scholarly journals An Integrated Fuzzy Fault Tree Model with Bayesian Network-Based Maintenance Optimization of Complex Equipment in Automotive Manufacturing

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7758
Author(s):  
Hamzeh Soltanali ◽  
Mehdi Khojastehpour ◽  
José Torres Farinha ◽  
José Edmundo de Almeida e Pais
Keyword(s):  
Bayesian Network ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
Fault Tree ◽  
Operation Time ◽  
Tree Model ◽  
Automotive Manufacturing ◽  
Decision Attributes ◽  
Filling System ◽  
Optimal Maintenance

Process integrity, insufficient data, and system complexity in the automotive manufacturing sector are the major uncertainty factors used to predict failure probability (FP), and which are very influential in achieving a reliable maintenance program. To deal with such uncertainties, this study proposes a fuzzy fault tree analysis (FFTA) approach as a proactive knowledge-based technique to estimate the FP towards a convenient maintenance plan in the automotive manufacturing industry. Furthermore, in order to enhance the accuracy of the FFTA model in predicting FP, the effective decision attributes, such as the experts’ trait impacts; scales variation; and assorted membership, and the defuzzification functions were investigated. Moreover, due to the undynamic relationship between the failures of complex systems in the current FFTA model, a Bayesian network (BN) theory was employed. The results of the FFTA model revealed that the changes in various decision attributes were not statistically significant for FP variation, while the BN model, that considered conditional rules to reflect the dynamic relationship between the failures, had a greater impact on predicting the FP. Additionally, the integrated FFTA–BN model was used in the optimization model to find the optimal maintenance intervals according to the estimated FP and total expected cost. As a case study, the proposed model was implemented in a fluid filling system in an automotive assembly line. The FPs of the entire system and its three critical subsystems, such as the filling headset, hydraulic–pneumatic circuit, and the electronic circuit, were estimated as 0.206, 0.057, 0.065, and 0.129, respectively. Moreover, the optimal maintenance interval for the whole filling system considering the total expected costs was determined as 7th with USD 3286 during 5000 h of the operation time.

scholarly journals An Integrated Fuzzy Fault Tree Model With Bayesian Network-based Maintenance Optimization of Complex Equipment in Automotive Manufacturing

2021 ◽  
Author(s):  
Hamzeh Soltanali ◽  
Mehdi Khojastehpour ◽  
José Torres Farinha
Keyword(s):  
Bayesian Network ◽  
Manufacturing Systems ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Model ◽  
Static Structure ◽  
Automotive Manufacturing ◽  
Knowledge Based ◽  
Complexity Issue ◽  
Complex Equipment

Knowledge-based approaches are useful alternatives to predict the Failure Probability (FP) coping with the insufficient data, process integrity, and complexity issue in manufacturing systems. This study proposes a Fault Tree Analysis (FTA) approach as proactive knowledge-based technique to estimate the FP based maintenance planning with subjective information from domain experts. However, the classical-FTA still suffers from uncertainty and static structure limitations which poses a substantial dilemma in predicting FP. To deal with the uncertainty issues, a Fuzzy-FTA (FFTA) model was developed by statistical analysing the effective attributes such as experts' trait impacts, scales variation and, assorted membership and defuzzification functions. Besides, a Bayesian Network (BN) theory was conducted to overcome the static limitation of classical-FTA. The results of FFTA model revealed that the changes in decision attributes were not statistically significant on FP variation while BN model considering conditional rules to reflect the dynamic relationship between events had more impact on predicting FP. After all, the integrated FFTA-BN model was used in the optimization model to find the optimal maintenance intervals according to estimated FP and the total expected cost. As a practical example, the proposed model was implemented in a semi-automatic filling system in an automotive production line. The outcomes could be useful for upgrading the availability and safety of complex equipment in manufacturing systems.

An investigation into manufacturing performance achievements accrued by Indian manufacturing organization through strategic 5S practices

2018 ◽  
Vol 67 (4) ◽  
pp. 754-787 ◽  
Author(s):  
Jugraj Singh Randhawa ◽  
Inderpreet Singh Ahuja
Keyword(s):  
Lean Manufacturing ◽  
Manufacturing Industry ◽  
Service Industry ◽  
Manufacturing Sector ◽  
Successful Implementation ◽  
Automotive Manufacturing ◽  
Content Type ◽  
Manufacturing Performance ◽  
Improvement Programs ◽  
Manufacturing Organization

Purpose The purpose of this paper is to evaluate the quantitative and qualitative benefits accrued by an Indian automotive parts industry through strategic 5S implementation initiatives. Design/methodology/approach The study involves evaluation of steps involved in systematic implementation of 5S program methodology in an automotive manufacturing organization and investigation of achievements accrued by the industry through the successful implementation of 5S program. Findings The empirical results of the study have revealed that effective practice of 5S program brings considerable level of improvements in the quality, production, cost optimizations, employee’s morale values and work culture in the manufacturing industry. The industry accrued both tangible and non-tangible benefits through the holistic adoption of 5S principals. 5S principals have been envisioned to further support other quality improvement programs like lean manufacturing initiatives of the organizations. Research limitations/implications The limitation of the study is that this research has been carried out in only manufacturing industry while similar study will be conducted in the service industry also. Originality/value Global competition in the manufacturing sector has provided necessary impetus for manufacturing organizations for affecting continuous improvements in manufacturing performance for achieving sustainability and profitability in the competitive market. 5S implementation is the fundamental tool for the overall achievements in both quantitative and qualitative performance enhancements in the manufacturing as well as service organizations.

M. A. Ayuh. Made in Jamaica: The Development of Manufacturing Sector. Baltimore: The Johns Hopkins University Press. 1981. xxii+128 pp.

1986 ◽  
Vol 25 (1) ◽  
pp. 93-95
Author(s):  
Najam-us- Saqib
Keyword(s):  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
Policy Makers ◽  
Industrial Base ◽  
Johns Hopkins University ◽  
Key Characteristics ◽  
The World ◽  
Caribbean Country ◽  
Bauxite Ore ◽  
Made In

Jamaica, known in the world for her rich deposits of bauxite ore, is a small Caribbean country with an area of 10991 square kilometers and a population of just over two million individuals. This beautifu11and, which was described by Columbus as "The fairest isle that eyes have beheld" has developed a remarkably diversified manufacturing sector starting from a modest industrial base. Jamaica's manufacturing industry enjoyed a respectable growth rate of about 6 percent per annum during the good old days of the euphoric '50s and '60s. However, those bright sunny days ''when to live was bliss" were followed by the chilling winter of much subdued progress. The rise and fall of growth have aroused considerable interest among economists and policy• makers. The book under review probes the causes of this behaviour by analysing key characteristics of Jamaican manufacturing sector and tracing its path of evolution.

Assessing the Risk of Noncompliance in Wastewater Treatment

1992 ◽  
Vol 26 (5-6) ◽  
pp. 1411-1420 ◽  
Author(s):  
S. H. Choudhury ◽  
S. L. Yu ◽  
Y. Y. Haimes
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Fault Tree ◽  
Treatment Plant ◽  
Risk Identification ◽  
System Component ◽  
System Failure ◽  
Tree Model ◽  
Risk Quantification ◽  
Failure Probabilities

This paper presents an integrated methodology that allows determining the probability of noncompliance for a given wastewater treatment plant. The methodology applies fault-tree analysis, which uses failure probabilities of individual components, to predict the overall system failure probability. The methodology can be divided into two parts : risk identification and risk quantification. In risk identification, the key components in the system are determined by analyzing the contribution of individual component failures toward system failure (i.e., noncompliance). In risk quantification, a fault-tree model is constructed for the particular system, component failure probabilities are estimated, and the fault-tree model is evaluated to determine the probability of occurrence of the top event (i.e., noncompliance). A list can be developed that ranks critical events on the basis of their contributions to the probability of noncompliance. Such a ranking should assist managers to determine which components require most attention for a better performance of the entire system. A wastewater treatment plant for treating metal-bearing rinse water from an electroplating industry is used as an example to demonstrate the application of this methodology.

scholarly journals Mechanisms of Environmental Regulation’s Impact on Green Technological Progress—Evidence from China’s Manufacturing Sector

2021 ◽  
Vol 13 (4) ◽  
pp. 1600
Author(s):  
Weijiang Liu ◽  
Mingze Du ◽  
Yuxin Bai
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Technological Change ◽  
Environmental Protection ◽  
Technological Progress ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
The Sustainable Development ◽  
Biased Technological Change ◽  
Chinese Manufacturing Industry

As the world’s largest developing country, and as the home to many of the world’s factories, China plays a crucial role in the sustainable development of the world economy regarding environmental protection, energy conservation, and emission reduction issues. Based on the data from 2003–2015, this paper examined the green total factor productivity and the technological progress in the Chinese manufacturing industry. A slack-based measure (SBM) Malmquist productivity index was used to measure the bias of technological change (BTC), input-biased technological change (IBTC), and output-biased technological change (OBTC) by decomposing the technological progress. It also investigated the mechanism of environmental regulation, property right structure, enterprise-scale, energy consumption structure, and other factors on China’s technological progress bias. The empirical results showed the following: (1) there was a bias of technological progress in the Chinese manufacturing industry during the research period; (2) although China’s manufacturing industry’s output tended to become greener, it was still characterized by a preference for overall CO2 output; and (3) the impact of environmental regulations on the Chinese manufacturing industry’s technological progress had a significant threshold effect. The flexible control of environmental regulatory strength will benefit the Chinese manufacturing industry’s technological development. (4) R&D investment, export delivery value, and structure of energy consumption significantly contributed to promoting technological progress. This study provides further insight into the sustainable development of China’s manufacturing sector to promote green-biased technological progress and to achieve the dual goal of environmental protection and healthy economic growth.

Application of Bayesian Network in Safety Evaluation of Metro Construction

2013 ◽  
Vol 838-841 ◽  
pp. 1463-1468
Author(s):  
Xiang Ke Liu ◽  
Zhi Shen Wang ◽  
Hai Liang Wang ◽  
Jun Tao Wang
Keyword(s):  
Bayesian Networks ◽  
Bayesian Network ◽  
Posterior Probability ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Safety Evaluation ◽  
Tree Analysis ◽  
Tunnel Blasting ◽  
Better Than

The paper introduced the Bayesian networks briefly and discussed the algorithm of transforming fault tree into Bayesian networks at first, then regarded the structures impaired caused by tunnel blasting construction as a example, introduced the built and calculated method of the Bayesian networks by matlab. Then assumed the probabilities of essential events, calculated the probability of top event and the posterior probability of each essential events by the Bayesian networks. After that the paper contrast the characteristics of fault tree analysis and the Bayesian networks, Identified that the Bayesian networks is better than fault tree analysis in safety evaluation in some case, and provided a valid way to assess risk in metro construction.

Fault-Tree Model for Risk Assessment of Bridge Failure: Case Study for Segmental Box Girder Bridges

2013 ◽  
Vol 19 (3) ◽  
pp. 326-334 ◽  
Author(s):  
Caitlyn Davis-McDaniel ◽  
Mashrur Chowdhury ◽  
Weichiang Pang ◽  
Kakan Dey
Keyword(s):  
Risk Assessment ◽  
Fault Tree ◽  
Tree Model ◽  
Box Girder Bridges ◽  
Box Girder ◽  
Girder Bridges ◽  
Bridge Failure

The Demographics of Trade-Affected Services and Manufacturing Workers (1987–1990): A Comparative Analysis

1995 ◽  
Vol 23 (4) ◽  
pp. 43-67
Author(s):  
Bartholomew Armah
Keyword(s):  
Manufacturing Industry ◽  
Service Sector ◽  
Manufacturing Sector ◽  
College Education ◽  
Service Industries ◽  
Highly Educated ◽  
Black And White ◽  
Industry Group ◽  
White Males ◽  
Group A

Using input-output data for 1987 and 1990, this study identifies the demographic characteristics of trade-affected workers in U.S. manufacturing and service industries. Trade-affected workers are defined as employees in industries that experienced a change (positive or negative) in net total (direct and indirect) trade-related employment between 1987 and 1990. For the period 1987–1990, three industry categories were examined: (a) industries that experienced an increase in positive net trade-related employment; (b) industries that experienced a decline in positive net trade-related employment; and (c) industries that suffered net trade-related employment losses in both years yet experienced an improvement over the period. The study finds that, while manufacturing industry workers in the most favorably affected industry group (i.e., group “a”) were more likely to be highly skilled (i.e., scientists & engineers), highly educated (i.e., over four years of college education), unionized, married and white males, corresponding service sector workers were predominantly unskilled (laborers), less educated, non-unionized, young (i.e., aged 16–24) and male (black and white). Furthermore, the service sector was associated with greater mean trade-related employment and output gains and lower mean employment and output losses than was the manufacturing sector.

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