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Radio tomographic imaging (RTI) is a technique for estimating spatial loss fields (SLFs), which maps the quantified attenuation of radio signals at every spatial location within monitored regions. In this study, we investigate RTI techniques in indoor factory environments, where the RTI techniques deteriorate because of severe multipath channels. We propose the binary radio tomographic imaging (binary RTI) method, where the attenuation level of each pixel in a SLF is defined as a binary value. The binary RTI method is suited for factory environments, including metallic objects, because radio signals are almost fully reflected rather than getting absorbed by such objects. In the proposed method, we suppose that transmitted signals are modulated with an orthogonal frequency division multiplexing (OFDM) format, and each receiver is equipped with multiple antenna elements. By adopting the two-dimensional multiple signal classification (MUSIC), the proposed method identifies whether the signals are transmitted in a line-of-sight (LOS) or a non-line-of-sight (NLOS) path. From the LOS/NLOS identification, we propose two algorithms to estimate the binary SLF: a simple greedy algorithm and a relaxation algorithm with low-rank approximation. We evaluate the performance of the proposed method via simulation experiments. To assess the applicability of the proposed method to factory environments, we assume a severe multipath environment where all the objects, wall, and ceiling are perfect electrical conductors, and show that by using an appropriate threshold parameter for the LOS/NLOS identification, the proposed method can estimate the binary SLF in the test environment.

Modern factory planning requires a holistic perspective taking economic as well as environmental sustainability over the entire factory life cycle into account. As a complex socio-technical system, the factory life cycle consists of multiple life cycles of the inherent factory elements. A holistic understanding of the individual life cycles and their interdependencies is missing for both planning and operation of a factory. Therefore, the goal is to develop a system understanding about life cycle-oriented factory planning and to analyze the contribution of relevant factory elements to the sustainability of a factory. As a result, a knowledge base for life cycle costing and assessment of the entire factory is established using an impact path model. The qualitative model supports factory planners in deriving planning measures for the sustainable design of a factory and in determining data requirements for the quantitative evaluation of the economic and environmental sustainability of a factory. It shows that the production and logistics concepts essentially define the sustainability potential during planning, while the resulting life cycle behavior of the process facilities and workers is responsible for the majority of costs and environmental impacts of a factory. Factory planners must therefore become aware of the implications of planning decisions on factory operation when developing concepts in the future. [ABSTRACT FROM AUTHOR]

Indoor air quality plays a significant role in human health, especially for those who spend the majority of their time indoors, as is the case of workers in the industrial field. The control of contaminants inside the occupational indoor environment becomes critically important for promoting health. In terms of Health Impact Assessment, indoor air quality inside a factory becomes an essential factor of industrial hygiene. Here, computational fluid dynamics-based indoor environmental design was applied to potentially evaluate the environmental quality in a factory and to improve industrial hygiene. In particular, this study proposes an integrated simulation procedure to predict the inhalation exposure concentration of a hazardous chemical compound (here, cyclohexanone) by using a multi-stage, one-way nesting method. This procedure connects a factory building space, a micro-climate around the human body, and a respiratory tract in the human body. This research provides quantitative and qualitative detailed information of contaminant dosing in workers. The exact inhalation dose of contaminants in the human airways can be estimated based on factory-environment conditions through this procedure. Subsequently, the average contaminant concentration in the work place and inside the human body can be calculated. [ABSTRACT FROM AUTHOR]

Mechanical and passive ventilation strategies directly impact indoor air quality. Passive ventilation has recently become widespread owing to its ability to reduce energy demand in buildings, such as the case of natural or cross ventilation. To understand the effect of natural ventilation on indoor environmental quality, outdoor–indoor flow paths need to be analyzed as functions of urban atmospheric conditions, topology of the built environment, and indoor conditions. Wind-driven natural ventilation (e.g., cross ventilation) can be calculated through the wind pressure coefficient distributions of outdoor wall surfaces and openings of a building, allowing the study of indoor air parameters and airborne contaminant concentrations. Variations in outside parameters will directly impact indoor air quality and residents’ health. Numerical modeling can contribute to comprehend these various parameters because it allows full control of boundary conditions and sampling points. In this study, numerical weather prediction modeling was used to calculate wind profiles/distributions at the atmospheric scale, and computational fluid dynamics was used to model detailed urban and indoor flows, which were then integrated into a dynamic downscaling analysis to predict specific urban wind parameters from the atmospheric to built-environment scale. Wind velocity and contaminant concentration distributions inside a factory building were analyzed to assess the quality of the human working environment by using a computer simulated person. The impact of cross ventilation flows and its variations on local average contaminant concentration around a factory worker, and inhaled contaminant dose, were then discussed. [ABSTRACT FROM AUTHOR]

The aim of this study is microbiological analysis of individual technological operations during the industrial production of cooked hams, focusing on lactic acid bacteria (LAB). Samples were during the course of the entire cooked ham production cycle in May–June (Experiment I) and November–December (Experiment II). A total of 215 samples were taken and subsequently tested. The difference in the occurrence of LAB in meat before thermal processing resulted from the initial level of contamination of the raw material. A reduction to the number of LAB from 4.0 to 5.0 log CFU/g of meat to a value of practically zero occurred during the thermal processing. The LAB population increased during storage of the finished products. A level of 7.0 log CFU/g was reached in slices of ham in the modified atmosphere after three (Experiment I) or two (Experiment II) weeks of storage, respectively. LAB of the genera Leuconostoc ( Leuc. carnosum , Leuc. mesenteroides and Leuc. gelidum ) occurred most frequently in samples of cooked ham after thermal processing. These species were also isolated from the production environment. Lactobacillus sakei , Lbc. curvatus and Weissella viridescens were other species of LAB that were isolated from samples after thermal processing. [ABSTRACT FROM AUTHOR]

Chocolate confectionery fillings are generally regarded as microbiologically stable. The stability of these fillings is largely due to the general practice of adding either alcohol or preservatives. Consumer demands are now stimulating producers to move away from adding alcohol or other preservatives to their confectionery fillings and instead to search for innovative formulations. Such changes in composition can influence the shelf life of the product and may lead to spoilage by xerophilic fungi. The aim of this study was to test whether the production environment of Belgian chocolate confectionery factories and common ingredients of chocolate confectioneries could be potential sources of contamination with xerophilic fungal species. In the factory environment, the general and strictly xerophilic fungal spore load was determined using an RCS Air Sampler device in combination with DG18 and MY50G medium, respectively. Four basic ingredients of chocolate confectionery fillings were also examined for fungal spore levels using a direct plating technique. Detected fungi were identified to species level by a combination of morphological characterization and sequence analysis. Results indicated a general fungal spore load in the range of 50–250 colony forming units per cubic meter of air (CFU/m 3 air) and a more strict xerophilic spore load below 50 CFU/m 3 air. These results indicate rather low levels of fungal spores present in the factory environment. The most prevalent fungi in the factory environment were identified as Penicillium spp., particularly Penicillium brevicompactum . Examination of the basic ingredients of confectionery fillings revealed nuts to be the most likely potential source of direct contamination. In nuts, the most prevalent fungal species identified were Eurotium , particularly Eurotium repens . [ABSTRACT FROM AUTHOR]

Abstract: A model system was developed for evaluating the efficacy of disinfectants for inactivating bacteria present in biofilms on surfaces within dairy factory environments. Mixed culture biofilms of six dairy factory isolates (pseudomonads, coliforms and presumptive staphylococci) were generated on factory floor tiles and subjected to up to three fouling and cleaning (FC) cycles. Disinfectants (hypochlorite, peroxyacetic acid-, acid anionic- and quaternary ammonium compound (QUAT)-based products) were applied after cleaning at the supplier''s recommended concentrations. Bacterial groups were enumerated using selective agar media. All disinfectants significantly (p <0.05) reduced surface counts of the three bacterial groups. The peroxyacetic acid-based product applied at 3.0% (v/v) achieved the greatest overall reductions in counts. In some cases, disinfectants were more biocidal towards particular bacterial groups. For example, hypochlorite demonstrated greater biocidal activity towards coliforms and staphylococci while the QUAT- and acid anionic-based disinfectants demonstrated greater biocidal activity towards staphylococci. The selective biocidal activity of hypochlorite and the acid anionic-based disinfectant was maintained over at least three FC cycles. The results demonstrate that disinfectants can alter the composition of the surface microflora and can be used to selectively reduce or eliminate particular bacterial groups from production environments. The model system was adapted to assess biofilm development and inactivation on a range of floor materials used in dairy factory environments. Clear differences were observed between surface materials at the end of the inoculation stage and following one FC cycle. For example, after one FC cycle, the highest bacterial counts were obtained for extruded floor tiles and the lowest for stainless steel and the polyurethane surface coating. The model system is versatile and there is scope to employ it to investigate a range of factors influencing the efficacy of cleaning and disinfection procedures towards biofilms. In addition, other microorganisms, such as pathogenic bacteria, may be added to the model biofilm and the influence of disinfectants on these investigated. [Copyright &y& Elsevier]

Wireless sensors have started being utilized for process monitoring in factory environments, which are typically harsh for low-power wireless communication due to their complicated layout and plentiful stationary/moving obstacles. Sensor radios available so far have been engineered for consumer-grade applications, featuring low cost, low power, and minimal radio complexity. In order to utilize such radios for factory applications, their channel characteristics and link quality must be investigated for optimal design and reliability assessment. In this paper, a series of measurements were made with IEEE 802.15.4-compliant sensor radios to study both their spatial and temporal characteristics with respect to the factory surroundings found in a university machine shop. Critical communication properties were investigated in terms of received signal strength, link quality indication, and packet error rate. It is found that received signal strength shows dependency on surrounding structures, radio link qualities with respect to received signal strength and link quality indication are stable before a grey zone is reached, and average link quality indicator serves as a better packet success rate indication than average received signal strength indication. The findings in this paper provide a useful guidance to the ongoing explorations for a methodology to predict radio performance at any location within a given factory floor plan and to online assess the time-variant link qualities. [ABSTRACT FROM PUBLISHER]