Optimisation of injection moulding process parameters using taguchi and desirability function

A large amount of plastic parts presently produced, makes it imperative to search for an alternative for recycling or making use of these materials, since they are not biodegradable. Injection moulding, one of the most prevalent plastics processing technique facilities these recycled materials to be substituted for virgin material in producing plastic parts. However, the deterioration in mechanical properties of the part made of recycled plastic is the major drawback that limits the usage of recycled plastic. One of the foremost causes is variation in processing parameters. It is of critical importance to effectively control all the influencing processing parameters during the manufacturing process by an appropriate optimisation method. Therefore, the main goal of conducting this research is to primarily investigate the effects of injection moulding parameters on the mechanical properties of plastic part made of recycled plastic and to optimise the identified process parameters. In order to achieve the goal, the significant process parameters is identified with proper research on previous studies. Then, a preliminary experiment is conducted by using the selected significant process parameters from previous researches to identify the process parameters value for the principal experiment. In this research, the principal experiment is conducted using recycled polypropylene by adopting L27 OA. The mechanical properties of the specimens are measured in term of tensile strength and flexural modulus respectively. From the experimental analysis and results, it is shown that the most significant processing parameters affecting the tensile strength are melt temperature, injection time and holding time. The most effective process parameters on flexural modulus are melt temperature, holding time and injection pressure. The optimum process parameters is 180°C of melt temperature, 55MPa injection pressure, 30mm/s injection speed, 8s injection time, 20MPa holding pressure, 3s holding time and 25s cooling time. These parameters have optimise the part quality to 199 kgf/cm2 of tensile strength and can result in flexural modulus of 10005 kgf/cm2. This proves that recycled materials are potentially substituted for virgin material. Therefore, the demand for natural resources and energy consumption due to virgin material production can be reduced and environmental problems due to plastics disposal can be diminished as well. Further in future, more responses on mechanical properties of material such as impact strength and compressive strength should be investigated to obtain even better properties of recycled PP

Mathematical modeling and optimization of laser cutting process using artificial intelligence methods

Laser cutting is one of more attractive non-conventional machining technologies which is being increasingly used in industry due to its efficiency. Laser cutting is based on the use of highly concentrated light energy, obtained by laser irradiation, for materials processing by melting or evaporation. Since it is desirable to remove the molten and evaporated material from the cutting zone as soon as possible, laser cutting is performed with a coaxial jet of an assist gas. From the technological point of view, laser cutting is a very complex process of interactions between the laser beam, assist gas and workpiece material, whose performances are influenced by a number of factors. Insufficient knowledge of the process as well as a lack of reliable and practical data about influential factors leads to underutilization of laser cutting technology with respect to the possibilities that it provides, but also to the fact that the cut quality does not satisfy users. In order to ensure achievement of the required cut quality, cost reduction and increase of productivity, it is necessary to quantify the relationships between process factors and process performances through the mathematical modeling. On the basis of developed relationships it is possible to perform a detailed analysis of the influence of process factors on process performances, identify near optimal factor values and control the process of laser cutting so as to improve the efficiency and cut quality. This paper presents the results of experimental studies carried out with the objective of modeling and optimization of laser cutting process i.e. assessment of process factors effects and application of obtained results for control of laser cutting process in order to increase the cut quality obtained in CO2 laser nitrogen cutting of stainless steel. Based on data from experimental studies carried out by using Taguchi’s orthogonal array, mathematical models relating cut quality characteristics and process factors such as laser power, cutting speed, assist gas pressure and focus position were developed. Mathematical modeling has been carried out using artificial neural networks, whereby the training of artificial neural networks was conducted by using Levenberg-Marquardt algorithm. On the basis of developed mathematical relationship between the cut quality characteristics and process factors, single and multi objective optimization of laser cutting was enabled. For the purpose of optimization two approaches were applied. The first approach is based on the integration of mathematical models created by artificial neural networks and meta-heuristic optimization methods. The second approach, which is aimed at determining the near optimal values of process factors in a way that the laser cutting process is robust to different causes of variation, was based on the application of Taguchi’s optimization method. In order to validate optimization solutions that were previously determined using different optimization methods, solve multi-criteria optimization problems and “off-line” control of laser cutting process, in the dissertation developed software prototype was presented. The modeling and optimization methodology presented in the dissertation and its implementation through the development of application software for industrial use, can raise planning of laser cutting process to a higher level and make process more economical and productive