The complexity of scheduling in manufacturing systems, is examined in this article, with a focus on the important factors that determine time and production costs. Addressing the inefficiencies in resource utilization and recognizing the limited integration of Information and Communication Technology (ICT), particularly the transformative 5G, in Kosovo's Manufacturing Industry, we advocate for an advanced scheduling model. This model aims to propel productivity, curtail production time and elevate overall manufacturing system performance. Grounded in linear programming, our developed model strategically optimizes the objective function, encompassing total flow time and makespan. Significantly, the model achieves optimal allocation of start and end times for each job, coupled with an efficient overall processing time, substantially reducing planning times for "job shop" scheduling problems. Beyond the immediate benefits, our adaptable scheduling model stands poised for seamless modification to accommodate diverse objective functions and instances, including the incorporation of 5G technology. The practical case study underscores the tangible benefits of our approach, showcasing its ability to streamline production processes and enhance operational efficiency within a real-world manufacturing setting. Future iterations may harness 5G's transformative capabilities to further refine and improve the the

Purpose: To enhance enterprise efficiency, this study examines the pivotal role of operations management in optimizing the use of materials, technology, equipment, and personnel, especially within the transformative framework of Industry 4.0. Design/methodology/approach: This article investigates operational preparation in the context of Industry 4.0. Through questionnaires and interviews with stakeholders, problems related to operational preparation were identified. To address these problems, a launching model was developed for production systems. The model considers several parameters important for the production process, including business goals, customer needs, and environmental conditions that impact enterprise performance and profit. Findings: The model determines the importance of jobs to be performed in a certain order to optimize production sequence. The proposed parameters are included in a mathematical-algorithmic launching model based on categorical levels related to the production process, such as profit, delivery times, processing times, total number of technological operations, product types, materials, required quality, product complexity, and resource use. The model was developed based on observations and investigations conducted in Kosovo's enterprises on operations research, and it has the potential to significantly improve production efficiency and profitability in the Industry 4.0 era. Practical implications: The findings of this study have practical implications for operations management within the Industry 4.0 framework, proposing a launching model designed to optimize production processes and enhance efficiency. Originality/value: The originality and value of this research lie in the development of a mathematical-algorithmic launching model that addresses operational preparation in the Industry 4.0 context, taking into account various crucial parameters.

This paper discusses two different thermo-technical systems for heating and cooling the three-story office building under consideration. Data were collected on natural gas energy consumption over three-year period. The measured data on energy consumption for heating and cooling the building with an absorption heat pump using natural gas as fuel was analyzed. The only device that can replace the absorption heat pump in both the heating and cooling seasons is the vapor compression heat pump. The absorption heat pump has higher energy consumption than the vapor compression heat pump and its price is about 30% higher, but the financial cost of energy from natural gas is about 39% lower than the electricity cost of the vapor compression heat pump. The absorption heat pump is a better solution than the compression heat pump because the total financial costs, which include the investment costs and the energy costs over 20 years of operation, are about 9% lower and because the absorption heat pump heats up to an ambient temperature of -20 degrees C, which is not the case with the vapor compression heat pump.

In this paper, some of the problems arising from the acquisition of digital photography intended to determine the dimensional accuracy of products are discussed. Different equipment (digital cameras, lenses, and lighting) was used when acquiring photos in different formats. In mechanical engineering, the tolerances of dimensional measurements of products range from a few microns to 100 microns. Based on that, the technical specifications and capabilities of the cameras and lenses used are analyzed. In addition to the sensor, the resolution of the photo is often limited by the lens. Prior to the acquisition of photographs, problems such as lighting, contrast, sharpness, and the problem of central projection are addressed. During acquisition, technical specifications of the lens such as focal length, minimum focusing distance, aperture, and other lens features that cause acquisition problems are considered. This research and analysis led to valuable insights and conclusions that will facilitate the preparation of the acquisition of digital photography to determine the dimensional accuracy of the product.

This paper investigates the state of Green Manufacturing and Environmental Sustainability Manufacturing in Kosovo's SMEs and identifies barriers to implementation within the Small and Medium Enterprises of Kosovo's Manufacturing Industry. The study uses the Delphi survey method, semi-structured questionnaires and interviews as research instruments. The aim of this study is to identify factors that affect green manufacturing and the main barriers to its implementation. The analysis revealed that Energy, Pollution, Emissions, Waste, and Water are the most significant factors affecting Green Production in Kosovo's SMEs. The study finds that lack of training and expertise in Green Manufacturing Principles, weak organizational structures, and management hesitation towards adopting new practices are the main barriers to the implementation of Green Manufacturing Principles in Kosovo's SMEs. The paper concludes that technical support and training are essential for overcoming these barriers and promoting the implementation of Green Manufacturing Principles in Kosovo's SMEs.

Some of the problems that arise during the processing of the acquired photo are analyzed in this paper.The most commonly used software tools in image processing require binary photography, and its conversion into the binary form is required first.Conversion problems, and their proper solution, are key steps for further machine determination of dimensional accuracy.Removing smudges on binary photos and rotating displays for photo overlap methods are the problems that are solved in the work, in order to successfully prepare the photo with software for further determination of the dimensional accuracy of the product.The knowledge gained in this paper will help scientists, and facilitate their.

Some of the problems that arise during image processing are analysed in this paper. The most commonly used software tools in image processing require binary photography, and its conversion into the binary form is required first. Conversion problems, and their proper solution, are key steps for further machine determination of product dimensions. Removing smudges on binary photos and rotating displays for photo overlap methods are the problems that are solved in the present work, in order to successfully prepare the photo with software for further determination of product dimensions. The knowledge gained in this paper will help scientists and facilitate their software preparation and processing of the photo used to determine the required dimensions of the product.

Recently, there have been done numerous investigations related to lean manufacturing techniques. However, very little has been reported about the implementation and selection of lean manufacturing in the Kosovo manufacturing industry. This article presents the application of lean tools through Kosovo manufacturing industries and the selection of the most useful lean techniques for developing a model for an innovative smart Kosovo enterprise which is our initiative in the process of preparing Kosovo enterprises for the new age of industry—Industry 4.0. After several visits through Kosovo enterprises, the literature review has noticed that there is no investigation in the selection and implementation of lean techniques and tools in Kosovo enterprises. The purpose was to understand how Kosovo manufacturing enterprises use lean techniques and which are the most useful techniques. Analyses have been done based on interviews and questionnaires. Seven basic lean techniques are selected based on the response from the questionnaire and representing basic lean tools for developing a model of a production system regarding Industry 4.0.

The rapid development of new technologies has led to a change in the ways of manufacturing in industrial organizations. As a result of this development, many companies and factories started to look for new forms of organizational structure and the implementation of new technologies in their manufacturing process. In this context, the CAD/CAM/CAE systems play a crucial role in the process of manufacturing and generally in the transition to digital manufacturing, as the basis of a new industrial revolution. This paper presents the application of new technologies in a product life-cycle, namely the application of an advanced CAD/CAM/CAE system to support the organizational lean manufacturing initiative of SMMEs in Kosovo as a means to achieve world-class performance. Two case studies have been completed, one on the advantages of applying the CAD/CAM system in product development and the second by applying traditional manufacturing. A further aim of this present paper is to bring initiatives to the collaborative environment and to bridge the gap between industry and educational institutions.

The article describes the possibility of application of computer on the process of planning and scheduling in Kosovo Enterprises. We have investigated job shop scheduling on the shop floor of the machining operation. Furthermore, particular attention is dedicated to the schedule activities in such a way to use equipment and all resources available in an efficient manner. For solving our problems, we have used the program package “LEKIN®” and Genetic Algorithm-GA for process planning and scheduling to demonstrate how planning and scheduling techniques will help Kosovo enterprises to optimize their processes.

The objective of this paper is to analyse some concepts of the project management techniques and the proposed mathematical model for estimating the project completion probability after crashing of PERT/CPM network. The main objective is to minimize the pessimistic time of the activity, which lies on the critical path by investing additional amounts of money to the project. The increment of the investment not only decreases the pessimistic time of the activities along the critical path, but it also decreases the expected time of activities along the critical path of the whole project duration.

Fuzzy Logic inherits its origins from the ancient philosophy and the philosopher's reflection of possibility of existence of the law that would be able to overcome the dualistic truth-lie principle. Lotfi E. Zadeh published his basic work on the theory of the fuzzy sets in 1965 and opened up a new area of research, activities and thinking. The first proven practical applications of the fuzzy logic followed in the 1970s. Zadeh, and others later, have prepared a fuzzy mathematical apparatus that allows the use of vague expressions and formulations (such as "Little Slow", "Usually Wrong", "Very Cold" or "Seldom Red"), which in strictly mathematical defined rules map the domain of imprecision of human thought and expression in the codomain of real solutions. Concisely, fuzzy logic mathematically emulates human thinking. Fuzzy logic is a tool that releases the possibility of exploiting subjective knowledge in the integration of knowledge, which is discussed in the paper through an overview of the simpler and complex problems we face in the process control. Although fuzzy logic is often associated with controllers and tackling with technical problems characterized by nonlinearity, it shows its flexibility and suitability in solving process management problems as well as in other areas of human interest. The paper proposes potent directions of application of fuzzy logic in process management, especially for tackling with decision-making problems. Appropriate lay out of fuzzy variables and fuzzy functions and formation a set of fuzzy rules enables decisions based on a smaller amount of information, than it is the case with conventional methods. In a business environment, the paradigm of fuzzy logic brings human subjectivity into objectivity of science and business processes, and as a method by which we can use subjective human knowledge and to use it as it is, without complex abstractions which indeed cause quality deterioration of the final solution.

Continuation of research on solving the problem of estimation of CNC grinding process parameters of multi-layer ceramics is presented in the paper. Heuristic analysis of the process was used to define the attributes of influence on the grinding process and the research model was set. For the problem of prediction - estimation of the grinding process parameters the following networks were used in experimental work: Modular Neural Network (MNN), Radial Basis Function Neural Network (RBFNN), General Regression Neural Network (GRNN) and Self-Organizing Map Neural Network (SOMNN). The experimental work, based on real data from the technological process was performed for the purpose of training and testing various architectures and algorithms of neural networks. In the architectures design process different rules of learning and transfer functions and other attributes were used. RMS error was used as a criterion for value evaluation and comparison of the realised neural networks and was compared with previous results obtained by Back-Propagation Neural Network (BPNN). In the validation phase the best results were obtained by Back-Propagation Neural Network (RMSE 12,43 %), Radial Basis Function Neural Network (RMSE 13,24 %,), Self-Organizing Map Neural Network (RMSE 13,38 %) and Modular Neural Network (RMSE 14,45 %). General Regression Neural Network (RMSE 21,78 %) gave the worst results.

Due to the complexity of grinding process of multilayer ceramics, and the need for a specific product quality, the choice of optimal technological parameters is a challenging task for the manufacturers. The main aim of investigation is to secure the demanded final product quality (plane parallelism) in the function of input parameters (machine, machine operator, foil and production line). "Soft computing techniques" are becoming more interesting to the researchers for the modelling of processing parameters of complex technological processes. In this paper, a soft computing technique, known as the Artificial Neural Networks (ANN), is used for the modelling and prediction of parameters of technological process of CNC grinding of multilayer ceramics. The results show that the ANN with the back-propagation algorithm justifies the application also to this problem. By designing different architectures of ANN (learning rules, transfer functions, number and structure of hidden layers and other) on the set of data from the production technological process, the best result of RMS error (10,76 %) in the process of learning and 12,07 % in the process of validation was achieved. The achieved results confirm the acceptability and the application of this investigation in the technological and operational preparation of production.

The paper presents a system that, according to the requirements referring to the product quality given in surface roughness, with minimum machining time and maximum metal removal rate, recommends optimal cutting parameters with the possibility of surface roughness control during the machining process. The suggested evolutionary neuro-fuzzy system for evaluation of surface roughness is composed of three units: surface roughness prediction by cutting parameters, multi-objective optimization of cutting parameters aimed at minimum machining time and maximum metal removal rate and control of obtained or required surface roughness by means of the features quantified from digital image of the observed machined surface. The paper outlines the idea and architecture of the system as well as the possibilities of implementation. The obtained results, illustrated by experimental research, justify the application and further development of the suggested evolutionary neuro-fuzzy system for evaluation of surface roughness within the given constraints. (c) 2016 Elsevier B.V. All rights reserved.