scholarly journals A Forecast and Mitigation Model of Construction Performance by Assessing Detailed Engineering Maturity at Key Milestones for Offshore EPC Mega-Projects

2019 ◽  
Vol 11 (5) ◽  
pp. 1256 ◽  
Author(s):  
Myung-Hun Kim ◽  
Eul-Bum Lee ◽  
Han-Suk Choi
Keyword(s):  
Fuzzy Inference ◽  
Risk Mitigation ◽  
Qualitative Comparative Analysis ◽  
Major Elements ◽  
Cost Overrun ◽  
Analytic Hierarchy ◽  
Cost Performance ◽  
Inference System ◽  
Trade Off ◽  
Statistical Confidence

The main subject of this research is to develop a forecast and mitigation model of schedule and cost performance during a detailed engineering stage of offshore engineering, procurement and construction (EPC) projects. The weight factors of major elements in detailed engineering completion rating index system (DECRIS) were measured using a fuzzy inference system (FIS) and an analytic hierarchy process (AHP). At five key engineering milestones, from an EPC contract being awarded to the start of construction, detailed engineering maturities were assessed in fourteen historical offshore EPC projects using the DECRIS model. DECRIS cutoff scores for successful project execution were defined at the key engineering milestones. A schedule and cost performance was forecasted and validated through comparison of DECRIS and other models using statistical confidence of a fuzzy set qualitative comparative analysis (fsQCA) and a regression analysis. As a mitigation method for engineering risks to EPC contractors, engineering resource enhancement is recommended for trade-off optimization of cost overrun using a Monte Carlo simulation. The main contribution of this research is that EPC contractors could continuously forecast construction costs and schedule performance utilizing the DECRIS model, and could review the adequacy of engineering resources, assessing the trade-off between said resources and cost/schedule risk mitigation.

scholarly journals Ranking patients on the kidney transplant waiting list based on fuzzy inference system

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Nasrin Taherkhani ◽  
Mohammad Mehdi Sepehri ◽  
Roghaye Khasha ◽  
Shadi Shafaghi
Keyword(s):  
Kidney Transplantation ◽  
Fuzzy Inference System ◽  
Scoring System ◽  
Fuzzy Inference ◽  
Waiting List ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Kidney Allocation ◽  
Single Output ◽  
Stage Renal Disease

Abstract Background Kidney transplantation is the best treatment for people with End-Stage Renal Disease (ESRD). Kidney allocation is the most important challenge in kidney transplantation process. In this study, a Fuzzy Inference System (FIS) was developed to rank the patients based on kidney allocation factors. The main objective was to develop an expert system, which would mimic the expert intuitive thinking and decision-making process in the face of the complexity of kidney allocation. Methods In the first stage, kidney allocation factors were identified. Next, Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) has been used to weigh them. The purpose of this stage is to develop a point scoring system for kidney allocation. Fuzzy if-then rules were extracted from the United Network for Organ Sharing (UNOS) dataset by constructing the decision tree, in the second stage. Then, a Multi-Input Single-Output (MISO) Mamdani fuzzy inference system was developed for ranking the patients on the waiting list. Results To evaluate the performance of the developed Fuzzy Inference System for Kidney Allocation (FISKA), it was compared with a point scoring system and a filtering system as two common approaches for kidney allocation. The results indicated that FISKA is more acceptable to the experts than the mentioned common methods. Conclusion Given the scarcity of donated kidneys and the importance of optimal use of existing kidneys, FISKA can be very useful for improving kidney allocation systems. Countries that decide to change or improve the kidney allocation system can simply use the proposed model. Furthermore, this model is applicable to other organs, including lung, liver, and heart.

scholarly journals Reliability centered maintenance actions prioritization using fuzzy inference systems

2016 ◽  
Vol 22 (4) ◽  
pp. 433-452 ◽  
Author(s):  
Mahmoud Awad ◽  
Rami Afif As’ad
Keyword(s):  
Ad Hoc ◽  
Fuzzy Inference ◽  
Risk Mitigation ◽  
Critical Role ◽  
Real Life ◽  
Cost Ratio ◽  
Relative Importance ◽  
Inference System ◽  
Content Type ◽  
Reliability Centered Maintenance

Purpose Deploying an effective maintenance strategy across an organization stands out as an essential risk mitigation measure that plays a critical role toward improving the reliability and availability of production facilities. The purpose of this paper is to propose a simple, yet well-structured approach toward prioritizing maintenance actions as part of a reliability centered maintenance (RCM) implementation plan, and selecting the most important subset of those actions subject to time and budget constraints. Design/methodology/approach A comprehensive RCM actions prioritization methodology is proposed using four criteria: severity, benefit to cost ratio, customer satisfaction, and easiness of action implementation. The method utilizes fuzzy inference system (FIS) to incorporate subject matter experts’ feedback into the decision-making process. The output of the FIS, which takes the form of a numerical weight that assesses the relative importance of each criterion, is then fed into a binary integer program that selects the optimal maintenance actions out of a set of possible actions. Findings The implementation of the developed methodology is demonstrated using a real-life example of a hydraulic brake system circuit that is used in construction equipment. The computational results illustrate the validity of the proposed approach and indicate that the selection of which maintenance actions to carry out is impacted by the relative importance (i.e. weight) of the considered criteria. Originality/value The work presented in this paper provides the decision makers with a systematic procedure that helps in selecting the most relevant maintenance actions instead of making the selection in a complete ad hoc manner or based merely on subjective opinions.

scholarly journals Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System

2018 ◽  
Vol 10 (12) ◽  
pp. 4780 ◽  
Author(s):  
Min-Sung Kim ◽  
Eul-Bum Lee ◽  
In-Hye Jung ◽  
Douglas Alleman
Keyword(s):  
Risk Assessment ◽  
Analytic Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Raw Materials ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Project Risk ◽  
Inference System ◽  
Hierarchy Process

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.

The AHP FIS Ship Handling Model for Determining Ferry Transportation Safety

2012 ◽  
Vol 209-211 ◽  
pp. 959-964 ◽  
Author(s):  
Priadi Antoni Arif ◽  
Tri Tjahjono ◽  
Abdellatif Benabdelhafid
Keyword(s):  
Fuzzy Inference ◽  
Transportation Safety ◽  
Difficulty Level ◽  
Economic Sustainability ◽  
Decision Tool ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Port Authorities ◽  
Hierarchy Process ◽  
Ship Handling

The operation of ship especially Ro-Ro ferry contributes much to support connectivity among islands for a country like Indonesia which has categorized as archipelago country. The reliability of Ro-Ro ferry operation will impact to the movement of cargo as well as passenger and later it could cause larger impact on the economic sustainability of region involved. The reliability of Ro-Ro ferry operation could be determined by operation function such ferry. One important function is ship handling function which consists of the interaction among human, technical, environment, management and weather. As the consequence to perform the objective of ship handling, the hazards might appear. It could be remarked that ferry accidents often occur during their service e.g. collision, grounding, sinking and contact. Such accident may be as part of the result of ship handling difficulty as part of ship handling function. Therefore, decision tool model based on the ship handling difficulty need to be developed. The first aim of this paper is to present the proposed ship handling model through the combination of Analytic Hierarchy Process (AHP) and Fuzzy Inference System (FIS). The second aim is to perform a simulation to compare the ship handling difficulty level for Ro-Ro ferry at several straits in Indonesia. The result of this research might be used by ship masters, shipping companies and port authorities to develop strategies in overcome the hazard of Ro-Ro ferries so the reliability of ferry operation could be maintained.

scholarly journals OPTIMIZED MANAGEMENT STRATEGY FOR CONSTRUCTION PROJECTS CONSIDERING THE TRADE-OFF OF ESTIMATE SCHEDULE AND COST AT COMPLETION

2019 ◽  
Vol 6 (2) ◽  
pp. 26-37
Author(s):  
Liem Stefani Meilia Gunawan
Keyword(s):  
Prediction Model ◽  
Construction Projects ◽  
Indifference Curve ◽  
Cost Overrun ◽  
Cost Performance ◽  
Trade Off ◽  
Project Duration ◽  
Pareto Curve ◽  
Uncertain Factor ◽  
Direct Equation

Nowadays, the minimization of project time and cost is an important issue. However, time and cost problems are difficult to solve. They are affected by the uncertain factor. Then, the construction project always fails to achieve the effectiveness of time and cost performance. It causes delays and cost overrun. In this research, SOS-NN-LSTM is required to establish the estimate schedule to completion (ESTC) and estimate cost to completion (ECTC) prediction model based on time now performance. Then, the prediction model will be integrated with MOSOS to obtain the optimal prediction value. The integration is needed because there is no direct equation to calculate the ESTC and ECTC. The Pareto curve identified based on the prediction values of MOSOS. The Pareto curve is used to determine the optimal trade-off between project duration and project cost. Then, the indifference curve is used to solve the trade-off problem between estimate schedule at completion (ESAC) dan estimate cost at completion (ECAC) which give the decision-maker preference.

The Role of Supply Chain Features in the Effectiveness of Sustainability Practices in the Service Supply Chain: Application of Fuzzy Rule-Based System

2019 ◽  
Vol 18 (03) ◽  
pp. 867-899 ◽  
Author(s):  
Fahimeh Aliakbari Nouri ◽  
Mohsen Shafiei Nikabadi ◽  
Laya Olfat
Keyword(s):  
Supply Chain ◽  
Service Sector ◽  
Fuzzy Inference ◽  
Fuzzy Rule ◽  
Affecting Factors ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Service Supply Chain ◽  
Practice Performance ◽  
The Government

This study analyzes the affecting variables on the relation of sustainability practice-performance in the service supply chain. The identified factors (supply chain features) are classified in a hierarchical structure of Fuzzy Analytic Hierarchy Process (FAHP): Macro Environment Features, Service Provider Features, Supplier Features, Employee Features, and Customer Features. Then, the FAHP is applied to identify the importance of each factor in the hospital supply chain, as an example of the service sector. To extract and predict the factors’ interactions, the knowledge base of the fuzzy if-then rules is constructed. The developed Fuzzy Inference System (FIS) gives insights on the supply chain features with significant impact on the effectiveness of sustainability initiatives. So, by predicting and strategically managing the affecting factors, service supply chain managers can have more effective and sustainable performance. The fuzzy surfaces indicate that the features of the macro environment, especially the government regulations, are crucial factors influencing the movement toward sustainability.

scholarly journals Multi-Response Optimization of Electrical Discharge Drilling Process of SS304 for Energy Efficiency, Product Quality, and Productivity

Materials ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 2897 ◽  
Author(s):  
Trung-Thanh Nguyen ◽  
Van-Tuan Tran ◽  
Mozammel Mia
Keyword(s):  
Energy Efficiency ◽  
Electrical Discharge ◽  
Fuzzy Inference ◽  
Removal Rate ◽  
Integrative Approach ◽  
Technical Solution ◽  
Drilling Process ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Electrical Discharge Drilling

The electrical discharge drilling (EDD) process is an effective machining approach to produce various holes in difficult-to-cut materials. However, the energy efficiency of the EDD operation has not thoroughly been considered in published works. The aim of the current work is to optimize varied parameters for enhancing the material removal rate (MRR), saving drilled energy (ED), and decreasing the expansion of the hole (HE) for the EDD process. Three advanced factors, including the gap voltage adjustor (GAP), capacitance parallel connection (CAP), and servo sensitivity selection (SV), are considered. The predictive models of the performances were proposed with the support of the adaptive neuro-based fuzzy inference system (ANFIS). An integrative approach combining the analytic hierarchy process (AHP) and the neighborhood cultivation genetic algorithm (NCGA) was employed to select optimal factors. The findings revealed the optimal values of the CAP, GAP, and SV were 6, 5, and 4, respectively. Moreover, the ED and HE were decreased by 16.78% and 28.68%, while the MRR was enhanced by 89.72%, respectively, as compared to the common setting values. The explored outcome can be employed as a technical solution to enhance the energy efficiency, drilled quality, and productivity of the EDD operation.

scholarly journals Estimation of fines amount in syariah criminal offences using adaptive neuro-fuzzy inference system (ANFIS) enhanced with analytic hierarchy process (AHP)

2019 ◽  
Vol 9 (6) ◽  
pp. 5537
Author(s):  
Ahmad Fitri Mazlam ◽  
Wan Nural Jawahir Hj Wan Yussof ◽  
Rabiei Mamat
Keyword(s):  
Analytic Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Individual Decision ◽  
Criminal Cases ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Neuro Fuzzy ◽  
The Individual ◽  
Hierarchy Process

<span lang="EN-US">All syariah criminal cases, especially in khalwat offence have their case-fact, and the judges typically look forward to all the facts which were tabulated by the prosecutors. A variety of criteria is considered by the judge to determine the fines amount that should be imposed on an accused who pleads guilty. In Terengganu, there were ten (10) judges, and the judgments were made by the individual decision upon the trial to decide the case. Each judge has a stake, principles and distinctive criteria in determining fines amount on an accused who pleads guilty and convicted. This research paper presents an Adaptive Neuro-fuzzy Inference System (ANFIS) technique combining with Analytic Hierarchy Process (AHP) for estimating fines amount in Syariah (khalwat) criminal. Datasets were collected under the supervision of registrar and syarie judge in the Department of Syariah Judiciary State Of Terengganu, Malaysia. The results showed that ANFIS+AHP could estimate fines efficiently than the traditional method with a very minimal error.</span>

Sign in / Sign up

Export Citation Format

Share Document