Ahmet Öztaş

Prediction and multi-objective optimization of high-strength concrete parameters via soft computing approaches

The optimization of composite materials such as concrete deals with the problem of selecting the values of several variables which determine composition, compressive stress, workability and cost etc. This study presents multi-objective optimization (MOO) of high-strength concretes (HSCs). One of the main problems in the optimization of HSCs is to obtain mathematical equations that represents concrete characteristic in terms of its constitutions. In order to solve this problem, a two step approach is used in this study. In the first step, the prediction of HSCs parameters is performed by using regression analysis, neural networks and Gen Expression Programming (GEP). The output of the first step is the equations that can be used to predict HSCs properties (i.e. compressive stress, cost and workability). In order to derive these equations the data set which contains many different mix proportions of HSCs is gathered from the literature. In the second step, a MOO model is developed by making use of the equations developed in the first step. The resulting MOO model is solved by using a Genetic Algorithm (GA). GA employs weighted and hierarchical method in order to handle multiple objectives. The performances of the prediction and optimization methods are also compared in the paper.

Contractor selection with Multi Criteria Decision Support tools

The selection of the most suitable contractor is crucial for the success of construction projects. An important task in contractor selection is to establish a set of decision criteria that can measure and judge the capabilities of contractors. Multiple Criteria Decision Support (MCDS) methods can be very useful to solve this problem. Several MCDS tools are used in the literature for this problem. In order to promote the usage of these methods a set of them are applied to a real problem. It is also aimed to present the relative performances, advantages and disadvantages of these methods.

Quality cost analysis in IS0‐9000‐certified Turkish companies

The aim of this paper is to determine the quality costs in ISO‐9000‐certified business organisations deriving from the application of the standards. In the beginning, the quality costs in implementing ISO‐9000 are investigated. The importance of the quality cost system is emphasised. Then, a quality cost system is proposed and quality cost analysis is performed on ISO‐9000‐certified Turkish companies. To determine the quality cost data, a questionnaire was prepared and sent to the selected companies. Collected quality costs data were then analysed using a number of analysis methods.

Current Status of Total Quality Management Implementation in the Turkish Cement Industry

Total Quality Management (TQM) is considered by many researchers as an important quality and business performance improvement tool. The popularity of the concept has led to an explosion of TQM-related literature but there is a dearth of research and literature dealing with TQM implementation in the Turkish Cement Industry (TCI). In this study, the level of implementation of TQM philosophy in TCI is investigated. The paper describes the main findings through the critical factors of TQM, knowledge of TQM and perception of quality, data acquisition methods (operations, customer, employee, suppliers/vendors), and training. A questionnaire was sent to member firms of the Turkish Cement Manufacturers’ Association (TCMA). This paper presents a prescription for solving problems in the implementation of TQM to TCI.