scholarly journals Fuzzy Logic in HEART and CREAM Methods to Assess Human Error and Find an Optimum Method Using a Hierarchical Fuzzy System: A Case Study in a Steel Factory

2022 ◽  
Author(s):  
REZIE BOROUN ◽  
YASER TAHMASBI BIRGANI ◽  
ZEINAB MOSAVIANASL ◽  
GHOLAM ABBAS SHIRALI
Keyword(s):  
Steel Industry ◽  
Fuzzy System ◽  
Human Error ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
System A ◽  
Technical Advances ◽  
Hierarchical Fuzzy System

Numerous studies have been conducted to assess the role of human errors in accidents in different industries. Human reliability analysis (HRA) has drawn a great deal of attention among safety engineers and risk assessment analyzers. Despite all technical advances and the development of processes, damaging and catastrophic accidents still happen in many industries. Human Error Assessment and Reduction Technique (HEART) and Cognitive Reliability and Error Analysis Method (CREAM) methods were compared with the hierarchical fuzzy system in a steel industry to investigate the human error. This study was carried out in a rolling unit of the steel industry, which has four control rooms, three shifts, and a total of 46 technicians and operators. After observing the work process, reviewing the documents, and interviewing each of the operators, the worksheets of each research method were completed. CREAM and HEART methods were defined in the hierarchical fuzzy system and the necessary rules were analyzed. The findings of the study indicated that CREAM was more successful than HEART in showing a better capability to capture task interactions and dependencies as well as logical estimation of the HEP in the plant studied. Given the nature of the tasks in the studied plant and interactions and dependencies among tasks, it seems that CREAM is a better method in comparison with the HEART method to identify errors and calculate the HEP.  

The Role of User Ownership and Positive User Attitudes in the Successful Adoption in Information Systems within NHS Community Trusts

2011 ◽  
pp. 113-137
Author(s):  
Crispin R. Coombs ◽  
Neil F. Doherty ◽  
John Loan-Clarke
Keyword(s):  
Best Practice ◽  
Academic Research ◽  
Community Healthcare ◽  
System A ◽  
User Attitudes ◽  
Two Factors ◽  
Multiple Case ◽  
Organizational Sector

The factors that influence the ultimate level of success or failure of systems development projects have received considerable attention in the academic literature. However, despite the existence of a ‘best practice’ literature many projects still fail. The record of the National Health Service has been particularly poor in this respect. The research reported in this paper proposes that two additional factors; user ownership and positive user attitudes warrant further development and investigation. The current study investigated these two factors in a homogenous organizational sector, Community NHS Trusts, using a common type of information system, in order to eliminate the potentially confounding influences of sector and system. A multiple case-study design incorporating five Community Healthcare Trusts was utilized. The key results from the analysis indicated that both user ownership and positive user attitudes were important mediating variables that were crucial to the success of a CIS. In addition, it was also identified that the adoption of best practice variables had a dual role, directly influencing the level of perceived success but also facilitating the development of user ownership and positive user attitudes. These results will be of particular interest to practising IM&T managers in the NHS and also to the wider academic research community.

Revisiting the FPSO São Mateus Accident From a Human Reliability Perspective Using Phoenix HRA Methodology

2020 ◽  
Author(s):  
Marilia A. Ramos ◽  
Alex Almeida ◽  
Marcelo R. Martins
Keyword(s):  
Human Error ◽  
Oil And Gas ◽  
Risk Estimation ◽  
Petroleum Industry ◽  
Oil And Gas Industry ◽  
Qualitative Assessment ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
Gas Industry

Abstract Several incidents in the offshore oil and gas industry have human errors among core events in incident sequence. Nonetheless, human error probabilities are frequently neglected by offshore risk estimation. Human Reliability Analysis (HRA) allows human failures to be assessed both qualitatively and quantitatively. In the petroleum industry, HRA is usually applied using generic methods developed for other types of operation. Yet, those may not sufficiently represent the particularities of the oil and gas industry. Phoenix is a model-based HRA method, designed to address limitations of other HRA methods. Its qualitative framework consists of three layers of analysis composed by a Crew Response Tree, a human response model, and a causal model. This paper applies a version of Phoenix, the Phoenix for Petroleum Refining Operations (Phoenix-PRO), to perform a qualitative assessment of human errors in the CDSM explosion. The CDSM was a FPSO designed to produce natural gas and oil to Petrobras in Brazil. On 2015 an explosion occurred leading to nine fatalities. Analyses of this accident have indicated a strong contribution of human errors. In addition to the application of the method, this paper discusses its suitability for offshore operations HRA analyses.

Role of Value Compatibility in it Adoption

2007 ◽  
Vol 22 (1) ◽  
pp. 69-78 ◽  
Author(s):  
Deborah Bunker ◽  
Karl-Heinz Kautz ◽  
Anne Luu Thanh Nguyen
Keyword(s):  
It Adoption ◽  
System A ◽  
Functional Factors ◽  
Computer Based ◽  
It Innovation ◽  
Self Service ◽  
And Training ◽  
Potential Use

Compatibility has been recognised as an important element in the adoption of IT innovations in organisations but as a concept it has been generally limited to technical or functional factors. Compatibility is also significant, however, with regard to value compatibility between the organisation, and the adopted IT innovation. We propose a framework to determine value compatibility analysing the organisation's and information system's structure, practices and culture, and explore the value compatibility of an organisation with its adopted self-service computer-based information system. A case study was conducted to determine the congruence of an organisation's value and IT value compatibility. This study found that there was a high correspondence in the organisational structure and practice dimensions; however, there were organisational culture disparities. The cultural disparities reflected the self-service acceptance and training issues experienced by the case organisation. These findings add insight into the problems experienced with value compatibility and the adoption of the information systems, and show the potential use of the proposed framework in the detection of such problems.

UNCERTAINTY OF HUMAN ERROR AND FUZZY APPROACH TO HUMAN RELIABILITY ANALYSIS

2006 ◽  
Vol 14 (01) ◽  
pp. 111-129 ◽  
Author(s):  
B. J. KIM ◽  
RAM R. BISHU
Keyword(s):  
Reliability Analysis ◽  
Nuclear Power ◽  
Power Plants ◽  
Human Error ◽  
Critical Factor ◽  
Fuzzy Approach ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
Fuzzy Logic Approach

Human error is regarded as a critical factor in catastrophic accidents such as disasters at nuclear power plants, air plane crashes, or derailed trains. Several taxonomies for human errors and methodologies for human reliability analysis (HRA) have been proposed in the literature. Generally, human errors have been modeled on the basis of probabilistic concepts with or without the consideration of cognitive aspects of human behaviors. Modeling of human errors through probabilistic approaches has shown a limitation on quantification of qualitative aspects of human errors and complexity of attributes from circumstances involved. The purpose of this paper is to investigate the methodologies for human reliability analysis and introduce a fuzzy logic approach to the evaluation of human interacting system's reliability. Fuzzy approach could be used to estimate human error effects under ambiguous interacting environments and assist in the design of error free work environments.

scholarly journals Role of Innovation in Sustainable Sanitation System: A Case Study of India

2021 ◽  
Vol 16 (2) ◽  
pp. 217-225
Author(s):  
Sumit Shekhar ◽  
◽  
Amrita Dwivedi
Keyword(s):  
Family Health ◽  
Wealth Index ◽  
National Family Health Survey ◽  
System A ◽  
Social Innovations ◽  
National Family ◽  
Different Types ◽  
Product And Process

Sanitation and water are one of those problems which have been given top priority in the sustainable agenda. However, scanty resources, geographical condition, natural environment, tradition, institutional and financial constraints lead to several challenges of feasibility, affordability, availability,and acceptability. This study reveals the inequality in the access to improved toilet facilities based on wealth index and locality of households using National Family Health Survey (NFHS) data. These problems can be addressed by applying different types of social innovations in which novelty in product and process can play a crucial role. This paper critically examines the role of innovation which can play in expanding transition to sustainable development in the sanitation sector which needs some financial, organizational, and institutional agreement. The progress in sanitation sector is dependent on the consumer behavior. However, it still lacks a variety of quality-price ranges and its utility as the basic needs of dignified life.

Analysis and Estimation of Human Errors From Major Accident Investigation Reports

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Caroline Morais ◽  
Raphael Moura ◽  
Michael Beer ◽  
Edoardo Patelli
Keyword(s):  
Human Error ◽  
Human Performance ◽  
Accident Investigation ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
Near Misses ◽  
Performance Shaping Factors ◽  
Major Accident ◽  
Using Data ◽  
Error Probabilities

Abstract Risk analyses require proper consideration and quantification of the interaction between humans, organization, and technology in high-hazard industries. Quantitative human reliability analysis approaches require the estimation of human error probabilities (HEPs), often obtained from human performance data on different tasks in specific contexts (also known as performance shaping factors (PSFs)). Data on human errors are often collected from simulated scenarios, near-misses report systems, and experts with operational knowledge. However, these techniques usually miss the realistic context where human errors occur. The present research proposes a realistic and innovative approach for estimating HEPs using data from major accident investigation reports. The approach is based on Bayesian Networks used to model the relationship between performance shaping factors and human errors. The proposed methodology allows minimizing the expert judgment of HEPs, by using a strategy that is able to accommodate the possibility of having no information to represent some conditional dependencies within some variables. Therefore, the approach increases the transparency about the uncertainties of the human error probability estimations. The approach also allows identifying the most influential performance shaping factors, supporting assessors to recommend improvements or extra controls in risk assessments. Formal verification and validation processes are also presented.

Development of a time-variant causal model of human error in construction with dynamic Bayesian network

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhangming Ma ◽  
Heap-Yih Chong ◽  
Pin-Chao Liao
Keyword(s):  
Bayesian Network ◽  
Human Error ◽  
Causal Model ◽  
Safety Management ◽  
Dynamic Bayesian Network ◽  
Human Errors ◽  
Content Type ◽  
Factors Affecting ◽  
Dynamic Causal Model

Purpose Human error is among the leading causes of construction-based accidents. Previous studies on the factors affecting human error are rather vague from the perspective of complex and changeable working environments. The purpose of this paper is to develop a dynamic causal model of human errors to improve safety management in the construction industry. A theoretical model is developed and tested through a case study. Design/methodology/approach First, the authors defined the causal relationship between construction and human errors based on the cognitive reliability and error analysis method (CREAM). A dynamic Bayesian network (DBN) was then developed by connecting time-variant causal relationships of human errors. Next, prediction, sensitivity analysis and diagnostic analysis of DBN were applied to demonstrate the function of this model. Finally, a case study of elevator installation was presented to verify the feasibility and applicability of the proposed approach in a construction work environment. Findings The results of the proposed model were closer to those of practice than previous static models, and the features of the systematization and dynamics are more efficient in adapting toward increasingly complex and changeable environments. Originality/value This research integrated CREAM as the theoretical foundation for a novel time-variant causal model of human errors in construction. Practically, this model highlights the hazards that potentially trigger human error occurrences, facilitating the implementation of proactive safety strategy and safety measures in advance.

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