Surface Laser Light Scattering (SLLS) is a heterodyne detection technique used to probe the surface properties of fluid interfaces. These interfaces are either liquid/liquid or vapor/liquid, and they may include insoluble monolayers or polymer films deposited on liquid surfaces as well as microemulsions in solution at low concentration. This technique provides one with a nonperturbative way to obtain surface tension and viscosity. A diffraction grating is employed to provide a stable local oscillatior, hence selecting an accurate ripplon wave vector . This thesis deals with the investigation of the interface between air and solution consisting of the methanol and water mixture and poly(N-isopropylacrylamide) or PNIPAM which is one of the fascinating polymeric materials. The polymer PNIPAM shows distinct responses to variations in the surrounding environment (such as thermal gradient, change in pH, etc.). The surface tension extracted from the SLLS data using the Kelvin equation is found to agree well with that obtained by using the Wilhelmy plate method. For the range of wave vectors cm-1, the power spectrum detected in frequency domain can be fit to a Lorentzian profile. Our experiments show that when the volume percentage of methanol increases, the interfacial property becomes insensitive to the presence of PNIPAM.

Materials requirements planning (MRP) is a widely used method for production planning and scheduling. Planned lead-time (PLT) and lot size are two of the input parameters for MRP systems, which determine planned order release dates. Presently, planned lead-time and lot size are estimated using independent methodologies. No existing PLT estimation methods consider factors such as machine breakdown, scrap-rate, etc. Moreover, they do not consider the capacity of a shop, which changes dynamically, because the available capacity at any given time is determined by the loading of the shop at that time. The absence of such factors in calculations leads to a huge lead-time difference between the actual lead-time and PLT, i.e., lead-time error. Altering the size of a lot will have an effect not only on the lead-time of that lot but also on that of other lots. The estimation of lot size and lead-time using independent methodologies currently does not completely capture the inter-dependent nature of lead-time and lot size. In this research, a lot-sizing model is modified in such a way that it minimizes the combination of setup cost, holding cost and work-in-process cost. This proposed approach embeds an optimization routine, which is based on dynamic programming on a manufacturing system model, which is based on open queuing network theory. Then, it optimizes lot size by using realistic estimates of WIP and the lead-time of different lots simultaneously for single-product, single-level bills of material. Experiments are conducted to compare the performance of the production plans generated by applying both conventional and the proposed methods. The results show that the proposed method has great potential and it can save up to 38% of total cost and minimize lead-time error up to 72%. / Master of Science