Beyond Life Cycle Assessment, an Integrative Design for Environment Approach for the Automotive Industry

1998 ◽  
Author(s):  
Kai Hockerts ◽  
Stephanie Adda ◽  
Helene Teulon ◽  
David Dowdell ◽  
Neil Kirkpatrick ◽  
...  
2021 ◽  
Author(s):  
Archimede Forcellese ◽  
Tommaso Mancia ◽  
Michela Simoncini ◽  
Serena Gentili ◽  
Marco Marconi ◽  
...  

Advanced materials, especially carbon fiber reinforced composites (CFRP), have gained the attention of different industries whichproduce lightweight and high-performance components. The most used manufacturing processes to realize these kinds of products are Resin Transfer Molding (RTM) and vacuum bag molding with autoclave curing. RTM is based on dry fiber technology and it appears the most promising manufacturing process to realized high-quality carbon fiber parts reducing cost and manufacturing time, especially if high pressure variants are employed. On the other hand, vacuum bag molding with autoclave curing is a very consolidated process which is, however, associated with long manufacturing time and costs as well as to low repeatability of the process due to the high labor input. Out-of-autoclave methods, such as pressure bag molding (PBM) have been developed to overcome the issues of vacuum bag molding process. From the environmental point of view, the manufacturing of CFRP components is associated with high environmental loads due to the impacts related to both raw materials and manufacturing processes. For this reason, reducing the energy consumption of production phases can lead to the development of greener CFRP products. In this context, the main scope of the present research is to evaluate and compare the environmental loads of a component for the automotive industry realized exploiting the RTM, the PBM and the bag molding processes to determine which one is eco-friendlier. This analysis has been conducted following the standard Life Cycle Assessment methodology based on a “cradle to gate” approach. In this way, the use phase and the disposal of the CFRP component have not been included in the analysis. Results have been evaluated by comparing the equivalent CO2 related to each manufacturing process.


2003 ◽  
Vol 8 (6) ◽  
pp. 379-381 ◽  
Author(s):  
Matthias Finkbeiner ◽  
Stephan Krinke ◽  
Dirk Oschmann ◽  
Thomas Saeglitz ◽  
Siegfried Schaper ◽  
...  

1996 ◽  
Vol 1 (1) ◽  
pp. 15-21 ◽  
Author(s):  
Konrad Saur ◽  
Johannes Gediga ◽  
Jens Hesselbach ◽  
Manfred Schuckert ◽  
Peter Eyerer

2019 ◽  
Vol 10 (4) ◽  
pp. 454-468 ◽  
Author(s):  
Salvinder Singh ◽  
Shahrum Abdullah

Purpose The purpose of this paper is to present the durability analysis in predicting the reliability life cycle for an automobile crankshaft under random stress load using the stochastic process. Due to the limitations associated with the actual loading history obtained from the experimental analysis or due to the sensitivity of the strain gauge, the fatigue reliability life cycle assessment has lower accuracy and efficiency for fatigue life prediction. Design/methodology/approach The proposed Markov process embeds the actual maximum and minimum stresses by a continuous updating process for stress load history data. This is to reduce the large credible intervals and missing loading points used for fatigue life prediction. With the reduction and missing loading intervals, the accuracy of fatigue life prediction for the crankshaft was validated using the statistical correlation properties. Findings It was observed that fatigue reliability corresponded well by reporting the accuracy of 95–98 per cent with a mean squared error of 1.5–3 per cent for durability and mean cycle to failure. Hence, the proposed fatigue reliability assessment provides an accurate, efficient, fast and cost-effective durability analysis in contrast to costly and lengthy experimental techniques. Research limitations/implications An important implication of this study is durability-based life cycle assessment by developing the reliability and hazard rate index under random stress loading using the stochastic technique in modeling for improving the sensitivity of the strain gauge. Practical implications The durability analysis is one of the fundamental attributes for the safe operation of any component, especially in the automotive industry. Focusing on safety, structural health monitoring aims at the quantification of the probability of failure under mixed mode loading. In practice, diverse types of protective barriers are placed as safeguards from the hazard posed by the system operation. Social implications Durability analysis has the ability to deal with the longevity and dependability of parts, products and systems in any industry. More poignantly, it is about controlling risk whereby engineering incorporates a wide variety of analytical techniques designed to help engineers understand the failure modes and patterns of these parts, products and systems. This would enable the automotive industry to improve design and increase the life cycle with the durability assessment field focussing on product reliability and sustainability assurance. Originality/value The accuracy of the simulated fatigue life was statistically correlated with a 95 per cent boundary condition towards the actual fatigue through the validation process using finite element analysis. Furthermore, the embedded Markov process has high accuracy in generating synthetic load history for the fatigue life cycle assessment. More importantly, the fatigue reliability life cycle assessment can be performed with high accuracy and efficiency in assessing the integrity of the component regarding structural integrity.


Author(s):  
Kelvin Kelvin

Salah satu produk yang dihasilkan oleh perusahaan jasa konstruksi adalah produk railing, dimana produk railing merupakan produk konstruksi pendukung bangunan yang berfungsi sebagai pembatas bangunan dengan bahan utama berupa material besi. Untuk dapat menghasilkan produk tersebut, diperlukan tahapan proses yang dimana setiap tahapan proses tersebut akan memberikan dampak terhadap lingkungan yang tidak dapat terlihat secara langsung. Dampak lingkungan tersebut dapat berupa pengaruh terhadap kesehatan manusia, ekosistem, dan sumber daya alam. Untuk itu dalam penelitian ini, dilakukan penilaian dampak lingkungan dari produk railing, serta perbaikan produk untuk mengurangi dampak lingkungan yang dihasilkan. Metode yang digunakan dalam penelitian ini adalah Life Cycle Assessment (LCA) dengan menggunakan bantuan software SimaPro, serta Metode Design for Environment (DFE) untuk perbaikan produk. Hasil yang didapatkan dari perbaikan produk railing pada penelitian ini adalah mampu mengurangi dampak lingkungan, dengan rincian 60,2% untuk dampak kesehatan manusia, 65,8% untuk dampak ekosistem, dan 53,2% untuk dampak sumber daya alam.


Resources ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 146 ◽  
Author(s):  
Karlewski ◽  
Lehmann ◽  
Ruhland ◽  
Finkbeiner

Identifying social impacts along the life cycle of their products is becoming increasingly important for companies. Social Life Cycle Assessment (SLCA) as a possible tool has not been conducted so far within industries with complex international supply chains using mainly company-specific data. As a novelty, this work presents a practical SLCA approach along with the first case studies for the automotive industry, based on a previously developed indicator set and an extensive data collection. Social data was collected from companies along the life cycle of two specific car components, while analyzing data availability, validity and comparability. To obtain product references, both a top-down and a bottom-up approach for quantitative indicators based on time effort and data availability on the process level were devised. Also, two options were developed for how qualitative indicators (e.g., written principles for Corruption) can be applied together with quantitative performance indicators (e.g., number of accidents). The general practical applicability of the approach could be demonstrated by four quantitative and seven qualitative indicators. It is a first step towards analyzing the social performance of products with complex supply chains on a company level. Remaining challenges/limitations include social data availability and quality and obtaining data at the process level (allocation) and should be addressed in future studies.


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