In the industrial sector, production processes are continuously evolving, but issues and delays in production are still commonplace. Complex problems often require input from production managers or experts even though Industry 4.0 provides advanced technological solutions. Small and medium-sized enterprises (SMEs) normally rely more on expert opinion since they face difficulties implementing the newest and most advanced Industry 4.0 technologies. This reliance on human expertise can cause delays in the production processes, ultimately, impacting the efficiency and profitability of the enterprise. As SMEs are mostly niche markets and produce small batches, dynamics in production operations and the need for quick responses cannot be avoided. To address these issues, a decision support method for dynamic production planning (DSM DPP) was developed to optimize the production processes. This method involves the use of algorithms and programming in Matlab to create a decision support module that provides solutions to complex problems in real-time. The aim of this method is to combine not only technical but also human factors to efficiently optimize dynamic production planning. It is hardly noticeable in other methods the involvement of human factors such as skills of operations, speed of working, or salary size. The method itself is based on real-time data so examples of the required I 4.0 technologies for production sites are described in this article—Industrial Internet of Things, blockchains, sensors, etc. Each technology is presented with examples of usage and the requirement for it. Moreover, to confirm the effectiveness of this method, tests were made with real data that were acquired from a metal processing company in Lithuania. The method was tested with existing production orders, and found to be universal, making it adaptable to different production settings. This study presents a practical solution to complex problems in industrial settings and demonstrates the potential for DSM DPP to improve production processes while checking the latest data from production sites that are conducted through cloud systems, sensors, IoT, etc. The implementation of this method in SMEs could result in significant improvements in production efficiency, ultimately, leading to increased profitability.

In this study, we analyzed the impact of the dyeing and the digital printing processes of linen/silk fabric (70% linen/30% silk) on its color fastness and shrinkage in the directions of warp and weft. This is a highly relevant topic because a single fabric combines two natural fibers of different origins—silk, a protein, is animal-based, whereas linen is derived from cellulose and is, thus, plant-based. Therefore, the different natures of the two fibers determine distinctive chemical properties. As a result, selecting the optimal technological course of processing for blended yarn fabrics and their yarn is a challenging task. The quality of the conducted finishing is determined by the physical properties of fabrics, such as color fastness to perspiration; soap; dry friction and wet friction; the pH of the fabric after finishing; and the shrinkage of the fabric in the directions of warp and weft. Here, color fastness was assigned the top grade with respect to all potentially harmful factors, except for wet friction. The evaluation proves that the technological regimes employed for digital printing and dyeing in the production item’s fabrics were properly selected.

The pilling resistance of fashion fabrics is a fundamentally important and frequently occurring problem during cloth wearing. The aim of this investigation was to evaluate the pilling performance of linen/silk woven fabrics with different mechanical and chemical finishing, establishing the influence of the raw material and the peculiarities of dyeing and digital printing with different dyestuff. The pilling results of the dyed fabrics were better than those of the grey fabrics and even a small amount of synthetic fiber worsened the pilling performance of the fabric. Singeing influenced the change in the pilling resistance of the linen/silk fabrics without changing the final pilling resistance result. Singeing had a stronger influence on the fabrics with a small amount of synthetic fibers. The pilling resistance of printed fabrics was better than that of grey and dyed fabrics without and with singeing. The pilling resistance of pigment-printed fabrics was better than that of the reactive-printed fabrics.

Small and medium-sized engineering production companies face challenges that are related to unpredicted rapid changes of availability of the work force, materials and equipment. Those challenges are especially difficult to solve for companies focusing on unit or batch production and when they are collaborating with customers who require short lead times. A four-month observation was carried out in a metal processing company in Lithuania to understand the most common rising problems and developing solution for computerised decision support systems. It was discovered that the company needs a computerised “employee centred” system for the improvement of the allocation of tasks to employees. Such a need proved to be the most urgent one, especially during pandemics. An algorithm for the analysis and automated allocation of the employees’ tasks has been developed and tested. The proposed algorithm is universal and may be applied in different SMEs for engineering production.

The aim of this article was to compare the shrinkage and air permeability properties of woolen fabrics and fabrics with regenerated wool woven with different weaves for establishing the suitability of regenerated wool for blankets. Two series of products with yarns of different raw materials were woven. One group of fabrics was woven with regenerated woolen yarn in the weft and woolen yarn in the warp. The other group of fabrics was woven only from 100% woolen yarns. The shrinkage in the directions of the warp and the weft and the air permeability of the fabrics with regenerated wool and 100% woolen fabrics with different weaves were investigated. The shrinkage in the directions of the warp and the weft in the fabrics with regenerated wool in the weft and 100% woolen fabrics depended on the float length in the weave. When the length of the weave increased, the shrinkage also increased. The air permeability value changed depending on the number of intersections and the float length. The fabrics with regenerated wool in the direction of the weft had higher air permeability. The Two-way analysis of variance (ANOVA) results showed that the weave influenced the shrinkage in the directions of the weft and warp, but the raw material had no influence on the shrinkage. The weave did not influence the air permeability, in contrast to the raw material. The shrinkage in the directions of the warp and weft and the air permeability did not depend on the interrelationships of the weave group and the raw material of the fabric.