Pedro Carreira

Bio Inspired Algorithms for Injection Moulding Optimization

Social behaviors of living organisms found in nature, like food searching, environment fitness and survival are inspiration for meta-heuristic mathematical models. Replicating these natural organism behaviors, several optimization algorithms have been developed and applied to technological processes. In this work, some nature inspired algorithms are applied to the injection problem in order to optimize the injection runners’ geometry, so that the overall cycle time is minimized. A key issue is the injection moulding process, as it strongly determines the cost per part. A global optimization strategy was implemented for the injection moulding cycle time, covering the main steps of process, filling time, cooling time, packing time and opening time. To achieve the optimum solution for each design variable and obtain the best time solution overall, it will enable to evaluate optimality, robustness, convergence, and variables dispersion for each used algorithm.

{OPTIMALMOULD} {\textbar} Cooling System Influence in Injection Moulding Cycle Time Optimization

Most works undertaken on injection moulding cooling time optimization aimed at reducing the time required to produce plastic parts, this way minimizing industrial costs. An optimal cooling system is proposed to improve the injection moulding design. A multi-objective genetic algorithm called NSGA-II is used, to obtain the optimal parameters in the optimal-mould design. This new design method is an efficient tool to get optimal parameters for injection moulding design. A real case study was carried out to test the optimization platform.

Optimalmould - part II: Global optimization of the injection moulding cycle time

The time required to produce a plastic part is a key issue in injection moulding process as it strongly determine the cost per part. Several approaches have been proposed to address this problem. However they do not cover all aspects related to the complete cycle time of the injection moulding process, only focusing on steps such as filling time, cooling time and packing time. This paper presents a global optimisation strategy for the injection moulding cycle time, covering all time steps related to the injection moulding process, including a novel mathematical model to predict the ejection time. An industrial case study was considered to validate the proposed approach. The obtained results are very close to the experimental ones.

Optimization of Thermoplastic Pre-Pregs Overmoulding

The search for new technological concepts in the field of injection of thermoplastic polymers, in order to optimize the process and reduce cycle time, faced us with a new concept in moulding, where two different technologies are proposed to be unified. The fabric impregnated with thermoplastic is an example of a quite new product that combines the potential of polymers with long reinforcing fibres. In order to process this new product, injection of polymers and thermoforming will be applied in only one operation. To allow cycle time prediction for this new technique, changes will be made in the formulation of conventional injection cycle time, in order to comprise the new necessary stages. In this work a new approach is proposed to obtain moulded parts of thermoplastic polymers with functional fabric only in a single processing cycle. The description of the new stages and its mathematical formulation is made, in function of the time needed to complete each one. The results presented come from processing parameters optimization using the Particle Swarm Optimization (PSO) algorithm.

Optimalmould-part I: Multi-objective optimization to moulds design for injection of polymers

The problem of mould design optimisation for polymer injection is a key issue for both mouldmaking and polymer injection industries. Several computational tools have proposed to address this problem. However they do not cover all aspects related to both mould design and injection moulding process, usually requiring the geometrical configuration of the initial mould solution. This paper presents a novel multi-objective optimisation tool, integrating CAD and CAE tools to optimise mould design parameters and injection moulding process parameters. No initial geometric definition of the mould is required. An industrial case study was considered to validate the proposed approach and the performance of several optimisation algorithms evaluated.