Paul H. Dembinski and Christophe Perritaz
Georg Simmel reached the conclusion that evolution drives money towards an ever‐higher level of functionality while, at the same time reducing its importance as a substance. This…
Abstract
Georg Simmel reached the conclusion that evolution drives money towards an ever‐higher level of functionality while, at the same time reducing its importance as a substance. This article confronts Simmel’s one hundred‐year‐old hypothesis with the changes money has undergone since the publication of his book, The Philosophy of Money, since the 1970s. We begin by presenting the main conclusions of Simmel’s inquiry into the essence of money. We focus on his findings concerning the unstable relationship between the substance and functions of money and on the notion of money as a social institution. The second part of the article relates Simmel’s analysis to various aspects of contemporary thinking on money, and presents the “double anchor” hypothesis on the monetary order. Then, this hypothesis is used to analyse how technology‐driven processes are causing specific monetary functions to become increasingly autonomous. What this implies, in turn, is the de facto break‐up of money. For the time being, this situation has not actually arisen, but the stage‐by‐stage break‐up of money is well under way, at various speeds, and taking advantage of any available technical opportunities, especially in the field of information technology. The expected total break‐up of money poses compelling problems that call for new conceptual, technical and institutional solutions.
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Michel Coulmont, Stacey Loomis, Sylvie Berthelot and Francesco Gangi
Tao Peng, Shuangmei Xu, Hong Zhang and Yi Zhu
Many process parameters in selective laser melting (SLM) can be configured to optimize build time, which directly relates to energy consumption, and to achieve acceptable part…
Abstract
Purpose
Many process parameters in selective laser melting (SLM) can be configured to optimize build time, which directly relates to energy consumption, and to achieve acceptable part quality. This study aims to investigate whether energy can be effectively reduced with acceptable mechanical properties. The influence of exposure time is primarily focused to correlate energy consumption to mechanical properties.
Design/methodology/approach
Through single-factor design and experiment result analysis, three levels of exposure time were examined in fabricating two sets of sample parts, for energy analysis and mechanical property tests. Manufacturing power profile was measured online, and four mechanical properties, tensile, flexural, torsional strengths and part density, were investigated. A graphical growth rate tendency (GRT) plot is proposed to jointly analyze multiple variables.
Findings
Energy consumption increases in fabricating a same part with the increase of exposure time in the tested range, but exposure time was found to influence build power rather than build time in the given SLM system. Mechanical properties do not increase linearly, and grow at different rates. It is found that within the tested range, increased energy consumption brought to a small improvement of part density, but a notable improvement of tensile strength and maximum torque.
Practical implications
Producing quality SLM parts can be energy-effective through quantitative study. The proposed GRT plot is an intuitive visual aid to compare the growth rates of different variables, which offers more information to additive manufacturing practitioners.
Originality/value
In this research, energy consumption and mechanical property are jointly analyzed for the first time to advance the knowledge of energy-effective SLM fabrication. This helps additive manufacturing technology to be truly energy-efficient and environmental-friendly.
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Shakeel Dilawar, Ahsan Khan, Asif Ur Rehman, Syed Zahid Husain and Syed Husain Imran Jaffery
The purpose of this study was to use bridge curvature method (BCM) to quantify stress, while multiscale modeling with adaptive coarsening predicted distortions based on…
Abstract
Purpose
The purpose of this study was to use bridge curvature method (BCM) to quantify stress, while multiscale modeling with adaptive coarsening predicted distortions based on experimentally validated models. Taguchi method and response surface method were used to optimize process parameters (energy density, hatch spacing, scanning speed and beam diameter).
Design/methodology/approach
Laser powder bed fusion (LPBF) offers significant design freedom but suffers from residual stresses due to rapid melting and solidification. This study presents a novel approach combining multiscale modeling and statistical optimization to minimize residual stress in SS316L.
Findings
Optimal parameters were identified through simulations and validated with experiments, achieving an 8% deviation. This approach significantly reduced printing costs compared to traditional trial-and-error methods. The analysis revealed a non-monotonic relationship between residual stress and energy density, with an initial increase followed by a decrease with increasing hatch spacing and scanning speed (both contributing to lower energy density). Additionally, beam diameter had a minimal impact compared to other energy density parameters.
Originality/value
This work offers a unique framework for optimizing LPBF processes by combining multiscale modeling with statistical techniques. The identified optimal parameters and insights into the individual and combined effects of energy density parameters provide valuable guidance for mitigating residual stress in SS316L, leading to improved part quality and performance.
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Harshad Sonar, Vivek Khanzode and Milind Akarte
The purpose of this paper is to identify various factors influencing additive manufacturing (AM) implementation from operational performance in the Indian manufacturing sector and…
Abstract
Purpose
The purpose of this paper is to identify various factors influencing additive manufacturing (AM) implementation from operational performance in the Indian manufacturing sector and to establish the hierarchical relationship among them.
Design/methodology/approach
The methodology includes three phases, namely, identification of factors through systematic literature review (SLR), interviews with experts to capture industry perspective of AM implementation factors and to develop the hierarchical model and classify it by deriving the interrelationship between the factors using interpretive structural modeling (ISM), followed with the fuzzy Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis.
Findings
This research has identified 14 key factors that influence the successful AM implementation in the Indian manufacturing sector. Based on the analysis, top management commitment is an essential factor with high driving power, which exaggerates other factors. Factors, namely, manufacturing flexibility, operational excellence and firm competitiveness are placed at the top level of the model, which indicates that they have less driving power and organizations need to focus on those factors after implementing the bottom-level factors.
Research limitations/implications
Additional factors may be considered, which are important for AM implementation from different industry contexts. The variations from different industry contexts and geographical locations can foster the theoretical robustness of the model.
Practical implications
The proposed ISM model sets the directions for business managers in planning the operational strategies for addressing AM implementation issues in the Indian manufacturing sector. Also, competitive strategies may be framed by organizations based on the driving and dependence power of AM implementation factors.
Originality/value
This paper contributes by identification of AM implementation factors based on in-depth literature review as per SLR methodology and validation of these factors from a variety of industries and developing hierarchical model by integrative ISM-MICMAC approach.