The appearance of a garment is affected by the quality of the fabrics used in its manufacture, as well as a number of factors determined by the technology of the garment manufacturing process. Since fabric quality, as the most important element of garment appearance, is determined by its mechanical properties, it is obvious that these properties directly impact fabric processing properties. It can be seen through various forms of fabric behavior under the loads that occur in sewing. Investigations of the correlations of the stress and fabric behavior are aimed at constructing a system to predict fabric behavior in garment manufacturing processes, as well as to predict the appearance of the garment to be manufactured. The investigation presented here deals with the impact of fabric mechanical properties on the quality of seam appearance, as defined by seam puckering and work-piece flotation. Machine learning methods included in the Orange software package were used to establish the importance of mechanical properties with respect to fabric behavior.

Antimicrobial finishing of textiles protects users from pathogenic microorganisms, which can cause medical and hygienic problem. The use of such textiles particularly increases in healthcare facilities, where reduction and transmission of pathogenic bacteria are important factors for preventing nosocomial infections. In the present study, the efficiency of fabric with silane quaternary ammonium compounds (Si-QAC) applied as active agents was evaluated. A test was performed according to ATCC 100-1999 Test Method after 0-, 24-and 48-hour incubation times. The treated textiles were effective against Enterococcus faecalis, Staphylococcus aureus and Klebsiella pneumoniae, but were not effective for Gramnegative Escherichia coli and Pseudomonas aeruginosa. Testing was also performed in hospital environment at infectious department where working clothes made of treated fabric were compared to normal working clothes. Antimicrobial textiles were not effective in a hospital environment, where average microbial count on medical workers' uniforms without antimicrobial protection was 1.4 × 10 9 cfu/mL, and 1.3 × 10 9 cfu/mL for uniforms made of antimicrobial material. Our conclusion is that quantities of application rates for Si-QAC should be higher or should be improved with applying another antimicrobial coating to obtain complex with dual activity.

Military and civil defense personnel are often involved in complex activities in a variety of outdoor environments. The choice of appropriate clothing ensembles represents an important strategy to establish the success of a military mission. The main aim of this study was to compare the known clothing insulation of the garment ensembles worn by soldiers during two winter outdoor field trials (hike and guard duty) with the estimated optimal clothing thermal insulations recommended to maintain thermoneutrality, assessed by using two different biometeorological procedures. The overall aim was to assess the applicability of such biometeorological procedures to weather forecast systems, thereby developing a comprehensive biometeorological tool for military operational forecast purposes. Military trials were carried out during winter 2006 in Pokljuka (Slovenia) by Slovene Armed Forces personnel. Gastrointestinal temperature, heart rate and environmental parameters were measured with portable data acquisition systems. The thermal characteristics of the clothing ensembles worn by the soldiers, namely thermal resistance, were determined with a sweating thermal manikin. Results showed that the clothing ensemble worn by the military was appropriate during guard duty but generally inappropriate during the hike. A general under-estimation of the biometeorological forecast model in predicting the optimal clothing insulation value was observed and an additional post-processing calibration might further improve forecast accuracy. This study represents the first step in the development of a comprehensive personalized biometeorological forecast system aimed at improving recommendations regarding the optimal thermal insulation of military garment ensembles for winter activities.

The study of fabric behaviour during its transformation from a two-dimensional (2D) product into a three-dimensional (3D) article of clothing is presented in this paper. Actual fabric transformation into a 3D article of clothing occurs in sewing processes, where the fabric is exposed to different mechanical loads and behaves accordingly. Fabric behaviour responses as an outcome of the mechanical loads to which it has been exposed, as well as their correlation with the parameters of the analysed fabric mechanical properties are investigated from this point of view. The system was designed for fabric behaviour prediction in garment manufacturing processes, based on wide fabric behaviour study. The ORANGE software tool used incorporates a lot of machine learning methods. On the basis of the input data (the parameters of mechanical properties) and input knowledge (fabric behaviour responses), it offers the prediction of fabric behaviour in garment manufacturing processes for the fabric selected.

Environment and situation awareness are key factors to effectively work or even to survive in harsh environment. Over recent decades, the need to adequately protect the human in various dangerous situations has forced the development of clothing industry in the direction to provide high innovative products, and equip their products with sensors or other means of smart technologies. Besides basic functions of protection, thermal and ergonomic comfort, these new generation protective garments have served also functions like monitoring and/or protection. Heat injury is a major issue for firefighters as they wear insulated clothing and cannot shed the heat generated from physical exertion. Early detection of heat issues is critical to stop dehydration and heat stress becoming fatal. Early onset of heat stress affects cognitive function which combined with operating in dangerous environment makes heat stress and dehydration a critical issue to monitor. Physiological status monitors measure firefighter's vital sign status, fatigue and exertion levels. This allows a Fire Chief to call in additional personnel before the crew gets exhausted and also gives an early warning to firemen before they run out of energy, as they may not be able to make voice calls over their radio. However early solutions have been only partly accepted by the professional end users. Design requirements such as cost, bulkiness, accuracy, independency, scalability, robustness are key parameters, which can cause high acceptance or usage prevention rapidly. We approached the development of intelligent fire suits integrated with a data acquisition (DAQ) system and we are using enabling technologies to collect measured physiological and environment information about the firefighter(s) remotely. In our first prototype we are monitoring basic physiological parameters as well the microenvironment temperature. With our DAQ solution we measure, combine, transfer physiological and environmental signals collected from and within the firefighter's suit to monitor and visualize whole firefighter platoons remotely.