Energy consideration in machining operations - towards explanatory models for optimisation results

Part of: Seliger, Günther (Ed.): Innovative solutions : proceedings / 11th Global Conference on Sustainable Manufacturing, Berlin, Germany, 23rd - 25th September, 2013. - Berlin: Universitätsverlag der TU Berlin, 2013. - ISBN 978-3-7983-2609-5 (online). - http://nbn-resolving.de/urn:nbn:de:kobv:83-opus4-40276. - pp. 153–158.This paper reports the application of a systematic research methodology for uncovering the reasons behind results obtained when energy is considered in machining optimisation. A direct search optimisation method was used as a numerical experimentation rig to investigate the reasoning behind the results obtained in applying Taguchi methods and Genetic algorithm (GA). Representative data was extracted from validated machining science equations and studied using graphical multivariate data analysis. The results showed that over 80% of reduction in energy consumption could be achieved over the recommendations from machining handbooks. It was shown that energy was non-conflicting with the cost and time, but conflicting with quality factors such as surface roughness and technical factors such as power requirement and cutting force. These characteristics of the solutions can provide an explanative motif required for practitioners to trust and use the optimisation results

An E3 ubiquitin-proteasome gene signature for predicting prognosis in patients with pancreatic cancer

Pancreatic cancer is the seventh leading cause of cancer death worldwide, which is demonstrated with remarkable resistance to radiotherapy and chemotherapy. The identification of prognosis signature and novel prognostic markers will facilitate patient stratification and an individualized precision therapy strategy. In this study, TCGA-PAAD was used to screen prognostic E3 ubiquitin ligases and establish prognostic signatures, and GEO database was used to verify the accuracy of prognostic signatures. Functional analysis, in vitro experiments and clinical cohort studies were used to analyze the function and prognostic efficacy of the target gene. An E3 ligase-based signature of 9 genes and the nomogram were developed, and the signature was proved to accurately predict the prognosis of patients with pancreatic cancer. WDR37 might be the most prognostic E3 ubiquitin ligase in pancreatic cancer, and the clinical cohort analyses suggested a tumor‐suppressive role. The results of functional analysis and in vitro experiments indicated that WDR37 may promote the degradation of TCP1 complex to inhibit tumor and improve immune cell infiltration. The E3 ligase-based signature accurately predicted the prognosis of patients with pancreatic cancer, so it can be used as a decision-making tool to guide the treatment of patients with pancreatic cancer. At the same time, WDR37, the main gene in E3PMP signature, can be used as the most prognostic E3 ubiquitin ligase in the treatment of pancreatic cancer

Sustainability consideration in machining of 2½d milled features

At present, sustainable manufacturing process has been widely demanded by manufacturing industry to address the financial pressure from increasing energy price and the political pressure from legislation on reduction of environmental impact. The motivation of this research is to reduce the environmental impact caused by high energy demand and consumption on the manufacturing process. This research addresses important issues related to the environmental impact of manufacturing operations. Through a review of literature and industrial practices, the following requirements have been identified: (i) Sustainability performance measures which can be used to effectively identify potential inefficiency, and recommend ways of improvement; (ii) Optimisation of existing manufacturing process which take energy as an additional factor in the optimisation of machining processes; and (iii) Development of new machining processes and technologies that move closer to the theoretical boundaries of energy efficiency. To address the above requirements, this project developed a set of energy prediction models and energy efficiency metrics to measure the energy usage during machining processes. The results show that energy consumption in machining 21/2D milled features can be improved by optimising the use of existing machining processes and by designing new machining processes and technologies. The characteristics of machining operations with energy considerations have been investigated using graphical multivariate data analysis techniques. A direct search method was used to conduct the optimisation procedure. This study showed that energy consumption decreases monotonically as process parameters (depth of cut, width of cut, spindle speed and feed rate) increase, and can be minimised up to 75% for machining Aluminium 7075-T6 by using Haas TM 1CE Vertical milling machine (maximum spindle speed 4,000rpm) without conflicting with cost and time under the constraints of spindle speed, cutting force and surface roughness. Typical optimisation methods have been found which can give similar results, and methods of opening up the reasoning process have been identified which enable practitioners to have more confidence in their results. An optimisation method has been proposed and tested for selecting optimal process parameters for a typical CNC milling operation resulting in the reduction of energy consumption. A scenario-based method has been developed to provide a comprehensive solution for decision makers to solve machining optimisation problems with sustainability considerations. An energy-efficient profiling toolpath strategy has also been developed to improve energy efficiency for 21/2D milled features. It was found that further reduction in energy consumption could be achieved compared to conventional cutting strategies. Finally, the developed methodologies can be integrated as a comprehensive framework into existing machining process improvement procedures to help process planners and manufacturing practitioners to improve the sustainability of manufacturing processes

Multiobjective Optimization Model for Profile Design of Hump Distributing Zone

Railway freight trains consist of many cars heading to different destinations. Hump is the special equipment that distributes cars with different destinations to different tracks in a marshalling station. In recent years, with the development of Chinese freight car technology, the axle load has risen from 21 ton to 23 ton and will rise to 27 ton in the future. Many rolling problems appear in the hump distributing zone with the application of 23-ton axle load cars, which will be exacerbated by 27-ton axle load cars. This paper proposes a multiobjective optimization model based on the angle of the hump profile design with minimizing weighted accumulating rolling time (WART) and hump height as optimization goals and uses the improved genetic algorithm NSGA-II to determine a solution. In case study, Pareto solution set is obtained, and the contrast analysis with traditional method is made

Financial Measures to Reduce Carbon Emissions in Britain, Japan and the United States: A SWOT Analysis

To mitigate global warming, China, the world’s largest greenhouse gas emitter, has set the goals of achieving carbon peak by 2030 and carbon neutrality by 2060, and financial measures could play an important role. To avoid unnecessary costs, China could learn from the experience of other countries to better understand the potential role of financial measures in achieving carbon emission reduction goals. Hence, this article adopts a SWOT analysis to compare the financial measures taken by Britain, Japan and the United States in the process of carbon emission reduction in the last twenty years. This article finds that government funds and financial innovation have contributed markedly to carbon emission reduction in those three countries. With the help of the SWOT analysis, we recommend that China take financial measures to help achieve carbon peaking and carbon neutrality goals from four aspects: formulating proper policy, regulating carbon trading market, strengthening international cooperation, and promoting innovation

A New Residual Life Prediction Method for Complex Systems Based on Wiener Process and Evidential Reasoning

A new residual life prediction method for complex systems based on Wiener process and evidential reasoning is proposed to predict the residual life of complex systems effectively. Moreover, the better maintenance strategies and decision supports are provided. For the residual life prediction of complex systems, the maximum likelihood method is adopted to estimate the drift coefficient, and the Bayesian method is adopted to update the parameters of Wiener process. The process of parameters estimation and the probability density function (PDF) of the residual life are deduced. To improve the accuracy of the residual life prediction results, the evidential reasoning (ER) is used to integrate the prediction results of Wiener process. Finally, a case study of gyroscope is examined to illustrate the feasibility and effectiveness of the proposed method, compared with fuzzy theory, which provides an important reference for the optimization of the reliability of complex systems and improvement

Corporate social responsibility disclosure, media reports, and enterprise innovation: Evidence from chinese listed companies

Given the limited response of enterprises to China’s national policy on the compulsory disclosure of corporate social responsibility (CSR), a deviation has occurred between policy orientation and reality. To explore the reasons behind this deviation, we investigated whether different types of media reports play an intermediary role in the process of CSR affecting corporate innovation based on the data of the companies listed on China’s Shenzhen Stock Exchange and Shanghai Stock Exchange from 2010 to 2019. The results show that the disclosure of CSR by the listed companies can significantly promote corporate innovation, which provides theoretical support for the national compulsory disclosure of CSR. Newspaper media reports and online media reports not only directly promote corporate innovation but also form a positive mediation path in the CSR disclosure and the promotion of corporate innovation. Further analysis shows that, among the five aspects of CSR, the disclosure of employee responsibility had the greatest effect on the corporate innovation, whereas the disclosure of social contribution responsibility only had a short-term inhibitory effect. Both newspaper media and online media reports on CSR disclosure were beneficial to corporate innovation. Positive and neutral reports may play the role of media governance to promote corporate innovation, whereas negative reports can restrain corporate innovation due to the market pressure effect produced by them, which also provides the basis for media supervision by the stat

Drivers behind energy consumption by rural households in Shanxi

Biomass is widely used by households for cooking and heating in rural China. Along with rapid economic growth over the last three decades, increasing rural households tend to use less biomass and more commercial energy such as coal and electricity. In this paper, we analyzed the key drivers behind energy consumption and switching by rural households based on survey data of energy consumption by rural households in ten villages of Shanxi province in China. Our econometric results show that income growth can induce less use of biomass and more use of coal and modern fuels. However, no evidence shows that even wealthy households has abandoned biomass use in Shanxi, mainly due to the “free” access to land and agricultural resources in these villages. Previous wealth of a household represented by house value can lead to more time spent on biomass collection. Access to land resources has positive effects on biomass use and collection. Other key variables include education, household size, the number of elderly members, and coal price. We also find huge differences between villages, indicating the importance of access to agricultural resources and markets

The Composite Impact of the Low-Carbon Development Policies in Beijing’s Urbanization: A Regional Dynamic CGE Modeling

The transition to a low-carbon economy, originated from the thinking on the energy future, climate change and sustainable development, has gained global momentum in recent decade. China in the industrialization and the urbanization process has to find an effective and inclusive strategy with policy mix for the low-carbon development. The research on the policies and planning for low-carbon development in China and as well Beijing is accordingly becoming a frontier of policy concerns. This report aims to highlight the offsetting and the synergy effects in terms of economic growth, energy consumption, and carbon emission by industry of policy pair by quantifying the impact of different low-carbon development policies. As supported by the GEF for the Second Beijing Environment Project, we take Beijing as a case to analyze counter-facturally the cost effective policy mix for low-carbon development in urbanization with a dynamic CGE model. This model is a SAM-based regional one, which follows the assumptions of energy consumption and CO2 emission by industries of the GRACE model by CICERO in Norway, the assumptions of commodity flows out-and-in of Beijing as depicted in the PRCGEM model by the IQTE Team at CASS. The policies in the designed scenarios include: (1) A flat increase in energy efficiency by industry; (2) An increase in investment in electricity industry; (3) A flat carbon tax by industry; (4) A policy pair, i.e a mix of carbon tax and investment subsidy for energy conservation and emission reduction to keep the governmental revenue neural. The conclusion is that the cost effective low-carbon development strategy should be one on the integrated application of practical policies