Currently available life cycle assessment (LCA) tools provide only a rough estimation of the environmental impact of different manufacturing operations (e.g. energy consumption). To address this limitation, a web-based and application programming interface (API) based process analysis software tools were developed to estimate the energy consumption of a computer numerically controlled (CNC) machine tool operation and to evaluate its environmental impact as a first step towards sustainable manufacturing analysis. Acceleration/deceleration of machine tool axes and the direction of axes movement were considered to estimate the total energy demand and processing time of the machine tool operation. Several tool path generation schemes were tested to analyze the energy consumption and resulting green house gas emission of CNC machine tool operation. It showed that tool path generation schemes affect the amount of energy and the processing time required to machine the same part, and location of the machining resulted in different amount and characteristics of green house gas emission.
The world-wide trend to environmental awareness is accompanied by a rising need for manufacturing technologies that spare energy and resources. The sustainability of products and processes becomes more and more a main competitive edge. However, the very essential aspect of abrasive tool design and its impact on process eco-efficiency have not been examined in a holistic view yet. Therefore this work evaluates the whole tool life from manufacturing to use phase and end-of-life. Abrasive tools have a huge variety in specifications, manufacturing steps and ingredients Therefore a framework has to be set up to evaluate tool manufacturing with a thorough investigation of main and auxiliary ingredients emissions waste and energy Tool design affects the abrasive machining process in terms of productivity workpiece quality and tool life. Relevant mechanisms of impact are discussed, evaluated and included into a suitable holistic life cycle management of abrasive tools. Not only the improvement of the single abrasive process, but moreover the process chain and leveraging effects on product performance are considered. Different scenarios for the end of life of abrasive tools conclude the life cycle management Abrasive tools are not only complex products but moreover important enablers for green manufacturing.
Combination of Speed Stroke Grinding and High Speed Grinding with Regard to Sustainability B. Linke , M. Duscha , F. Klocke , D. Dornfeld Laboratory for Manufacturing and Sustainability (LMAS) at UC Berkeley, USA Laboratory for Machine Tools and Production Engineering (WZL) at RWTH Aachen University, Germany Abstract Production engineering is under constant pressure to satisfy industrial demands for improved productivity while simultaneously achieving high workpiece quality. In addition, environmental awareness is a growing concern for production engineering to address. New technologies like speed stroke grinding represent new opportunities for increased productivity. This paper shows how the combination of speed stroke grinding and high speed machining can boost both process performance and workpiece quality. The theoretical consideration of active mechanisms is validated by experiments. The concluding discussion on energetic and environmental aspects emphasizes that only a thorough choice of process parameters leads to high process sustainability. Furthermore, lower tensile or even compressive stresses can positively leverage increased manufacturing effort to optimize the overall product life cycle. Keywords: Grinding, High-speed machining, Energy awareness 1 INTRODUCTION Production engineering is under constant pressure to satisfy industrial demands for improved productivity while also achieving high workpiece quality. Furthermore, growing environmental awareness is an additional requirement that production engineers must increasingly address. There are still several gaps in the evaluation of process eco-efficiency and material effectiveness [1]. Holistic data is hard to obtain and system boundary selection can strongly affect the assessment. Establishing a sustainable manufacturing strategy requires metrics for decision making at all levels of the enterprise. To design these metrics, the company’s goals (i.e. the concerns to address and the appropriate metric type to achieve the goals) and the scope (i.e. the appropriate geographic and manufacturing extent) have to be defined [2]. Suitable metric types include energy use, global climate change, non-renewable resource consumption, and water consumption. Grinding has been historically regarded as only a finishing operation at the end of the process chain. But abrasive processes today also offer a large potential for high performance machining. The main kinematic process parameters table speed, v w , depth of cut, a e , and grinding wheel speed, v s , have a high influence on the thermal and mechanical effects in surface grinding [3]. New technologies like speed stroke grinding represent new ways to increase productivity. This surface grinding method is pendulum grinding with increased table speeds. Advantages arise from the changing active chip formation mechanisms [4, 5, 6]. Disadvantages like high wheel wear may be resolved by combining speed stroke grinding with high speed machining and its intrinsic mechanisms to decrease chip sizes and forces [7, 8]. This paper shows promising results for enhanced process performance and workpiece quality by combining two grinding strategies. MECHANISMS IN GRINDING PROCESSES 2.1 Basic considerations The specific material removal rate, Q' w , is often used to compare different grinding processes by productivity. The specific material removal rate can be increased by changing the table or workpiece speed, v w , or the depth of cut, a e (equation (1)). Q' w = a e ⋅ v w Thermal and mechanical effects are superimposed in grinding processes and strongly affect surface integrity. The influence of fundamental parameters can be explained based on the maximum undeformed chip thickness, h cu,max (equation (2)) [9-13]. h cu, max = c gw v ⋅ w v s e 1 a ⋅ e d eq e 1 where c gw is the constant for grinding wheel topography, d eq is the equivalent grinding wheel diameter, and e 1 is an exponent based on experimental regression analysis. The grinding mechanisms can also be evaluated by the grinding energy, e c , which is calculated using the specific tangential force, F' t , the grinding wheel speed, v s , and the specific material removal rate, Q' w (equation (3)) [14]. e c = F' t ⋅ v s Q' w The grinding energy, e c , is the energy expended per unit volume of material removal, which is the sum of the energies of chip formation, e ch , friction, e fr , workpiece deformation, e def , and the kinetic energy of the chips, e kin . 2.2 Potential of speed stroke grinding The speed stroke grinding process is a promising technology with table speeds up to 200 m/min and accelerations up to 50 m/s² [6, 15]. Inasaki performed the
Determination of the life-cycle environmental and human health impacts of semiconductor logic is essential to a better understanding of the role information technology can play in achieving energy efficiency or global warming potential reduction goals. This study provides a life-cycle assessment for digital logic chips over seven technology generations, spanning from 1995 through 2010. Environmental indicators include global warming potential, acidification, eutrophication, ground-level ozone (smog) formation, potential human cancer and non-cancer health effects, ecotoxicity and water use. While impacts per device area related to fabrication infrastructure and use-phase electricity have increased steadily, those due to transportation and fabrication direct emissions have fallen as a result of changes in process technology, device and wafer sizes and yields over the generations. Electricity, particularly in the use phase, and direct emissions from fabrication are the most important contributors to life-cycle impacts. Despite the large quantities of water used in fabrication, across the life cycle, the largest fraction of water is consumed in generation of electricity for use-phase power. Reducing power consumption in the use phase is the most effective way to limit impacts, particularly for the more recent generations of logic.
As the miniaturization trend continues in the semiconductor manufacturing industry, atomic layer deposition has received much attention in recent years due to its ability to obtain atomic layer control of film growth [1][2]. ALD operates by alternating exposure of a surface to vapors of two or more chemical reactants to deposit an atomic layer film on the surface. As needed, the deposition process can be repeated to obtain a film layer for a specific thickness. ALD can deposit highly uniform and conformal thin films on extremely complex surfaces [3], and accordingly, has potential applications on a wide variety of electronic products including CMOS chips, flat panel display, optical filters, etc.[4].
Strategies to reduce energy demand in manufacturing processes are becoming necessary due to the growing concern of carbon emissions and the expected rise of electricity prices over time. To guide the development of these strategies, the results of a life-cycle energy consumption analysis of milling machine tools are first highlighted to show the effect of several factors such as degree of automation, manufacturing environment, transportation, material inputs, and facility inputs on environmental impact. An overview of design and operation strategies to reduce energy consumption is thereafter presented including the implementation of a Kinetic Energy Recovery System (KERS), a process parameter selection strategy, and a web-based energy estimation tool.
Toxic chemicals used in product design and manufacturing are grave concerns due to their toxic impact on human health. Implementing sustainable material selection strategies on toxic chemicals can substantially improve the sustainability of products in both design and manufacturing processes. In this paper, a schematic method is presented for characterizing and benchmarking the human health impact of toxic chemicals, as a visual aid to facilitate decision-making in the material selection process for sustainable design and manufacturing. In this schematic method, the human health impact of a toxic chemical is characterized by two critical parameters: daily exposure risk R and environmental persistence T. The human health impact of a toxic chemical is represented by its position in the R−T two-dimensional plot, which enables the screening and benchmarking of toxic chemicals to be easily made through comparing their relative positions in the characterization plot. A case study is performed on six toxic chemicals commonly used as solvents for cleaning and degreasing in product development and manufacturing.
Millisecond scale benzotriazole (BTA) adsorption kinetics in acidic aqueous solution containing 0.01 M glycine and 0.01 M BTA have been investigated. Chronoamperometry was used to measure current densities on the surface of a micro-copper electrode in pH 4 aqueous solutions containing 0.01 M glycine with or without 0.01 M BTA. In the presence of BTA the current density decreased as the inverse of the square root of time for a few seconds due to adsorption of BTA. At potentials above 0.4 V saturated calomel electrode the current leveled off after a second or so due to the formation of a Cu(I)BTA monolayer on the copper surface. Based on these data a governing equation was constructed and solved to determine the initial kinetics of BTA adsorption. Analysis shows that material removal during copper chemical mechanical planarization (CMP) in this slurry chemistry occurs mostly by direct dissolution of copper species into the aqueous solution rather than mechanical removal of oxidized or pure copper species and that each interaction between a pad asperity and a given site on the copper removes only a small fraction of the Cu(I)BTA species present at that site. (C) 2010 The Electrochemical Society. [DOI: 10.1149/1.3499217] All rights reserved.
Several strategies in the areas of process planning, machine design, and machine operation exist to develop green machine tools. Before exploring different solutions, a life-cycle energy analysis is first presented to guide subsequent investigation. The results of this analysis provide a range of the environmental impact of the use of machine tools in different types of manufacturing facilities. One strategy explored energy consumption reduction by process parameter selection. The specific energy of the NV1500 DCG was characterized to estimate the environmental burden of the manufacture of a standard part under various cutting conditions. Finally, we present a software solution to implement green machining strategies to aid process planning. This software is a “dashboard” program that estimates environmental impact for a given NC program.
Implementing green manufacturing, as the first step towards sustainable production, has been growing in interest and importance over the last few years. The opportunities for developing advanced manufacturing capabilities while, at the same time, reducing the impact of manufacturing on energy use, water and resource consumption and, overall, green house gas emissions and carbon footprint are numerous. This paper reviews the background, vocabulary and motivation for green manufacturing and highlights the competitive opportunities for manufacturers who embrace, seriously, this growing movement. The terms green and sustainable are defined in a manufacturing context, metrics and tools for assessing manufacturing are described, and some concrete examples of how to begin and what are others doing are given. Some of the future directions of green manufacturing are discussed.
Multiple frameworks have been developed for sustainable or green manufacturing systems and products, which can be roughly divided into life cycle assessment methodologies and life-cycle assessment standards. Methodologies include process LCA, input-output LCA, and hybrid LCA; standards include the ISO14044 standard, the US EPA Life-Cycle Engineering Standard, and various emerging greenhouse gas protocols. We discuss in this paper the differences between these frameworks, and define the specific use cases where each framework is best suited. We achieve this by looking at manufacturing systems and processes across spatial and temporal levels of complexity and assess the suitability of existing frameworks at each level. The main questions addressed are: (1) what are appropriate LCA methodologies for different scales of manufacturing? (2) how do existing standards apply across various levels of manufacturing?
A life-cycle energy consumption analysis of a Bridgeport manual mill and a Mori Seiki DuraVertical 5060 has been conducted. The use phase incorporated three manufacturing environments: a community shop, a job shop, and a commercial facility. The CO2-equivalent emissions were presented per machined part. While the use phase comprised the majority of the overall emissions, the manufacturing phase emissions were significant especially for the job shop, which is not as efficient as the other facilities due to its inherent need for flexibility. Since the Mori Seiki is heavier, the manufacturing phase of this machine tool had a greater impact on emissions than the Bridgeport. Transportation was small relative to the use phase, which was dominated by cutting, HVAC, and lighting. These results highlight areas for energy reductions in machine tool design as well as the importance of facility type to the manufacture of any product.
Recently, an increasing number of customers of the machine tool industry have applied life cycle costing (LCC) to compare the cost-effectiveness of different investment options. These concepts have mainly been used to address maintenance costs since these have proven to be one of the most important cost drivers. The approach of life cycle performance (LCP) broadens LCC by considering the relationship between the costs and benefits of a machine over its entire life cycle. With the increasing importance of environmental consciousness, it has become crucial to incorporate environmental impact when evaluating machines. A framework is presented that enables the integration of green manufacturing principles into LCP-evaluation. The role of interoperability within this framework is also discussed.
Solid state drives (SSDs) show potential for environmental benefits over magnetic data storage due to their lower power consumption. To investigate this possibility, a life-cycle assessment (LCA) of NAND flash over five technology generations (150 nm, 120 nm, 90 nm, 65 nm, and 45 nm) is presented to quantify environmental impacts occurring in flash production and to view their trends over time. The inventory of resources and emissions in flash manufacturing, electricity generation, and some chemicals are based on process data, while that of fab infrastructure, water and the remaining chemicals are determined using economic input-output life-cycle assessment (EIO-LCA) or hybrid LCA. Over the past decade, impacts have fallen in all impact categories per gigabyte. Sensitivity analysis shows that the most influential factors over the life-cycle global warming potential (GWP) of flash memory are abatement of perfluorinated compounds and reduction of electricity-related emissions in manufacturing. A limited comparison between the life-cycle energy use and GWP of a 100 GB laptop SSD and hard disk drive shows higher impacts for SSD in many use phase scenarios. This comparison is not indicative for all impact categories, however, and is not conclusive due to differences in boundary and functional unit.
Environmental assessment of photovoltaic systems is a rich field, with representations of many technologies, regions and methodologies. This paper discusses some of the factors that strongly affect the outcomes of studies, encourages detailed reporting of normalization parameters and scope, and discusses a cradle to grave framework for benchmarking life cycle assessments of photovoltaic systems.
Supply-chain greenhouse gas emissions and water scarcity are investigated as important components of sustainable manufacturing systems and a different impact reduction approach is suggested for each metric. Greenhouse gas emissions have a global impact regardless of emission location, which allows for supply-chain tradeoffs, whereas water scarcity is a local measure that is useful in predicting the long-term sustainability of a manufacturing location. Using publicly available data, greenhouse gas supply-chain tradeoffs are shown to exist between transportation distances, transportation mode, and regional electricity mix. This study sets the groundwork for designing and implementing reduced impact supply-chain networks.
Motion control in high-speed micromilling processes requires fast, accurate following of a specified curvilinear path. The accuracy with which the path can be followed is determined by the speed at which individual trajectories can be generated and sent to the control system. The time required to generate the trajectory is dependent on the representations used for the curvilinear trajectory path. In this study, we introduce the use of subdivision curves as a method for generating high-speed micromilling trajectories. Subdivision curves are discretized curves which are specified as a series of recursive refinements of a coarse mesh. By applying these recursive properties, machining trajectories can be computed very efficiently. Using a set of representative test curves, we show that with subdivision curves, trajectories can be generated significantly faster than with NURBS curves, which is the most common method currently used in generating high-speed machining trajectories. Trajectories are computed efficiently with subdivision curves as they are natively discretized, and do not require additional evaluation steps, unlike in the case of NURBS curves. The reduced trajectory generation time allows for improved performance in high-speed, high-precision micromilling. We discuss the use of several metrics to quantify the quality of the subdivision interpolation, and apply them in calculating the error during trajectory generation for the test curves.
In this work a multibody collision model, amenable to large‐scale computation, is developed to simulate a jet of near‐field grains impinging on a surface. This model is developed by computing momentum exchange for grain–grain and grain–surface interactions. The grain–grain interactions consist of collisions as well as near‐field interactions. The analysis of these flows is separated into three components: (1) volume averaged quantities; (2) average surface tractions; and (3) average outflow conditions. For the surface stress calculations, parametric studies are performed on the properties of the surface and the grains through their coefficients of restitution, the strength of the near‐field interactions, and the angle of attack of the jet. For the outflow calculations the flux of momentum through the simulation space is performed for varying near‐field forces between the grains and varying degrees of surface roughness. Copyright © 2009 John Wiley & Sons, Ltd.
The development of "green" machine tools will require novel approaches for design, production and operation for energy savings and reduced environmental impact. We describe here work on three projects: i. influence of process parameters on power consumption of end-milling using force and process time models with experimental verification. Process parameters are chosen to minimize process time since power consumed by a machine tool is essentially independent of the load and energy per unit manufactured decreases with process time; ii. KERS (kinetic energy recovery system) for machine design and modeling the integration of a recovery system into a machine tool to calculate the amount of energy that could be recovered, and whether the environmental benefits are significant; and iii. evaluation of interoperability solutions, such as MTConnect, as tools enabling a standardized "plug-and-play" platform to integrate sensors with a unified monitoring scheme to achieve improved energy performance.
Existing Life Cycle Assessment does not take into account the relative temporal differences in inventory data. The lack of such considerations could lead to an inaccurate analysis of impacts and to incorrect conclusions in the comparative studies of products with comparable inventories but different life cycle times. In this paper, we report on our research of the investigation of the embedded temporal differences in LCA, and propose a simple method to calculate the temporal space of the subject system for life cycle assessment. A case study is performed on VW Golf A4 Car based on previous LCA results. The temporal space of the vehicle, as estimated, is found to be approximately 11.04 years. We establish the emission pattern of CO2 along the time scale to demonstrate the effects of product life cycle durations on the LCA modeling and the inventory results. The life cycle inventory flow is discounted using a traditional economic discounting method with two discounting rates, 5% and 10%, respectively. The discounted results indicate that significant differences could be achieved on the life cycle inventory results.
