Tao Peng

Bio: Tao Peng is an academic researcher from Zhejiang University. The author has contributed to research in topics: Energy consumption & Efficient energy use. The author has an hindex of 18, co-authored 56 publications receiving 1051 citations. Previous affiliations of Tao Peng include University of Auckland.

Sustainability of additive manufacturing: An overview on its energy demand and environmental impact

Abstract: Additive Manufacturing (AM) has been rapidly developing over the last decade. It shows great potential in reducing the need for energy- and resource-intensive manufacturing processes, which in turn reduces the amount of material required in the supply chain, and enables more environmentally benign practices. However, the question of how to realize these potential benefits has received little attention. This paper aims to provide an overview of the Sustainability of Additive Manufacturing (SAM). The context of the SAM is introduced, with a focus on energy and environmental impacts. Resource consumption is identified as the most important aspect. Examination from a life cycle perspective is also presented, with explicit discussions on opportunities to reduce energy and material consumption through design, material preparation, manufacturing, usage, and end-of-life treatment. Statistical data analysis provides an overview of impact forecasts, highlighting the importance of and need for thorough research on sustainability. The eco-design concept enabled by AM is identified as the most promising and effective technology, further extending and completing its design capability. This also determines the opportunities for energy and environmental optimization in subsequent processes. Most existing research is in process- and system-specific modeling, and few AM processes and systems have been studied, with generally premature conclusions. General models for each type of AM process are still necessary. Lastly, five research priorities are suggested: improve systematic data integration and management, correlate energy and quality, develop intelligent machinery, focus on material preparation and recycling, and discover innovative applications using AM.

A big data-driven framework for sustainable and smart additive manufacturing

Abstract: From the last decade, additive manufacturing (AM) has been evolving speedily and has revealed the great potential for energy-saving and cleaner environmental production due to a reduction in material and resource consumption and other tooling requirements. In this modern era, with the advancements in manufacturing technologies, academia and industry have been given more interest in smart manufacturing for taking benefits for making their production more sustainable and effective. In the present study, the significant techniques of smart manufacturing, sustainable manufacturing, and additive manufacturing are combined to make a unified term of sustainable and smart additive manufacturing (SSAM). The paper aims to develop framework by combining big data analytics, additive manufacturing, and sustainable smart manufacturing technologies which is beneficial to the additive manufacturing enterprises. So, a framework of big data-driven sustainable and smart additive manufacturing (BD-SSAM) is proposed which helped AM industry leaders to make better decisions for the beginning of life (BOL) stage of product life cycle. Finally, an application scenario of the additive manufacturing industry was presented to demonstrate the proposed framework. The proposed framework is implemented on the BOL stage of product lifecycle due to limitation of available resources and for fabrication of AlSi10Mg alloy components by using selective laser melting (SLM) technique of AM. The results indicate that energy consumption and quality of the product are adequately controlled which is helpful for smart sustainable manufacturing, emission reduction, and cleaner production.

Energy-efficient machining systems: a critical review

Abstract: Sustainable machining as a critical part in sustainable manufacturing has been valued by manufacturing enterprises of all sizes. The traditional short-term financial considerations are substituted by longer-term sustainable strategies to ensure the competitiveness, and ultimately, the survival of the company. Energy-efficient machining system, which promotes sustainable machining, is the focus of this paper. The energy-efficient machining system requires a comprehensive understanding as well as optimisation of energy consumption. Literature in this field is carefully reviewed and summarised. Energy consumption models, which are regarded as the core of the energy-efficient machining systems, are grouped into four categories, i.e. theoretical, empirical, discrete event-based, and hybrid models. Then, energy optimisation methodologies and strategies are discussed for energy-efficient process planning and production scheduling. The applications such as tool condition monitoring can employ energy information as useful input. Research inspired by energy-efficient machining studies is briefly introduced. The main elements of an individual energy-efficient machining system are then summarised. Discussions, research suggestions, and future directions are given at the end.

Influence of energy density on energy demand and porosity of 316L stainless steel fabricated by selective laser melting

Abstract: Selective laser melting (SLM) is one of the most widely used metal additive manufacturing technologies in producing high density parts. Energy density, a key-parameter combination, has been recognized to have a relationship with part formation, but such a relationship is extremely complex. This work aims to investigate energy density as a measure to evaluate energy demand in fabricating pore-free 316L stainless steel SLM parts. Key parameters in energy density were considered in the developed energy demand model. The impact of energy density on the porosity was analyzed with the data from experiments and existing works. Either low or high energy density can result in larger and more pore formation, and the influencing parameter was laser power, followed by layer thickness, scan speed, and hatch space. An effective energy-optimal (E2O) zone was proposed, where a relationship between energy density and porosity was developed. It is suggested that high laser power with high scan speeds can deliver energy to a thicker layer with relatively stable melt pool, fabricating high density parts. Hatch space can be decided accordingly to actual melt pool formation. This combination can effectively reduce energy density, and corresponding energy demand.

Digital Twin: Enabling Technologies, Challenges and Open Research

Abstract: Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues

Abstract: This paper reviews the recent development of Digital Twin technologies in manufacturing systems and processes, to analyze the connotation, application scenarios, and research issues of Digital Twin-driven smart manufacturing in the context of Industry 4.0. To understand Digital Twin and its future potential in manufacturing, we summarized the definition and state-of-the-art development outcomes of Digital Twin. Existing technologies for developing a Digital Twin for smart manufacturing are reviewed under a Digital Twin reference model to systematize the development methodology for Digital Twin. Representative applications are reviewed with a focus on the alignment with the proposed reference model. Outstanding research issues of developing Digital Twins for smart manufacturing are identified at the end of the paper.

Material-structure-performance integrated laser-metal additive manufacturing.

Abstract: BACKGROUND Metallic components are the cornerstone of modern industries such as aviation, aerospace, automobile manufacturing, and energy production. The stringent requirements for high-performance metallic components impede the optimization of materials selection and manufacturing. Laser-based additive manufacturing (AM) is a key strategic technology for technological innovation and industrial sustainability. As the number of applications increases, so do the scientific and technological challenges. Because laser AM has domain-by-domain (e.g., point-by-point, line-by-line, and layer-by-layer) localized forming characteristics, the requisite for printing process and performance control encompasses more than six orders of magnitude, from the microstructure (nanometer- to micrometer-scale) to macroscale structure and performance of components (millimeter- to meter-scale). The traditional route of laser-metal AM follows a typical “series mode” from design to build, resulting in a cumbersome trial-and-error methodology that creates challenges for obtaining high-performance goals. ADVANCES We propose a holistic concept of material-structure-performance integrated additive manufacturing (MSPI-AM) to cope with the extensive challenges of AM. We define MSPI-AM as a one-step AM production of an integral metallic component by integrating multimaterial layout and innovative structures, with an aim to proactively achieve the designed high performance and multifunctionality. Driven by the performance or function to be realized, the MSPI-AM methodology enables the design of multiple materials, new structures, and corresponding printing processes in parallel and emphasizes their mutual compatibility, providing a systematic solution to the existing challenges for laser-metal AM. MSPI-AM is defined by two methodological ideas: “the right materials printed in the right positions” and “unique structures printed for unique functions.” The increasingly creative methods for engineering both micro- and macrostructures within single printed components have led to the use of AM to produce more complicated structures with multimaterials. It is now feasible to design and print multimaterial components with spatially varying microstructures and properties (e.g., nanocomposites, in situ composites, and gradient materials), further enabling the integration of functional structures with electronics within the volume of a laser-printed monolithic part. These complicated structures (e.g., integral topology optimization structures, biomimetic structures learned from nature, and multiscale hierarchical lattice or cellular structures) have led to breakthroughs in both mechanical performance and physical/chemical functionality. Proactive realization of high performance and multifunctionality requires cross-scale coordination mechanisms (i.e., from the nano/microscale to the macroscale). OUTLOOK Our MSPI-AM continues to develop into a practical methodology that contributes to the high performance and multifunctionality goals of AM. Many opportunities exist to enhance MSPI-AM. MSPI-AM relies on a more digitized material and structure development and printing, which could be accomplished by considering different paradigms for AM materials discovery with the Materials Genome Initiative, standardization of formats for digitizing materials and structures to accelerate data aggregation, and a systematic printability database to enhance autonomous decision-making of printers. MSPI-oriented AM becomes more intelligent in processes and production, with the integration of intelligent detection, sensing and monitoring, big-data statistics and analytics, machine learning, and digital twins. MSPI-AM further calls for more hybrid approaches to yield the final high-performance/multifunctional achievements, with more versatile materials selection and more comprehensive integration of virtual manufacturing and real production to navigate more complex printing. We hope that MSPI-AM can become a key strategy for the sustainable development of AM technologies. Download high-res image Open in new tab Download Powerpoint Material-structure-performance integrated additive manufacturing (MSPI-AM). Versatile designed materials and innovative structures are simultaneously printed within an integral metallic component to yield high performance and multifunctionality, integrating in parallel the core elements of material, structure, process, and performance and a large number of related coupling elements and future potential elements to enhance the multifunctionality of printed components and the maturity and sustainability of laser AM technologies.

FDM-Based 3D Printing of Polymer and Associated Composite: A Review on Mechanical Properties, Defects and Treatments.

Abstract: Fused deposition modelling (FDM) is one of the fastest-growing additive manufacturing methods used in printing fibre-reinforced composites (FRC). The performances of the resulting printed parts are limited compared to those by other manufacturing methods due to their inherent defects. Hence, the effort to develop treatment methods to overcome these drawbacks has accelerated during the past few years. The main focus of this study is to review the impact of those defects on the mechanical performance of FRC and therefore to discuss the available treatment methods to eliminate or minimize them in order to enhance the functional properties of the printed parts. As FRC is a combination of polymer matrix material and continuous or short reinforcing fibres, this review will thoroughly discuss both thermoplastic polymers and FRCs printed via FDM technology, including the effect of printing parameters such as layer thickness, infill pattern, raster angle and fibre orientation. The most common defects on printed parts, in particular, the void formation, surface roughness and poor bonding between fibre and matrix, are explored. An inclusive discussion on the effectiveness of chemical, laser, heat and ultrasound treatments to minimize these drawbacks is provided by this review.