During the last decades, especially in large-scale construction projects, it is one of the widely applied strategies that the main contractors work with many subcontractors and overtake a large part of the works. This trend brings out the problem of selection of subcontractors. The classical approaches in the construction industry to select the subcontractor are the general practice reference, the lowest bid, and the familiarity. This creates major risks for contractors since the construction sector involves time-limited projects with a large variety of complex works. Putting the subcontractor selection on a scientific basis and minimizing the risks by choosing the most appropriate subcontractor among the bidders for a particular type of work, require for the construction industry to determine not only consistent and efficient but also uncomplicated and plain model. Instead of the widespread conventional application, this study represents a new alternative approach to the subcontractor selection with Additive Ratio Assessment Method, which is one of the multi-criteria decision-making techniques. Additive Ratio Assessment Method is quite practical and convenient to use among the other multi-criteria decision-making methods. This study aimed to demonstrate the use of Additive Ratio Assessment Method on subcontractor selection problems by exemplifying a real case application.
This paper provides the design for air conditioning system and two different defuzzification methods. The air conditioner intelligent system is the control of two control parameter: the temperature and the humidity of the area. The inputs received by the temperature and humidity sensors give the closest output values for the air conditioning system. The simulation result shows temperature and humidity of the heat exchange by using defuzzification methods of centroid and middle of maxima (MoM) in the Fuzzy Logic Toolbox of MATLAB package program.
Smartphones are attracting increasing interest due to how they are revolutionizing our lives. On the other hand, hardware and software failures that occur in them are continually present. This work aims to investigate these failures in a typical smartphone by collecting data from a class of people. Concerns have been raised that call into question the efficiency of applied methods for identifying and prioritizing the potential defects. The widely used hybridized engineering method, Fuzzy Failure Mode and Effect Analysis (F-FMEA), is an excellent approach to solving these problems. The F-FMEA method was applied to prioritize the potential failures based on their Severity (S), expected Occurrence (O), and the likelihood of Detectability (D). After collecting failure data from different users on a selected smartphone, two well-known defuzzification methods facing the Risk Priority Number (RPN) in F-FMEA were applied. Despite this interest, to the best of our knowledge, no one has studied smartphone failures with a technique that combines the results of different fuzzy applications. Thus, to combine the results of the derived fuzzy subsystems for the average value, we suggest a summative defuzzification method. Our findings indicate that F-FMEA with a summative defuzzification procedure is a clear improvement on the F-FMEA method. Even though the summation method modifies close results of the defuzzification one, it was shown that it provides more accurate results.
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