Assembly line balancing is well-known in mass production system but this problem is non-deterministicpolynomial-time(NP)-hard, even for a simple straight line. Although several heuristic methods havebeen introduced and used by researchers, knowing and using an effective method in solving these typesof problems in less computational time have a considerable place in the area of line balancing problem.In this research, a new heuristic approach, known as critical node method (CNM), was introduced andtested by solving several test problems available in the literature so as to solve straight assembly lines.Finally, the obtained results are compared with 9 other heuristic rules in some performance measures.Thus, it is concluded that the proposed CNM is better than the rest in all the measures.
Tailing sand is the residue mineral from tin extraction that contains between 94% and 99.5% silica, which can be used as moulding sand. It is found in abundance in the Kinta Valley in the state of Perak, Malaysia. Adequate water content and clay in moulding sand are important factors for better strength and
casting quality of products made from tailing sand. Samples of tailing sand were investigated according
to the American Foundrymen Society (AFS) standard. Cylindrical test pieces of Ø50 mm×50 mm in height from various sand-water ratios were compacted by applying three ramming blows of 6666g each using a Ridsdale-Dietert metric standard rammer. The specimens were tested for green compression strength using a Ridsdale-Dietert universal sand strength machine. Before the tests were conducted, moisture content of the tailing sand was measured using a moisture analyser. A mixture bonded with 8% clay possesses higher green compression strength compared to samples bonded with 4% clay. The results also show that in order to achieve maximum green compression strength, the optimum allowable moisture content for mixtures bonded with 8% clay is ranged between 3.75 and 6.5% and for mixtures bonded with 4% clay is 3-5.5%.
This work was carried out with the aim to optimise the tool path by simulating the removal of material in a finite element environment which is controlled by a genetic algorithm (GA). To simulate the physical removal of material during machining, a finite element model was designed to represent a thin walled workpiece. The target was to develop models which mimic the actual cutting process using the finite element method (FEM), to validate the developed tool path strategy algorithm with the actual machining process and to programme the developed algorithm into the software. The workpiece was to be modelled using the CAD (ABAQUS CAE) software to create a basic geometry co-ordinate system which could then be used to create the finite element method and necessary requirement by ABAQUS, such as the boundary condition, the material type, and the element type.