A novel architecture for a reconfigurable micro machining cell

There is a growing demand for machine tools that are specifically designed for the manufacture of micro-scale components. Such machine tools are integrated into flexible micro-manufacturing systems. Design objectives for such tools include energy efficiency, small footprint and importantly flexibility, with the ability to easily reconfigure the manufacturing system in response to process requirements and product demands. Such systems find application in medical, photonics, automotive and electronic industries. In this paper, a new architecture for a reconfigurable micro manufacturing system is presented. The proposed architecture comprises a micro manufacturing cell with the key design feature being a hexagonal-base on which three tool heads can be attached to three of its sides. Each such machine-tool head, or processing module, is able to perform a different manufacturing process. These tool heads are interchangeable, enabling the cell to be configured to process a wide range of components with different materials, dimensions, tolerances and specification. Additional components of the cell include manipulation robots and an automated buffer unit. Such cells can be integrated into a manufacturing system via a modular conveyor belt to transfer parts from one cell to another and into assembly. A key consideration of the architecture is a control system that is also modular and reconfigurable; such that when new processing modules are introduced the control system is aware of the change and adjusts accordingly. Further to this coordination, issues between modules and machining cells are also considered. Other design considerations include work-piece holding and manipulation. This paper provides an overview of the architecture, the key design and implementation challenges as well as a high level operational performance assessment by means of a discrete event simulation model of the micro factory cell

Develop an autonomous product-based reconfigurable manufacturing system

With the ever-emerging market including mass customization and product variety, reconfigurable manufacturing systems (RMS) have been presented as the solution. A manufacturing system that combines the benefits of the two classic manufacturing systems to increase responsiveness and reduce production time and costs. To cope with the lack of physical systems, an RMS system have been built at UiT Narvik. Today, both reconfiguration and deciding layout must be executed manually by a human. A task that is both incredibly time consuming and far from optimal. A method of automating the layout generation and thus the manufacturing system is presented in this thesis. To the author’s knowledge such experiment has not been performed previously. Layouts is generated with a NSGA-II algorithm in Python by minimizing objectives from a developed mathematical model. The results have been tested with a MiR-100 mobile robot placing five modules in two different layouts. The results have been compared with a digital visualization for validation. In addition to the visualization, videos of the physical system's automated layout generation are presented. The results concludes that the method both generates feasible layouts as well as enhancing the automation of the system

Towards smart layout design for a reconfigurable manufacturing system

Global competition and increased variety in products have created challenges for manufacturing companies. One solution to handle the variety in production is to use reconfigurable manufacturing systems (RMS). These are modular systems where machines can be rearranged depending on what is being manufactured. However, implementing a rearrangeable system drastically increases complexity, among which one challenge with RMS is how to design a new layout for a customized product in a highly autonomous and responsive fashion, known as the layout design problem. In this paper, we combine several Industry 4.0 technologies, i.e., IIoT, digital twin, simulation, advanced robotics, and artificial intelligence (AI), together with optimization to create a smart layout design system for RMS. The system automates the layout design process of RMS and removes the need for humans to design a new layout of the system

Automatic generation of human machine interface screens from component-based reconfigurable virtual manufacturing cell

Increasing complexity and decreasing time-tomarket require changes in the traditional way of building automation systems. The paper describes a novel approach to automatically generate the Human Machine Interface (HMI) screens for component-based manufacturing cells based on their corresponding virtual models. Manufacturing cells are first prototyped and commissioned within a virtual engineering environment to validate and optimise the control behaviour. A framework for reusing the embedded control information in the virtual models to automatically generate the HMI screens is proposed. Finally, for proof of concept, the proposed solution is implemented and tested on a test rig

A methodology for controlling the consequences of demand variability in the design of manufacturing systems

Today's unprecedented demand changes flood the global market. Staying competitive is now a matter of responding quickly and cost-effectively to variability. To address this paradigm, flexibility is a key aspect to tackle. Studies show that integrating flexibility in design of systems increases their performance by 25%, yet application procedures are still not very well established. This dissertation proposes a solution methodology for this problem. Aiming control of demand variability consequences, an integrated approach of optimization, screening, and simulation modelling has been developed. Applied to a case study in the furniture manufacturing industry, the methodology highlighted numerous opportunities of improvement in the manufacturing site. Indeed, by applying a flexible design, the overall performance goals were reached and a plan of action was initiated.The results support the proposed methodology as a viable solution for the problem addressed, nevertheless future success involves more than the pure application of this procedure, as flexibility is also a way of thinking

Prescriptive System for Reconfigurable Manufacturing Systems considering Variable Demand and Production Rates

O mercado atual é dinâmico criando a necessidade de resposta a mudanças imprevisíveis de mercado por parte das empresas de forma a permanecerem competitivas. Para lidar com a mudança de paradigma, de produção em massa para customização em massa, a flexibilidade de manufatura é crucial. A atual digitalização da indústria proporciona novas oportunidades em relação a sistemas de apoio à decisão em tempo real permitindo que as empresas tomem decisões estratégicas e obtenham vantagem competitiva e valor comercial acrescido. Nesta dissertação pretende-se implementar um Sistema Prescritivo que sugere sequências de throughputs tendo em consideração objetivos de produção semanais e falhas em equipamentos num contexto de Manufatura Reconfigurável. O Sistema Prescritivo proposto é constituído por dois módulos: Simulação do ambiente de manufatura e o optimizador. O módulo de simulação é modelado com base em teoria de grafos e o optimizador com base em Algoritmos Genéticos. O seu output é uma sequência de throughputs que equilibram da melhor forma as ações de manutenção e produtividade. De forma a avaliar os indivíduos gerados pelo algoritmo genético, estes são aplicados ao primeiro módulo e o seu impacto no sistema de produção analisado. O sistema apresentado mostra notáveis melhorias na mitigação dos efeitos de downtime das máquinas durante a produção. As métricas utilizadas na medição do desempenho do sistema são a variação na produção de peças em relação ao target, descrito nesta dissertação como diferencial, e disponibilidade de produção do sistema. Todos os testes realizados apresentam um diferencial consideravelmente melhor e em certas instâncias, a disponibilidade aumenta ligeiramente. Não obstante, ainda que os resultados obtidos nas configurações testadas sejam robustos, necessita de mais estudos de modo a que seja possível a generalização dos resultados obtidos ao longo desta dissertação.The current market is dynamic and, consequently, industries need to be able to meet unpredictable market changes in order to remain competitive. To address the change in paradigm, from mass production to mass customization, manufacturing flexibility is key. Moreover, the current digitalization opens opportunities regarding real-time decision support systems allowing the companies to make strategic decisions and gain competitive advantage and business value. The aim of this dissertation is to implement a Prescriptive System that suggests sequences of throughputs that take into consideration weekly production targets and machine failures applied to Reconfigurable Manufacturing Systems. The Prescriptive System is mainly composed of two modules: manufacturing environment simulation and optimizer. The simulation module is modeled based on graph theory and the second one on Genetic Algorithms. Its output is a sequence of throughputs that best balances maintenance actions and productivity. In order to evaluate the individuals generated by the algorithm, candidate solutions are fed to the first module and their impact on the production system assessed. The proposed Prescriptive System shows large improvements in the mitigation of machines downtime effects in productivity when compared without any optimization approach. The metrics used to measure the performance of the system are the variation of pieces produced in relation to target, named in the current dissertation as differential, and Availability of the production system. In all tests performed, the differential largely improved and, in some instances, the availability slightly increased. Despite the robust results obtained in the tested configurations, further research should be conducted in order to be able to generalize the obtained results in this dissertation to non-tested configurations

An integrated system to design machine layouts for modular special purpose machines

This thesis introduces the development of an integrated system for the design of layouts for special purpose machines (SPMs). SPMs are capable of performing several machining operations (such as drilling, milling, and tapping) at the same time. They consist of elements that can be arranged in different layouts. Whilst this is a unique feature that makes SPMs modular, a high level of knowledge and experience is required to rearrange the SPM elements in different configurations, and also to select appropriate SPM elements when product demand changes and new layouts are required. In this research, an integrated system for SPM layout design was developed by considering the following components: an expert system tool, an assembly modelling approach for SPM layouts, an artificial intelligence tool, and a CAD design environment. SolidWorks was used as the 3D CAD environment. VisiRule was used as the expert system tool to make decisions about the selection of SPM elements. An assembly modelling approach was developed with an SPM database using a linked list structure and assembly relationships graph. A case-based reasoning (CBR) approach was developed and applied to automate the selection of SPM layouts. These components were integrated using application programing interface (API) features and Visual Basic programming language. The outcome of the application of the novel approach that was developed in this thesis is reducing the steps for the assembly process of the SPM elements and reducing the time for designing SPM layouts. As a result, only one step is required to assemble any two SPM elements and the time for the selection process of SPM layouts is reduced by approximately 75% compared to the traditional processes. The integrated system developed in this thesis will help engineers in design and manufacturing fields to design SPM layouts in a more time-effective manner