Establishing Relationships Between Manufacturing Sustainability and Performance

2010 ◽  
Author(s):  
Matthew Johnson ◽  
Delcie Durham
Keyword(s):  
Life Cycle ◽  
Environmental Impact ◽  
Removal Rate ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Feed Speed ◽  
Productivity Cost ◽  
Full Life Cycle ◽  
Time Basis ◽  
And Performance

The current LCA methods assess a product’s sustainability over its full life cycle, cradle-to-grave. While the number(s) obtained detail the contributions a process makes to a product in terms of energy intensity or the generation of wastes, it is insufficient to optimize a process for both sustainability and performance objectives. The Economic Input/Output Life Cycle Analysis (EIO-LCA) was used to investigate whether metrics could be identified which address sustainability — performance issues in materials processing. This method lends itself to the assessment of processes on a unit time basis while allowing for calculation of resources used and byproducts expelled. Productivity of manufacturing processes is also based on time. For example, material removal rate is related to processing feed, speed, and the geometry and tolerances established during design. A scaled waterjet cutting process was tested to investigate the unit time relationships. The EIO-LCA was conducted and the subsequent environmental impact in the form of total energy consumed and equivalent CO2 expelled evaluated per unit time, establishing the relationship to cutting speed. Although this is a static LCA at set conditions, it suggests that relationships can be explored between the regulation of resources, productivity, cost and environmental impact by varying the processing parameters.

Research on the Concept of Controlled Speed Based on Cutting Band Saw

2013 ◽  
Vol 584 ◽  
pp. 45-49
Author(s):  
Ying Chun Xue
Keyword(s):  
Removal Rate ◽  
Cutting Speed ◽  
Machine Design ◽  
Feed Speed ◽  
Cutting Efficiency ◽  
The Past ◽  
Equation Solving ◽  
Cutting Machine ◽  
Band Saw ◽  
Core Problem

Speed control is the core problem of cutting machine design, the past has been the experience of adjusting the cutting speed, the lack of theoretical basis, randomness. In view of this, according to the basic requirements of cutting efficiency maximization, deduces the removal rate and feed speed, time equation, solving the cutting efficiency problem exists in the design of machine, and established when the removal rate is constant, relation curves of shear rate and time. Use of the method of cutting machine design, can improve the accuracy and scientific design, has higher application value.

Machining Efficiency Model Based on the Multiple Regression Theory in Turning Glass Ceramics

2012 ◽  
Vol 201-202 ◽  
pp. 1092-1095
Author(s):  
Lian Jie Ma ◽  
Ai Bing Yu ◽  
Ya Dong Gong
Keyword(s):  
Prediction Model ◽  
Multiple Regression ◽  
Removal Rate ◽  
High Reliability ◽  
Cutting Speed ◽  
Glass Ceramics ◽  
Least Square Method ◽  
Least Square ◽  
Feed Speed ◽  
Tools Wear

The materials removal rate (V/VB) was selected to be objective function. It is comprehensive parameter about materials and tools wear. Through turning glass ceramics experimentation, the materials removal influence of cutting speed, cutting depth and feed speed were study. Based on least square method, the multiple regression prediction model of materials removal rate was built. And the model was tested. It was applied to predictive and control. The results indicated: this model was well to express materials removal law in turning glass ceramics. The multiple regression prediction model is high remarkable. The prediction value was coincident with measure value. This model is high reliability. So, expect materials removal rate can been obtained by this model, and choosing the technological parameter can been guided.

scholarly journals Influence of machining parameters on surface texture of Inconel 718 after grinding with multi-granular wheels

2019 ◽  
Vol 91 (3) ◽  
Author(s):  
Adrian Kopytowski ◽  
Rafał Świercz ◽  
Rafał Nowicki ◽  
Grigor Stambolov
Keyword(s):  
Surface Texture ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Feed Speed ◽  
Machining Parameters ◽  
Exploratory Research ◽  
Machining Processes ◽  
Advanced Machining ◽  
Machine Elements

Requirements currently imposed on machine elements are constantly growing. It requires to develop new, advanced machining processes. One of the commonly used finishing process is grinding. The article presents the results of the exploratory research in the process of surface grinding with abrasive multigrain wheels of samples made of Inconel 718. The influence of input parameters was investigated: cutting speed Vc, transverse feed speed Fp, longitudinal feed speed Fw, on roughness parameters (Sa) and the bearing capacity curve. Based on the conducted research, statistical models of the grinding process were elaborated, which allow to select the most favorable processing parameters depending on the required quality of the surface texture.

scholarly journals Bridge Carbon Emissions and Driving Factors Based on a Life-Cycle Assessment Case Study: Cable-Stayed Bridge over Hun He River in Liaoning, China

2020 ◽  
Vol 17 (16) ◽  
pp. 5953 ◽  
Author(s):  
ZhiWu Zhou ◽  
Julián Alcalá ◽  
Víctor Yepes
Keyword(s):  
Life Cycle ◽  
Environmental Impact ◽  
Building Materials ◽  
Future Research ◽  
Cable Stayed Bridge ◽  
Full Life Cycle ◽  
Global Environmental ◽  
Bridge Structures ◽  
Development Analysis

Due to the rapid growth of the construction industry’s global environmental impact, especially the environmental impact contribution of bridge structures, it is necessary to study the detailed environmental impact of bridges at each stage of the full life cycle, which can provide optimal data support for sustainable development analysis. In this work, the environmental impact case of a three-tower cable-stayed bridge was analyzed through openLCA software, and more than 23,680 groups of data were analyzed using Markov chain and other research methods. It was concluded that the cable-stayed bridge contributed the most to the global warming potential value, which was mainly concentrated in the operation and maintenance phases. The conclusion shows that controlling the exhaust pollution of passing vehicles and improving the durability of building materials were the key to reducing carbon contribution and are also important directions for future research.

scholarly journals A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study

2021 ◽  
Vol 16 (4) ◽  
pp. 443-456
Author(s):  
D.D. Trung ◽  
H.X. Thinh
Keyword(s):  
Decision Making ◽  
Surface Roughness ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Multi Criteria Decision Making ◽  
Turning Process ◽  
Decision Methods ◽  
Determination Methods

Multi-criteria decision-making is important and it affects the efficiency of a mechanical processing process as well as an operation in general. It is understood as determining the best alternative among many alternatives. In this study, the results of a multi-criteria decision-making study are presented. In which, sixteen experiments on turning process were carried out. The input parameters of the experiments are the cutting speed, the feed speed, and the depth of cut. After conducting the experiments, the surface roughness and the material removal rate (MRR) were determined. To determine which experiment guarantees the minimum surface roughness and maximum MRR simultaneously, four multi-criteria decision-making methods including the MAIRCA, the EAMR, the MARCOS, and the TOPSIS were used. Two methods the Entropy and the MEREC were used to determine the weights for the criteria. The combination of four multi-criteria making decision methods with two determination methods of the weights has created eight ranking solutions for the experiments, which is the novelty of this study. An amazing result was obtained that all eight solutions all determined the same best experiment. From the obtained results, a recommendation was proposed that the multi-criteria making decision methods and the weighting methods using in this study can also be used for multi-criteria making decision in other cases, other processes.

scholarly journals Multi-Objective Optimization of Processing Parameters for Disc-Mill Cutter Machining Blisk-Tunnel Based on GRA-RBF-FA Method

2019 ◽  
Vol 37 (1) ◽  
pp. 160-166
Author(s):  
Nan Zhang ◽  
Yaoyao Shi ◽  
Chen Yang ◽  
Zhen Chen ◽  
Jiang Liu
Keyword(s):  
Removal Rate ◽  
Rbf Neural Network ◽  
Cutting Speed ◽  
Integrated Approach ◽  
Processing Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Mill Cutter ◽  
Cutting Height ◽  
Grey Relational

The process of disc-mill cutter machining blisk-tunnel is a typical multi-input and multi-output system, therefore multi-objective optimization is applied to improve the process. In this paper, an integrated approach that Grey Relational Analysis(GRA)couples with Radial Basis Function (RBF) neural network and Firefly algorithm (FA) is used to solve the optimization problem. The aim is to satisfy the minimum cutting force and maximum material removal rate simultaneously by optimizing the cutting speed, feed rate per tooth and cutting height. The results for verifying experiment indicated that GRA-RBF-FA method can be applied to optimize the processing parameters of disc-mill cutter machining TC17 blisk-tunnel and the optimization results are superior to the GRA's.

scholarly journals Prediction of tool wear in CFRP drilling based on neural network with multicharacteristics and multisignal sources

2021 ◽  
Vol 30 ◽  
pp. 2633366X2098723
Author(s):  
Guoqiang Zhu ◽  
Shanshan Hu ◽  
Hongqun Tang
Keyword(s):  
Neural Network ◽  
Tool Wear ◽  
Cutting Speed ◽  
Polycrystalline Diamond ◽  
Vibration Signal ◽  
Processing Parameters ◽  
Drilling Process ◽  
Feed Speed ◽  
Ann Model ◽  
Energy Value

Carbon fiber-reinforced polymer (CFRP) drilling is a typical process in the aircraft industry. Because the components of CFRP are different and uneven, it is difficult to extract tool wear characteristics from the machining signals, which are composed of the processing characteristics of various materials and the tool state characteristics. The aim of this work is to present a new comprehensive approach based on multicharacteristics and multisignal sources to predict the tool wear state during CFRP drilling through a combination of a backpropagation (BP) artificial neural network (ANN) model and an efficient automatic system depending on the sliding window algorithm. It was verified that the peak factor and Kurtosis coefficient of different signals and the energy value of the d5 layer of the thrust force signal and the d3 layer of the vibration signal after wavelet decomposition were related to tool wear. Among them, the energy value of the d3 layer of the vibration signal was selected as the wear indicator and was able to describe the state of the tool during the CFRP drilling process regardless of the drilling conditions and individual tool differences. A confirmatory drilling experiment using 6-mm-diameter polycrystalline diamond twist drilling under different processing parameters was conducted to verify the ANN model based on multicharacteristics and multisignal sources. A lower feed speed and a higher cutting speed were both highly correlated with the VB value of flank wear. Drill wear accelerated because of the occurrence of adhesive wear when the number of drilled holes reached around 90. The accuracy of the neural network model is 80–87% when using the value of only one characteristic but clearly increases based on multicharacteristics and multisignal sources in real time, indicating that the BP ANN model has higher accuracy in predicting the tool state in CFRP drilling through the sensor signal fusion method.

Processing Parameters Optimization on Control of Residual Stresses and Distortion during High-Speed Milling of Thin-Walled Workpiece

2012 ◽  
Vol 531-532 ◽  
pp. 118-121
Author(s):  
Xiao Hui Jiang ◽  
Bei Zhi Li ◽  
Xiao Yan Zuo ◽  
Jian Guo Yang
Keyword(s):  
Residual Stresses ◽  
High Speed ◽  
Removal Rate ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Calculation Model ◽  
Parameters Optimization ◽  
Machining Processes ◽  
High Speed Milling ◽  
Thin Walled

In the aerospace and auto industries, the residual tensile stresses will cause the structures broke and damaged. Hence, different methods were considered to optimize the machining processes. In this article, a residual stresses calculation model using AdvantEdge 2D turning was integrated with 2D milling physical model in order to analyze high-speed milling thin-walled workpiece. Through optimizing the processing parameters (improving the cutting speed and decreasing the cutting depth) during high-speed milling, not only we can get a high removal rate and receive a distribution of equably surface residual stresses, but also a slowing down trend of in-depth residual stress can be obtained. In addition, we evaluate this method using a typical part at the sensitive area, and the machining quality can be improved obviously.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

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