Variable structure controller for plastic injection moulding system

This paper discusses the approach to design of combined ANN and PID temperature controller for a plastic injection moulding system. The proposed method is based on integration of a conventional PID (PI) controller and a multilayer ANN. At the initial stage of operation, the ANN is trained in offline mode to approximately identify the dynamic parameters of the regulator optimised in terms of speed of response and overshoot. Under routine operation mode the ANN control structure is responsible for the fast transients whereas PID (PI) controller provides the high accuracy at the steady state condition. The paper focuses on the structure switching mechanism and the influence on the transient accuracy. In order to verify the proposed approach, the control system having various types of heaters has been modelled and simulated in Matlab/Simulink. The data obtained from the experiment verified the developed model and confirmed the results of simulations

Viscosity Regulation in Polymer Extrusion

The interesting background and history of polymer extrusion are first introduced in this thesis. The complexity of the extrusion process is described, along with sources of disturbances. A literature review of the types of controllers that have been used for viscosity regulation in polymer extrusion is given, including the proportional-integral-derivative (PID) proportional-integral (PI) controllers. Polymer viscosity in extrusion is difficult to model accurately and its regulation is prone to disturbances. Active Disturbance Rejection Control (ADRC) is the right method for addressing the model inaccuracies and facilitates a straightforward solution to accommodate industrial needs with parameters that can be easily tuned by the operator. To do this, first the problem of viscosity regulation has to be reformulated as a disturbance rejection problem. This thesis demonstrates, using a circuit and simulation, an advanced solution. The initial results are encouraging, showing better control than P

Predictive Methodology for Quality Assessment in Injection Molding Comparing Linear Regression and Neural Networks

The use of recycled polypropylene in industry to reduce environmental impact is increasing. Design for manufacturing and process simulation is a key stage in the development of plastic parts. Traditionally, a trial-and-error methodology is followed to eliminate uncertainties regarding geometry and process. A new proposal is presented, combining simulation with the design of experiments and creating prediction models for seven different process and part quality output features. These models are used to optimize the design without developing additional time-consuming simulations. The study aims to compare the precision and correlation of these models. The methods used are linear regression and artificial neural network (ANN) fitting. A wide range of eight injection parameters and geometry variations are used as inputs. The predictability of nonlinear behavior and compensatory effects due to the complex relationships between this wide set of parameter combinations is analyzed further in the state of the art. Results show that only Back Propagation Neural Networks (BPNN) are suitable for correlating all quality features in a single formula. The use of prediction models accelerates the optimization of part design, applying multiple criteria to support decision-making. The methodology is applied to the design of a plastic support for induction hobs. Furthermore, this methodology has demonstrated that a weight reduction of 27% is feasible. However, it is necessary to combine process parameters that differ from the standard ones with a non-uniform thickness distribution so that the remaining injection parameters, material properties, and dimensions fall within tolerances

Thermal management in laminated die system

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Control, Automation and Systems on August 2014, available online: http://dx.doi.org/10.1007/s12555-013-0348-6The thermal control of a die is crucial for the development of high efficiency injection moulds. For an effective thermal management, this research provides a strategy to identify a thermal dynamic model and to design a controller. The neural network techniques and finite element analysis enable modeling to deal with various cycle-times for moulding process and uncertain dynamics of a die. Based on the system identification which is experimentally validated using a real system, controllers are designed using fuzzy-logic and self-tuning PID methods with backpropagation and radial basis function neural networks to tune control parameters. Through a comparative study, each controller’s performance is verified in terms of response time and tracking accuracy under different moulding processes with multiple cycle-times

An efficient industry 4.0 architecture for energy conservation using an automatic machine monitor and control in the foundry

In this article, a machine monitor and control architecture (MMCA) satisfying the industry 4.0 standard is proposed for energy conservation by optimizing the core moulding machine in industrial automation. Since the foundry environment is a fine dust area and is maintained at very high temperatures (around 140°C), the manual operation of machines is more complex and demanding. Moreover, the monitoring and controlling of machines need highly reliable eco-friendly systems. With real-time data logging, the proposed MMCA prototype system has been installed to monitor and control the overall process in a single core shooter machine (CSM). The parameters controlled using MMCA in foundry machinery include pressure, temperature and power consumption. The complete system can be controlled using an intranet or Internet connection without any human intervention in the machinery environment, which operates at a very high temperature. After explaining the architecture and its features, the experimental results are presented on a real-time implementation of the framework to validate the optimal energy management by the proposed MMCA. The experiments were performed on a CSM, which is automated for practical industrial applications. Its real-time implementation ensures that MMCA-based monitoring and controlling is more effective and advantageous than the programmable logic controller-based machine monitoring

Thermal Management in Laminated Die Systems Using Neural Networks

The thermal control of a die is crucial for the development of high efficiency injection moulds. For successful thermal management, this research provides an effective control strategy to find sensor locations, identify thermal dynamic models, and design controllers. By applying a clustering method and sensitivity analysis, sensor locations are identified. The neural network and finite element analysis techniques enable the modeling to deal with various cycle-times for the moulding process and uncertain dynamics of a die. A combination of off-line training through finite element analysis and training using on-line learning algorithms and experimental data is used for the system identification. Based on the system identification which is experimentally validated using a real system, controllers are designed using fuzzy-logic and self-adaptive PID methods with backpropagation (BP) and radial basis function (RBF) neural networks to tune control parameters. Direct adaptive inverse control and additive feedforward control by adding direct adaptive inverse control to self-adaptive PID controllers are also provided. Through a comparative study, each controller’s performance is verified in terms of response time and tracking accuracy under different moulding processes with multiple cycle-times. Additionally, the improved cooling effectiveness of the conformal cooling channel designed in this study is presented by comparing with a conventional straight channel

Structure development and properties in advanced injection molding processes : development of a versatile numerical tool

Spuitgieten is een van de meest gebruikte technieken om polymere materialen vorm te geven. De techniek is populair doordat complexe geometrieën kunnen worden gerealiseerd met hoge productiesnelheden. Verbeteringen in de techniek, ingevoerd sinds de jaren 50, zijn voornamelijk gericht op verhoging van de productie-efficiency en van de productkwaliteit. Ook werden er onconventionele productietechnieken ontwikkeld, zoals gasinjectie enmeerkomponent-spuitgieten, terwijl daarnaast soms ook meerdere materiaalsoorten worden gebruikt, zoals bij het omspuiten van metalen of keramieke objecten. Productontwikkelaars richten zich nu op verkleining van de lengteschaal, verhogen van de precisie en voorspelling van de levensduur. Om dit proces te ondersteunen zijn in de laatste 30 jaar verschillende numerieke modellen ontwikkeld. De meeste daarvan richten zich op verbeterd productontwerp om problemen te voorkomen met inhomogeen vulgedrag, ongebalanceerde druk- en temperatuurverdelingen en typische spuitgietproblemen als positie van samenvloeinaden en luchtinsluitingen. Ook richt de modelleringaandacht zich op het voorspellen van eigenschappen, voornamelijk gefocuseerd op de voorspelling van krimp en kromtrekgedrag. Dit proefschrift poogt bij te dragen aan de voorspelling van eindeigenschappen van gespuitgiete producten en bouwt voort op het in onze groep ontwikkelde volledig driedimensionale computermodel, VIp3D, zoals dat in Hoofdstuk 2 wordt gepresenteerd. In Hoofdstuk 3 bestuderen we amorfe polymeren gespoten via GAIM, gasinjectie, en voorspellen de stromings-geïnduceerde residu-spanningen in termen van de ingevroren moleculaire oriëntatie. Hierbij wordt een ontkoppelde berekening gebruikt waarin de elastische effecten geen invloed hebben op de kinematica van de stroming. InHoofdstuk 4 berekenen we de temperatuur- en drukgeïnduceerde spanningen, gebruikmakend van een gelineariseerd visco-elastisch constitutiefmodel. De 3D resultaten worden vergeleken met 2D berekeningen bekend uit de literatuur. Vervolgens richt de aandacht zich op semikristallijne polymeren en meer precies op de morfologie-ontwikkeling in isotactisch Polypropeen (iPP). De complexe thermomechanische geschiedenis die materiaaldeeltjes ondergaan in het spuitgietproces, maakt het voorspellen van kristallisatie, gegeven de sterke afhankelijkheid daarvan van de stromingscondities, niet eenvoudig; zelfs de stroming in de extruder kan invloed hebben. Vandaar dat eenvoudiger stromingen, met beter gedefinieerde begin-en randvoorwaarden, vereist zijn om de modellen voor de beschrijving van kristallisatie-kinetiek te valideren. In Hoofdstuk 5 wordt de morfologieontwikkeling in iPP bestudeerd gebruikmakend van een zogenaamde multi-pass reometer en van een capillairviscosimeter. In beide opstellingen wordt het materiaal blootgesteld aan eenduidige stromingscondities en is de geschiedenis bekend; we noemen dit prototype stromingen. Het gehanteerde model maakt gebruik van een genestelde set differentiaalvergelijkingen om stromings-geïnduceerde kristallisatie te beschrijven. De voorspelde laagdiktes, die gedeeltelijk het gevolg zijn van stromings-geïnduceerde kristallisatie, en gedeeltelijk van kristallisatie in rust, worden vergeleken met experimentele resultaten verkregen met gepolariseerde optische microscopie. De voorspelde morfologieën blijken opvallend en verheugend kwantitatief. In Hoofdstuk 6 richten we ons op de experimentele en numerieke morfologieën zoals die zich ontwikkelen bij het spuitgieten van een schijf, waarbij gebruik is gemaakt van een nieuwe, zij het wat academische, spuitgiet-technologie waarin één helft van de matrijs tijdens injectie kan roteren en transleren. De microstructuur wordt gekarakteriseerd en demoleculaire oriëntatie gemeten. De volledige 3D simulaties blijken in staat het proces te beschrijven. Tot slot worden in Hoofdstuk 7 de belangrijkste conclusies samengevat en aanbevelingen voor toekomstig onderzoek gegeven

Natural Degradation: Polymer Degradation under Different Conditions

This book focuses on some fundamental issues of polymers’ natural degradation. It is mostly devoted to the different aspects of biodegradation, but some data on the action of water, oxygen, ozone, and UV/Vis light is also included. The consideration of the biodegradation in vivo as the superposition of decay and synthesis provides the opportunity for a fresh look at well-known processes

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018