Wind turbines emit low frequency noise (LFN) and large turbines generally generate more LFN than small turbines. The dominant source of LFN is the interaction between incoming turbulence and the blades. Measurements suggest that indoor levels of LFN in dwellings typically are within recommended guideline values, provided that the outdoor level does not exceed corresponding guidelines for facade exposure. Three cross-sectional questionnaire studies show that annoyance from wind turbine noise is related to the immission level, but several explanations other than low frequency noise are probable. A statistically significant association between noise levels and self-reported sleep disturbance was found in two of the three studies. It has been suggested that LFN from wind turbines causes other, and more serious, health problems, but empirical support for these claims is lacking.
To handle the complex and flexible manufacturing of today it is vital to have well functional information systems for the operators so that they know when, what and where to assemble. The current designs of assembly work instructions differ much between companies, but also between plants within the same company. The digitalization trends and initiatives such as Industry 4.0 show the manufacturing industry the advantages to incorporate new methods and tools into their businesses. Even though manufacturing IT systems are designed to be adaptive to product and volume changes, they are still widely characterized by their rigid structures. Making large changes to manufacturing IT systems with comprehensive structures is complex and requires large amounts of resources. Therefore, it is important for the manufacturing companies to make the correct investments. In previous studies, two current state analyses have been conducted with the aim to map manufacturing engineering processes and IT systems producing assembly work instructions in a mass customization context. This paper presents results from the third part of a longitudinal study which focuses on identifying operators' information needs in manual assembly of heavy vehicles. This third study aims to identify the information gap between the current state and the wanted state by assessing information needs at 13 assembly stations in three plants belonging to a global production network. The purpose is to identify design requirements for future assembly information systems enabling the practical use of the digitalization.
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