Abstract: In this paper we propose a computer-aided solution
with Genetic Algorithms in order to reduce the drafting of reports:
FMEA analysis and Control Plan required in the manufacture of the
product launch and improved knowledge development teams for
future projects. The solution allows to the design team to introduce
data entry required to FMEA. The actual analysis is performed using
Genetic Algorithms to find optimum between RPN risk factor and
cost of production. A feature of Genetic Algorithms is that they are
used as a means of finding solutions for multi criteria optimization
problems. In our case, along with three specific FMEA risk factors is
considered and reduce production cost. Analysis tool will generate
final reports for all FMEA processes. The data obtained in FMEA
reports are automatically integrated with other entered parameters in
Control Plan. Implementation of the solution is in the form of an
application running in an intranet on two servers: one containing
analysis and plan generation engine and the other containing the
database where the initial parameters and results are stored. The
results can then be used as starting solutions in the synthesis of other
projects. The solution was applied to welding processes, laser cutting
and bending to manufacture chassis for buses. Advantages of the
solution are efficient elaboration of documents in the current project
by automatically generating reports FMEA and Control Plan using
multiple criteria optimization of production and build a solid
knowledge base for future projects. The solution which we propose is
a cheap alternative to other solutions on the market using Open
Source tools in implementation.
Abstract: The popularity of quality management system models
continues to grow despite the transitional crisis in 2008. Their
development is associated with demands of the new requirements for
entrepreneurs, such as risk analysis projects and more emphasis on
supervision of outsourced processes. In parallel, it is appropriate to
focus attention on the selection of companies aspiring to a quality
management system. This is particularly important in the automotive
supplier industry, where requirements transferred to the levels in the
supply chain should be clear, transparent and fairly satisfied. The
author has carried out a series of researches aimed at finding the
factors that allow for the effective implementation of the quality
management system in automotive companies. The research was
focused on four groups of companies: 1) manufacturing (parts and
assemblies for the purpose of sale or for vehicle manufacturers), 2)
service (repair and maintenance of the car) 3) services for the
transport of goods or people, 4) commercial (auto parts and vehicles).
The identified determinants were divided into two types of criteria:
internal and external, as well as hard and soft. The article presents the
hard – technical factors that an automotive company must meet in
order to achieve the goal of the quality management system
implementation.