This study provides much-needed empirical study of workplace inclusion of underresourced employees of low socioeconomic status. Based upon a conservation of resources perspective, we have examined the centrality of resources as a key inclusion process for well-being outcomes for employees with insufficient resources. In the context of misuse of institutional power over operative workers within highly segmented and hierarchical work settings, this study validates the importance of economic inclusion for fostering workers' well-being via fair employment practices. This study also offers new knowledge of the integrative resource model of workplace inclusion research by validating workers' personal resources of learning orientation as an internal condition for strengthening the positive effect of economic inclusion on well-being.
Semiconductor industry faces a continuous challenge to decrease the transistor size as well as to increase the yield by eliminating defect sources. One of the sources of particle defects is ultra pure water used in different production tools at different stages of processing. In this paper, particle count data measured in ultra pure water is related to the yield of two large size products. An impact of nano-particle present in ultra pure water on yield of up to 4-6 % has been found in two different products.
In many process steps of integrated circuits (IC’s) fabrication, silicon wafers are coming in contact with process liquids such as ultra pure water (UPW) and aqueous and non-aqueous chemical mixtures. During these process steps, liquid-borne particle contamination can deposit on the wafer surface. Particle contamination from UPW is an important factor influencing random yield loss of IC’s [ ]. A number of yield models are used to predict yields including Poisson, Murphy, Seeds, and negative binomial models [ , ]. However, these models are based on the assumption that particles are randomly deposited on the wafer surface [ ].
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