S. occupational injury surveillance capabilities to better identify, monitor, and quantify the burden of fatal and non-fatal incidents involving robots (e.g., development of new source or event codes). Scarce robotics safety research exists and has not specifically addressed the safety of new types of robots (such as collaborative and mobile robots) in work environments. Systematic studies are needed on the impacts of personal, environmental, and task-related risk factors on worker injuries associated with robots as well as evidence-based interventions for robotics safety.

BLS [2016a]. TABLE A-4. Fatal occupational injuries by primary and secondary source of injury for all fatal injuries and by major private industry 1 sector, all United States, 2015. In: Census of Fatal Occupational Injuries, 2015. Washington, DC: U.S. Department of Labor, Bureau of Labor Statistics, https://www.bls.gov/iif/oshcfoi1.htm#2015external icon.

BLS [2016b]. Chart 4. Distribution of nonfatal occupational injuries and illnesses by private industry sector, 2015. In: 2015 Survey of Occupational Injuries & Illnesses Summary Estimates Charts Package. Washington, DC: U.S. Department of Labor, Bureau of Labor Statistics, https://www.bls.gov/iif/oshwc/osh/os/osch0057.pdfpdf iconexternal icon.

BLS [2016c]. TABLE R65. Number and percent distribution of nonfatal occupational injuries and illnesses involving days away from work by industry and number of days away from work, and median number of days away from work, private industry, 2015. In: Case and Demographic Characteristics for Work-related Injuries and Illnesses Involving Days Away From Work. Washington, DC: U.S. Department of Labor, Bureau of Labor Statistics, https://www.bls.gov/iif/oshcdnew2015.htm#Resource_Table_categories-2015external icon.

Division of Safety Research [2017]. Robot-related workplace fatality analyses: Census of Fatal Occupational Injuries Research File (provided to NIOSH by Bureau of Labor Statistics). Morgantown, WV: Division of Safety Research. Unpublished.

IFR [2016]. Executive summary world robotics 2016 industrial robots. Frankfurt, Germany: International Federation of Robotics, https://ifr.org/img/uploads/Executive_Summary_WR_Industrial_Robots_20161.pdf.external icon

OSHA [2016]. Region 4: Alabama auto parts supplier to Kia and Hyundai, staffing agencies face $2.5M in fines after robot fatally crashes young bride-to-be. News release, December 14, https://www.osha.gov/news/newsreleases/region4/12142016external icon.

Page last reviewed: April 24, 2018