5. Conclusions and future researches
This research presents an innovative real-time system for the
integrated evaluation of manual task analysis (time and methods)
and ergonomics objective assessment of the postures taken by the
workers during the execution of operations.
Its potential, compared to previous researches presented in literature
(Vignais et al., 2013), is mainly based on the using of a fullbody
motion capture system, composed by a wearable suit with 17
inertial sensors, integrated with a set of real-time data analysis
tools that permits its application in a wide range of industrial sector
and operations, such as warehousing, productions and assembly
systems, manual workstations and others.
In this paper, the application of this system in warehouse environments
is illustrated due to their complexity. In fact, the manual
handling activities, typical of warehousing systems, interest the
movements of the entire body of the workers and they require
the simultaneous use of different types of ergonomics evaluations
methods in order to complete their assessment.
Moreover, the ergonomics analysis has been integrated with a
developed specific data analysis tool for the real-time collection
of tasks time and the methods used to perform them. A specific
module helps the users select the most suitable ergonomics methods
and sets a series of threshold parameters to underline when
the chosen method fails and needs a post processing phase. It also
introduces several additional factors settable by the users to consider
these limitations inside the real-time evaluations.
This integration permits to make the analysis more accurate
and helps the decision makers to achieve the final scope using a
win–win approach optimizing productivity and ergonomics
aspects (Battini et al. 2009).
As demonstrated by the literature (Vignais et al., 2013), it is
important to give a certain feedback to the users from this kind
of system. In this research, all the ergonomics evaluation tools
are characterized by colored scaling indices available in real-time,
in portable screens for the workers or in a virtual 3D environment
for managers and engineers.
The application in two real case studies has demonstrated the
validity of the systems reaching important results in productivity
increases and ergonomics improvements both in the re-design of
the warehouses and in the training of human in the execution of
the most critical manual tasks.
Future researches will be focused on the integration of the system
with several light sensors for the electromyography (EMG),
able to collect the data about the real muscles activity and then
the real applied strength during the handling of loads. More
improvements will be necessary on the tool for the time and
method task analysis, developing an automatic procedure to collect
this information with advanced technologies as voice command
and control.
Acknowledgments
The authors would like to thank the support and funding from
Fondazione Cariverona. This research was a part of ‘‘Progetto Tre
Poli 2’’ and ‘‘Progetto Tre Poli 4’’.