CIRP Annals Online sorted by Year and Volume
|
CIRP ANNALS 2024
|
|
|
|
|
STC A |
|
Implementing Circular Economy Activities in Manufacturing for Environmental Sustainability
|
|
Tomohiko Sakao (2), Nancy Bocken, Nabil Nasr, Yasushi Umeda (1)
|
|
STC A, 73/2/2024, P.8
|
|
Keywords: Lifecycle, Service, Business model |
Abstract : Manufacturers around the globe are expected—with growing urgency—to contribute to the implementation of a circular economy (CE) to enhance
environmental sustainability. However, to put circularity into practice, companies need to be better guided. Responding to their need, this paper 1)
documents research-based insights for CE implementation; 2) clarifies key CE concepts; 3) highlights learning of research and innovation for CE in various
regions; 4) outlines guiding principles for CE implementation; and 5) proposes issues for future research to various communities with a cross-disciplinary
approach in mind. The adopted method is a literature review supplemented with stakeholder interviews.
|
STC C |
|
Sustainable machining: Recent Technological advances
|
|
A. Shokrani (2), P.J. Arrazola (1), D. Biermann (1), P. Mativenga (2), I.S. Jawahir (1)
|
|
STC C, 73/2/2024, P.9
|
|
Keywords: Machining, Sustainable machining, Cutting tool |
Abstract : Multiple international organizations and many governments around the world have declared climate emergency. There is a pressing need to minimize the
environmental impacts of human activities including manufacturing processes. Machining by mechanical cutting is a fundamental manufacturing process
and minimizing and eliminating its environmental impacts is vital. In this keynote paper, sustainability in the context of machining is identified. The
resources used in machining have been categorized and the social and environmental impacts and potential methods to reduce them have been identified.
The findings are critically discussed and the gaps and challenges for future research direction are highlighted.
|
STC Cross-STC |
|
Efficiently preserving material resources in manufacturing: Industrial symbiosis revisited
|
|
J.R. Duflou (1) , K. Wegener (1), A.E. Tekkaya (1) , M. Hauschild (1), F. Bleicher (1), J. Yan (2), B. Hendrick
|
|
STC Cross-STC, 73/2/2024, P.6
|
|
Keywords: Sustainable Development, Recycling, Material Efficiency |
Abstract : The fraction of materials that does not reach the target product in discrete manufacturing is very significant. Directing secondary material streams towards
other manufacturing processes, possibly after intermediate pre-processing, offers opportunities for more energy and resource efficient recycling routes.
This paper contributes to the exploration of such symbiotic recycling strategies by identifying relevant process mechanisms and by systematically scanning
the manufacturing domain for relevant process combinations. Emerging and proven symbiotic combinations within the discrete manufacturing domain
are reviewed, with proper attention for the quantification of the thus avoided environmental impact. A series of representative case studies illustrates the
feasibility of applying industrial symbiosis principles in a discrete manufacturing context, with uniform data sheets providing detailed information on
relevant research achievements.
|
|
Artificial Intelligence in manufacturing: state of the art, perspectives, and future directions
|
|
Robert X. Gao (1), Jörg Krüger (1), Marion Merklein (1), Hans-Christian Möhring (2), József Váncza (1)
|
|
STC Cross-STC, 73/2/2024, P.7
|
|
Keywords: : Artificial Intelligence, Smart Manufacturing, Machine Learning |
Abstract : Inspired by the natural intelligence of humans and bio-evolution, Artificial Intelligence (AI) has seen accelerated growth since the beginning of
the 21st century. Successful AI applications have been broadly reported, with Industry 4.0 providing a thematic platform for AI-related research
and development in manufacturing. This paper highlights applications of AI in manufacturing, ranging from production system design and
planning to process modeling, optimization, quality assurance, maintenance, automated assembly and disassembly. In addition, the paper
presents an overview of representative manufacturing problems and matching AI solutions, and a perspective of future research to leverage AI
towards the realization of smart manufacturing.
|
STC Dn |
|
Integration of datascience with product design towards data-driven design
|
|
Ang Liu (2), Stephen Lu (1), Fei Tao (2), Nabil Anwer (1)
|
|
STC Dn, 73/2/2024, P.10
|
|
Keywords: Product design, Data science, Data-driven design |
Abstract : This paper investigates the integration of data science and product design towards data-driven design (D3). Data science has potential to facilitate design
decision-making through insight extraction, predictive analytics, and automatic decisions. Various D3 applications are reviewed in three dimensions: the
design dimension about design operations, the data dimension about design-specific/design-relevant data and SOME data-related challenges, and the
method dimension about design methods and data science methods. Some social and ethical considerations in D3 applications are explored. This paper
also opens some discussions on potential avenues and complexities for future research in this dynamic field.
|
STC E |
|
Dynamic Beam Shaping - Improving Laser Materials Processing via Feature Synchronous Energy Coupling
|
|
M. Schmidt (1), K. Cvecek, J. Duflou (1), F. Vollertsen (1), C.B. Arnold, M.J. Matthews
|
|
STC E, 73/2/2024, P.11
|
|
Keywords: Adaptive control, Laser, Beam shaping |
Abstract : Today, tailored laser beams are rarely used and thus an opportunity to optimize existing or introduce new processes is missed. New methods of dynamic
beam shaping have the potential to change that in future. This keynote paper deals with methods allowing a transient energy input into the workpiece at
such time scales that the underlying interaction processes are guided towards the desired result. It shows principles, categorizes necessary system
technology, and gives application examples to familiarize the reader with the top
|
STC F |
|
Artificial intelligence in metal forming
|
|
Jian Cao (1), Markus Bambach (2), Marion Merklein (1), Mojtaba Mozaffar, Tianju Xue
|
|
STC F, 73/2/2024, P.1
|
|
Keywords: Artificial intelligence, Machine learning, Material characterization, Process design, Process control |
Abstract : Forming processes are known for their intricacies in prediction and control due to the complex loading conditions and material flow. This paper will first
introduce the AI algorithms used or having potential to be used in forming, and then investigate the state-of-the-art advances of AI-based technologies in
forming processes with four main pillars of process simulation, process design and optimization, in-situ process control, and qualification and certification
of forming processes and formed products. Future directions of AI in forming for both academic research and industrial applications will be proposed to
leverage digitalization and data science to explore new solutions in forming processes.
|
STC G |
|
Advances in modeling of fixed-abrasive processes
|
|
Peter Krajnik (2), Konrad Wegener (1), Thomas Bergs (2), Albert J. Shih (1)
|
|
STC G, 73/2/2024, P.2
|
|
Keywords: Grinding, Modeling, Simulation |
Abstract : Research over the last 70 years has led to a better understanding of fixed-abrasive machining processes. This knowledge is often expressed in the form of
physical and empirical models that cover forces, power, specific energy, wheel/workpiece topography, wear, thermal aspects, cooling, dressing, and more.
This paper first examines the established models that continue to constitute the fundamental knowledge base in fixed-abrasive technology. Special
attention is given to geometry, kinematics, and thermomechanical modeling. Recent advances in process monitoring and big data analytics provide new
opportunities to further strengthen the state of the art in modeling through data-driven approaches. In addition, examples on how models – implemented
in simulation software – can be used to predict and optimize industrial operations have been demonstrated. This is illustrated by several use cases from
real production, including bearing, creep-feed form, gear, camshaft, crankshaft, and centerless grinding, along with diamond-wheel truing.
|
STC M |
|
Hybrid metal additive/subtractive machine tools and applications
|
|
Scott Smith (1), Tony Schmitz (2), Thomas Feldhausen, Michael Sealy (2)
|
|
STC M, 73/2/2024, P.3
|
|
Keywords: Hybrid, Additive Manufacturing, Machine tool |
Abstract : Additive manufacturing creates parts by depositing a preform, typically layer by layer. Subtractive manufacturing involves removing material
from a preform to create parts. Hybrid machine tools combine both additive and subtractive processes in the same workspace. They can be used
to create parts that meet functional tolerance and surface finish requirements, or to create features that are difficult to produce using additive
or subtractive processes alone. This paper describes hybrid metal additive/subtractive machine tools. It covers design considerations, sensors
and controls, process management, programming and software, and the impact on the design space. It also identifies future research challenges.
|
STC P |
|
Integrated metrology for advanced manufacturing
|
|
Andreas Archenti (2), Wei Gao (1), Alkan Donmez (1), Enrico Savio (1), Naruhiro Irino (2)
|
|
STC P, 73/2/2024, P.4
|
|
Keywords: Metrology, Integration, Advanced manufacturing |
Abstract : The transition from conventional standalone metrology to integrated metrology has been accelerating in advanced manufacturing over the past decade.
This keynote paper defines the concept of integrated metrology, which extends beyond parts inspection and encompasses processes and manufacturing
equipment to enhance efficiency and productivity. The paper presents the characteristics, benefits, constraints, and future possibilities of integrated
metrology for parts, processes, and equipment. It also includes a classification of the physical quantities of measurands, the corresponding measuring
instruments, data and communication methods, uncertainty, and traceability. The paper also discusses future challenges and emerging trends.
|
STC S |
|
Surface conditioning in cutting and abrasive processes
|
|
Volker Schulze (2), Jan Aurich (1), I.S. Jawahir (1), Bernhard Karpuschewski (1), Jiwang Yan (2)
|
|
STC S, 73/2/2024, P.5
|
|
Keywords: Cutting, Sensor Monitoring, Control, Surface Integrity |
Abstract : Cutting and abrasive processes affect the surface layer state of the components treated. This determines their performance in service. An adjustment of
the surface layer properties would allow for enhanced performance. This paper introduces the influences of named processes on the surface layer state
and their systematics. Models and sensor concepts for surface conditioning are described and combined to soft sensors which are the basis for active
control within the processes. A validation study and actual applications of the conditioning concept are shown, allowing for further technological and
scientific understanding of surface conditioning and its contribution to material and energy efficiency.
|
