Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Integrated performance prediction and quality control in manufacturing systems

textPredicting the condition of a degrading dynamic system is critical for implementing successful control and designing the optimal operation and maintenance strategies throughout the lifetime of the system. In many situations, especially in manufacturing, systems experience multiple degradation cycles, failures, and maintenance events throughout their lifetimes. In such cases, historical records of sensor readings observed during the lifecycle of a machine can yield vital information about degradation patterns of the monitored machine, which can be used to formulate dynamic models for predicting its future performance. Besides the ability to predict equipment failures, another major component of cost effective and high-throughput manufacturing is tight control of product quality. Quality control is assured by taking periodic measurements of the products at various stages of production. Nevertheless, quality measurements of the product require time and are often executed on costly measurement equipment, which increases the cost of manufacturing and slows down production. One possible way to remedy this situation is to utilize the inherent link between the manufacturing equipment condition, mirrored in the readings of sensors mounted on that machine, and the quality of products coming out of it. The concept of Virtual Metrology (VM) addresses the quality control problem by using data-driven models that relate the product quality to the equipment sensors, enabling continuous estimation of the quality characteristics of the product, even when physical measurements of product quality are not available. VM can thus bring significant production benefits, including improved process control, reduced quality losses and higher productivity. In this dissertation, new methods are formulated that will combine long-term performance prediction of sensory signatures from a degrading manufacturing machine with VM quality estimation, which enables integration of predictive condition monitoring (prediction of sensory signatures) with predictive manufacturing process control (predictive VM model). The recently developed algorithm for prediction of sensory signatures is capable of predicting the system condition by comparing the similarity of the most recent performance signatures with the known degradation patterns available in the historical records. The method accomplishes the prediction of non-Gaussian and non-stationary time-series of relevant performance signatures with analytical tractability, which enables calculations of predicted signature distributions with significantly greater speeds than what can be found in literature. VM quality estimation is implemented using the recently introduced growing structure multiple model system paradigm (GSMMS), based on the use of local linear dynamic models. The concept of local models enables representation of complex, non-linear dependencies with non-Gaussian and non-stationary noise characteristics, using a locally tractable model representation. Localized modeling enables a VM that can detect situations when the VM model is not adequate and needs to be improved, which is one of the main challenges in VM. Finally, uncertainty propagation with Monte Carlo simulation is pursued in order to propagate the predicted distributions of equipment signatures through the VM model to enable prediction of distributions of the quality variables using the readily available sensor readings streaming from the monitored manufacturing machine. The newly developed methods are applied to long-term production data coming from an industrial plasma-enhanced chemical vapor deposition (PECVD) tool operating in a major semiconductor manufacturing fab.Mechanical Engineerin

Digital twins: Understanding the added value of integrated models for through-life engineering services

Digital twins are digital representations of physical products or systems that consist of multiple models from various domains describing them on multiple scales. By means of communication, digital twins change and evolve together with their physical counterparts throughout their lifecycle. Domain-specific partial models that make up the digital twin, such as the CAD model or the degradation model, are usually well known and provide accurate descriptions of certain parts of the physical asset. However, in complex systems, the value of integrating the partial models increases because it facilitates the study of their complex behaviours which only emerge from the interactions between various parts of the system. The paper proposes that the partial models of the digital twin share a common model space that integrates them through a definition of their interrelations and acts as a bridge between the digital twin and the physical asset. The approach is illustrated in a case of a mechatronic product - a differential drive mobile robot developed as a testbed for digital twin research. It is demonstrated how the integrated models add value to different stages of the lifecycle, allowing for evaluation of performance in the design stage and real-time reflection with the physical asset during its operation

The role of supply chain integration in achieving competitive advantage: A study of UK automobile manufacturers

The competitive nature of the global automobile industry has resulted in a battle for efficiency and consistency in supply chain management (SCM). For manufacturers, the diversified network of suppliers represents more than just a production system; it is a strategic asset that must be managed, evaluated, and revised in order to attain competitive advantage. One capability that has become an increasingly essential means of alignment and assessment is supply chain integration (SCI). Through such practices, manufacturers create informational capital that is inimitable, yet transferrable, allowing suppliers to participate in a mutually-beneficial system of performance-centred outcomes. From cost reduction to time improvements to quality control, the benefits of SCI extend throughout the supply chain lifecycle, providing firms with improved predictability, flexibility, and responsiveness. Yet in spite of such benefits, key limitations including exposure to risks, supplier failures, or changing competitive conditions may expose manufacturers to a vulnerable position that can severely impact value and performance. The current study summarizes the perspectives and predictions of managers within the automobile industry in the UK, highlighting a dynamic model of interdependency and interpolation that embraces SCI as a strategic resource. Full commitment to integration is critical to achieving improved outcomes and performance; therefore, firms seeking to integrate throughout their extended supply chain must be willing to embrace a less centralized locus of control

Overview of Remaining Useful Life prediction techniques in Through-life Engineering Services

Through-life Engineering Services (TES) are essential in the manufacture and servicing of complex engineering products. TES improves support services by providing prognosis of run-to-failure and time-to-failure on-demand data for better decision making. The concept of Remaining Useful Life (RUL) is utilised to predict life-span of components (of a service system) with the purpose of minimising catastrophic failure events in both manufacturing and service sectors. The purpose of this paper is to identify failure mechanisms and emphasise the failure events prediction approaches that can effectively reduce uncertainties. It will demonstrate the classification of techniques used in RUL prediction for optimisation of products’ future use based on current products in-service with regards to predictability, availability and reliability. It presents a mapping of degradation mechanisms against techniques for knowledge acquisition with the objective of presenting to designers and manufacturers ways to improve the life-span of components

Lifecycle management of process analytical methods for pharmaceuticals quality control

Trabalho Final de Mestrado Integrado, Ciências Farmacêuticas, 2022, Universidade de Lisboa, Faculdade de Farmácia.A esperança média de vida da população mundial, tem aumentado bastante nos últimos cem anos e isto, deve-se ao facto das novas descobertas na medicina, principalmente as descobertas de novas substâncias ativas que ajudam a combater patologias que já existiam ou novas que vão aparecendo. Com isto, houve um grande crescimento do mercado de medicamentos, pois estes permitem que algumas pessoas com condições médicas debilitadas mantenham a qualidade de vida, apesar do quadro clínico. Contudo os medicamentos, também têm reações adversas que podem prejudicar a qualidade de vida dos doentes e, para minimizar esta situação, é necessário supervisionar e garantir a qualidade dos produtos farmacêuticos. Consequentemente, em 1994 foi criada e terminada em 1996, a International Council for Harmonisation Quality Guideline 2 – Validação de Procedimentos Analíticos, com o intuito de conseguir validar novos procedimentos analíticos ou que já existiam, avaliando ensaios, impurezas, potência e qualquer outra medida quantitativa ou qualitativa. Garantindo que os medicamentos são seguros para o consumo dos doentes, fazendo assim um controlo estratégico do benefício-risco do medicamento ou da substância ativa. Todavia, com o passar dos anos, com o aumento da tecnologia e dos métodos analíticos, esta diretriz foi revelando algumas limitações, não sendo adequada para alguns métodos analíticos que foram surgindo recentemente. Por isso, foi necessário criar uma nova diretriz que conseguisse abranger todos estes novos métodos e, posto isso, em 2022, foi apresentado o texto provisório da International Council for Harmonisation Quality Guideline 14 – Desenvolvimento de Procedimentos Analíticos. Esta diretriz tem como objetivo conseguir regular o desenvolvimento de novos métodos analíticos, para que se melhore a comunicação entre a indústria farmacêutica e agências reguladoras. No entanto, esta nova diretriz, no seu texto atual encontra-se em vários aspetos incompleta, vaga, com falta de consistência na informação do documento e confusa, sendo necessário uma revisão do documento na íntegra, para que seja um acréscimo real relativamente à diretriz existente (ICH Q2).The average life expectation of the world population has increased significantly in the last hundred years, and this is due to the fact of new discoveries in medicine, mainly as discoveries of new active substances that help to fight pathologies that already existed or new ones that are appearing. With this, there was a great growth in the drug market, as they allow some people with debilitated medical conditions to maintain their quality of life, despite their clinical condition. However, medicines also have adverse reactions that can impair the quality of life of patients and, to minimize this situation, it is also necessary to supervise and guarantee the quality of pharmaceutical products. Consequently, in 1994, the International Council for Harmonization Quality Guideline 2 – Validation of Analytical Procedures was created and ended in 1996, in order to validate new or existing analytical procedures, evaluating tests, impurities, potency and any other quantitative or qualitative measurement. Ensuring that medicines are safe for patients to consume, thus making a strategic control of the benefit-risk of the medicine or active substance. However, over the years, with the increase in technology and analytical methods, this guideline has revealed some limitations, not being suitable for some analytical methods that have emerged recently. Therefore, it was necessary to create a new guideline that could cover all these new methods and, therefore, in 2022, the provisional text of the International Council for Harmonization Quality Guideline 14 – Development of Analytical Procedures was presented. This guideline aims to regulate the development of new analytical methods, in order to improve communication between the pharmaceutical industry and regulatory agencies. Nevertheless, this new guideline, in its current text, is incomplete, vague, with a lack of consistency in the information in the document and confusing, requiring a revision of the document in its entirety, so that it is a real addition to the guideline existing (ICH-Q2)

Digital Twin Technology

Digital twin technology is considered to be the core technology of realizing Cyber-Physical System (CPS). It is the simulation technology that integrates multidisciplinary, multiphysical quantity, multiscale and multi probability by making full use of physical model, sensor update, operation history and other data. It is the mapping technology for the whole lifecycle process of physical equipment in virtual space. It is the basic technology of Industrial 4.0. This chapter mainly introduces: (1) the generation of digital twin technology; (2) the definition and characteristics of digital twin technology; (3) the relationship between digital twin and digital thread; (4) the implementation of the product digital twin model; and (5) the research progress and application of digital twin research

Local Digital Twin-based control of a cobot-assisted assembly cell based on Dispatching Rules

In the context of an increasing digitalization of production processes, Digital Twins (DT) are emerging as new simulation paradigm for manufacturing, which leads to potential advances in the production planning and control of production systems. In particular, DT can support production control activities thanks to the bidirectional connection in near real-time with the modeled system. Research on DT for production planning and control of automated systems is already ongoing, but manual and semi-manual systems did not receive the same attention. In this paper, a novel framework focused on a local DT is proposed to control a cobot-assisted assembly cell. The DT replicates the behavior of the cell, providing accurate predictions of its performances in alternative scenarios. Then, building on these predicted estimates, the controller selects, among different dispatching rules, the most appropriate one to pursue different performance objectives. This has been proven beneficial through a simulation assessment of the whole assembly line considered as testbed

ARMD Workshop on Materials and Methods for Rapid Manufacturing for Commercial and Urban Aviation

This report documents the goals, organization and outcomes of the NASA Aeronautics Research Mission Directorates (ARMD) Materials and Methods for Rapid Manufacturing for Commercial and Urban Aviation Workshop. The workshop began with a series of plenary presentations by leaders in the field of structures and materials, followed by concurrent symposia focused on forecasting the future of various technologies related to rapid manufacturing of metallic materials and polymeric matrix composites, referred to herein as composites. Shortly after the workshop, questionnaires were sent to key workshop participants from the aerospace industry with requests to rank the importance of a series of potential investment areas identified during the workshop. Outcomes from the workshop and subsequent questionnaires are being used as guidance for NASA investments in this important technology area