Yes / Micro-injection moulding (μIM) stands out as preferable technology to enable the mass production of polymeric components with micro- and nano-structured surfaces. One of the major challenges of these processes is related to the quality assurance of the manufactured surfaces: the time needed to perform accurate 3D surface acquisitions is typically much longer than a single moulding cycle, thus making impossible to integrate in-line measurements in the process chain. In this work, the authors proposed a novel solution to this problem by defining a process monitoring strategy aiming at linking sensitive in-line monitored process variables with the replication quality. A nano-structured surface for antibacterial applications was manufactured on a metal insert by laser structuring and replicated using two different polymers, polyoxymethylene (POM) and polycarbonate (PC). The replication accuracy was determined using a laser scanning confocal microscope and its dependence on the variation of the main μIM parameters was studied using a Design of Experiments (DoE) experimental approach. During each process cycle, the temperature distribution of the polymer inside the cavity was measured using a high-speed infrared camera by means of a sapphire window mounted in the movable plate of the mould. The temperature measurements showed a high level of correlation with the replication performance of the μIM process, thus providing a fast and effective way to control the quality of the moulded surfaces in-line. / MICROMAN project (“Process Fingerprint for Zero-defect Net-shape MICRO MANufacturing”, http://www.microman.mek.dtu.dk/) - H2020 (Project ID: 674801), H2020 agreement No. 766871 (HIMALAIA), H2020 ITN Laser4Fun (agreement No. 675063)

Este modelo contempla o cenário em que a sequência de frações não-conformes no decorrer de um ciclo do processo de produção aumenta gradativamente (situação comum, por exemplo, quando o desgaste de um equipamento é gradual), diferentemente dos modelos de Taguchi, Nayebpour e Woodall e Nandi e Sreehari (1997), que acomodam sequências de frações não-conformes assumindo no máximo três valores, e de Nandi e Sreehari (1999) e Trindade, Ho e Quinino (2007) que contemplam funções de degradação mais simples. O desenvolvimento é baseado nos trabalhos de Ferguson e Antoniak para o cálculo da distribuição a posteriori de uma medida P desconhecida, associada a uma função de distribuição F desconhecida que representa a sequência de frações não-conformes ao longo de um ciclo, supondo, a priori, mistura de Processos Dirichlet. A aplicação consiste na estimação da função de distribuição F e as estimativas de Bayes são analisadas através de alguns casos particulares / In this work, we propose an alternative model for Taguchi´s On-Line Quality-Monitoring Procedure for Attributes under a Bayesian nonparametric framework. This model may be applied to production processes the sequences of defective fractions during a cycle of which increase gradually (for example, when an equipment deteriorates little by little), differently from either Taguchi\'s, Nayebpour and Woodall\'s and Nandi and Sreehari\'s models that allow at most three values for the defective fraction or Nandi and Sreehari\'s and Trindade, Ho and Quinino\'s which take into account simple deterioration functions. The development is based on Ferguson\'s and Antoniak\'s papers to obtain a posteriori distribution for an unknown measure P, associated with an unknown distribution function F that represents the sequence of defective fractions, considering a prior mixture of Dirichlet Processes. The results are applied to the estimation of the distribution function F and the Bayes estimates are analised through some particular cases.

Este modelo contempla o cenário em que a sequência de frações não-conformes no decorrer de um ciclo do processo de produção aumenta gradativamente (situação comum, por exemplo, quando o desgaste de um equipamento é gradual), diferentemente dos modelos de Taguchi, Nayebpour e Woodall e Nandi e Sreehari (1997), que acomodam sequências de frações não-conformes assumindo no máximo três valores, e de Nandi e Sreehari (1999) e Trindade, Ho e Quinino (2007) que contemplam funções de degradação mais simples. O desenvolvimento é baseado nos trabalhos de Ferguson e Antoniak para o cálculo da distribuição a posteriori de uma medida P desconhecida, associada a uma função de distribuição F desconhecida que representa a sequência de frações não-conformes ao longo de um ciclo, supondo, a priori, mistura de Processos Dirichlet. A aplicação consiste na estimação da função de distribuição F e as estimativas de Bayes são analisadas através de alguns casos particulares / In this work, we propose an alternative model for Taguchi´s On-Line Quality-Monitoring Procedure for Attributes under a Bayesian nonparametric framework. This model may be applied to production processes the sequences of defective fractions during a cycle of which increase gradually (for example, when an equipment deteriorates little by little), differently from either Taguchi\'s, Nayebpour and Woodall\'s and Nandi and Sreehari\'s models that allow at most three values for the defective fraction or Nandi and Sreehari\'s and Trindade, Ho and Quinino\'s which take into account simple deterioration functions. The development is based on Ferguson\'s and Antoniak\'s papers to obtain a posteriori distribution for an unknown measure P, associated with an unknown distribution function F that represents the sequence of defective fractions, considering a prior mixture of Dirichlet Processes. The results are applied to the estimation of the distribution function F and the Bayes estimates are analised through some particular cases.

The growing customer demands for product variety have put unprecedented pressure on the manufacturing companies. To maintain their competitiveness, manufacturing companies need to frequently and efficiently adapt their processes while providing high-quality products. Different advanced manufacturing technologies, such as industrial robotics, have seen a drastic usage increase. Nevertheless, traditional quality methods, such as quality inspection, suffer from significant limitations in highly customised small batch production. For quality inspection to remain fundamental for zero-defect manufacturing and Industry 4.0, an increase in flexibility, speed, availability and decision upon conformance reliability is needed. If robots could perform in-line quality inspection, defective components might be prevented from continuing to the next production stage. Recent developments in robot cognition and sensor systems have enabled the robot to carry out perception tasks they were previously unable to do. The purpose of this thesis is to explore the usage of robotic in-line quality inspection during changeable zero-defect manufacturing. To fulfil this aim, this thesis adopts a mixed-methods research approach to qualitative and quantitative studies, as well as theoretical and empirical ones. The foundation for this thesis is an extensive literature review and two case studies that have been performed in close collaboration with manufacturing companies to investigate how in-line quality inspection is perceived and utilised to enhance industrial robots. The empirical studies also aimed at identifying and describing what opportunities arise from having robotic in-line quality inspection systems. The result of this thesis is a synthesis of literature and empirical findings. From the literature review/study, the need for enhancing quality inspection was identified and a multi-layer quality inspection framework suitable for the digital transformation was proposed. The framework is built on the assumption that data (used and collected) needs to be validated, holistic, and online, i.e. when needed, for the system to effectively decide upon conformity to surpass the challenges of reliability, flexibility and autonomy. Empirical studies show that industrial robotic applications can be improved in precision and flexibility using the in-line quality inspection system as measurement-assisted. Nevertheless, this methodological changes and robot application face the hurdle of previous and current management decisions when passing from one industrial paradigm to another (e.g. mass production to flexible production). A discussion on equipment design and manufacturing process harmony and how in-line quality inspection and management can harmonise such a system was provided.