Supply chain management in small and medium-sized enterprises is aimed at ensuring both short-and long-term effectiveness and efficiency of these enterprises. Management practically ensures that small and medium-sized enterprises, as dynamic, self-controlled, controlled and open systems, adapt to the operating environment, which is inherently dynamic, open and stochastic. Traditional approach to management of small and medium-sized enterprises is associated with overstocking and providing excessive capacity as a means of protection against demand variability. Owing to the possibility of rapid and major changes in the marketplace, this approach presents a great risk with potential adverse effects. Contemporary approach to management of small and medium-sized enterprises implies that these enterprises operate following the "feel and react" principle, as opposed to the traditional "produce and then sell" principle. A fast response to the demand variability requires efficient solutions for all elements that constitute the supply chain: demand management, planning, procurement, warehousing, production, transport and distribution. For these very reasons, there is a need to address the issue of supply chain optimization, inasmuch since every organizational system wants to utilize the synergistic effect of a whole and be as efficient and effective as possible. As the synergistic effect depends heavily on both the strategy chosen and managerial decisions made by the managers at the operational level during adjustment of work processes, they are requested to make decision closely tailored to the entire organizational system. Taking the above mentioned problem into account, a growing number of researchers have recently been asking questions and searching for a solution on how chosen strategies and managerial decisions made by the managers at the operational level during adjustment of work processes may contribute to enhancement of effectiveness and efficiency of the entire enterprise.

The success of small and medium enterprises to adapt to constant changes in the environment largely depends on the different strategies and management decisions taken by managers at the operational level. This paper is searching for a tool that would allow managers at all levels to consider the effects of their decisions on the success of the enterprise as a whole. In this sense, the application of system dynamics developed one modular simulation model of business processes of SMEs. Developed model recognizes the specificities of SMEs, such as a large range of products, the use of a wide variety of materials, production in small batches and requests for reduction of lead time (Lead Time). The effects of various strategies and management decisions can be observed by monitoring the dependence of performance measures of simulated process on values of model parameters. Through four experiments the effects of changes in inventory management policies, the availability and size of the lot were simulated. The results of experiments showed that the variation of the model parameters should be oriented simultaneously towards several of the aforementioned directions.

High surface texture of textile materials is rougher than other printing substrates which can cause excessive macro non-uniformity. Adding metal oxides into the ink to enhance material properties usually add to surface roughness and increase print mottle. In this paper copper(I)oxide particles and different amounts of Pinus sylvestris L. plant extract were added to modified alginate paste (CHT-NV) prior to printing. The aim of this paper is to inspect the influence of added metal oxide and plant extract on the print quality of linen based material via surface macro non-uniformity GLCM determination method. In the pattern recognition phase, the co-occurrence matrix is applied to calculate the texture characteristics, such as contrast, correlation, energy, entropy and homogeneity. The research results indicated that the metal oxide particles have had a negative influence on macro uniformity of printed linen. Increasing of the concentration of extract leads to a dilution of the printing paste, and thus to a greater penetration of copper ions between the threads of the fabric, as well as into the yarn itself.

We present a platform for integrated CAD/CAPP part design based on Elementary Machining Features (EMF) and intelligent approach for setup planning and operation sequencing based on a genetic algorithm through two papers. In this paper, as Part II of this platform, CAD/CAPP integration was realized via information from the enriched EMF, as well as production rules and a genetic algorithm. This is done for the purpose of the automated machining operation sequencing. Operation sequencing was conducted by using the improved genetic algorithm (GA).The improved GA uses integer representation for operations and implements modified genetic operators, enabling the achievement of high results in a reasonable computational time. In the paper we present a comprehensive case study applied to some existing and one new industrial example, confirming a high level of usability of the proposed GA and overall platform. Experimental results show that the improved GA algorithm gives slightly better results than similar algorithms in literature. For industrial example, we use body of the hydraulics cylinder which consists of 52 EMF. After implementation of the proposed methodology, the optimal machining operation sequence was identified, as well as the total machining cost of 142.49 BAM.

Textile materials are increasingly being subjected to the process of printing. The printing process with its parameters significantly affects the properties of textile materials and clothes made from these materials. This paper examines the effect of the parameters of inkjet printing on thermal resistance characteristics of printed textile materials. As the essential print parameters were selected tone value and a different number of passes. In this research were used knitted fabric materials of 100% cotton fibers and 100% polyester fibers. Results of the research demonstrated that, in addition to material composition, the inkjet printing process with its parameters have a significant influence on the thermal resistance of printed textile materials. The values of the thermal resistance of the printed samples show that the increase in the number of applications of ink in the printing results in a rise in the value on cotton knitwear, and decrease in thermal resistance value on polyester knitwear.