1,379 research outputs found
Multi-objective Tool Sequence Optimization in 2.5D Pocket CNC Milling for Minimizing Energy Consumption and Machining Cost
Tool sequence selection is an important task for 2.5D pocket milling and has a significant influence on both the energy consumption and machining cost of the final product. In this paper, the influence of tool sequence on energy consumption is firstly analyzed. Then a multi-objective tool sequence optimization model is proposed with the objective of minimizing energy consumption and machining cost and solved by the graph algorithm. Finally, a case study is carried out to validate the proposed model and search for the trade-off solutions between energy consumption and machining cost
Energy efficient cutting parameter optimization
Mechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented
Latest Developments in Industrial Hybrid Machine Tools that Combine Additive and Subtractive Operations
Hybrid machine tools combining additive and subtractive processes have arisen as a solution to increasing manufacture requirements, boosting the potentials of both technologies, while compensating and minimizing their limitations. Nevertheless, the idea of hybrid machines is relatively new and there is a notable lack of knowledge about the implications arisen from their in-practice use. Therefore, the main goal of the present paper is to fill the existing gap, giving an insight into the current advancements and pending tasks of hybrid machines both from an academic and industrial perspective. To that end, the technical-economical potentials and challenges emerging from their use are identified and critically discussed. In addition, the current situation and future perspectives of hybrid machines from the point of view of process planning, monitoring, and inspection are analyzed. On the one hand, it is found that hybrid machines enable a more efficient use of the resources available, as well as the production of previously unattainable complex parts. On the other hand, it is concluded that there are still some technological challenges derived from the interaction of additive and subtractive processes to be overcome (e.g., process planning, decision planning, use of cutting fluids, and need for a post-processing) before a full implantation of hybrid machines is fulfilledSpecial thanks are addressed to the Industry and Competitiveness Spanish Ministry for the support on the DPI2016-79889-R INTEGRADDI project and to the PARADDISE project H2020-IND-CE-2016-17/H2020-FOF-2016 of the European Union's Horizon 2020 research and innovation program
Energy Consumption Analysis Of Machining Centers Using Bayesian Analysis And Genetic Optimization
Responding to the current urgent need for low carbon emissions and high
efficiency in manufacturing processes, the relationships between three
different machining factors (depth of cut, feed rate, and spindle rate) on
power consumption and surface finish (roughness) were analysed by applying a
Bayesian seemingly unrelated regressions (SUR) model. For the analysis, an
optimization criterion was established and minimized by using an optimization
algorithm that combines evolutionary algorithm methods with a derivative-based
(quasi-Newton) method to find the optimal conditions for energy consumption
that obtains a good surface finish quality. A Bayesian ANOVA was also performed
to identify the most important factors in terms of variance explanation of the
observed outcomes. The data were obtained from a factorial experimental design
performed in two computerized numerical control (CNC) vertical machining
centers (Haas UMC-750 and Leadwell V-40iT). Some results from this study show
that the feed rate is the most influential factor in power consumption, and the
depth of cut is the factor with the stronger influence on roughness values. An
optimal operational point is found for the three factors with a predictive
error of less than 0.01% and 0.03% for the Leadwell V-40iT machine and the Haas
UMC-750 machine, respectively
Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies
Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin
Hybrid Manufacturing Processes Used in the Production of Complex Parts: A Comprehensive Review
Additive manufacturing is defined as a process based on the superposition of layers of materials in order to obtain 3D parts; however, the process does not allow achieve the adequate and necessary surface finishing. In addition, with the development of new materials with superior properties, some of them acquire high hardness and strength, consequently decreasing their ability to be machined. To overcome this shortcoming, a new technology assembling additive and subtractive processes, was developed and implemented. In this process, the additive methods are integrated into a single machine with subtractive processes, often called hybrid manufacturing. The additive manufacturing process is used to produce the part with high efficiency and flexibility, whilst machining is then triggered to give a good surface finishing and dimensional accuracy. With this, and without the need to transport the part from one machine to another, the manufacturing time of the part is reduced, as well as the production costs, since the waste of material is minimized, with the additive–subtractive integration. This work aimed to carry out an extensive literature review regarding additive manufacturing methods, such as binder blasting, directed energy deposition, material extrusion, material jetting, powder bed fusion, sheet laminating and vat polymerization, as well as machining processes, studying the additive-subtractive integration, in order to analyze recent developments in this area, the techniques used, and the results obtained. To perform this review, ScienceDirect, Web of Knowledge and Google Scholar were used as the main source of information because they are powerful search engines in science information. Specialized books have been also used, as well as several websites. The main keywords used in searching information were: “CNC machining”, “hybrid machining”, “hybrid manufacturing”, “additive manufacturing”, “high-speed machining” and “post-processing”. The conjunction of these keywords was crucial to filter the huge information currently available about additive manufacturing. The search was mainly focused on publications of the current century. The work intends to provide structured information on the research carried out about each one of the two considered processes (additive manufacturing and machining), and on how these developments can be taken into consideration in studies about hybrid machining, helping researchers to increase their knowledge in this field in a faster way. An outlook about the integration of these processes is also performed. Additionally, a SWOT analysis is also provided for additive manufacturing, machining and hybrid manufacturing processes, observing the aspects inherent to these technologies.The present work was done and funded under the scope of the projects ON-SURF (ANI |
P2020 | POCI-01-0247-FEDER-024521 and MCTool21 “Manufacturing of cutting tools for the 21st
century: from nano-scale material design to numerical process simulation” (ref.: “POCI-01-0247-
FEDER-045940”) co-funded by Portugal 2020 and FEDER, through COMPETE 2020-Operational
Programme for Competitiveness and Internationalisation. This work is also sponsored by FEDER
National funds FCT under the project CEMMPRE ref. “UIDB/00285/2020”. F.J.G. Silva also thanks
INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Indústria due to
its support.info:eu-repo/semantics/publishedVersio
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Low carbon manufacturing: Fundamentals, methodology and application case studies
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The requirement and awareness of the carbon emissions reduction in several scales and
application of sustainable manufacturing have been now critically reviewed as important manufacturing trends in the 21st century. The key requirements for carbon emissions reduction in this context are energy efficiency, resource utilization, waste minimization and even the reduction of total carbon footprint. The recent approaches tend to only analyse and evaluate
carbon emission contents of interested engineering systems. However, a systematic approach based on strategic decision making has not been officially defined with no standards or guidelines further formulated yet. The above requirements demand a fundamentally new approach to future applications of sustainable low carbon manufacturing. Energy and resource efficiencies and effectiveness based low carbon manufacturing (EREEbased LCM) is thus proposed in this research. The proposed EREE-based LCM is able to provide the systematic approach for integrating three key elements (energy efficiency, resource utilization and waste minimization) and taking account of them comprehensively in a scientific manner. The proposed approach demonstrates the solution for reducing carbon emissions in
manufacturing systems at both the machine and shop floor levels. An integrated framework has been developed to demonstrate the feasible approach to achieve effective EREE-based LCM at different manufacturing levels including machine, shop floor,
enterprise and supply chains. The framework is established in the matrix form with appropriate tools and methodologies related to the three keys elements at each manufacturing level. The theoretical model for EREE-based LCM is also presented, which consists of three essential elements including carbon dioxide emissions evaluation, an optimization method and waste
reduction methodology. The preliminary experiment and simulations are carried out to evaluate the proposed concept. The modelling of EREE-based LCM has been developed for both the machine and shop floor
levels. At the machine level, the modelling consists of the simulation of energy consumption due to the effect of machining set-up, the optimization model and waste minimization related to the optimized machining set-up. The simulation is established using sugeno type fuzzy logic. The learning method uses on experimental data (cutting trials) while the optimization model is created using mamdani type fuzzy logic with grey relational grade technique. At the shop floor level, the modelling is designed dependent on the cooperation with machine level modelling. The determination of the work assignment including machining set-up depends on fuzzy integer linear programming for several objectives with the evaluation of energy consumption data from
machine level modelling. The simulation method is applied as the part of shop floor level modelling in order to maximize resource utilization and minimize undesired waste. The output from the shop floor level modelling is machine production a planning with preventive plan that can minimize the total carbon footprint. The axiomatic design theory has been applied to generate the comprehensive conceptual model E-R-W-C (energy, resource, waste and carbon footprint) of EREE-based LCM as a generic
perspective of the systematic modelling. The implementation of EREE-based LCM on both the
machine and shop floor levels are demonstrated using MATLAB toolbox and ProModel based simulation. The proposed concept, framework and modelling have been further evaluated and validated through case studies and experimental results.This work is financially supported by The Royal Thai Government
Reconfigurable and transportable container-integrated production system
In this paper, the concept and the prototype realization of a novel reconfigurable small-footprint manufacturing system in a transportable container is presented. The containerized format enables transportation of the system to provide on-site manufacturing, enabling the benefits of localized service delivery without duplication of equipment at multiple locations. Three industrial product use cases with varying manufacturing and performance requirements were analyzed. All of the use cases demanded highly customized products with high quality in low production volumes. Based on their requirements, a general system specification was derived and used to develop a concept for the container-integrated factory. A reconfigurable, modular manufacturing system is integral to the overall container concept. Production equipment was integrated in the form of interchangeable process modules, which can be quickly connected by standard utility supply and control interfaces. A modular and self-configuring control system provides assisted production workflow programming, while a modular process chain combining Additive Manufacturing, milling, precision assembly and cleaning processes has been developed. A prototype of the container-integrated factory with reconfigurable process modules and control system has been established, with full functionality and feasibility of the system demonstrated
Hybrid modeling to support the smart manufacturing: concepts, theoretic contributions and real-case applications about Hybrid and Wisdom-based Systems
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