Yavuz Selim Ozdemir

In recent years, efficient processes have become increasingly important because of high-level competition in the production industry. The concept of Industry 4.0 is a relatively new and effective method for managing production processes. Because the Industry 4.0 implementation process includes connections between objects, humans, and systems, it is quite difficult to evaluate and measure the performance. At this stage, performance criteria can be applied. However, linguistic evaluation of criteria makes the problem too complicated to solve. The purpose of this paper is to present a novel fuzzy performance measurement model for Industry 4.0 in small and medium-sized manufacturing firms. A hybrid spherical fuzzy analytic hierarchy process (SF-AHP)—weighted score methodology (WSM) is proposed for the performance measurement and scoring process. In the application part of this paper, the propounded methodology was applied to five companies. The results of this study can be used as a reference for experts in the performance measurement of the Industry 4.0 process.

Power plants plays an important role in term of economic and social affect in all societies. Most of economic sectors and manufacturers are depended in the outcome of power plants in one side and electricity is a vital need of all households and entire society. Therefore, the performance of power plants and consequently their sustainability is crucial concept in the current century. This article proposes a generalized efficiency measurement model for multi-plant firms in terms of returns to scale and number of outputs. This yields to some new indicators for efficiency measurement in an un-communal and communal environment for the local and global analysis. The idea is explained by providing a graphical illustration and numerical example. Proposed models are used for energy efficiency analysis of 46 power plants of 19 provinces in Iran. Local and global aspect of energy efficiency are investigated by using proposed models for aforementioned case study. Primary results are shown that, higher potential energy saving in the communal global environment compared with the local analysis. This highlight the corporation of production electricity units, namely, power plants in this study is a requirement for sustainable energy supply.

Supply chain management is to improve competitive stress. In today’s world, competitive terms and customer sense have altered in favor of an environmentalist manner. As a result of this, green supplier selection has become a very important topic. In the green supplier selection approach, agility, lean process, sustainability, environmental sensitivity, and durability are pointed. Like the classical supplier selection problems, environmental criteria generally emphasize green supplier selection. However, these two problem approaches are different from each other in terms of carbon footprint, water consumption, environmental and recycling applications. Due to the problem structure, a resolution is defined that includes an algorithm based on q-Rung Orthopair Fuzzy (q-ROF) TOPSIS method. Brief information about q-ROF sets is given before the methodology of the q-ROF model is introduced. By using the proposed method and q-ROF sets, an application was made with today’s uncertain conditions. In the conclusion part, a comparison is made with classical TOPSIS, Intuitionistic Fuzzy TOPSIS and q-ROF TOPSIS methodology. As a result, more stable and accurate results are obtained with q-ROF TOPSIS.

Competitive market conditions today are becoming more challenging in every sector. Companies must determine their road maps in terms of short, mid and long-term strategies. The selection of the most suitable strategy by a group of decision makers is a very complicated process. As the same linguistic expression can represent different meanings to different people the fuzzy decision-making process is a good tool to use in group decisions. Various methods and different linguistic terms are used to define fuzzy sets. In recent years, the interval type-2 fuzzy AHP and interval type-2 TOPSIS methods have been introduced in the literature, as well as the type-1 fuzzy AHP and type-1 fuzzy TOPSIS methods. The aim of this study is to present a new model for group decision-making with the Balanced Score Card, fuzzy AHP and fuzzy TOPSIS methods by using interval type-2 fuzzy sets. The proposed model was applied in the strategy selection process of a large-scale public transportation company that operates in Istanbul/Turkey.

TIn the management of a military or civilian project, it is vital for a project manager to make the best decision by using the appropriate methods to evaluate the budget and time correctly to administer a successful policy. In recent years, the Fuzzy Analytic Hierarchy Process (FAHP) method has been frequently employed to solve multi-criteria decision-making problems in order to assess various data sets obtained from different decision-makers. This article aimed to choose the most suitable one of the latest technology-cargo helicopters widely used in many countries in line with the need of the Turkish Armed Forces, which is crucial for evaluating opinions of many decision makers. For the model of the selection of the most appropriate cargo helicopter, the study investigated which helicopters would offer the most suitable alternatives and as a result, three types of cargo helicopters were identified. These helicopters were compared based on twenty-eight criteria. The model presented a fuzzy AHP method which is clarified by Center of Gravity method using trapezoidal fuzzy numbers to figure out the cargo helicopter.