scholarly journals Weakness Ranking Method for Subsystems of Heavy-Duty Machine Tools Based on FMECA Information

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhaojun Yang ◽  
Jinyan Guo ◽  
Hailong Tian ◽  
Chuanhai Chen ◽  
Yongfu Zhu ◽  
...  
Keyword(s):  
Machine Tools ◽  
Ranking Method ◽  
Maintenance Cost ◽  
Heavy Duty ◽  
Ranking Methods ◽  
Failure Data ◽  
Mode Effect ◽  
Electromechanical Products ◽  
Order Preference ◽  
Best Worst Method

AbstractHeavy-duty machine tools are composed of many subsystems with different functions, and their reliability is governed by the reliabilities of these subsystems. It is important to rank the weaknesses of subsystems and identify the weakest subsystem to optimize products and improve their reliabilities. However, traditional ranking methods based on failure mode effect and critical analysis (FMECA) does not consider the complex maintenance of products. Herein, a weakness ranking method for the subsystems of heavy-duty machine tools is proposed based on generalized FMECA information. In this method, eight reliability indexes, including maintainability and maintenance cost, are considered in the generalized FMECA information. Subsequently, the cognition best worst method is used to calculate the weight of each screened index, and the weaknesses of the subsystems are ranked using a technique for order preference by similarity to an ideal solution. Finally, based on the failure data collected from certain domestic heavy-duty horizontal lathes, the weakness ranking result of the subsystems is obtained to verify the effectiveness of the proposed method. An improved weakness ranking method that can comprehensively analyze and identify weak subsystems is proposed herein for designing and improving the reliability of complex electromechanical products.

scholarly journals Comparative method of moora, copras and topsis based on weighting of best worst method in supplier selection at ABC mining companies in Indonesia

2020 ◽  
Vol 19 (2) ◽  
pp. 890
Author(s):  
Ryco Puji Setyono ◽  
Riyanarto Sarno
Keyword(s):  
Delphi Method ◽  
Supplier Selection ◽  
Comparative Method ◽  
Multi Objective Optimization ◽  
Ranking Methods ◽  
Quality Cost ◽  
Mining Companies ◽  
Order Preference ◽  
Copras Method ◽  
Best Worst Method

<p>Supplier selection is essential to the business. The risks posed by suppliers will have a significant impact on the company's performance. Each business has distinct supplier features to mitigate this.These characteristics are divided into criteria in supplier selection. In this study, the criteria in supplier selection will be weighted by Best Worst Method (BWM) and comparing the three ranking methods, Complex Proportional Assessment (COPRAS), Multi-Objective Optimization berdasarkan Analisis Rasio (MOORA) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The sample in this study is an ABC manufacturing company engaged in mining from Indonesia. From the results of the study, there were 16 criteria using the Delphi Method. These criteria are divided into four main criteria, namely service, quality, cost and time. From the results of weighting BWM, the price sub criteria on cost criteria have the greatest weight for ABC companies. The results of the weighting are then carried out by supplier ranking by comparing the COPRAS, MOORA and TOPSIS approaches. In comparing these three methods, approaches are used based on accuracy and complexity. The COPRAS method has the highest accuracy and lowest complexity according to the ABC company.</p>

scholarly journals Failure Analysis for Hydraulic System of Heavy-Duty Machine Tool with Incomplete Failure Data

2021 ◽  
Vol 11 (3) ◽  
pp. 1249
Author(s):  
Shizheng Li ◽  
Zhaojun Yang ◽  
Hailong Tian ◽  
Chuanhai Chen ◽  
Yongfu Zhu ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Machine Tools ◽  
Hydraulic System ◽  
Rough Set Theory ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Weak Links ◽  
Heavy Duty ◽  
Tree Analysis ◽  
Failure Data

A hydraulic system is a key subsystem of heavy-duty machine tools with a high failure intensity, the failure of which often causes shutdown of production and economic loss in machining. Therefore, it is necessary to implement failure analysis to identify the weak links of system and improve the reliability. For hydraulic system, there is often an amount of failure data collected in field, which help to calculate the occurrence probability of basic events through fault tree analysis method. However, the data are incomplete and uncertain. To address this issue, this study presents a fault tree analysis methodology. Experts’ opinions are utilized, combined with field data based on the Dempster–Shafer theory and rough set theory to fill the incompleteness and eliminate the uncertainty. For application in a case study, a fault tree of the hydraulic system of heavy-duty machine tools is firstly constructed. Then, the importance analysis is performed to help identify the weak links of hydraulic system. The results show the critical basic events affecting the safety and reliability of a hydraulic system.

Design and Test of a Novel Sliding Guideway with Oily-Porous Joint for Heavy-Duty Machine Tools

2018 ◽  
Vol 11 (2) ◽  
pp. 119-126
Author(s):  
Chongnian Qu ◽  
Shaohua Guo ◽  
Xuyan Liu ◽  
Zhiguo Zhong ◽  
Mingyue Cui ◽  
...  
Keyword(s):  
Machine Tools ◽  
Heavy Duty

Towards less energy intensive heavy-duty machine tools: Power consumption characteristics and energy-saving strategies

Energy ◽  
2019 ◽  
Vol 178 ◽  
pp. 263-276 ◽  
Author(s):  
Zhendong Shang ◽  
Dong Gao ◽  
Zhipeng Jiang ◽  
Yong Lu
Keyword(s):  
Power Consumption ◽  
Energy Saving ◽  
Machine Tools ◽  
Heavy Duty

Temperature Variables Selection for Thermal Error Modeling of Heavy-Duty CNC Milling-Boring Machine Tools

2011 ◽  
Vol 188 ◽  
pp. 171-174
Author(s):  
Gang Wei Cui ◽  
D. Gao ◽  
L. Wang ◽  
Y.X. Yao
Keyword(s):  
Machine Tools ◽  
Thermal Error ◽  
Error Modeling ◽  
Cnc Milling ◽  
Heavy Duty ◽  
Thermal Error Modeling ◽  
Selection Strategies ◽  
Variables Selection ◽  
Selection For ◽  
Feed Axis

One of the difficult issues in thermal error modeling is to select appropriate temperature variables. In this paper, two selection strategies are introduced to overcome this difficulty. After measuring the temperatures and thermal errors of a heavy-duty CNC milling-boring machine tool by a laser tracker, four temperature variables which are the foundation of thermal error modeling are selected for each feed axis from fifteen temperature variables according to major factor strategy and non-interrelated strategy.

Comparison of Different Ranking Methods in Wine Tasting

2017 ◽  
Vol 12 (2) ◽  
pp. 203-210 ◽  
Author(s):  
Jing Cao ◽  
Lynne Stokes
Keyword(s):  
Game Theory ◽  
Rank Order ◽  
Ranking Method ◽  
The Other ◽  
Ranking Methods ◽  
Squared Error Loss ◽  
The Third ◽  
Squared Error ◽  
Suitable Measure ◽  
Jel Classifications

AbstractIn this paper, we compare three ranking methods in wine tasting in terms of their respective accuracy levels. The first two are the original-score average and rank average, which are conventional methods in practice. The third is a relatively new ranking method called Shapley ranking. It is a game-theory-based ranking method, whereby judges are required not to rank order or score all the wines but only to choose a subset that they find meritorious. A simulation study is designed, wherein the data-generating scheme mimics how the real wine-tasting data are produced. We also consider two criteria in the comparison: the squared-error loss, which is a suitable measure when accurate ranking of all wines is of interest; and the percentile loss, which only considers whether the wines are correctly put in a certain subset. The main conclusion from our study is that the ranking based on score average is generally more accurate than that based on rank average. Shapley ranking, with the consideration that it puts less burden on judges in wine tasting, may outperform the other methods in certain conditions. (JEL Classifications: C11, C15, D72, D81)

scholarly journals Constructing a Reliable Health Indicator for Bearings Using Convolutional Autoencoder and Continuous Wavelet Transform

2020 ◽  
Author(s):  
Mohammadreza Kaji ◽  
Jamshid Parvizian ◽  
Hans Wernher van de Venn
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Degradation Process ◽  
Remaining Useful Life ◽  
Data Driven ◽  
Maintenance Cost ◽  
Continuous Wavelet ◽  
Health Indicator ◽  
Failure Data ◽  
Convolutional Autoencoder

Estimating the remaining useful life (RUL) of components is a crucial task to enhance the reliability, safety, productivity, and to reduce maintenance cost. In general, predicting the RUL of a component includes constructing a health indicator (HI) to infer the current condition of the component, and modelling the degradation process, to estimate the future behavior. Although many signal processing and data-driven based methods were proposed to construct the HI, most of the existing methods are based on manual feature extraction techniques, and need the prior knowledge of experts, or rely on a large amount of failure data. Therefore, in this study, a new data-driven method based on the convolutional autoencoder (CAE) is presented to construct the HI. For this purpose, the continuous wavelet transform (CWT) technique is used to convert the raw acquired vibrational signals into a two-dimensional image; then, the CAE model, which learns the healthy operation data distribution, is used to construct the HI. The proposed method is tested on a benchmark bearing dataset and compared with several other traditional HI construction models. Experimental results indicate that the constructed HI exhibits a monotonically increasing degradation trend and has a good performance to detect incipient faults.

scholarly journals O41: JOURNAL RANKING METHODS AND THEIR APPLICATION IN GENERAL SURGERY - A SYSTEMATIC REVIEW

2021 ◽  
Vol 108 (Supplement_1) ◽  
Author(s):  
SR Arshad ◽  
ER Gallivan ◽  
H Skinner ◽  
J Kerry ◽  
JR Burke ◽  
...  
Keyword(s):  
Impact Factor ◽  
Objective Assessment ◽  
Ranking Method ◽  
Systematic Search ◽  
Journal Ranking ◽  
Ranking Methods ◽  
Academic Surgery ◽  
Ovid Medline ◽  
Based Medicine ◽  
Scimago Journal Rank

Abstract Introduction Bibliometrics enable the objective assessment of a journals quality and prestige, making them vital to academic surgical integrity. This paper systematically reviews the evidence for current journal-ranking platforms. Method An initial systematic search identified published journal bibliometrics on 5th November 2019. Studies assessing journal bibliometrics were identified through a second systematic search through OVID Medline database (PROSPERO:159689) on 18th November 2019. Non-English papers and those solely referring to author and institutional ranking methods were excluded. A coding framework was developed to assess strengths and limitations of journal bibliometrics. Result The systematic search returned 2480 articles. All abstracts were reviewed leaving 474 for full assessment. 306 papers were included in the final synthesis. 12 journal bibliometrics were identified. SCImago Journal Rank (SJR) was deemed the most robust journal ranking method. Impact Factor (IF) is the most commonly used but has clear limitations. Altmetrics are likely to become more important. Ranking the Top 25 general surgical journals using SJR and IF results in clear discordance. Conclusion Impact Factor is susceptible to manipulation by journals putting its reliability into question. This has huge implications for academic surgery, the appraisal of evidence and its downstream assessment for inclusion into clinical guidelines and practice. SJR is more robust and it is recommended that this ranking method is adopted by the academic surgical community going forward. Take-home message The widely used Impact Factor can be manipulated by journals, which has implications for academic surgery and evidence-based medicine. SCImago Journal Rank is more robust and should be adopted by the academic surgical community.

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