Abstract:
The way in which a manufacturing system is designed is a crucial determinant of its
ability to meet the current competitive challenges. The existing literature and research
findings draw attention to the importance of addressing human factors in the design of
the manufacturing systems to face these challenges. However, the evidence gathered
from the literature clearly illustrates that organisations are not fully incorporating
human factors (macro- and micro-ergonomics) in the design of manufacturing systems.
In addition, the current system design practices tend to relegate ergonomics evaluation
to post-design, leaving ergonomists little opportunity to make significant and important
changes.
This thesis details a study which investigates the role of human factors in
manufacturing systems design and how it can be integrated into automated
manufacturing decision-making. Focus is given to the area of manufacturing
automation selection within workstation and cell design. The aim of this research is to
support manufacturing systems designers to better incorporate human factors in
manufacturing systems design.
A research programme has been designed to fulfil this aim. It consisted of three phases:
industrial survey, decision support tool formulation, and practical evaluation. The first
phase involved conducting interviews with leading manufacturing organisations in the
United Kingdom to determine the work practice in industry and the need for'
improvements. The second phase comprised the design and development of the
decision support tool in a workbook and software application. The final phase was the
evaluation of the tool in collaboration with industry.
Overall the outcome of this research was a novel structured approach that deploys both
the Quality Function Deployment and Failure Mode and Effect Analysis methods to
incorporate human factors alongside technical, organisational, and economical factors
in the decision-making process of manufacturing systems design, thereby allowing the
consideration of human factors at the feasibility study stage.