Papers by Keyword: Process Optimisation

Abstract: This paper describes a new approach for planning additive manufacturing (AM) technology. Based on the technological heredity between the stages of the process chain, an optimisation method is proposed that makes it possible to minimise manufacturing costs under consideration of the quality requirements.

Abstract: The paper presents results of FEA-based optimisation of the tool design of a clinching process with a closed single-part die. The studied materials are the bake-hardening steel CR240BH, 1.5 mm thick, on the punch side and the die-cast aluminium alloy AlSi10MnMg, 2.95 mm thick, on the die side. The optimisation was aimed at suppression of cracks that appear at the bottom of the clinch joint in AlSi10MnMg in the case of using conventional tool designs. By varying geometry parameters of the tools it was possible to reduce crack probability, though along with slightly worse, but still acceptable geometry parameters of the clinch joint.

Abstract: Process parameters optimisation has been identified as a potential approach to realise a greener injection moulding process. However, reduction in the process energy consumption does not necessarily imply a good part quality. An effective multi-response optimisation process can be demanding and often relies on extensive operational experience from human operators. Therefore, this research focuses on an attempt to develop a more user-friendly approach which could simultaneously deal with the requirements of energy efficiency and part quality. This research proposes a novel approach using a dynamic Shainin Design of Experiment (DOE) methodology to determine an optimal combination of process parameters used in the injection moulding process. The Shainin DOE method is adopted to pinpoint the most important factors on energy consumption and the targeted part quality whereas the ‘dynamic’ term refers to the signal-response system. The effectiveness of the proposed approach was illustrated by investigating the influence of various dominant parameters on the specific energy consumption (SEC) and the Charpy impact strength (CIS) of polypropylene (PP) material after being injection-moulded into impact test specimens. From the experimental results, barrel temperature was identified as the signal factor while mould temperature and cooling time were used as control factors in the full factorial experiments. Then, response function modelling (RFM) was built to characterise the signal-response relationship as a function of the control factors. Finally, RFM led to a trade-off solution where reducing part-to-part variation for CIS resulted in an increase of SEC. Therefore, the research outcomes have demonstrated that the proposed methodology can be practically applied at the factory shop floor to achieve different performance output targets specified by the customer or the manufacturer’s intent.

Abstract: Based on the structural entropy, this paper establishes a model for analyzing the degree of order of different structure of small or medium sized make-to-order stationery enterprise by using system limitation entropy and quality entropy. This quantificational method to evaluate the process optimization of production system is well validated.

Abstract: There were serious transverse corner cracks on continuous casting slab of automobile frame steel plate in Panzhihua Steel before, and study on the control of transverse corner cracks had been carried out. Some effective countermeasures are put forward, such as the optimization of ratio of heat flux density on narrow side and broad side of casting slab (RHFD) and mold powder, as well as the stabilization of casting speed and working condition of caster. Industrial test shows that the transverse corner cracks on continuous casting slab have been significantly reduced, and the lines and peeling defects on hot rolled sheet have been eliminated due to the transverse corner cracks.

Abstract: There are complicated correlations between process parameters and quality indicators in candy manufacturing. The objective of this work is to develop an optimization system of candy production process to improve final candy quality and to increase production efficiency. The study is conducted by using an artificial neural network data mining method to obtain optimization knowledge of process parameters from large amount of saved process data. The software platform including data processing, statistic analysis, data mining and graphical display module was developed and the quality forecasting models for typical processing operations were discussed. Experiments indicated that the system can optimize and predict the quality of candy production process effectively.

Abstract: The application of automation to industries brings revolution for manufacturing techniques and allows more sophisticated, flexible, reliable, and cost-effective manufacturing process control. Automation is to use control system to reduce human labor intervention during manufacturing processes and production. It plays very important role and puts strong impact in industries. Automation is not only significantly increasing the production speed but also more accurately controlling product quality. The automated manufacturing can maintain consistent quality, shorten lead time, simplify material handling, optimize work flow, and meet the product demand for flexibility and convertibility in production. The current economic globalization requires significant labor cost reduction through industry automation, better machine tools, and efficient production process. This paper is to design and develop a new automated and high speed machinery system for filling high viscous liquids. It includes the design of automated and high speed machinery, computer aided modeling and simulation of automated mechanical system, and prototype testing. The major advantages of this new automated and high speed liquid filling system include reliable function, high volume filling rates, good sealing capacity, and cost-effective manufacturing process. This new automated and high speed manufacturing systems has been analyzed by computer aided modeling and simulation, and verified through prototype testing. Both results indicate that this automated and high speed manufacturing systems can keep high product quantity and reliable product quality.

Abstract: To avoid the defects of plastic products and improve product quality have been an important problem for mold designers. In this paper, Autodesk Moldflow software are applied to a plastic control cover injection molding process simulation and find out the actual molding process and true conditions of the dynamic filling, pressure and cooling process in the process of forming. The forming process of parameters such as pressure, temperature and speed are given in order to improve the accuracy of the mould design and product precision.

Abstract: In order to decrease the residue content of sulfite of apple slices, the desulfurization by water, alkali solution and ultrasonic were studied. Results showed that the optimal parameters of the orthogonal design for eliminating the sulfur by water were: 60°C of temperature, 1:6 of solid-liquid ratio, 45 min/time of water refresh cycle, 3h of time. In this optimal condition, the desulfurization was 96.054%, and the residue content of sulfite was 0.090 g/kg. While the optimum conditions of alkali method were: using 0.06% Ca (OH) ₂ with the solid-liquid ratio 1:5.4 at 54°C. In this optimal condition, the desulfurization rate was 96.673%, and the residue content was down to 0.076g/kg.The optimal parameters for eliminating the sulfur by ultrasonic were: solid-liquid ratio1:6, treatment time 25 min, ultrasonic power 120w, temperature 35°C. In this optimal condition, the desulfurization rate was 97.418%, and the residue content of sulfite was only 0.059g/kg.

Abstract: The mechanism and method were deduced on surface modification of nano-ZnO by titanate coupling agent. EVADPE/ZnO nanocomposite material was prepared, and the tensile strength was tested. Three relatively optimal groups of process parameters were obtained by orthogonal experiment, BP-GA model and BP-PSO model respectively, in which the parameter obtained through BP-GA model was equal to that obtained through BP-PSO model. The iterative times of BP-PSO algorithm were smaller than that of BP-PSO algorithm. With analysis, it was showed that the group of process parameters obtained by BP-GA model and BP-PSO model based on the orthogonal experiment data were much better than that group obtained by orthogonal experiment. The optimal velocity of BP-PSO algorithm was faster than that of BP-PSO model.