Browsing by Author "Simsek, Baris"

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Building a Graphical User Interface for Concrete Production Processes: A Combined Application of Statistical Process Control and Design of Experiment
(2019) Simsek, Baris; Pakdil, Fatma; Ic, Yusuf Tansel; Guvenc, Ali Bilge; AGQ-5008-2022
Quality improvement and control in the manufacturing industry is a necessity for responding timely to increase customer needs and sustainability expectations. In order to decrease the variance in design and production functions, graphical user interface was built in this study implementing a combined methodology based on multi-response design of experiment and statistical process control. Graphical user interface based on MATLAB (R) toolbox allows analyzing the sufficiency of measurement system, calculating the capability of concrete production process, optimizing the manufacturing process via TOPSIS-based Taguchi design methodology and comparing the improvement rate of the process capability indices based on current and optimum conditions. After the Gauge R&R analysis, the current system process capability was considered for the C30/37 class (C30) normal weight concrete through process capability indices. In optimal system, process capability ratios, which are the degrees of compliance with the specifications of C30, were determined on the basis of TOPSIS-based Taguchi optimization. Eventually, the actual capability improvement provided through the proposed methodology was considered quite significant.
Development of A Graphical User Interface for Determining The Optimal Mixture Parameters of Normal Weight Concretes: A Response Surface Methodology Based Quadratic Programming Approach
(2014) Simsek, Baris; Ic, Yusuf Tansel; Simsek, Emir H.; Guvenc, Ali Bilge; https://orcid.org/0000-0001-9274-7467; AGE-3003-2022
The optimization of a normal weight concrete mixture proportions for determination of the desired concrete quality is an important issue for concrete manufacturers and users. In this study, the constrained quadratic programming methodology is based on meta-models developed by using response surface methodology for determining optimal normal weight concrete mixture proportions. We developed a graphical user interface to take the burden of numerous experiments and complex mathematical calculations away from laboratory experts and manufacturers. However, we developed a graphical user interface based on MATLAB (R) toolbox which allows performing optimization of normal weight concrete mixture proportions interactively. The GUI was tested through real case studies and satisfactorily results were obtained. The results showed that developed graphical user interface was functional, effective and flexible in solving the optimization problems of normal weight concrete mixture proportions. (C) 2014 Elsevier B.V. All rights reserved.
Driver Performance Appraisal Using GPS Terminal Measurements: A Conceptual Framework
(2013) Simsek, Baris; Pakdil, Fatma; Dengiz, Berna; Testik, Murat Caner; 0000-0003-2389-4759; AAE-3672-2019; G-6133-2013
Objective measurement for performance appraisal is vital but rarely conducted in a methodologically sound manner. In this paper, we provide a thorough assessment of how objective and fair performance appraisals of drivers can be conducted. Furthermore, a unique conceptual framework is provided for evaluation of safety interventions and operational performance through monitoring quantitative driver performance measures. The conceptual framework makes use of online-measurements obtained from Global Positioning System (GPS) terminals, and the data are evaluated using statistical process control (SPC) tools. SPC tools are useful in comparing individual driver performance to overall performance as well as for identifying time-dependent factors that influence performance. Quantitative performance measures considered in the study include speed violations, vehicle idle duration, and fuel consumption. As an illustration of the concepts and implementation at a logistics firm is provided. (C) 2012 Elsevier Ltd. All rights reserved.
Enhanced Stent Imaging System Guided Percutaneous Coronary Intervention Is Linked to Optimize Stent Placement
(2022) Avci, Ilhan Ilker; Zeren, Gonul; Sungur, Mustafa Azmi; Akdeniz, Evliya; Simsek, Baris; Yilmaz, Mehmet Fatih; Can, Fatma; Gurkan, Ufuk; Karagoz, Ali; Tanboga, Ibrahim Halil; Karabay, Can Yucel; 36178093
Stent under-expansion is a predictor of restenosis and stent thrombosis. It remains uncertain whether enhanced stent imaging (ESI) (CLEARstent) guidance can improve stent under-expansion. Our aim was to assess the effect of using ESI on stent under-expansion, after percutaneous coronary intervention (PCI) in a single center, cross-sectional observational study. Participants attending our cardiology clinic with stable angina or acute coronary syndrome, from March to September 2020 were recruited. A total of 164 patients who underwent post-PCI ESI (CLEARstent) were compared with 77 age- and sex-matched control patients. Post-procedural minimal lumen diameter (MLD) was calculated. The patients in the ESI-guided PCI group, had a median age of 61 (54-69 IQR 25-75) years and 76.8% (n = 126) were males. The patients in ESI-guided PCI group had a greater minimal lumen diameter compared with the X-ray guided PCI group (beta eta coefficient:2.88 (95% CI:2.58-2.99) vs beta eta coefficient 2.55 (95% CI 2.34-2.63), P < .001). Our finding supports the use of the ESI system to optimize stent placement as expressed by the MLD.
Fuzzy failure mode and effect analysis application to reduce risk level in a ready-mixed concrete plant: A fuzzy rule based system modelling approach
(2020) Simsek, Baris; Ic, Yusuf Tansel
In this study, failure mode and effect analysis were applied to evaluate and eliminate potential failure modes in a Ready-Mixed Concrete Plant using a fuzzy-rule-base system. The questionnaires were specially prepared for each sub-department such as production plant, workshop and maintenance, dumping grounds, materials transportation and storage, utilities, administrative office, social facility, quality control laboratory and wastewater pool and recycling facilities. The questions were answered by the workers in each section. Risk Priority Numbers (RPNs) and Fuzzy Risk Priority Numbers (FRPN), which measure potential failure modes, were calculated using the risk parameters. High-risk areas were identified, and some suggestions were made to reduce accident risk at the Ready-Mixed Concrete Plant. Three questionnaires were prepared, based on these suggestions, and distributed to workers to determine whether the suggestions would reduce the risk or not. Based on conditions at the time the recommendations were implemented and improvement rates were calculated. The results showed that the fuzzy failure mode and effect analysis methodology were effective in identifying and eliminating potential failure modes at the Ready-Mixed Concrete Plant. The results can also be used by other ready-mixed concrete manufacturers who want to improve the safety of their operations. (C) 2020 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
Hybridizing a fuzzy multi-response Taguchi optimization algorithm with artificial neural networks to solve standard ready-mixed concrete optimization problems
(2016) Simsek, Baris; Ic, Yusuf Tansel; Simsek, Emir Huseyin
In this study, a fuzzy multi-response standard ready-mixed concrete (SRMC) optimization problem is addressed. This problem includes two conflicting quality optimization objectives. One of these objectives is to minimize the production cost. The other objective is to assign the optimal parameter set of SRMC's ingredient to each activity. To solve this problem, a hybrid fuzzy multi-response optimization and artificial neural network (ANN) algorithm is developed. The ANN algorithm is integrated into the multi-response SRMC optimization framework to predict and improve the quality of SRMC. The results show that fuzzy multi-response optimization model is more effective than crisp multi-response optimization model according to final production cost. However, the ANN model also gave more accurate results than the fuzzy model considering the regression analysis results.
Multi-response Simulation Optimization Approach for The Performance Optimization of An Alarm Monitoring Center
(2014) Simsek, Baris; Ic, Yusuf Tansel; https://orcid.org/0000-0001-9274-7467; AGE-3003-2022
This study offers a multi-response simulation-optimization approach to optimize an Alarm Monitoring Center's performance. In this paper, the multi-response simulation-optimization application is firstly addressed in the Alarm Monitoring Center. Five performance criteria affect the performance of Alarm Monitoring Center and five factors, each of which has three control levels, are identified. The data belonging to the performance criteria, which are determined, are obtained with the help of the running scenarios combining with the factor levels using Taguchi design. Then, signals to the noise (S/N) ratios are calculated for these which are obtained from the performance data. A decision matrix is generated with S/N ratios; the TOPSIS method is used to transfer the multi-response problems into the single-response problems. The system improvement rate is also determined by finding the levels of factors to optimize the system using Taguchi's single response optimization methodology.(C) 2014 Elsevier Ltd. All rights reserved.
A RSM-Based Multi-Response Optimization Application for Determining Optimal Mix Proportions of Standard Ready-Mixed Concrete
(2016) Simsek, Baris; Ic, Yusuf Tansel; https://orcid.org/0000-0001-9274-7467; AGE-3003-2022