During implementation of construction projects, durations of activities are affected by various factors. Because of this, both during the planning phase of the project as well as the construction phase, managers try to estimate, or predict, the length of any delays that may occur. Such estimates allow for the ability to take appropriate action in terms of planning and management during the execution of construction works. This paper presents the use of the non-deterministic concept for describing the uncertainty of estimating works duration. The concept uses the theory of fuzzy sets. The author describes a method for fuzzy estimations of construction works duration based on the fact that uncertain data is an inherent factor in the conditions of construction projects. An example application of the method is presented. The author shows a fuzzy estimation for the duration of an activity, taking into consideration the distorting influence caused by malfunctioning construction equipment and delivery delays of construction materials.

The basic element of a project organizing construction works is a schedule. The preparation of the data necessary to specify the timings of the construction completion as indicated in the schedule involves information that is uncertain and hard to quantify. The article presents the methods of building a schedule which includes a fuzzy amount of labour, time standards and number of workers. The proposed procedure allows determining the real deadline for project completion, taking into account variable factors affecting the duration of the individual works.

The paper presents an approach to evaluating a building throughout its whole life cycle in relation to its sustainable development. It describes basic tools and techniques of evaluating and analysing the costs in the whole life cycle of the building, such as Life Cycle Assessment, Life Cycle Management, Life Cycle Cost and Social Life Cycle Assessment. The aim of the paper is to propose a model of cost evaluation throughout the building life cycle. The model is based on the fuzzy sets theory which allows the calculations to include the risks associated with the sustainable development, with the management of the investment and with social costs. Costs incurred in the subsequent phases of the building life cycle are analysed and modelled separately by means of a membership function. However, the effect of the analysis is a global cost evaluation for the whole life cycle of the building.

Article deals with the problem of technology selection for construction project. Three criteria were proposed: cost, time and technological complexity. To solve the problem, fuzzy preference relations were used. Authors present an algorithm supporting multi-criteria decision-making process. The algorithm creates fuzzy preference relations on the basis of the fuzzy comparison: “xᵢ is better than xj”.Then, with the use of criteria weights it creates general fuzzy preference relation, finds all non-dominated (admissible) alternatives and the best one among them. The algorithm consists of 7 steps. Authors show application of the proposed algorithm – example calculations.

The article presents the use of the Mamdani fuzzy reasoning model to develop a proposal of a system controlling partnering relations in construction projects. The system input variables include: current assessments of particular partnering relation parameters, the weights of these parameters’ impact on time, cost, quality and safety of implementation of construction projects, as well as the importance of these project assessment criteria for its manager. For each of the partnering relation parameters, the project’s manager will receive controlrecommendations. Moreover, the parameter to be improved first will be indicated. The article contains a calculation example of the system’s operations.

The article introduces a new proposal of a defuzzification method, which can be implemented in fuzzy controllers. The first chapter refers to the origin of fuzzy sets. Next, a modern development based on this theory is presented in the form of ordered fuzzy numbers (OFN). The most important characteristics of ordered fuzzy numbers are also presented. In the following chapter, details about the defuzzification process are given as part of the fuzzy controller model. Then a new method of defuzzification is presented. The method is named center of circles intersection (CCI). The authors compare this method with a similar geometric solution: triangular expanding (TE) and geometric mean (GM). Also, the results are compared with other methods such as center of gravity (COG), first of maxima (FOM) and last of maxima (LOM). The analysis shows that the proposed solution works correctly and provides results for traditional fuzzy numbers as well as directed fuzzy numbers. The last chapter contains a summary, in which more detailed conclusions are provided and further directions of research are indicated.

The paper presents the method for multicriteria design of a synchronous generator voltage regulator. The results of the voltage regulator polyoptimisation are compromise sets for a classic controller of type PI and fuzzy logic controller of type Takagi-Sugeno-Kang. A genetic algorithm is used to solve the polyoptimisation problem.

Indian SMEs are going to play pivotal role in transforming Indian economy and achieving

double digit growth rate in near future. Performance of Indian SMEs is vital in making

India as a most preferred manufacturing destination worldwide under India’s “Make in India

Policy”. Current research was based on Indian automotive SMEs. Indian automotive SMEs

must develop significant agile capability in order to remain competitive in highly uncertain

global environment. One of the objectives of the research was to find various enablers of

agility through literature survey. Thereafter questionnaire administered exploratory factor

analysis was performed to extract various factors of agility relevant in Indian automotive

SMEs environment. Multiple regression analysis was applied to assess the relative importance

of these extracted factors. “Responsiveness” was the most important factor followed by

“Ability to reconfigure”, “Ability to collaborate”, and “Competency”. Thereafter fuzzy logic

bases algorithm was applied to assess the current level of agility of Indian automotive SMEs.

It was found as “Slightly Agile”, which was the deviation from the targeted level of agility.

Fuzzy ranking methodology facilitated the identification & criticalities of various barriers

to agility, so that necessary measures can be taken to improve the current agility level of

Indian automotive SMEs. The current research may helpful in finding; key enablers of agility,

assessing the level of agility, and ranking of the various enablers of agility to point out the

weak zone of agility so that subsequent corrective action may be taken in any industrial

environment similar to India automotive SMEs.

The selection of a contractor is one of the most important among decisions made by the ownerof a construction. The application of the prequalification procedure enables the selection of themost competent tenderers. Various mathematical models are helpful in carrying out prequalificationprocedure. In the paper, some selected mathematical models are briefly characterized and modelbased on the theory of fuzzy sets is offered. The applied model takes into consideration theowner’s various objectives, as well as different evaluation criteria. The results of the sensitivityanalysis of the model are also presented. Part of a computer software applying an earlier presentedprequalification mathematical model is described.

The new approach to the construction project planning is presented in the article. The classical net model is enriched by the fuzzy decision node. The decision node allows for alternate choices dependent on appearing circumstances. The alternative net model with fuzzy decision node is an acyclic multi-graph, where some, chosen nodes (events) have multiple connections. These connections represent alternative methods of the certain work execution. Every work (activity) (i, j) in the net model with alternative methods of work execution, despite the basic information comprising the execution time, the cost, the number of necessary workers, should comprise additional information e.g. about a complexity of works, a real feasibility. The alternative ways of a given work execution are evaluated in the decision node based on the fuzzy decision model. Each method is evaluated by assigning it the preference level in a form of the value of the membership function – „equal or higher” μ_≥. The most preferable way of the work execution in a given circumstances, will have the highest value of preference level. When the choice is done the net model is solved in the traditional way. Therefore, the paper concentrates on the process of choosing the method of work execution in the fuzzy decision node. The example calculations accompanying the process of decision taking are presented too. The model requires the use of linguistic variables, a fuzzy numbers, as well as fuzzy preference relations together with some calculations applied the probability theory.

This work depicts the effects of deep cryogenically treated high-speed steel on machining. In recent research, cryogenic treatment has been acknowledged for improving the life or performance of tool materials. Hence, tool materials such as the molybdenum-based high-speed tool steel are frequently used in the industry at present. Therefore, it is necessary to observe the tool performance in machining; the present research used medium carbon steel (AISI 1045) under dry turning based on the L9 orthogonal array. The effect of untreated and deep cryogenically treated tools on the turning of medium carbon steel is analyzed using the multi-input-multi-output fuzzy inference system with the Taguchi approach. The cutting speed, feed rate and depth of cut were the selected process parameters with an effect on surface roughness and the cutting tool edge temperature was also observed. The results reveal that surface roughness decreases and cutting tool edge temperature increases on increasing the cutting speed. This is followed by the feed rate and depth of cut. The deep cryogenically treated tool caused a reduction in surface roughness of about 11% while the cutting tool edge temperature reduction was about 23.76% higher than for an untreated tool. It was thus proved that the deep cryogenically treated tool achieved better performance on selected levels of the turning parameters.

The paper shows methods of analysis and assessment of partnering relations of construction enterprises with the use of questionnaires, statistics, and fuzzy logic. The results were obtained from Polish, Slovak and Ukrainian enterprises. The definition of partnering in the construction industry indicates that it is a qualitative concept. By applying a scale in the questionnaire, and due to mathematical analysis of the data, the final research result, showing the level of partnering relations of construction enterprises, is rendered quantitatively.

The consideration of uncertainties in numerical simulation is generally reasonable and is often indicated in order to provide reliable results, and thus is gaining attraction in various fields of simulation technology. However, in multibody system analysis uncertainties have only been accounted for quite sporadically compared to other areas.

The term uncertainties is frequently associated with those of random nature, i.e. aleatory uncertainties, which are successfully handled by the use of probability theory. Actually, a considerable proportion of uncertainties incorporated into dynamical systems, in general, or multibody systems, in particular, is attributed to so-called epistemic uncertainties, which include, amongst others, uncertainties due to a lack of knowledge, due to subjectivity in numerical implementation, and due to simplification or idealization. Hence, for the modeling of epistemic uncertainties in multibody systems an appropriate theory is required, which still remains a challenging topic. Against this background, a methodology will be presented which allows for the inclusion of epistemic uncertainties in modeling and analysis of multibody systems. This approach is based on fuzzy arithmetic, a special field of fuzzy set theory, where the uncertain values of the model parameters are represented by socalled fuzzy numbers, reflecting in a rather intuitive and plausible way the blurred range of possible parameter values. As a result of this advanced modeling technique, more comprehensive system models can be derived which outperform the conventional, crisp-parameterized models by providing simulation results that reflect both the system dynamics and the effect of the uncertainties.

The methodology is illustrated by an exemplary application of multibody dynamics which reveals that advanced modeling and simulation techniques using some well-thought-out inclusion of the presumably limiting uncertainties can provide significant additional benefit.

Groundwater quality modelling plays an important role in water resources management decision making processes. Accordingly, models must be developed to account for the uncertainty inherent in the modelling process, from the sample measurement stage through to the data interpretation stages. Artificial intelligence models, particularly fuzzy inference sys-tems (FIS), have been shown to be effective in groundwater quality evaluation for complex aquifers. In the current study, fuzzy set theory is applied to groundwater-quality related decision-making in an agricultural production context; the Mamdani, Sugeno, and Larsen fuzzy logic-based models (MFL, SFL, and LFL, respectively) are used to develop a series of new, generalized, rule-based fuzzy models for water quality evaluation using widely accepted irrigation indices and hydro-logical data from the Sarab Plain, Iran. Rather than drawing upon physiochemical groundwater quality parameters, the pre-sent research employs widely accepted agricultural indices (e.g., irrigation criteria) when developing the MFL, SFL and LFL groundwater quality models. These newly-developed models, generated significantly more consistent results than the United States Soil Laboratory (USSL) diagram, addressed the inherent uncertainty in threshold data, and were effective in assessing groundwater quality for agricultural uses. The SFL model is recommended as it outperforms both MFL and LFL in terms of accuracy when assessing groundwater quality using irrigation indices.

The quality of the squeeze castings is significantly affected by secondary dendrite arm spacing, which is influenced by squeeze cast input

parameters. The relationships of secondary dendrite arm spacing with the input parameters, namely time delay, pressure duration, squeeze

pressure, pouring and die temperatures are complex in nature. The present research work focuses on the development of input-output

relationships using fuzzy logic approach. In fuzzy logic approach, squeeze cast process variables are expressed as a function of input

parameters and secondary dendrite arm spacing is expressed as an output parameter. It is important to note that two fuzzy logic based

approaches have been developed for the said problem. The first approach deals with the manually constructed mamdani based fuzzy

system and the second approach deals with automatic evolution of the Takagi and Sugeno’s fuzzy system. It is important to note that the

performance of the developed models is tested for both linear and non-linear type membership functions. In addition the developed models

were compared with the ten test cases which are different from those of training data. The developed fuzzy systems eliminates the need of

a number of trials in selection of most influential squeeze cast process parameters. This will reduce time and cost of trial experimentations.

The results showed that, all the developed models can be effectively used for making prediction. Further, the present research work will

help foundrymen to select parameters in squeeze casting to obtain the desired quality casting without much of time and resource

consuming.

The article includes presentation of fuzzy numbers application in projects prioritizing at

manufacturing and service providing enterprises. The following criteria have been applied

as a basis for projects prioritizing analysis in enterprise: NPV index, linked with the enterprise strategic aims, project execution cost, project time, project scope and risk. As the

criteria selected were of measurable and non-measurable character in projects prioritizing

evaluation, the fuzzy decision making system has been developed, in which a linguistic value

has been defined for each criterion of projects prioritizing. Knowledge base has been developed afterwards, presenting cause-effect dependencies in projects prioritizing. Knowledge

base consisted of conditional rules. Fuzzy system of decision making in project prioritizing

has been developed in MATLAB application.

The decision making fuzzy system established, constitutes an efficient tool for projects prioritizing, on the basis of criteria given and concluding system developed. The obtained analysis

results provide basis for the decision making parties to set the projects execution sequences.

The article outlines how to use the convergence of collections to determine the position of a mobile device based on the WiFi radio signal strength with the use of fuzzy sets. The main aim is the development of the method for indoor position determination based on existing WiFi network infrastructure indoors. The approach is based on the WiFi radio infrastructure existing inside the buildings and requires operating mobile devices such as smartphones or tablets. An SQL database engine is also necessary as a widespread data interface. The SQL approach is not limited to the determination of the position but also to the creation of maps in which the system dening the position of the mobile device will operate. In addition, implementation issues are presented along with the distribution of the burden of performing calculations and the benets of such an approach for determining the location. The authors describe how to decompose the task of determining the position in a client-server architecture.