Abstract: Nowadays the market for industrial companies is becoming more and more globalized and highly competitive, forcing them to shorten the duration of the manufacturing system development time in order to reduce the time to market. In order to achieve this target, the hierarchical systems used in previous manufacturing systems are not enough because they cannot deal effectively with unexpected situations. To achieve flexibility in manufacturing systems, the concept of an Autonomous Decentralized Flexible Manufacturing System (AD-FMS) is useful. In this paper, we introduce a hypothetical reasoning based algorithm called the Algorithm for Future Anticipative Reasoning (AFAR) which is able to decide on a conceivable next action of an Automated Guided Vehicle (AGV) that works autonomously in the AD-FMS.
Abstract: To create a solution for a specific problem in machine
learning, the solution is constructed from the data or by use a search
method. Genetic algorithms are a model of machine learning that can
be used to find nearest optimal solution. While the great advantage of
genetic algorithms is the fact that they find a solution through
evolution, this is also the biggest disadvantage. Evolution is inductive,
in nature life does not evolve towards a good solution but it evolves
away from bad circumstances. This can cause a species to evolve into
an evolutionary dead end. In order to reduce the effect of this
disadvantage we propose a new a learning tool (criteria) which can be
included into the genetic algorithms generations to compare the
previous population and the current population and then decide
whether is effective to continue with the previous population or the
current population, the proposed learning tool is called as Keeping
Efficient Population (KEP). We applied a GA based on KEP to the
production line layout problem, as a result KEP keep the evaluation
direction increases and stops any deviation in the evaluation.
Abstract: Lean, which was initially developed by Toyota, is
widely implemented in other companies to improve competitiveness.
This research is an attempt to identify the adoption of lean in the
production system of Malaysian car manufacturer, Proton using case
study approach. To gain the in-depth information regarding lean
implementation, an activity on the assembly line called Set Parts
Supply (SPS) was studied. The result indicates that by using lean
principles, tools and techniques in the implementation of SPS enabled
to achieve the goals on safety, quality, cost, delivery and morale. The
implementation increased the size of the workspace, improved the
quality of assembly and the delivery of parts supply, reduced the
manpower, achieved cost savings on electricity and also increased the
motivation of manpower in respect of attendance at work. A
framework of SPS implementation is suggested as a contribution for
lean practices in production system.