Prediction of unit process life cycle inventory (UPLCI) energy consumption in a friction stir weld

2015 ◽  
Vol 18 ◽  
pp. 46-54 ◽  
Author(s):  
Amber Shrivastava ◽  
Michael Overcash ◽  
Frank E. Pfefferkorn
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Life Cycle Inventory ◽  
Friction Stir Weld ◽  
Unit Process ◽  
Friction Stir

scholarly journals Energy consumption model of plasma spraying based on unit process life cycle inventory

2020 ◽  
Vol 9 (6) ◽  
pp. 15324-15334 ◽  
Author(s):  
Liming Wang ◽  
Xueju Ran ◽  
Yanle Li ◽  
Fangyi Li ◽  
Jing Liu ◽  
...  
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Plasma Spraying ◽  
Life Cycle Inventory ◽  
Unit Process ◽  
Energy Consumption Model ◽  
Consumption Model

Unit Process Life Cycle Inventory Models of Hot Forming Processes

2013 ◽  
Author(s):  
Jennifer J. Buis ◽  
John W. Sutherland ◽  
Fu Zhao
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Process Improvement ◽  
Life Cycle Inventory ◽  
Sustainable Manufacturing ◽  
Hot Forming ◽  
Process Conditions ◽  
Machining Processes ◽  
Unit Process ◽  
Starting Point

Life cycle assessment (LCA) is a widely used tool to evaluate the environmental profile of a product or process, and can serve as a starting point for product and process improvement. Using LCA to support sustainable product design and sustainable manufacturing has recently attracted increasing interest. Unfortunately, the available life cycle inventory databases have very limited coverage of manufacturing processes. To make matters worse, the available datasets are either highly aggregated or consider only selected processes and process conditions. In addition, in the case of the latter, the data provided may be based on limited measurements or even just estimates. This raises questions on applicability of these databases to manufacturing process improvement where different operating parameters and conditions are adopted. Recently a novel methodology called “unit process life cycle inventory” or “uplci” has been proposed to address these issues, and models for several machining processes (e.g., turning, milling, and drilling) and joining (e.g, submerged arc welding) have been developed. This paper follows the uplci approach and develops models for a series of hot forming processes, including billet heating, performing, and indirect extrusion. It is shown that the model predictions on energy consumption are in good agreement with data measured on a production line. For hot forming processes, the results suggest that billet heating dominates the overall energy consumption and the carbon footprint relative to the deformation steps.

Machine-Specific Energy Estimation Using the Unit Process Life Cycle Inventory (UPLCI) Model

2020 ◽  
Author(s):  
Johan Thoft Krogshave ◽  
Till Boettjer ◽  
Devarajan Ramanujan
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Machine Tool ◽  
Specific Energy ◽  
Life Cycle Inventory ◽  
Estimation Errors ◽  
Workpiece Material ◽  
Energy Estimation ◽  
Unit Process ◽  
Adjustment Factors

Abstract This paper discusses a method for machine-specific energy estimation in milling processes using the unit process life cycle inventory (UPLCI) model. To this end, we develop a standard methodology for constructing an adjusted UPLCI model that includes adjustment factors for uncertainties in machine tool specifications and the specific cutting energy of a workpiece material. The adjustment factors are calculated through experimental measurement of energy consumption for a standard test part on a specific machine tool. To validate the adjusted UPLCI model, we conducted a case study which experimentally measured the energy consumption for machining three parts made of Aluminum 6082 on a Chevalier QP2040-L three-axis vertical milling machine. Results show that the UPLCI model consistently overestimated the total energy consumption for machining the three parts and had significant estimation errors (314%, 499%, 286%). The largest sources of error in the UPLCI model were from overestimating the idle and basic power consumption of the machine tool. The adjusted UPLCI model significantly reduced the estimation errors for the same tests (27%, 0.3%, 36%).

Reusable unit process life cycle inventory for manufacturing: grinding

2017 ◽  
Vol 11 (6) ◽  
pp. 643-653 ◽  
Author(s):  
Barbara Linke ◽  
Michael Overcash
Keyword(s):  
Life Cycle ◽  
Life Cycle Inventory ◽  
Unit Process

Production Chains of Soft-Weak Stones: Life Cycle Inventory of Techniques and Technologies

2020 ◽  
Vol 848 ◽  
pp. 137-144
Author(s):  
Isabella Bianco ◽  
Gian Andrea Blengini
Keyword(s):  
Supply Chain ◽  
Life Cycle ◽  
Life Cycle Inventory ◽  
Raw Materials ◽  
Cutting Tools ◽  
Secondary Data ◽  
Primary Data ◽  
Dimension Stone ◽  
Unit Process ◽  
Processing Plants

The dimension stone sector is more and more active in developing new solutions to improve the sustainability of its supply chain, partly as a consequence of the current EU policies on Circular Economy and Raw Materials. The Life Cycle Assessment (LCA) is a recognized scientific tool for evaluating environmental impacts of the processes. Nevertheless, in the stone sector, LCA is hindered by the scarce availability of Life Cycle Inventory (LCI) datasets for the specific processes of the stone supply chain. This paper provides LCI datasets of the most common and widespread techniques and related technologies for quarrying, cutting and finishing soft-weak stones. To this aim primary data were collected in Italian marble quarries and processing plants and in companies producing cutting tools. When necessary, industry data were complemented with secondary data from literature. High replicability and flexibility of the datasets is obtained through the provision of Unit process inventories for each technology/technique and through the set of parameters. In addition, the uncertainty of the resulting LCI datasets has been evaluated with the well-established procedure of Ecoinvent pedigree matrix. The availability of these datasets contributes to the population of Life Cycle databases and is expected to boost the measurement and enhancement of the key aspects of sustainability in the stone sector.

Reusable unit process life cycle inventory for manufacturing: stereolithography

2019 ◽  
Vol 13 (6) ◽  
pp. 675-684 ◽  
Author(s):  
Timothy Simon ◽  
Yiran Yang ◽  
Wo Jae Lee ◽  
Jing Zhao ◽  
Lin Li ◽  
...  
Keyword(s):  
Life Cycle ◽  
Life Cycle Inventory ◽  
Unit Process
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